diff --git a/MANIFEST.in b/MANIFEST.in index 388882df0c..4c16c09d58 100644 --- a/MANIFEST.in +++ b/MANIFEST.in @@ -1,8 +1,7 @@ include LICENSE.txt include README.md -recursive-include ppocr/utils *.txt utility.py character.py check.py -recursive-include ppocr/data/det *.py +recursive-include ppocr/utils *.txt utility.py logging.py +recursive-include ppocr/data/ *.py recursive-include ppocr/postprocess *.py -recursive-include ppocr/postprocess/lanms *.* -recursive-include tools/infer *.py +recursive-include tools/infer *.py \ No newline at end of file diff --git a/PPOCRLabel/Makefile b/PPOCRLabel/Makefile new file mode 100644 index 0000000000..7d72a890cb --- /dev/null +++ b/PPOCRLabel/Makefile @@ -0,0 +1,35 @@ +# ex: set ts=8 noet: + +all: qt5 test + +test: testpy3 + +testpy2: + python -m unittest discover tests + +testpy3: + python3 -m unittest discover tests + +qt4: qt4py2 + +qt5: qt5py3 + +qt4py2: + pyrcc4 -py2 -o libs/resources.py resources.qrc + +qt4py3: + pyrcc4 -py3 -o libs/resources.py resources.qrc + +qt5py3: + pyrcc5 -o libs/resources.py resources.qrc + +clean: + rm -rf ~/.labelImgSettings.pkl *.pyc dist labelImg.egg-info __pycache__ build + +pip_upload: + python3 setup.py upload + +long_description: + restview --long-description + +.PHONY: all diff --git a/PPOCRLabel/PPOCRLabel.py b/PPOCRLabel/PPOCRLabel.py new file mode 100644 index 0000000000..b4c73083c4 --- /dev/null +++ b/PPOCRLabel/PPOCRLabel.py @@ -0,0 +1,2014 @@ +# Copyright (c) <2015-Present> Tzutalin +# Copyright (C) 2013 MIT, Computer Science and Artificial Intelligence Laboratory. Bryan Russell, Antonio Torralba, +# William T. Freeman. Permission is hereby granted, free of charge, to any person obtaining a copy of this software and +# associated documentation files (the "Software"), to deal in the Software without restriction, including without +# limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the +# Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: +# The above copyright notice and this permission notice shall be included in all copies or substantial portions of +# the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT +# NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT +# SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF +# CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN +# THE SOFTWARE. + +#!/usr/bin/env python +# -*- coding: utf-8 -*- +# pyrcc5 -o libs/resources.py resources.qrc +import argparse +import ast +import codecs +import os.path +import platform +import subprocess +import sys +from functools import partial +from collections import defaultdict +import json + + +__dir__ = os.path.dirname(os.path.abspath(__file__)) +sys.path.append(__dir__) +sys.path.append(os.path.abspath(os.path.join(__dir__, '../..'))) +sys.path.append("..") + +from paddleocr import PaddleOCR + +try: + from PyQt5 import QtCore, QtGui, QtWidgets + from PyQt5.QtGui import * + from PyQt5.QtCore import * + from PyQt5.QtWidgets import * +except ImportError: + # needed for py3+qt4 + # Ref: + # http://pyqt.sourceforge.net/Docs/PyQt4/incompatible_apis.html + # http://stackoverflow.com/questions/21217399/pyqt4-qtcore-qvariant-object-instead-of-a-string + if sys.version_info.major >= 3: + import sip + + sip.setapi('QVariant', 2) + from PyQt4.QtGui import * + from PyQt4.QtCore import * + +from combobox import ComboBox +from libs.constants import * +from libs.utils import * +from libs.settings import Settings +from libs.shape import Shape, DEFAULT_LINE_COLOR, DEFAULT_FILL_COLOR +from libs.stringBundle import StringBundle +from libs.canvas import Canvas +from libs.zoomWidget import ZoomWidget +from libs.autoDialog import AutoDialog +from libs.labelDialog import LabelDialog +from libs.colorDialog import ColorDialog +from libs.toolBar import ToolBar +from libs.ustr import ustr +from libs.hashableQListWidgetItem import HashableQListWidgetItem + +__appname__ = 'PPOCRLabel' + + +class WindowMixin(object): + + def menu(self, title, actions=None): + menu = self.menuBar().addMenu(title) + if actions: + addActions(menu, actions) + return menu + + def toolbar(self, title, actions=None): + toolbar = ToolBar(title) + toolbar.setObjectName(u'%sToolBar' % title) + # toolbar.setOrientation(Qt.Vertical) + toolbar.setToolButtonStyle(Qt.ToolButtonTextUnderIcon) + if actions: + addActions(toolbar, actions) + self.addToolBar(Qt.LeftToolBarArea, toolbar) + return toolbar + + +class MainWindow(QMainWindow, WindowMixin): + FIT_WINDOW, FIT_WIDTH, MANUAL_ZOOM = list(range(3)) + + def __init__(self, lang="ch", defaultFilename=None, defaultPrefdefClassFile=None, defaultSaveDir=None): + super(MainWindow, self).__init__() + self.setWindowTitle(__appname__) + + # Load setting in the main thread + self.settings = Settings() + self.settings.load() + settings = self.settings + self.lang = lang + # Load string bundle for i18n + if lang not in ['ch', 'en']: + lang = 'en' + self.stringBundle = StringBundle.getBundle(localeStr='zh-CN' if lang=='ch' else 'en') # 'en' + getStr = lambda strId: self.stringBundle.getString(strId) + + self.defaultSaveDir = defaultSaveDir + self.ocr = PaddleOCR(use_pdserving=False, use_angle_cls=True, det=True, cls=True, use_gpu=False, lang=lang) + + if os.path.exists('./data/paddle.png'): + result = self.ocr.ocr('./data/paddle.png', cls=True, det=True) + + # For loading all image under a directory + self.mImgList = [] + self.mImgList5 = [] + self.dirname = None + self.labelHist = [] + self.lastOpenDir = None + self.result_dic = [] + + self.changeFileFolder = False + self.haveAutoReced = False + self.labelFile = None + self.currIndex = 0 + + + # Whether we need to save or not. + self.dirty = False + + self._noSelectionSlot = False + self._beginner = True + self.screencastViewer = self.getAvailableScreencastViewer() + self.screencast = "https://github.com/PaddlePaddle/PaddleOCR" + + # Load predefined classes to the list + self.loadPredefinedClasses(defaultPrefdefClassFile) + + # Main widgets and related state. + self.labelDialog = LabelDialog(parent=self, listItem=self.labelHist) + self.autoDialog = AutoDialog(parent=self) + + self.itemsToShapes = {} + self.shapesToItems = {} + self.itemsToShapesbox = {} + self.shapesToItemsbox = {} + self.prevLabelText = getStr('tempLabel') + self.model = 'paddle' + self.PPreader = None + self.autoSaveNum = 10 + + ################# file list ############### + self.fileListWidget = QListWidget() + self.fileListWidget.itemClicked.connect(self.fileitemDoubleClicked) + self.fileListWidget.setIconSize(QSize(25, 25)) + filelistLayout = QVBoxLayout() + filelistLayout.setContentsMargins(0, 0, 0, 0) + filelistLayout.addWidget(self.fileListWidget) + + self.AutoRecognition = QToolButton() + self.AutoRecognition.setToolButtonStyle(Qt.ToolButtonTextBesideIcon) + self.AutoRecognition.setIcon(newIcon('Auto')) + autoRecLayout = QHBoxLayout() + autoRecLayout.setContentsMargins(0, 0, 0, 0) + autoRecLayout.addWidget(self.AutoRecognition) + autoRecContainer = QWidget() + autoRecContainer.setLayout(autoRecLayout) + filelistLayout.addWidget(autoRecContainer) + + fileListContainer = QWidget() + fileListContainer.setLayout(filelistLayout) + self.filedock = QDockWidget(getStr('fileList'), self) + self.filedock.setObjectName(getStr('files')) + self.filedock.setWidget(fileListContainer) + self.addDockWidget(Qt.LeftDockWidgetArea, self.filedock) + + ######## Right area ########## + listLayout = QVBoxLayout() + listLayout.setContentsMargins(0, 0, 0, 0) + + self.editButton = QToolButton() + self.reRecogButton = QToolButton() + self.reRecogButton.setIcon(newIcon('reRec', 30)) + self.reRecogButton.setToolButtonStyle(Qt.ToolButtonTextBesideIcon) + + self.newButton = QToolButton() + self.newButton.setToolButtonStyle(Qt.ToolButtonTextBesideIcon) + self.SaveButton = QToolButton() + self.SaveButton.setToolButtonStyle(Qt.ToolButtonTextBesideIcon) + self.DelButton = QToolButton() + self.DelButton.setToolButtonStyle(Qt.ToolButtonTextBesideIcon) + + + lefttoptoolbox = QHBoxLayout() + lefttoptoolbox.addWidget(self.newButton) + lefttoptoolbox.addWidget(self.reRecogButton) + lefttoptoolboxcontainer = QWidget() + lefttoptoolboxcontainer.setLayout(lefttoptoolbox) + listLayout.addWidget(lefttoptoolboxcontainer) + + + ################## label list #################### + # Create and add a widget for showing current label items + self.labelList = QListWidget() + labelListContainer = QWidget() + labelListContainer.setLayout(listLayout) + self.labelList.itemActivated.connect(self.labelSelectionChanged) + self.labelList.itemSelectionChanged.connect(self.labelSelectionChanged) + self.labelList.itemDoubleClicked.connect(self.editLabel) + # Connect to itemChanged to detect checkbox changes. + self.labelList.itemChanged.connect(self.labelItemChanged) + self.labelListDock = QDockWidget(getStr('recognitionResult'),self) + self.labelListDock.setWidget(self.labelList) + self.labelListDock.setFeatures(QDockWidget.NoDockWidgetFeatures) + listLayout.addWidget(self.labelListDock) + + ################## detection box #################### + self.BoxList = QListWidget() + + self.BoxList.itemActivated.connect(self.boxSelectionChanged) + self.BoxList.itemSelectionChanged.connect(self.boxSelectionChanged) + self.BoxList.itemDoubleClicked.connect(self.editBox) + # Connect to itemChanged to detect checkbox changes. + self.BoxList.itemChanged.connect(self.boxItemChanged) + self.BoxListDock = QDockWidget(getStr('detectionBoxposition'), self) + self.BoxListDock.setWidget(self.BoxList) + self.BoxListDock.setFeatures(QDockWidget.NoDockWidgetFeatures) + listLayout.addWidget(self.BoxListDock) + + ############ lower right area ############ + leftbtmtoolbox = QHBoxLayout() + leftbtmtoolbox.addWidget(self.SaveButton) + leftbtmtoolbox.addWidget(self.DelButton) + leftbtmtoolboxcontainer = QWidget() + leftbtmtoolboxcontainer.setLayout(leftbtmtoolbox) + listLayout.addWidget(leftbtmtoolboxcontainer) + + self.dock = QDockWidget(getStr('boxLabelText'), self) + self.dock.setObjectName(getStr('labels')) + self.dock.setWidget(labelListContainer) + + + ########## zoom bar ######### + self.imgsplider = QSlider(Qt.Horizontal) + self.imgsplider.valueChanged.connect(self.CanvasSizeChange) + self.imgsplider.setMinimum(-150) + self.imgsplider.setMaximum(150) + self.imgsplider.setSingleStep(1) + self.imgsplider.setTickPosition(QSlider.TicksBelow) + self.imgsplider.setTickInterval(1) + op = QGraphicsOpacityEffect() + op.setOpacity(0.2) + self.imgsplider.setGraphicsEffect(op) + # self.imgsplider.setAttribute(Qt.WA_TranslucentBackground) + self.imgsplider.setStyleSheet("background-color:transparent") + self.imgsliderDock = QDockWidget(getStr('ImageResize'), self) + self.imgsliderDock.setObjectName(getStr('IR')) + self.imgsliderDock.setWidget(self.imgsplider) + self.imgsliderDock.setFeatures(QDockWidget.DockWidgetFloatable) + self.imgsliderDock.setAttribute(Qt.WA_TranslucentBackground) + self.addDockWidget(Qt.RightDockWidgetArea, self.imgsliderDock) + + self.zoomWidget = ZoomWidget() + self.colorDialog = ColorDialog(parent=self) + self.zoomWidgetValue = self.zoomWidget.value() + + ########## thumbnail ######### + hlayout = QHBoxLayout() + m = (0, 0, 0, 0) + hlayout.setSpacing(0) + hlayout.setContentsMargins(*m) + self.preButton = QToolButton() + self.preButton.setIcon(newIcon("prev",40)) + self.preButton.setIconSize(QSize(40, 100)) + self.preButton.clicked.connect(self.openPrevImg) + self.preButton.setStyleSheet('border: none;') + self.preButton.setShortcut('a') + self.iconlist = QListWidget() + self.iconlist.setViewMode(QListView.IconMode) + self.iconlist.setFlow(QListView.TopToBottom) + self.iconlist.setSpacing(10) + self.iconlist.setIconSize(QSize(50, 50)) + self.iconlist.setMovement(False) + self.iconlist.setResizeMode(QListView.Adjust) + self.iconlist.itemClicked.connect(self.iconitemDoubleClicked) + self.iconlist.setStyleSheet("background-color:transparent; border: none;") + self.iconlist.setHorizontalScrollBarPolicy(Qt.ScrollBarAlwaysOff) + self.nextButton = QToolButton() + self.nextButton.setIcon(newIcon("next", 40)) + self.nextButton.setIconSize(QSize(40, 100)) + self.nextButton.setStyleSheet('border: none;') + self.nextButton.clicked.connect(self.openNextImg) + self.nextButton.setShortcut('d') + + hlayout.addWidget(self.preButton) + hlayout.addWidget(self.iconlist) + hlayout.addWidget(self.nextButton) + + + iconListContainer = QWidget() + iconListContainer.setLayout(hlayout) + iconListContainer.setFixedHeight(100) + + ########### Canvas ########### + self.canvas = Canvas(parent=self) + self.canvas.zoomRequest.connect(self.zoomRequest) + self.canvas.setDrawingShapeToSquare(settings.get(SETTING_DRAW_SQUARE, False)) + + scroll = QScrollArea() + scroll.setWidget(self.canvas) + scroll.setWidgetResizable(True) + self.scrollBars = { + Qt.Vertical: scroll.verticalScrollBar(), + Qt.Horizontal: scroll.horizontalScrollBar() + } + self.scrollArea = scroll + self.canvas.scrollRequest.connect(self.scrollRequest) + + self.canvas.newShape.connect(self.newShape) + self.canvas.shapeMoved.connect(self.updateBoxlist) # self.setDirty + self.canvas.selectionChanged.connect(self.shapeSelectionChanged) + self.canvas.drawingPolygon.connect(self.toggleDrawingSensitive) + + centerLayout = QVBoxLayout() + centerLayout.setContentsMargins(0, 0, 0, 0) + centerLayout.addWidget(scroll) + #centerLayout.addWidget(self.icondock) + centerLayout.addWidget(iconListContainer,0,Qt.AlignCenter) + centercontainer = QWidget() + centercontainer.setLayout(centerLayout) + + # self.scrolldock = QDockWidget('WorkSpace',self) + # self.scrolldock.setObjectName('WorkSpace') + # self.scrolldock.setWidget(centercontainer) + # self.scrolldock.setFeatures(QDockWidget.NoDockWidgetFeatures) + # orititle = self.scrolldock.titleBarWidget() + # tmpwidget = QWidget() + # self.scrolldock.setTitleBarWidget(tmpwidget) + # del orititle + self.setCentralWidget(centercontainer) #self.scrolldock + self.addDockWidget(Qt.RightDockWidgetArea, self.dock) + + + # self.filedock.setFeatures(QDockWidget.DockWidgetFloatable) + self.filedock.setFeatures(self.filedock.features() ^ QDockWidget.DockWidgetFloatable) + + self.dockFeatures = QDockWidget.DockWidgetClosable | QDockWidget.DockWidgetFloatable + self.dock.setFeatures(self.dock.features() ^ self.dockFeatures) + + self.filedock.setFeatures(QDockWidget.NoDockWidgetFeatures) + + ###### Actions ####### + action = partial(newAction, self) + quit = action(getStr('quit'), self.close, + 'Ctrl+Q', 'quit', getStr('quitApp')) + + open = action(getStr('openFile'), self.openFile, + 'Ctrl+O', 'open', getStr('openFileDetail')) + + opendir = action(getStr('openDir'), self.openDirDialog, + 'Ctrl+u', 'open', getStr('openDir')) + + + save = action(getStr('save'), self.saveFile, + 'Ctrl+V', 'verify', getStr('saveDetail'), enabled=False) + + alcm = action(getStr('choosemodel'), self.autolcm, + 'Ctrl+M', 'next', getStr('tipchoosemodel')) + + deleteImg = action(getStr('deleteImg'), self.deleteImg, 'Ctrl+Shift+D', 'close', getStr('deleteImgDetail'), + enabled=True) + + resetAll = action(getStr('resetAll'), self.resetAll, None, 'resetall', getStr('resetAllDetail')) + + color1 = action(getStr('boxLineColor'), self.chooseColor1, + 'Ctrl+L', 'color_line', getStr('boxLineColorDetail')) + + createMode = action(getStr('crtBox'), self.setCreateMode, + 'w', 'new', getStr('crtBoxDetail'), enabled=False) + editMode = action('&Edit\nRectBox', self.setEditMode, + 'Ctrl+J', 'edit', u'Move and edit Boxs', enabled=False) + + create = action(getStr('crtBox'), self.createShape, + 'w', 'new', getStr('crtBoxDetail'), enabled=False) + + delete = action(getStr('delBox'), self.deleteSelectedShape, + 'backspace', 'delete', getStr('delBoxDetail'), enabled=False) + copy = action(getStr('dupBox'), self.copySelectedShape, + 'Ctrl+C', 'copy', getStr('dupBoxDetail'), + enabled=False) + + hideAll = action(getStr('hideBox'), partial(self.togglePolygons, False), + 'Ctrl+H', 'hide', getStr('hideAllBoxDetail'), + enabled=False) + showAll = action(getStr('showBox'), partial(self.togglePolygons, True), + 'Ctrl+A', 'hide', getStr('showAllBoxDetail'), + enabled=False) + + help = action(getStr('tutorial'), self.showTutorialDialog, None, 'help', getStr('tutorialDetail')) + showInfo = action(getStr('info'), self.showInfoDialog, None, 'help', getStr('info')) + showSteps = action(getStr('steps'), self.showStepsDialog, None, 'help', getStr('steps')) + + zoom = QWidgetAction(self) + zoom.setDefaultWidget(self.zoomWidget) + self.zoomWidget.setWhatsThis( + u"Zoom in or out of the image. Also accessible with" + " %s and %s from the canvas." % (fmtShortcut("Ctrl+[-+]"), + fmtShortcut("Ctrl+Wheel"))) + self.zoomWidget.setEnabled(False) + + zoomIn = action(getStr('zoomin'), partial(self.addZoom, 10), + 'Ctrl++', 'zoom-in', getStr('zoominDetail'), enabled=False) + zoomOut = action(getStr('zoomout'), partial(self.addZoom, -10), + 'Ctrl+-', 'zoom-out', getStr('zoomoutDetail'), enabled=False) + zoomOrg = action(getStr('originalsize'), partial(self.setZoom, 100), + 'Ctrl+=', 'zoom', getStr('originalsizeDetail'), enabled=False) + fitWindow = action(getStr('fitWin'), self.setFitWindow, + 'Ctrl+F', 'fit-window', getStr('fitWinDetail'), + checkable=True, enabled=False) + fitWidth = action(getStr('fitWidth'), self.setFitWidth, + 'Ctrl+Shift+F', 'fit-width', getStr('fitWidthDetail'), + checkable=True, enabled=False) + # Group zoom controls into a list for easier toggling. + zoomActions = (self.zoomWidget, zoomIn, zoomOut, + zoomOrg, fitWindow, fitWidth) + self.zoomMode = self.MANUAL_ZOOM + self.scalers = { + self.FIT_WINDOW: self.scaleFitWindow, + self.FIT_WIDTH: self.scaleFitWidth, + # Set to one to scale to 100% when loading files. + self.MANUAL_ZOOM: lambda: 1, + } + + edit = action(getStr('editLabel'), self.editLabel, + 'Ctrl+E', 'edit', getStr('editLabelDetail'), + enabled=False) + + ######## New actions ####### + AutoRec = action(getStr('autoRecognition'), self.autoRecognition, + 'Ctrl+Shift+A', 'Auto', getStr('autoRecognition'), enabled=False) + + reRec = action(getStr('reRecognition'), self.reRecognition, + 'Ctrl+Shift+R', 'reRec', getStr('reRecognition'), enabled=False) + + singleRere = action(getStr('singleRe'), self.singleRerecognition, + 'Ctrl+R', 'reRec', getStr('singleRe'), enabled=False) + + createpoly = action(getStr('creatPolygon'), self.createPolygon, + 'q', 'new', 'Creat Polygon', enabled=True) + + saveRec = action(getStr('saveRec'), self.saveRecResult, + '', 'save', getStr('saveRec'), enabled=False) + + saveLabel = action(getStr('saveLabel'), self.saveLabelFile, # + 'Ctrl+S', 'save', getStr('saveLabel'), enabled=False) + + self.editButton.setDefaultAction(edit) + self.newButton.setDefaultAction(create) + self.DelButton.setDefaultAction(deleteImg) + self.SaveButton.setDefaultAction(save) + self.AutoRecognition.setDefaultAction(AutoRec) + self.reRecogButton.setDefaultAction(reRec) + # self.preButton.setDefaultAction(openPrevImg) + # self.nextButton.setDefaultAction(openNextImg) + + ############# Zoom layout ############## + zoomLayout = QHBoxLayout() + zoomLayout.addStretch() + self.zoominButton = QToolButton() + self.zoominButton.setToolButtonStyle(Qt.ToolButtonTextBesideIcon) + self.zoominButton.setDefaultAction(zoomIn) + self.zoomoutButton = QToolButton() + self.zoomoutButton.setToolButtonStyle(Qt.ToolButtonTextBesideIcon) + self.zoomoutButton.setDefaultAction(zoomOut) + self.zoomorgButton = QToolButton() + self.zoomorgButton.setToolButtonStyle(Qt.ToolButtonTextBesideIcon) + self.zoomorgButton.setDefaultAction(zoomOrg) + zoomLayout.addWidget(self.zoominButton) + zoomLayout.addWidget(self.zoomorgButton) + zoomLayout.addWidget(self.zoomoutButton) + + zoomContainer = QWidget() + zoomContainer.setLayout(zoomLayout) + zoomContainer.setGeometry(0, 0, 30, 150) + + shapeLineColor = action(getStr('shapeLineColor'), self.chshapeLineColor, + icon='color_line', tip=getStr('shapeLineColorDetail'), + enabled=False) + shapeFillColor = action(getStr('shapeFillColor'), self.chshapeFillColor, + icon='color', tip=getStr('shapeFillColorDetail'), + enabled=False) + + + # Label list context menu. + labelMenu = QMenu() + addActions(labelMenu, (edit, delete)) + + self.labelList.setContextMenuPolicy(Qt.CustomContextMenu) + self.labelList.customContextMenuRequested.connect( + self.popLabelListMenu) + + # Draw squares/rectangles + self.drawSquaresOption = QAction(getStr('drawSquares'), self) + self.drawSquaresOption.setCheckable(True) + self.drawSquaresOption.setChecked(settings.get(SETTING_DRAW_SQUARE, False)) + self.drawSquaresOption.triggered.connect(self.toogleDrawSquare) + + # Store actions for further handling. + self.actions = struct(save=save, open=open, resetAll=resetAll, deleteImg=deleteImg, + lineColor=color1, create=create, delete=delete, edit=edit, copy=copy, + saveRec=saveRec, singleRere=singleRere,AutoRec=AutoRec,reRec=reRec, + createMode=createMode, editMode=editMode, + shapeLineColor=shapeLineColor, shapeFillColor=shapeFillColor, + zoom=zoom, zoomIn=zoomIn, zoomOut=zoomOut, zoomOrg=zoomOrg, + fitWindow=fitWindow, fitWidth=fitWidth, + zoomActions=zoomActions, saveLabel=saveLabel, + fileMenuActions=( + open, opendir, saveLabel, resetAll, quit), + beginner=(), advanced=(), + editMenu=(createpoly, edit, copy, delete,singleRere, + None, color1, self.drawSquaresOption), + beginnerContext=(create, edit, copy, delete, singleRere), + advancedContext=(createMode, editMode, edit, copy, + delete, shapeLineColor, shapeFillColor), + onLoadActive=( + create, createMode, editMode), + onShapesPresent=(hideAll, showAll)) + + # menus + self.menus = struct( + file=self.menu('&'+getStr('mfile')), + edit=self.menu('&'+getStr('medit')), + view=self.menu('&'+getStr('mview')), + autolabel=self.menu('&PaddleOCR'), + help=self.menu('&'+getStr('mhelp')), + recentFiles=QMenu('Open &Recent'), + labelList=labelMenu) + + + # Sync single class mode from PR#106 + self.singleClassMode = QAction(getStr('singleClsMode'), self) + self.singleClassMode.setShortcut("Ctrl+Shift+S") + self.singleClassMode.setCheckable(True) + self.singleClassMode.setChecked(settings.get(SETTING_SINGLE_CLASS, False)) + self.lastLabel = None + # Add option to enable/disable labels being displayed at the top of bounding boxes + self.displayLabelOption = QAction(getStr('displayLabel'), self) + self.displayLabelOption.setShortcut("Ctrl+Shift+P") + self.displayLabelOption.setCheckable(True) + self.displayLabelOption.setChecked(settings.get(SETTING_PAINT_LABEL, False)) + self.displayLabelOption.triggered.connect(self.togglePaintLabelsOption) + + addActions(self.menus.file, + (opendir, None, saveLabel, saveRec, None, resetAll, deleteImg, quit)) + + addActions(self.menus.help, (showSteps, showInfo)) + addActions(self.menus.view, ( + self.displayLabelOption, # labels, + None, + hideAll, showAll, None, + zoomIn, zoomOut, zoomOrg, None, + fitWindow, fitWidth)) + + addActions(self.menus.autolabel, (AutoRec, reRec, alcm, None, help)) # + + self.menus.file.aboutToShow.connect(self.updateFileMenu) + + # Custom context menu for the canvas widget: + addActions(self.canvas.menus[0], self.actions.beginnerContext) + addActions(self.canvas.menus[1], ( + action('&Copy here', self.copyShape), + action('&Move here', self.moveShape))) + + + self.statusBar().showMessage('%s started.' % __appname__) + self.statusBar().show() + + # Application state. + self.image = QImage() + self.filePath = ustr(defaultFilename) + self.lastOpenDir = None + self.recentFiles = [] + self.maxRecent = 7 + self.lineColor = None + self.fillColor = None + self.zoom_level = 100 + self.fit_window = False + # Add Chris + self.difficult = False + + ## Fix the compatible issue for qt4 and qt5. Convert the QStringList to python list + if settings.get(SETTING_RECENT_FILES): + if have_qstring(): + recentFileQStringList = settings.get(SETTING_RECENT_FILES) + self.recentFiles = [ustr(i) for i in recentFileQStringList] + else: + self.recentFiles = recentFileQStringList = settings.get(SETTING_RECENT_FILES) + + size = settings.get(SETTING_WIN_SIZE, QSize(1200, 800)) + + position = QPoint(0, 0) + saved_position = settings.get(SETTING_WIN_POSE, position) + # Fix the multiple monitors issue + for i in range(QApplication.desktop().screenCount()): + if QApplication.desktop().availableGeometry(i).contains(saved_position): + position = saved_position + break + self.resize(size) + self.move(position) + saveDir = ustr(settings.get(SETTING_SAVE_DIR, None)) + self.lastOpenDir = ustr(settings.get(SETTING_LAST_OPEN_DIR, None)) + + self.restoreState(settings.get(SETTING_WIN_STATE, QByteArray())) + Shape.line_color = self.lineColor = QColor(settings.get(SETTING_LINE_COLOR, DEFAULT_LINE_COLOR)) + Shape.fill_color = self.fillColor = QColor(settings.get(SETTING_FILL_COLOR, DEFAULT_FILL_COLOR)) + self.canvas.setDrawingColor(self.lineColor) + # Add chris + Shape.difficult = self.difficult + + + # ADD: + # Populate the File menu dynamically. + self.updateFileMenu() + + # Since loading the file may take some time, make sure it runs in the background. + if self.filePath and os.path.isdir(self.filePath): + self.queueEvent(partial(self.importDirImages, self.filePath or "")) + elif self.filePath: + self.queueEvent(partial(self.loadFile, self.filePath or "")) + + # Callbacks: + self.zoomWidget.valueChanged.connect(self.paintCanvas) + + self.populateModeActions() + + # Display cursor coordinates at the right of status bar + self.labelCoordinates = QLabel('') + self.statusBar().addPermanentWidget(self.labelCoordinates) + + # Open Dir if deafult file + if self.filePath and os.path.isdir(self.filePath): + self.openDirDialog(dirpath=self.filePath, silent=True) + + def keyReleaseEvent(self, event): + if event.key() == Qt.Key_Control: + self.canvas.setDrawingShapeToSquare(False) + + def keyPressEvent(self, event): + if event.key() == Qt.Key_Control: + # Draw rectangle if Ctrl is pressed + self.canvas.setDrawingShapeToSquare(True) + + + def noShapes(self): + return not self.itemsToShapes + + + def populateModeActions(self): + self.canvas.menus[0].clear() + addActions(self.canvas.menus[0], self.actions.beginnerContext) + self.menus.edit.clear() + actions = (self.actions.create,) # if self.beginner() else (self.actions.createMode, self.actions.editMode) + addActions(self.menus.edit, actions + self.actions.editMenu) + + + def setDirty(self): + self.dirty = True + self.actions.save.setEnabled(True) + + def setClean(self): + self.dirty = False + self.actions.save.setEnabled(False) + self.actions.create.setEnabled(True) + + def toggleActions(self, value=True): + """Enable/Disable widgets which depend on an opened image.""" + for z in self.actions.zoomActions: + z.setEnabled(value) + for action in self.actions.onLoadActive: + action.setEnabled(value) + + def queueEvent(self, function): + QTimer.singleShot(0, function) + + def status(self, message, delay=5000): + self.statusBar().showMessage(message, delay) + + def resetState(self): + self.itemsToShapes.clear() + self.shapesToItems.clear() + self.itemsToShapesbox.clear() # ADD + self.shapesToItemsbox.clear() + self.labelList.clear() + self.BoxList.clear() + self.filePath = None + self.imageData = None + self.labelFile = None + self.canvas.resetState() + self.labelCoordinates.clear() + # self.comboBox.cb.clear() + self.result_dic = [] + + def currentItem(self): + items = self.labelList.selectedItems() + if items: + return items[0] + return None + + def currentBox(self): + items = self.BoxList.selectedItems() + if items: + return items[0] + return None + + def addRecentFile(self, filePath): + if filePath in self.recentFiles: + self.recentFiles.remove(filePath) + elif len(self.recentFiles) >= self.maxRecent: + self.recentFiles.pop() + self.recentFiles.insert(0, filePath) + + def beginner(self): + return self._beginner + + def advanced(self): + return not self.beginner() + + def getAvailableScreencastViewer(self): + osName = platform.system() + + if osName == 'Windows': + return ['C:\\Program Files\\Internet Explorer\\iexplore.exe'] + elif osName == 'Linux': + return ['xdg-open'] + elif osName == 'Darwin': + return ['open'] + + ## Callbacks ## + def showTutorialDialog(self): + subprocess.Popen(self.screencastViewer + [self.screencast]) + + def showInfoDialog(self): + from libs.__init__ import __version__ + msg = u'Name:{0} \nApp Version:{1} \n{2} '.format(__appname__, __version__, sys.version_info) + QMessageBox.information(self, u'Information', msg) + + def showStepsDialog(self): + msg = stepsInfo(self.lang) + QMessageBox.information(self, u'Information', msg) + + def createShape(self): + assert self.beginner() + self.canvas.setEditing(False) + self.actions.create.setEnabled(False) + self.canvas.fourpoint = False + + def createPolygon(self): + assert self.beginner() + self.canvas.setEditing(False) + self.canvas.fourpoint = True + self.actions.create.setEnabled(False) + + def toggleDrawingSensitive(self, drawing=True): + """In the middle of drawing, toggling between modes should be disabled.""" + self.actions.editMode.setEnabled(not drawing) + if not drawing and self.beginner(): + # Cancel creation. + print('Cancel creation.') + self.canvas.setEditing(True) + self.canvas.restoreCursor() + self.actions.create.setEnabled(True) + + def toggleDrawMode(self, edit=True): + self.canvas.setEditing(edit) + self.actions.createMode.setEnabled(edit) + self.actions.editMode.setEnabled(not edit) + + def setCreateMode(self): + assert self.advanced() + self.toggleDrawMode(False) + + def setEditMode(self): + assert self.advanced() + self.toggleDrawMode(True) + self.labelSelectionChanged() + + def updateFileMenu(self): + currFilePath = self.filePath + + def exists(filename): + return os.path.exists(filename) + + menu = self.menus.recentFiles + menu.clear() + files = [f for f in self.recentFiles if f != + currFilePath and exists(f)] + for i, f in enumerate(files): + icon = newIcon('labels') + action = QAction( + icon, '&%d %s' % (i + 1, QFileInfo(f).fileName()), self) + action.triggered.connect(partial(self.loadRecent, f)) + menu.addAction(action) + + def popLabelListMenu(self, point): + self.menus.labelList.exec_(self.labelList.mapToGlobal(point)) + + def editLabel(self): + if not self.canvas.editing(): + return + item = self.currentItem() + if not item: + return + text = self.labelDialog.popUp(item.text()) + if text is not None: + item.setText(text) + # item.setBackground(generateColorByText(text)) + self.setDirty() + self.updateComboBox() + + ######## detection box related functions ####### + + def boxItemChanged(self, item): + shape = self.itemsToShapesbox[item] + + box = ast.literal_eval(item.text()) + # print('shape in labelItemChanged is',shape.points) + if box != [(p.x(), p.y()) for p in shape.points]: + # shape.points = box + shape.points = [QPointF(p[0], p[1]) for p in box] + + # QPointF(x,y) + # shape.line_color = generateColorByText(shape.label) + self.setDirty() + else: # User probably changed item visibility + self.canvas.setShapeVisible(shape, True)#item.checkState() == Qt.Checked + + def editBox(self): # ADD + if not self.canvas.editing(): + return + item = self.currentBox() + if not item: + return + text = self.labelDialog.popUp(item.text()) + + imageSize = str(self.image.size()) + width, height = self.image.width(), self.image.height() + if text: + try: + text_list = eval(text) + except: + msg_box = QMessageBox(QMessageBox.Warning, 'Warning', 'Please enter the correct format') + msg_box.exec_() + return + if len(text_list) < 4: + msg_box = QMessageBox(QMessageBox.Warning, 'Warning', 'Please enter the coordinates of 4 points') + msg_box.exec_() + return + for box in text_list: + if box[0] > width or box[0] < 0 or box[1] > height or box[1] < 0: + msg_box = QMessageBox(QMessageBox.Warning, 'Warning', 'Out of picture size') + msg_box.exec_() + return + + item.setText(text) + # item.setBackground(generateColorByText(text)) + self.setDirty() + self.updateComboBox() + + def updateBoxlist(self): + shape = self.canvas.selectedShape + item = self.shapesToItemsbox[shape] # listitem + text = [(int(p.x()), int(p.y())) for p in shape.points] + item.setText(str(text)) + self.setDirty() + + def indexTo5Files(self, currIndex): + if currIndex < 2: + return self.mImgList[:5] + elif currIndex > len(self.mImgList)-3: + return self.mImgList[-5:] + else: + return self.mImgList[currIndex - 2 : currIndex + 3] + + + # Tzutalin 20160906 : Add file list and dock to move faster + def fileitemDoubleClicked(self, item=None): + self.currIndex = self.mImgList.index(ustr(os.path.join(os.path.abspath(self.dirname), item.text()))) + filename = self.mImgList[self.currIndex] + if filename: + self.mImgList5 = self.indexTo5Files(self.currIndex) + # self.additems5(None) + self.loadFile(filename) + + def iconitemDoubleClicked(self, item=None): + self.currIndex = self.mImgList.index(ustr(os.path.join(item.toolTip()))) + filename = self.mImgList[self.currIndex] + if filename: + self.mImgList5 = self.indexTo5Files(self.currIndex) + # self.additems5(None) + self.loadFile(filename) + + def CanvasSizeChange(self): + if len(self.mImgList) > 0: + self.zoomWidget.setValue(self.zoomWidgetValue + self.imgsplider.value()) + + # React to canvas signals. + def shapeSelectionChanged(self, selected=False): + if self._noSelectionSlot: + self._noSelectionSlot = False + else: + shape = self.canvas.selectedShape + if shape: + self.shapesToItems[shape].setSelected(True) + self.shapesToItemsbox[shape].setSelected(True) # ADD + else: + self.labelList.clearSelection() + self.actions.delete.setEnabled(selected) + self.actions.copy.setEnabled(selected) + self.actions.edit.setEnabled(selected) + self.actions.shapeLineColor.setEnabled(selected) + self.actions.shapeFillColor.setEnabled(selected) + self.actions.singleRere.setEnabled(selected) + + def addLabel(self, shape): + shape.paintLabel = self.displayLabelOption.isChecked() + item = HashableQListWidgetItem(shape.label) + item.setFlags(item.flags() | Qt.ItemIsUserCheckable) + item.setCheckState(Qt.Unchecked) if shape.difficult else item.setCheckState(Qt.Checked) + # Checked means difficult is False + # item.setBackground(generateColorByText(shape.label)) + self.itemsToShapes[item] = shape + self.shapesToItems[shape] = item + self.labelList.addItem(item) + # print('item in add label is ',[(p.x(), p.y()) for p in shape.points], shape.label) + + # ADD for box + item = HashableQListWidgetItem(str([(int(p.x()), int(p.y())) for p in shape.points])) + self.itemsToShapesbox[item] = shape + self.shapesToItemsbox[shape] = item + self.BoxList.addItem(item) + for action in self.actions.onShapesPresent: + action.setEnabled(True) + self.updateComboBox() + + def remLabel(self, shape): + if shape is None: + # print('rm empty label') + return + item = self.shapesToItems[shape] + self.labelList.takeItem(self.labelList.row(item)) + del self.shapesToItems[shape] + del self.itemsToShapes[item] + self.updateComboBox() + + # ADD: + item = self.shapesToItemsbox[shape] + self.BoxList.takeItem(self.BoxList.row(item)) + del self.shapesToItemsbox[shape] + del self.itemsToShapesbox[item] + self.updateComboBox() + + def loadLabels(self, shapes): + s = [] + for label, points, line_color, fill_color, difficult in shapes: + shape = Shape(label=label) + for x, y in points: + + # Ensure the labels are within the bounds of the image. If not, fix them. + x, y, snapped = self.canvas.snapPointToCanvas(x, y) + if snapped: + self.setDirty() + + shape.addPoint(QPointF(x, y)) + shape.difficult = difficult + shape.close() + s.append(shape) + + # if line_color: + # shape.line_color = QColor(*line_color) + # else: + # shape.line_color = generateColorByText(label) + # + # if fill_color: + # shape.fill_color = QColor(*fill_color) + # else: + # shape.fill_color = generateColorByText(label) + + self.addLabel(shape) + self.updateComboBox() + self.canvas.loadShapes(s) + + def singleLabel(self, shape): + if shape is None: + # print('rm empty label') + return + item = self.shapesToItems[shape] + item.setText(shape.label) + self.updateComboBox() + + # ADD: + item = self.shapesToItemsbox[shape] + item.setText(str([(int(p.x()), int(p.y())) for p in shape.points])) + self.updateComboBox() + + def updateComboBox(self): + # Get the unique labels and add them to the Combobox. + itemsTextList = [str(self.labelList.item(i).text()) for i in range(self.labelList.count())] + + uniqueTextList = list(set(itemsTextList)) + # Add a null row for showing all the labels + uniqueTextList.append("") + uniqueTextList.sort() + + # self.comboBox.update_items(uniqueTextList) + + def saveLabels(self, annotationFilePath, mode='Auto'): + # Mode is Auto means that labels will be loaded from self.result_dic totally, which is the output of ocr model + annotationFilePath = ustr(annotationFilePath) + + def format_shape(s): + # print('s in saveLabels is ',s) + return dict(label=s.label, # str + line_color=s.line_color.getRgb(), + fill_color=s.fill_color.getRgb(), + points=[(p.x(), p.y()) for p in s.points], # QPonitF + # add chris + difficult=s.difficult) # bool + + shapes = [] if mode == 'Auto' else \ + [format_shape(shape) for shape in self.canvas.shapes] + # Can add differrent annotation formats here + + for box in self.result_dic: + trans_dic = {"label": box[1][0], "points": box[0], 'difficult': False} + if trans_dic["label"] is "" and mode == 'Auto': + continue + shapes.append(trans_dic) + + try: + trans_dic = [] + for box in shapes: + trans_dic.append({"transcription": box['label'], "points": box['points'], 'difficult': box['difficult']}) + self.PPlabel[annotationFilePath] = trans_dic + + if mode == 'Auto': + self.Cachelabel[annotationFilePath] = trans_dic + + # else: + # self.labelFile.save(annotationFilePath, shapes, self.filePath, self.imageData, + # self.lineColor.getRgb(), self.fillColor.getRgb()) + # print('Image:{0} -> Annotation:{1}'.format(self.filePath, annotationFilePath)) + return True + except: + self.errorMessage(u'Error saving label data') + return False + + def copySelectedShape(self): + self.addLabel(self.canvas.copySelectedShape()) + # fix copy and delete + self.shapeSelectionChanged(True) + + + def labelSelectionChanged(self): + item = self.currentItem() + if item and self.canvas.editing(): + self._noSelectionSlot = True + self.canvas.selectShape(self.itemsToShapes[item]) + shape = self.itemsToShapes[item] + + def boxSelectionChanged(self): + item = self.currentBox() + if item and self.canvas.editing(): + self._noSelectionSlot = True + self.canvas.selectShape(self.itemsToShapesbox[item]) + shape = self.itemsToShapesbox[item] + + def labelItemChanged(self, item): + shape = self.itemsToShapes[item] + label = item.text() + if label != shape.label: + shape.label = item.text() + # shape.line_color = generateColorByText(shape.label) + self.setDirty() + elif not ((item.checkState()== Qt.Unchecked) ^ (not shape.difficult)): + shape.difficult = True if item.checkState() == Qt.Unchecked else False + self.setDirty() + else: # User probably changed item visibility + self.canvas.setShapeVisible(shape, True) # item.checkState() == Qt.Checked + # self.actions.save.setEnabled(True) + + # Callback functions: + def newShape(self): + """Pop-up and give focus to the label editor. + + position MUST be in global coordinates. + """ + if len(self.labelHist) > 0: + self.labelDialog = LabelDialog( + parent=self, listItem=self.labelHist) + + # Sync single class mode from PR#106 + if self.singleClassMode.isChecked() and self.lastLabel: + text = self.lastLabel + else: + text = self.labelDialog.popUp(text=self.prevLabelText) + self.lastLabel = text + + if text is not None: + self.prevLabelText = self.stringBundle.getString('tempLabel') + # generate_color = generateColorByText(text) + shape = self.canvas.setLastLabel(text, None, None)#generate_color, generate_color + self.addLabel(shape) + if self.beginner(): # Switch to edit mode. + self.canvas.setEditing(True) + self.actions.create.setEnabled(True) + else: + self.actions.editMode.setEnabled(True) + self.setDirty() + + else: + # self.canvas.undoLastLine() + self.canvas.resetAllLines() + + def scrollRequest(self, delta, orientation): + units = - delta / (8 * 15) + bar = self.scrollBars[orientation] + bar.setValue(bar.value() + bar.singleStep() * units) + + def setZoom(self, value): + self.actions.fitWidth.setChecked(False) + self.actions.fitWindow.setChecked(False) + self.zoomMode = self.MANUAL_ZOOM + self.zoomWidget.setValue(value) + + def addZoom(self, increment=10): + self.setZoom(self.zoomWidget.value() + increment) + + def zoomRequest(self, delta): + # get the current scrollbar positions + # calculate the percentages ~ coordinates + h_bar = self.scrollBars[Qt.Horizontal] + v_bar = self.scrollBars[Qt.Vertical] + + # get the current maximum, to know the difference after zooming + h_bar_max = h_bar.maximum() + v_bar_max = v_bar.maximum() + + # get the cursor position and canvas size + # calculate the desired movement from 0 to 1 + # where 0 = move left + # 1 = move right + # up and down analogous + cursor = QCursor() + pos = cursor.pos() + relative_pos = QWidget.mapFromGlobal(self, pos) + + cursor_x = relative_pos.x() + cursor_y = relative_pos.y() + + w = self.scrollArea.width() + h = self.scrollArea.height() + + # the scaling from 0 to 1 has some padding + # you don't have to hit the very leftmost pixel for a maximum-left movement + margin = 0.1 + move_x = (cursor_x - margin * w) / (w - 2 * margin * w) + move_y = (cursor_y - margin * h) / (h - 2 * margin * h) + + # clamp the values from 0 to 1 + move_x = min(max(move_x, 0), 1) + move_y = min(max(move_y, 0), 1) + + # zoom in + units = delta / (8 * 15) + scale = 10 + self.addZoom(scale * units) + + # get the difference in scrollbar values + # this is how far we can move + d_h_bar_max = h_bar.maximum() - h_bar_max + d_v_bar_max = v_bar.maximum() - v_bar_max + + # get the new scrollbar values + new_h_bar_value = h_bar.value() + move_x * d_h_bar_max + new_v_bar_value = v_bar.value() + move_y * d_v_bar_max + + h_bar.setValue(new_h_bar_value) + v_bar.setValue(new_v_bar_value) + + def setFitWindow(self, value=True): + if value: + self.actions.fitWidth.setChecked(False) + self.zoomMode = self.FIT_WINDOW if value else self.MANUAL_ZOOM + self.adjustScale() + + def setFitWidth(self, value=True): + if value: + self.actions.fitWindow.setChecked(False) + self.zoomMode = self.FIT_WIDTH if value else self.MANUAL_ZOOM + self.adjustScale() + + def togglePolygons(self, value): + for item, shape in self.itemsToShapes.items(): + self.canvas.setShapeVisible(shape, value) + + def loadFile(self, filePath=None): + """Load the specified file, or the last opened file if None.""" + self.resetState() + self.canvas.setEnabled(False) + if filePath is None: + filePath = self.settings.get(SETTING_FILENAME) + + # Make sure that filePath is a regular python string, rather than QString + filePath = ustr(filePath) + # Fix bug: An index error after select a directory when open a new file. + unicodeFilePath = ustr(filePath) + # unicodeFilePath = os.path.abspath(unicodeFilePath) + # Tzutalin 20160906 : Add file list and dock to move faster + # Highlight the file item + if unicodeFilePath and self.fileListWidget.count() > 0: + if unicodeFilePath in self.mImgList: + index = self.mImgList.index(unicodeFilePath) + fileWidgetItem = self.fileListWidget.item(index) + print('unicodeFilePath is', unicodeFilePath) + fileWidgetItem.setSelected(True) + ### + self.iconlist.clear() + self.additems5(None) + for i in range(5): + item_tooltip = self.iconlist.item(i).toolTip() + # print(i,"---",item_tooltip) + if item_tooltip == ustr(filePath): + titem = self.iconlist.item(i) + titem.setSelected(True) + self.iconlist.scrollToItem(titem) + break + else: + self.fileListWidget.clear() + self.mImgList.clear() + self.iconlist.clear() + + # if unicodeFilePath and self.iconList.count() > 0: + # if unicodeFilePath in self.mImgList: + + if unicodeFilePath and os.path.exists(unicodeFilePath): + self.imageData = read(unicodeFilePath, None) + self.canvas.verified = False + + image = QImage.fromData(self.imageData) + if image.isNull(): + self.errorMessage(u'Error opening file', + u"

Make sure %s is a valid image file." % unicodeFilePath) + self.status("Error reading %s" % unicodeFilePath) + return False + self.status("Loaded %s" % os.path.basename(unicodeFilePath)) + self.image = image + self.filePath = unicodeFilePath + self.canvas.loadPixmap(QPixmap.fromImage(image)) + + if self.validFilestate(filePath) is True: + self.setClean() + else: + self.dirty = False + self.actions.save.setEnabled(True) + + self.canvas.setEnabled(True) + self.adjustScale(initial=True) + self.paintCanvas() + self.addRecentFile(self.filePath) + self.toggleActions(True) + self.showBoundingBoxFromPPlabel(filePath) + + self.setWindowTitle(__appname__ + ' ' + filePath) + + # Default : select last item if there is at least one item + if self.labelList.count(): + self.labelList.setCurrentItem(self.labelList.item(self.labelList.count() - 1)) + self.labelList.item(self.labelList.count() - 1).setSelected(True) + + self.canvas.setFocus(True) + return True + return False + + + def showBoundingBoxFromPPlabel(self, filePath): + imgidx = self.getImglabelidx(filePath) + if imgidx not in self.PPlabel.keys(): + return + shapes = [] + for box in self.PPlabel[imgidx]: + shapes.append((box['transcription'], box['points'], None, None, box['difficult'])) + + print(shapes) + self.loadLabels(shapes) + self.canvas.verified = False + + + def validFilestate(self, filePath): + if filePath not in self.fileStatedict.keys(): + return None + elif self.fileStatedict[filePath] == 1: + return True + else: + return False + + def resizeEvent(self, event): + if self.canvas and not self.image.isNull() \ + and self.zoomMode != self.MANUAL_ZOOM: + self.adjustScale() + super(MainWindow, self).resizeEvent(event) + + def paintCanvas(self): + assert not self.image.isNull(), "cannot paint null image" + self.canvas.scale = 0.01 * self.zoomWidget.value() + self.canvas.adjustSize() + self.canvas.update() + + def adjustScale(self, initial=False): + value = self.scalers[self.FIT_WINDOW if initial else self.zoomMode]() + self.zoomWidget.setValue(int(100 * value)) + + def scaleFitWindow(self): + """Figure out the size of the pixmap in order to fit the main widget.""" + e = 2.0 # So that no scrollbars are generated. + w1 = self.centralWidget().width() - e + h1 = self.centralWidget().height() - e -110 + a1 = w1 / h1 + # Calculate a new scale value based on the pixmap's aspect ratio. + w2 = self.canvas.pixmap.width() - 0.0 + h2 = self.canvas.pixmap.height() - 0.0 + a2 = w2 / h2 + return w1 / w2 if a2 >= a1 else h1 / h2 + + def scaleFitWidth(self): + # The epsilon does not seem to work too well here. + w = self.centralWidget().width() - 2.0 + return w / self.canvas.pixmap.width() + + def closeEvent(self, event): + if not self.mayContinue(): + event.ignore() + else: + settings = self.settings + # If it loads images from dir, don't load it at the begining + if self.dirname is None: + settings[SETTING_FILENAME] = self.filePath if self.filePath else '' + else: + settings[SETTING_FILENAME] = '' + + settings[SETTING_WIN_SIZE] = self.size() + settings[SETTING_WIN_POSE] = self.pos() + settings[SETTING_WIN_STATE] = self.saveState() + settings[SETTING_LINE_COLOR] = self.lineColor + settings[SETTING_FILL_COLOR] = self.fillColor + settings[SETTING_RECENT_FILES] = self.recentFiles + settings[SETTING_ADVANCE_MODE] = not self._beginner + if self.defaultSaveDir and os.path.exists(self.defaultSaveDir): + settings[SETTING_SAVE_DIR] = ustr(self.defaultSaveDir) + else: + settings[SETTING_SAVE_DIR] = '' + + if self.lastOpenDir and os.path.exists(self.lastOpenDir): + settings[SETTING_LAST_OPEN_DIR] = self.lastOpenDir + else: + settings[SETTING_LAST_OPEN_DIR] = '' + + settings[SETTING_SINGLE_CLASS] = self.singleClassMode.isChecked() + settings[SETTING_PAINT_LABEL] = self.displayLabelOption.isChecked() + settings[SETTING_DRAW_SQUARE] = self.drawSquaresOption.isChecked() + settings.save() + try: + self.saveLabelFile() + except: + pass + + def loadRecent(self, filename): + if self.mayContinue(): + self.loadFile(filename) + + def scanAllImages(self, folderPath): + extensions = ['.%s' % fmt.data().decode("ascii").lower() for fmt in QImageReader.supportedImageFormats()] + images = [] + + for file in os.listdir(folderPath): + if file.lower().endswith(tuple(extensions)): + relativePath = os.path.join(folderPath, file) + path = ustr(os.path.abspath(relativePath)) + images.append(path) + natural_sort(images, key=lambda x: x.lower()) + return images + + + + def openDirDialog(self, _value=False, dirpath=None, silent=False): + if not self.mayContinue(): + return + + defaultOpenDirPath = dirpath if dirpath else '.' + if self.lastOpenDir and os.path.exists(self.lastOpenDir): + defaultOpenDirPath = self.lastOpenDir + else: + defaultOpenDirPath = os.path.dirname(self.filePath) if self.filePath else '.' + if silent != True: + targetDirPath = ustr(QFileDialog.getExistingDirectory(self, + '%s - Open Directory' % __appname__, + defaultOpenDirPath, + QFileDialog.ShowDirsOnly | QFileDialog.DontResolveSymlinks)) + else: + targetDirPath = ustr(defaultOpenDirPath) + self.lastOpenDir = targetDirPath + self.importDirImages(targetDirPath) + + def importDirImages(self, dirpath, isDelete = False): + if not self.mayContinue() or not dirpath: + return + if self.defaultSaveDir and self.defaultSaveDir != dirpath: + self.saveLabelFile() + + if not isDelete: + self.loadFilestate(dirpath) + self.PPlabelpath = dirpath+ '/Label.txt' + self.PPlabel = self.loadLabelFile(self.PPlabelpath) + self.Cachelabelpath = dirpath + '/Cache.cach' + self.Cachelabel = self.loadLabelFile(self.Cachelabelpath) + if self.Cachelabel: + self.PPlabel = dict(self.Cachelabel, **self.PPlabel) + self.lastOpenDir = dirpath + self.dirname = dirpath + + + self.defaultSaveDir = dirpath + self.statusBar().showMessage('%s started. Annotation will be saved to %s' % + (__appname__, self.defaultSaveDir)) + self.statusBar().show() + + self.filePath = None + self.fileListWidget.clear() + self.mImgList = self.scanAllImages(dirpath) + self.mImgList5 = self.mImgList[:5] + self.openNextImg() + doneicon = newIcon('done') + closeicon = newIcon('close') + for imgPath in self.mImgList: + filename = os.path.basename(imgPath) + if self.validFilestate(imgPath) is True: + item = QListWidgetItem(doneicon, filename) + else: + item = QListWidgetItem(closeicon, filename) + self.fileListWidget.addItem(item) + + print('dirPath in importDirImages is', dirpath) + self.iconlist.clear() + self.additems5(dirpath) + self.changeFileFolder = True + self.haveAutoReced = False + self.AutoRecognition.setEnabled(True) + self.reRecogButton.setEnabled(True) + self.actions.AutoRec.setEnabled(True) + self.actions.reRec.setEnabled(True) + self.actions.saveLabel.setEnabled(True) + + + def openPrevImg(self, _value=False): + if len(self.mImgList) <= 0: + return + + if self.filePath is None: + return + + currIndex = self.mImgList.index(self.filePath) + self.mImgList5 = self.mImgList[:5] + if currIndex - 1 >= 0: + filename = self.mImgList[currIndex - 1] + self.mImgList5 = self.indexTo5Files(currIndex - 1) + if filename: + self.loadFile(filename) + + def openNextImg(self, _value=False): + if not self.mayContinue(): + return + + if len(self.mImgList) <= 0: + return + + filename = None + if self.filePath is None: + filename = self.mImgList[0] + self.mImgList5 = self.mImgList[:5] + else: + currIndex = self.mImgList.index(self.filePath) + if currIndex + 1 < len(self.mImgList): + filename = self.mImgList[currIndex + 1] + self.mImgList5 = self.indexTo5Files(currIndex + 1) + else: + self.mImgList5 = self.indexTo5Files(currIndex) + if filename: + print('file name in openNext is ',filename) + self.loadFile(filename) + + def openFile(self, _value=False): + if not self.mayContinue(): + return + path = os.path.dirname(ustr(self.filePath)) if self.filePath else '.' + formats = ['*.%s' % fmt.data().decode("ascii").lower() for fmt in QImageReader.supportedImageFormats()] + filters = "Image & Label files (%s)" % ' '.join(formats + ['*%s' % LabelFile.suffix]) + filename = QFileDialog.getOpenFileName(self, '%s - Choose Image or Label file' % __appname__, path, filters) + if filename: + if isinstance(filename, (tuple, list)): + filename = filename[0] + self.loadFile(filename) + # print('filename in openfile is ', self.filePath) + self.filePath = None + self.fileListWidget.clear() + self.iconlist.clear() + self.mImgList = [filename] + self.openNextImg() + if self.validFilestate(filename) is True: + item = QListWidgetItem(newIcon('done'), filename) + self.setClean() + elif self.validFilestate(filename) is None: + item = QListWidgetItem(newIcon('close'), filename) + else: + item = QListWidgetItem(newIcon('close'), filename) + self.setDirty() + self.fileListWidget.addItem(filename) + self.additems5(None) + print('opened image is', filename) + + def updateFileListIcon(self, filename): + pass + + def saveFile(self, _value=False, mode='Manual'): + # Manual mode is used for users click "Save" manually,which will change the state of the image + if self.filePath: + imgidx = self.getImglabelidx(self.filePath) + self._saveFile(imgidx, mode=mode) + + + def saveFileAs(self, _value=False): + assert not self.image.isNull(), "cannot save empty image" + self._saveFile(self.saveFileDialog()) + + def saveFileDialog(self, removeExt=True): + caption = '%s - Choose File' % __appname__ + filters = 'File (*%s)' % LabelFile.suffix + openDialogPath = self.currentPath() + dlg = QFileDialog(self, caption, openDialogPath, filters) + dlg.setDefaultSuffix(LabelFile.suffix[1:]) + dlg.setAcceptMode(QFileDialog.AcceptSave) + filenameWithoutExtension = os.path.splitext(self.filePath)[0] + dlg.selectFile(filenameWithoutExtension) + dlg.setOption(QFileDialog.DontUseNativeDialog, False) + if dlg.exec_(): + fullFilePath = ustr(dlg.selectedFiles()[0]) + if removeExt: + return os.path.splitext(fullFilePath)[0] # Return file path without the extension. + else: + return fullFilePath + return '' + + def _saveFile(self, annotationFilePath, mode='Manual'): + if mode == 'Manual': + if annotationFilePath and self.saveLabels(annotationFilePath, mode=mode): + self.setClean() + self.statusBar().showMessage('Saved to %s' % annotationFilePath) + self.statusBar().show() + currIndex = self.mImgList.index(self.filePath) + item = self.fileListWidget.item(currIndex) + item.setIcon(newIcon('done')) + + self.fileStatedict[self.filePath] = 1 + if len(self.fileStatedict)%self.autoSaveNum ==0: + self.saveFilestate() + self.savePPlabel(mode='Auto') + + self.fileListWidget.insertItem(int(currIndex), item) + self.openNextImg() + self.actions.saveRec.setEnabled(True) + + elif mode == 'Auto': + if annotationFilePath and self.saveLabels(annotationFilePath, mode=mode): + + self.setClean() + self.statusBar().showMessage('Saved to %s' % annotationFilePath) + self.statusBar().show() + + def closeFile(self, _value=False): + if not self.mayContinue(): + return + self.resetState() + self.setClean() + self.toggleActions(False) + self.canvas.setEnabled(False) + self.actions.saveAs.setEnabled(False) + + def deleteImg(self): + deletePath = self.filePath + if deletePath is not None: + deleteInfo = self.deleteImgDialog() + if deleteInfo == QMessageBox.Yes: + if platform.system() == 'Windows': + from win32com.shell import shell, shellcon + shell.SHFileOperation((0, shellcon.FO_DELETE, deletePath, None, + shellcon.FOF_SILENT | shellcon.FOF_ALLOWUNDO | shellcon.FOF_NOCONFIRMATION, + None, None)) + # linux + elif platform.system() == 'Linux': + cmd = 'trash ' + deletePath + os.system(cmd) + # macOS + elif platform.system() == 'Darwin': + import subprocess + absPath = os.path.abspath(deletePath).replace('\\', '\\\\').replace('"', '\\"') + cmd = ['osascript', '-e', + 'tell app "Finder" to move {the POSIX file "' + absPath + '"} to trash'] + print(cmd) + subprocess.call(cmd, stdout=open(os.devnull, 'w')) + + if self.filePath in self.fileStatedict.keys(): + self.fileStatedict.pop(self.filePath) + imgidx = self.getImglabelidx(self.filePath) + if imgidx in self.PPlabel.keys(): + self.PPlabel.pop(imgidx) + self.openNextImg() + self.importDirImages(self.lastOpenDir, isDelete=True) + + def deleteImgDialog(self): + yes, cancel = QMessageBox.Yes, QMessageBox.Cancel + msg = u'The image will be deleted to the recycle bin' + return QMessageBox.warning(self, u'Attention', msg, yes | cancel) + + def resetAll(self): + self.settings.reset() + self.close() + proc = QProcess() + proc.startDetached(os.path.abspath(__file__)) + + def mayContinue(self): # + if not self.dirty: + return True + else: + discardChanges = self.discardChangesDialog() + if discardChanges == QMessageBox.No: + return True + elif discardChanges == QMessageBox.Yes: + self.saveFile() + return True + else: + return False + + def discardChangesDialog(self): + yes, no, cancel = QMessageBox.Yes, QMessageBox.No, QMessageBox.Cancel + msg = u'You have unsaved changes, would you like to save them and proceed?\nClick "No" to undo all changes.' + return QMessageBox.warning(self, u'Attention', msg, yes | no | cancel) + + def errorMessage(self, title, message): + return QMessageBox.critical(self, title, + '

%s

%s' % (title, message)) + + def currentPath(self): + return os.path.dirname(self.filePath) if self.filePath else '.' + + def chooseColor1(self): + color = self.colorDialog.getColor(self.lineColor, u'Choose line color', + default=DEFAULT_LINE_COLOR) + if color: + self.lineColor = color + Shape.line_color = color + self.canvas.setDrawingColor(color) + self.canvas.update() + self.setDirty() + + def deleteSelectedShape(self): + self.remLabel(self.canvas.deleteSelected()) + self.setDirty() + if self.noShapes(): + for action in self.actions.onShapesPresent: + action.setEnabled(False) + + def chshapeLineColor(self): + color = self.colorDialog.getColor(self.lineColor, u'Choose line color', + default=DEFAULT_LINE_COLOR) + if color: + self.canvas.selectedShape.line_color = color + self.canvas.update() + self.setDirty() + + def chshapeFillColor(self): + color = self.colorDialog.getColor(self.fillColor, u'Choose fill color', + default=DEFAULT_FILL_COLOR) + if color: + self.canvas.selectedShape.fill_color = color + self.canvas.update() + self.setDirty() + + def copyShape(self): + self.canvas.endMove(copy=True) + self.addLabel(self.canvas.selectedShape) + self.setDirty() + + def moveShape(self): + self.canvas.endMove(copy=False) + self.setDirty() + + def loadPredefinedClasses(self, predefClassesFile): + if os.path.exists(predefClassesFile) is True: + with codecs.open(predefClassesFile, 'r', 'utf8') as f: + for line in f: + line = line.strip() + if self.labelHist is None: + self.labelHist = [line] + else: + self.labelHist.append(line) + + + def togglePaintLabelsOption(self): + for shape in self.canvas.shapes: + shape.paintLabel = self.displayLabelOption.isChecked() + + def toogleDrawSquare(self): + self.canvas.setDrawingShapeToSquare(self.drawSquaresOption.isChecked()) + + def additems(self, dirpath): + for file in self.mImgList: + pix = QPixmap(file) + _, filename = os.path.split(file) + filename, _ = os.path.splitext(filename) + item = QListWidgetItem(QIcon(pix.scaled(100, 100, Qt.IgnoreAspectRatio, Qt.FastTransformation)), + filename[:10]) + item.setToolTip(file) + self.iconlist.addItem(item) + + def additems5(self, dirpath): + for file in self.mImgList5: + pix = QPixmap(file) + _, filename = os.path.split(file) + filename, _ = os.path.splitext(filename) + pfilename = filename[:10] + if len(pfilename) < 10: + lentoken = 12 - len(pfilename) + prelen = lentoken // 2 + bfilename = prelen * " " + pfilename + (lentoken - prelen) * " " + # item = QListWidgetItem(QIcon(pix.scaled(100, 100, Qt.KeepAspectRatio, Qt.SmoothTransformation)),filename[:10]) + item = QListWidgetItem(QIcon(pix.scaled(100, 100, Qt.IgnoreAspectRatio, Qt.FastTransformation)),pfilename) + # item.setForeground(QBrush(Qt.white)) + item.setToolTip(file) + self.iconlist.addItem(item) + owidth = 0 + for index in range(len(self.mImgList5)): + item = self.iconlist.item(index) + itemwidget = self.iconlist.visualItemRect(item) + owidth += itemwidget.width() + self.iconlist.setMinimumWidth(owidth + 50) + + def getImglabelidx(self, filePath): + if platform.system()=='Windows': + spliter = '\\' + else: + spliter = '/' + filepathsplit = filePath.split(spliter)[-2:] + return filepathsplit[0] + '/' + filepathsplit[1] + + def autoRecognition(self): + assert self.mImgList is not None + print('Using model from ', self.model) + + uncheckedList = [i for i in self.mImgList if i not in self.fileStatedict.keys()] + self.autoDialog = AutoDialog(parent=self, ocr=self.ocr, mImgList=uncheckedList, lenbar=len(uncheckedList)) + self.autoDialog.popUp() + self.currIndex=len(self.mImgList) + self.loadFile(self.filePath) # ADD + self.haveAutoReced = True + self.AutoRecognition.setEnabled(False) + self.actions.AutoRec.setEnabled(False) + self.setDirty() + self.saveCacheLabel() + + + def reRecognition(self): + img = cv2.imread(self.filePath) + # org_box = [dic['points'] for dic in self.PPlabel[self.getImglabelidx(self.filePath)]] + if self.canvas.shapes: + self.result_dic = [] + rec_flag = 0 + for shape in self.canvas.shapes: + box = [[int(p.x()), int(p.y())] for p in shape.points] + assert len(box) == 4 + img_crop = get_rotate_crop_image(img, np.array(box, np.float32)) + if img_crop is None: + msg = 'Can not recognise the detection box in ' + self.filePath + '. Please change manually' + QMessageBox.information(self, "Information", msg) + return + result = self.ocr.ocr(img_crop, cls=True, det=False) + if result[0][0] is not '': + result.insert(0, box) + print('result in reRec is ', result) + self.result_dic.append(result) + if result[1][0] == shape.label: + print('label no change') + else: + rec_flag += 1 + + if len(self.result_dic) > 0 and rec_flag > 0: + self.saveFile(mode='Auto') + self.loadFile(self.filePath) + self.setDirty() + elif len(self.result_dic) == len(self.canvas.shapes) and rec_flag == 0: + QMessageBox.information(self, "Information", "The recognition result remains unchanged!") + else: + print('Can not recgonise in ', self.filePath) + else: + QMessageBox.information(self, "Information", "Draw a box!") + + def singleRerecognition(self): + img = cv2.imread(self.filePath) + shape = self.canvas.selectedShape + box = [[int(p.x()), int(p.y())] for p in shape.points] + assert len(box) == 4 + img_crop = get_rotate_crop_image(img, np.array(box, np.float32)) + if img_crop is None: + msg = 'Can not recognise the detection box in ' + self.filePath + '. Please change manually' + QMessageBox.information(self, "Information", msg) + return + result = self.ocr.ocr(img_crop, cls=True, det=False) + if result[0][0] is not '': + result.insert(0, box) + print('result in reRec is ', result) + if result[1][0] == shape.label: + print('label no change') + else: + shape.label = result[1][0] + self.singleLabel(shape) + self.setDirty() + print(box) + + def autolcm(self): + vbox = QVBoxLayout() + hbox = QHBoxLayout() + self.panel = QLabel() + self.panel.setText(self.stringBundle.getString('choseModelLg')) + self.panel.setAlignment(Qt.AlignLeft) + self.comboBox = QComboBox() + self.comboBox.setObjectName("comboBox") + self.comboBox.addItems(['Chinese & English', 'English', 'French', 'German', 'Korean', 'Japanese']) + vbox.addWidget(self.panel) + vbox.addWidget(self.comboBox) + self.dialog = QDialog() + self.dialog.resize(300, 100) + self.okBtn = QPushButton(self.stringBundle.getString('ok')) + self.cancelBtn = QPushButton(self.stringBundle.getString('cancel')) + + self.okBtn.clicked.connect(self.modelChoose) + self.cancelBtn.clicked.connect(self.cancel) + self.dialog.setWindowTitle(self.stringBundle.getString('choseModelLg')) + + hbox.addWidget(self.okBtn) + hbox.addWidget(self.cancelBtn) + + vbox.addWidget(self.panel) + vbox.addLayout(hbox) + self.dialog.setLayout(vbox) + self.dialog.setWindowModality(Qt.ApplicationModal) + self.dialog.exec_() + if self.filePath: + self.AutoRecognition.setEnabled(True) + self.actions.AutoRec.setEnabled(True) + + + def modelChoose(self): + print(self.comboBox.currentText()) + lg_idx = {'Chinese & English': 'ch', 'English': 'en', 'French': 'french', 'German': 'german', + 'Korean': 'korean', 'Japanese': 'japan'} + del self.ocr + self.ocr = PaddleOCR(use_pdserving=False, use_angle_cls=True, det=True, cls=True, use_gpu=False, + lang=lg_idx[self.comboBox.currentText()]) + self.dialog.close() + + def cancel(self): + self.dialog.close() + + def loadFilestate(self, saveDir): + self.fileStatepath = saveDir + '/fileState.txt' + self.fileStatedict = {} + if not os.path.exists(self.fileStatepath): + f = open(self.fileStatepath, 'w', encoding='utf-8') + else: + with open(self.fileStatepath, 'r', encoding='utf-8') as f: + states = f.readlines() + for each in states: + file, state = each.split('\t') + self.fileStatedict[file] = 1 + + + def saveFilestate(self): + with open(self.fileStatepath, 'w', encoding='utf-8') as f: + for key in self.fileStatedict: + f.write(key + '\t') + f.write(str(self.fileStatedict[key]) + '\n') + + + def loadLabelFile(self, labelpath): + labeldict = {} + if not os.path.exists(labelpath): + f = open(labelpath, 'w', encoding='utf-8') + + else: + with open(labelpath, 'r', encoding='utf-8') as f: + data = f.readlines() + for each in data: + file, label = each.split('\t') + if label: + label = label.replace('false', 'False') + label = label.replace('true', 'True') + labeldict[file] = eval(label) + else: + labeldict[file] = [] + return labeldict + + + def savePPlabel(self,mode='Manual'): + savedfile = [self.getImglabelidx(i) for i in self.fileStatedict.keys()] + with open(self.PPlabelpath, 'w', encoding='utf-8') as f: + for key in self.PPlabel: + if key in savedfile and self.PPlabel[key] != []: + f.write(key + '\t') + f.write(json.dumps(self.PPlabel[key], ensure_ascii=False) + '\n') + + if mode=='Manual': + msg = 'Images that have been checked are saved in '+ self.PPlabelpath + QMessageBox.information(self, "Information", msg) + + def saveCacheLabel(self): + with open(self.Cachelabelpath, 'w', encoding='utf-8') as f: + for key in self.Cachelabel: + f.write(key + '\t') + f.write(json.dumps(self.Cachelabel[key], ensure_ascii=False) + '\n') + + def saveLabelFile(self): + self.saveFilestate() + self.savePPlabel() + + def saveRecResult(self): + if None in [self.PPlabelpath, self.PPlabel, self.fileStatedict]: + QMessageBox.information(self, "Information", "Save file first") + return + + rec_gt_dir = os.path.dirname(self.PPlabelpath) + '/rec_gt.txt' + crop_img_dir = os.path.dirname(self.PPlabelpath) + '/crop_img/' + if not os.path.exists(crop_img_dir): + os.mkdir(crop_img_dir) + + with open(rec_gt_dir, 'w', encoding='utf-8') as f: + for key in self.fileStatedict: + idx = self.getImglabelidx(key) + for i, label in enumerate(self.PPlabel[idx]): + if label['difficult']: continue + img = cv2.imread(key) + img_crop = get_rotate_crop_image(img, np.array(label['points'], np.float32)) + img_name = os.path.splitext(os.path.basename(idx))[0] + '_crop_'+str(i)+'.jpg' + cv2.imwrite(crop_img_dir+img_name, img_crop) + f.write('crop_img/'+ img_name + '\t') + f.write(label['transcription'] + '\n') + + QMessageBox.information(self, "Information", "Cropped images has been saved in "+str(crop_img_dir)) + +def inverted(color): + return QColor(*[255 - v for v in color.getRgb()]) + + +def read(filename, default=None): + try: + with open(filename, 'rb') as f: + return f.read() + except: + return default + + +def get_main_app(argv=[]): + """ + Standard boilerplate Qt application code. + Do everything but app.exec_() -- so that we can test the application in one thread + """ + app = QApplication(argv) + app.setApplicationName(__appname__) + app.setWindowIcon(newIcon("app")) + # Tzutalin 201705+: Accept extra agruments to change predefined class file + argparser = argparse.ArgumentParser() + argparser.add_argument("--lang", default='en', nargs="?") + argparser.add_argument("--predefined_classes_file", + default=os.path.join(os.path.dirname(__file__), "data", "predefined_classes.txt"), + nargs="?") + args = argparser.parse_args(argv[1:]) + # Usage : labelImg.py image predefClassFile saveDir + win = MainWindow(lang=args.lang, + defaultPrefdefClassFile=args.predefined_classes_file) + win.show() + return app, win + + +def main(): + '''construct main app and run it''' + app, _win = get_main_app(sys.argv) + return app.exec_() + + +if __name__ == '__main__': + + resource_file = './libs/resources.py' + if not os.path.exists(resource_file): + output = os.system('pyrcc5 -o libs/resources.py resources.qrc') + assert output is 0, "operate the cmd have some problems ,please check whether there is a in the lib " \ + "directory resources.py " + import libs.resources + sys.exit(main()) diff --git a/PPOCRLabel/README.md b/PPOCRLabel/README.md new file mode 100644 index 0000000000..4e1e230405 --- /dev/null +++ b/PPOCRLabel/README.md @@ -0,0 +1,153 @@ +English | [简体中文](README_ch.md) + +# PPOCRLabel + +PPOCRLabel is a semi-automatic graphic annotation tool suitable for OCR field. It is written in python3 and pyqt5, supporting rectangular box annotation and four-point annotation modes. Annotations can be directly used for the training of PPOCR detection and recognition models. + + + +### Recent Update + +- 2020.12.18: Support re-recognition of a single label box (by [ninetailskim](https://github.com/ninetailskim) ), perfect shortcut keys. + +## Installation + +### 1. Install PaddleOCR + +Refer to [PaddleOCR installation document](https://github.com/PaddlePaddle/PaddleOCR/blob/develop/doc/doc_ch/installation.md) to prepare PaddleOCR + +### 2. Install PPOCRLabel + +#### Windows + Anaconda + +Download and install [Anaconda](https://www.anaconda.com/download/#download) (Python 3+) + +``` +pip install pyqt5 +cd ./PPOCRLabel # Change the directory to the PPOCRLabel folder +python PPOCRLabel.py +``` + +#### Ubuntu Linux + +``` +pip3 install pyqt5 +pip3 install trash-cli +cd ./PPOCRLabel # Change the directory to the PPOCRLabel folder +python3 PPOCRLabel.py +``` + +#### macOS +``` +pip3 install pyqt5 +pip3 uninstall opencv-python # Uninstall opencv manually as it conflicts with pyqt +pip3 install opencv-contrib-python-headless # Install the headless version of opencv +cd ./PPOCRLabel # Change the directory to the PPOCRLabel folder +python3 PPOCRLabel.py +``` + +## Usage + +### Steps + +1. Build and launch using the instructions above. + +2. Click 'Open Dir' in Menu/File to select the folder of the picture.[1] + +3. Click 'Auto recognition', use PPOCR model to automatically annotate images which marked with 'X' [2]before the file name. + +4. Create Box: + + 4.1 Click 'Create RectBox' or press 'W' in English keyboard mode to draw a new rectangle detection box. Click and release left mouse to select a region to annotate the text area. + + 4.2 Press 'P' to enter four-point labeling mode which enables you to create any four-point shape by clicking four points with the left mouse button in succession and DOUBLE CLICK the left mouse as the signal of labeling completion. + +5. After the marking frame is drawn, the user clicks "OK", and the detection frame will be pre-assigned a "TEMPORARY" label. + +6. Click 're-Recognition', model will rewrite ALL recognition results in ALL detection box[3]. + +7. Double click the result in 'recognition result' list to manually change inaccurate recognition results. + +8. Click "Check", the image status will switch to "√",then the program automatically jump to the next(The results will not be written directly to the file at this time). + +9. Click "Delete Image" and the image will be deleted to the recycle bin. + +10. Labeling result: the user can save manually through the menu "File - Save Label", while the program will also save automatically after every 10 images confirmed by the user.the manually checked label will be stored in *Label.txt* under the opened picture folder. + Click "PaddleOCR"-"Save Recognition Results" in the menu bar, the recognition training data of such pictures will be saved in the *crop_img* folder, and the recognition label will be saved in *rec_gt.txt*[4]. + +### Note + +[1] PPOCRLabel uses the opened folder as the project. After opening the image folder, the picture will not be displayed in the dialog. Instead, the pictures under the folder will be directly imported into the program after clicking "Open Dir". + +[2] The image status indicates whether the user has saved the image manually. If it has not been saved manually it is "X", otherwise it is "√", PPOCRLabel will not relabel pictures with a status of "√". + +[3] After clicking "Re-recognize", the model will overwrite ALL recognition results in the picture. +Therefore, if the recognition result has been manually changed before, it may change after re-recognition. + +[4] The files produced by PPOCRLabel can be found under the opened picture folder including the following, please do not manually change the contents, otherwise it will cause the program to be abnormal. + +| File name | Description | +| :-----------: | :----------------------------------------------------------: | +| Label.txt | The detection label file can be directly used for PPOCR detection model training. After the user saves 10 label results, the file will be automatically saved. It will also be written when the user closes the application or changes the file folder. | +| fileState.txt | The picture status file save the image in the current folder that has been manually confirmed by the user. | +| Cache.cach | Cache files to save the results of model recognition. | +| rec_gt.txt | The recognition label file, which can be directly used for PPOCR identification model training, is generated after the user clicks on the menu bar "File"-"Save recognition result". | +| crop_img | The recognition data, generated at the same time with *rec_gt.txt* | + +## Explanation + +### Shortcut keys + +| Shortcut keys | Description | +| ---------------- | ------------------------------------------------ | +| Ctrl + shift + A | Automatically label all unchecked images | +| Ctrl + shift + R | Re-recognize all the labels of the current image | +| W | Create a rect box | +| Q | Create a four-points box | +| Ctrl + E | Edit label of the selected box | +| Ctrl + R | Re-recognize the selected box | +| Backspace | Delete the selected box | +| Ctrl + V | Check image | +| Ctrl + Shift + d | Delete image | +| D | Next image | +| A | Previous image | +| Ctrl++ | Zoom in | +| Ctrl-- | Zoom out | +| ↑→↓← | Move selected box | + +### Built-in Model + +- Default model: PPOCRLabel uses the Chinese and English ultra-lightweight OCR model in PaddleOCR by default, supports Chinese, English and number recognition, and multiple language detection. + +- Model language switching: Changing the built-in model language is supportable by clicking "PaddleOCR"-"Choose OCR Model" in the menu bar. Currently supported languages​include French, German, Korean, and Japanese. + For specific model download links, please refer to [PaddleOCR Model List](https://github.com/PaddlePaddle/PaddleOCR/blob/develop/doc/doc_en/models_list_en.md#multilingual-recognition-modelupdating) + +- Custom model: The model trained by users can be replaced by modifying PPOCRLabel.py in [PaddleOCR class instantiation](https://github.com/PaddlePaddle/PaddleOCR/blob/develop/PPOCRLabel/PPOCRLabel.py#L110) referring [Custom Model Code](https://github.com/PaddlePaddle/PaddleOCR/blob/develop/doc/doc_en/whl_en.md#use-custom-model) + +### Export partial recognition results + +For some data that are difficult to recognize, the recognition results will not be exported by **unchecking** the corresponding tags in the recognition results checkbox. + +*Note: The status of the checkboxes in the recognition results still needs to be saved manually by clicking Save Button.* + +### Error message + +- If paddleocr is installed with whl, it has a higher priority than calling PaddleOCR class with paddleocr.py, which may cause an exception if whl package is not updated. + +- For Linux users, if you get an error starting with **objc[XXXXX]** when opening the software, it proves that your opencv version is too high. It is recommended to install version 4.2: + + ``` + pip install opencv-python==4.2.0.32 + ``` +- If you get an error starting with **Missing string id **,you need to recompile resources: + ``` + pyrcc5 -o libs/resources.py resources.qrc + ``` +- If you get an error ``` module 'cv2' has no attribute 'INTER_NEAREST'```, you need to delete all opencv related packages first, and then reinstall the headless version of opencv + ``` + pip install opencv-contrib-python-headless + ``` + +### Related + +1.[Tzutalin. LabelImg. Git code (2015)](https://github.com/tzutalin/labelImg) diff --git a/PPOCRLabel/README_ch.md b/PPOCRLabel/README_ch.md new file mode 100644 index 0000000000..c4b4b07e3f --- /dev/null +++ b/PPOCRLabel/README_ch.md @@ -0,0 +1,134 @@ +[English](README.md) | 简体中文 + +# PPOCRLabel + +PPOCRLabel是一款适用于OCR领域的半自动化图形标注工具,使用python3和pyqt5编写,支持矩形框标注和四点标注模式,导出格式可直接用于PPOCR检测和识别模型的训练。 + + + +#### 近期更新 + +- 2020.12.18: 支持对单个标记框进行重新识别(by [ninetailskim](https://github.com/ninetailskim) ),完善快捷键。 + +## 安装 + +### 1. 安装PaddleOCR +参考[PaddleOCR安装文档](https://github.com/PaddlePaddle/PaddleOCR/blob/develop/doc/doc_ch/installation.md)准备好PaddleOCR + +### 2. 安装PPOCRLabel +#### Windows + Anaconda + +``` +pip install pyqt5 +cd ./PPOCRLabel # 将目录切换到PPOCRLabel文件夹下 +python PPOCRLabel.py --lang ch +``` + +#### Ubuntu Linux + +``` +pip3 install pyqt5 +pip3 install trash-cli +cd ./PPOCRLabel # 将目录切换到PPOCRLabel文件夹下 +python3 PPOCRLabel.py --lang ch +``` + +#### macOS +``` +pip3 install pyqt5 +pip3 uninstall opencv-python # 由于mac版本的opencv与pyqt有冲突,需先手动卸载opencv +pip3 install opencv-contrib-python-headless # 安装headless版本的open-cv +cd ./PPOCRLabel # 将目录切换到PPOCRLabel文件夹下 +python3 PPOCRLabel.py --lang ch +``` + +## 使用 + +### 操作步骤 + +1. 安装与运行:使用上述命令安装与运行程序。 +2. 打开文件夹:在菜单栏点击 “文件” - "打开目录" 选择待标记图片的文件夹[1]. +3. 自动标注:点击 ”自动标注“,使用PPOCR超轻量模型对图片文件名前图片状态[2]为 “X” 的图片进行自动标注。 +4. 手动标注:点击 “矩形标注”(推荐直接在英文模式下点击键盘中的 “W”),用户可对当前图片中模型未检出的部分进行手动绘制标记框。点击键盘P,则使用四点标注模式(或点击“编辑” - “四点标注”),用户依次点击4个点后,双击左键表示标注完成。 +5. 标记框绘制完成后,用户点击 “确认”,检测框会先被预分配一个 “待识别” 标签。 +6. 重新识别:将图片中的所有检测画绘制/调整完成后,点击 “重新识别”,PPOCR模型会对当前图片中的**所有检测框**重新识别[3]。 +7. 内容更改:双击识别结果,对不准确的识别结果进行手动更改。 +8. 确认标记:点击 “确认”,图片状态切换为 “√”,跳转至下一张(此时不会直接将结果写入文件)。 +9. 删除:点击 “删除图像”,图片将会被删除至回收站。 +10. 保存结果:用户可以通过菜单中“文件-保存标记结果”手动保存,同时程序也会在用户每确认10张图片后自动保存一次。手动确认过的标记将会被存放在所打开图片文件夹下的*Label.txt*中。在菜单栏点击 “文件” - "保存识别结果"后,会将此类图片的识别训练数据保存在*crop_img*文件夹下,识别标签保存在*rec_gt.txt*中[4]。 + +### 注意 + +[1] PPOCRLabel以文件夹为基本标记单位,打开待标记的图片文件夹后,不会在窗口栏中显示图片,而是在点击 "选择文件夹" 之后直接将文件夹下的图片导入到程序中。 + +[2] 图片状态表示本张图片用户是否手动保存过,未手动保存过即为 “X”,手动保存过为 “√”。点击 “自动标注”按钮后,PPOCRLabel不会对状态为 “√” 的图片重新标注。 + +[3] 点击“重新识别”后,模型会对图片中的识别结果进行覆盖。因此如果在此之前手动更改过识别结果,有可能在重新识别后产生变动。 + +[4] PPOCRLabel产生的文件放置于标记图片文件夹下,包括一下几种,请勿手动更改其中内容,否则会引起程序出现异常。 + +| 文件名 | 说明 | +| :-----------: | :----------------------------------------------------------: | +| Label.txt | 检测标签,可直接用于PPOCR检测模型训练。用户每保存10张检测结果后,程序会进行自动写入。当用户关闭应用程序或切换文件路径后同样会进行写入。 | +| fileState.txt | 图片状态标记文件,保存当前文件夹下已经被用户手动确认过的图片名称。 | +| Cache.cach | 缓存文件,保存模型自动识别的结果。 | +| rec_gt.txt | 识别标签。可直接用于PPOCR识别模型训练。需用户手动点击菜单栏“文件” - "保存识别结果"后产生。 | +| crop_img | 识别数据。按照检测框切割后的图片。与rec_gt.txt同时产生。 | + +## 说明 + +### 快捷键 + +| 快捷键 | 说明 | +| ---------------- | ---------------------------- | +| Ctrl + shift + A | 自动标注所有未确认过的图片 | +| Ctrl + shift + R | 对当前图片的所有标记重新识别 | +| W | 新建矩形框 | +| Q | 新建四点框 | +| Ctrl + E | 编辑所选框标签 | +| Ctrl + R | 重新识别所选标记 | +| Backspace | 删除所选框 | +| Ctrl + V | 确认本张图片标记 | +| Ctrl + Shift + d | 删除本张图片 | +| D | 下一张图片 | +| A | 上一张图片 | +| Ctrl++ | 缩小 | +| Ctrl-- | 放大 | +| ↑→↓← | 移动标记框 | + +### 内置模型 + + - 默认模型:PPOCRLabel默认使用PaddleOCR中的中英文超轻量OCR模型,支持中英文与数字识别,多种语言检测。 + + - 模型语言切换:用户可通过菜单栏中 "PaddleOCR" - "选择模型" 切换内置模型语言,目前支持的语言包括法文、德文、韩文、日文。具体模型下载链接可参考[PaddleOCR模型列表](https://github.com/PaddlePaddle/PaddleOCR/blob/develop/doc/doc_ch/models_list.md). + + - 自定义模型:用户可根据[自定义模型代码使用](https://github.com/PaddlePaddle/PaddleOCR/blob/develop/doc/doc_ch/whl.md#%E8%87%AA%E5%AE%9A%E4%B9%89%E6%A8%A1%E5%9E%8B),通过修改PPOCRLabel.py中针对[PaddleOCR类的实例化](https://github.com/PaddlePaddle/PaddleOCR/blob/develop/PPOCRLabel/PPOCRLabel.py#L110)替换成自己训练的模型。 + +### 导出部分识别结果 + +针对部分难以识别的数据,通过在识别结果的复选框中**取消勾选**相应的标记,其识别结果不会被导出。 + +*注意:识别结果中的复选框状态仍需用户手动点击保存后才能保留* + +### 错误提示 +- 如果同时使用whl包安装了paddleocr,其优先级大于通过paddleocr.py调用PaddleOCR类,whl包未更新时会导致程序异常。 + +- PPOCRLabel**不支持对中文文件名**的图片进行自动标注。 + +- 针对Linux用户::如果您在打开软件过程中出现**objc[XXXXX]**开头的错误,证明您的opencv版本太高,建议安装4.2版本: + ``` + pip install opencv-python==4.2.0.32 + ``` + +- 如果出现 ```Missing string id``` 开头的错误,需要重新编译资源: + ``` + pyrcc5 -o libs/resources.py resources.qrc + ``` + +- 如果出现``` module 'cv2' has no attribute 'INTER_NEAREST'```错误,需要首先删除所有opencv相关包,然后重新安装headless版本的opencv + ``` + pip install opencv-contrib-python-headless + ``` +### 参考资料 + +1.[Tzutalin. LabelImg. Git code (2015)](https://github.com/tzutalin/labelImg) diff --git a/ppocr/modeling/heads/self_attention/__init__.py b/PPOCRLabel/__init__.py similarity index 100% rename from ppocr/modeling/heads/self_attention/__init__.py rename to PPOCRLabel/__init__.py diff --git a/PPOCRLabel/combobox.py b/PPOCRLabel/combobox.py new file mode 100644 index 0000000000..8526b45392 --- /dev/null +++ b/PPOCRLabel/combobox.py @@ -0,0 +1,46 @@ +# Copyright (c) <2015-Present> Tzutalin +# Copyright (C) 2013 MIT, Computer Science and Artificial Intelligence Laboratory. Bryan Russell, Antonio Torralba, +# William T. Freeman. Permission is hereby granted, free of charge, to any person obtaining a copy of this software and +# associated documentation files (the "Software"), to deal in the Software without restriction, including without +# limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the +# Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: +# The above copyright notice and this permission notice shall be included in all copies or substantial portions of +# the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT +# NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT +# SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF +# CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN +# THE SOFTWARE. + +import sys +try: + from PyQt5.QtWidgets import QWidget, QHBoxLayout, QComboBox +except ImportError: + # needed for py3+qt4 + # Ref: + # http://pyqt.sourceforge.net/Docs/PyQt4/incompatible_apis.html + # http://stackoverflow.com/questions/21217399/pyqt4-qtcore-qvariant-object-instead-of-a-string + if sys.version_info.major >= 3: + import sip + sip.setapi('QVariant', 2) + from PyQt4.QtGui import QWidget, QHBoxLayout, QComboBox + + +class ComboBox(QWidget): + def __init__(self, parent=None, items=[]): + super(ComboBox, self).__init__(parent) + + layout = QHBoxLayout() + self.cb = QComboBox() + self.items = items + self.cb.addItems(self.items) + + self.cb.currentIndexChanged.connect(parent.comboSelectionChanged) + + layout.addWidget(self.cb) + self.setLayout(layout) + + def update_items(self, items): + self.items = items + + self.cb.clear() + self.cb.addItems(self.items) diff --git a/PPOCRLabel/data/gif/steps.gif b/PPOCRLabel/data/gif/steps.gif new file mode 100644 index 0000000000..6ea998500b Binary files /dev/null and b/PPOCRLabel/data/gif/steps.gif differ diff --git a/PPOCRLabel/data/gif/steps_en.gif b/PPOCRLabel/data/gif/steps_en.gif new file mode 100644 index 0000000000..e59339350a Binary files /dev/null and b/PPOCRLabel/data/gif/steps_en.gif differ diff --git a/PPOCRLabel/data/paddle.png b/PPOCRLabel/data/paddle.png new file mode 100644 index 0000000000..b1099c73b5 Binary files /dev/null and b/PPOCRLabel/data/paddle.png differ diff --git a/PPOCRLabel/data/predefined_classes.txt b/PPOCRLabel/data/predefined_classes.txt new file mode 100644 index 0000000000..e69de29bb2 diff --git a/PPOCRLabel/libs/__init__.py b/PPOCRLabel/libs/__init__.py new file mode 100644 index 0000000000..0df0cc8460 --- /dev/null +++ b/PPOCRLabel/libs/__init__.py @@ -0,0 +1,2 @@ +__version_info__ = ('1', '0', '0') +__version__ = '.'.join(__version_info__) diff --git a/PPOCRLabel/libs/autoDialog.py b/PPOCRLabel/libs/autoDialog.py new file mode 100644 index 0000000000..09fbeb56b3 --- /dev/null +++ b/PPOCRLabel/libs/autoDialog.py @@ -0,0 +1,155 @@ +try: + from PyQt5.QtGui import * + from PyQt5.QtCore import * + from PyQt5.QtWidgets import * +except ImportError: + from PyQt4.QtGui import * + from PyQt4.QtCore import * + +import json + +from libs.utils import newIcon + +BB = QDialogButtonBox + + +class Worker(QThread): + progressBarValue = pyqtSignal(int) + listValue = pyqtSignal(str) + endsignal = pyqtSignal(int, str) + handle = 0 + + def __init__(self, ocr, mImgList, mainThread, model): + super(Worker, self).__init__() + self.ocr = ocr + self.mImgList = mImgList + self.mainThread = mainThread + self.model = model + self.setStackSize(1024*1024) + + def run(self): + try: + findex = 0 + for Imgpath in self.mImgList: + if self.handle == 0: + self.listValue.emit(Imgpath) + if self.model == 'paddle': + self.result_dic = self.ocr.ocr(Imgpath, cls=True, det=True) + + # 结果保存 + if self.result_dic is None or len(self.result_dic) == 0: + print('Can not recognise file is : ', Imgpath) + pass + else: + strs = '' + for res in self.result_dic: + chars = res[1][0] + cond = res[1][1] + posi = res[0] + strs += "Transcription: " + chars + " Probability: " + str(cond) + \ + " Location: " + json.dumps(posi) +'\n' + # Sending large amounts of data repeatedly through pyqtSignal may affect the program efficiency + self.listValue.emit(strs) + self.mainThread.result_dic = self.result_dic + self.mainThread.filePath = Imgpath + # 保存 + self.mainThread.saveFile(mode='Auto') + findex += 1 + self.progressBarValue.emit(findex) + else: + break + self.endsignal.emit(0, "readAll") + self.exec() + except Exception as e: + print(e) + raise + + +class AutoDialog(QDialog): + + def __init__(self, text="Enter object label", parent=None, ocr=None, mImgList=None, lenbar=0): + super(AutoDialog, self).__init__(parent) + self.setFixedWidth(1000) + self.parent = parent + self.ocr = ocr + self.mImgList = mImgList + self.pb = QProgressBar() + self.pb.setRange(0, lenbar) + self.pb.setValue(0) + + layout = QVBoxLayout() + layout.addWidget(self.pb) + self.model = 'paddle' + self.listWidget = QListWidget(self) + layout.addWidget(self.listWidget) + + self.buttonBox = bb = BB(BB.Ok | BB.Cancel, Qt.Horizontal, self) + bb.button(BB.Ok).setIcon(newIcon('done')) + bb.button(BB.Cancel).setIcon(newIcon('undo')) + bb.accepted.connect(self.validate) + bb.rejected.connect(self.reject) + layout.addWidget(bb) + bb.button(BB.Ok).setEnabled(False) + + self.setLayout(layout) + # self.setWindowTitle("自动标注中") + self.setWindowModality(Qt.ApplicationModal) + + # self.setWindowFlags(Qt.WindowCloseButtonHint) + + self.thread_1 = Worker(self.ocr, self.mImgList, self.parent, 'paddle') + self.thread_1.progressBarValue.connect(self.handleProgressBarSingal) + self.thread_1.listValue.connect(self.handleListWidgetSingal) + self.thread_1.endsignal.connect(self.handleEndsignalSignal) + + def handleProgressBarSingal(self, i): + self.pb.setValue(i) + + def handleListWidgetSingal(self, i): + self.listWidget.addItem(i) + titem = self.listWidget.item(self.listWidget.count() - 1) + self.listWidget.scrollToItem(titem) + + def handleEndsignalSignal(self, i, str): + if i == 0 and str == "readAll": + self.buttonBox.button(BB.Ok).setEnabled(True) + self.buttonBox.button(BB.Cancel).setEnabled(False) + + def reject(self): + print("reject") + self.thread_1.handle = -1 + self.thread_1.quit() + # del self.thread_1 + # if self.thread_1.isRunning(): + # self.thread_1.terminate() + # self.thread_1.quit() + # super(AutoDialog,self).reject() + while not self.thread_1.isFinished(): + pass + self.accept() + + def validate(self): + self.accept() + + def postProcess(self): + try: + self.edit.setText(self.edit.text().trimmed()) + # print(self.edit.text()) + except AttributeError: + # PyQt5: AttributeError: 'str' object has no attribute 'trimmed' + self.edit.setText(self.edit.text()) + print(self.edit.text()) + + def popUp(self): + self.thread_1.start() + return 1 if self.exec_() else None + + def closeEvent(self, event): + print("???") + # if self.thread_1.isRunning(): + # self.thread_1.quit() + # + # # self._thread.terminate() + # # del self.thread_1 + # super(AutoDialog, self).closeEvent(event) + self.reject() diff --git a/PPOCRLabel/libs/canvas.py b/PPOCRLabel/libs/canvas.py new file mode 100644 index 0000000000..bb166baca6 --- /dev/null +++ b/PPOCRLabel/libs/canvas.py @@ -0,0 +1,798 @@ +# Copyright (c) <2015-Present> Tzutalin +# Copyright (C) 2013 MIT, Computer Science and Artificial Intelligence Laboratory. Bryan Russell, Antonio Torralba, +# William T. Freeman. Permission is hereby granted, free of charge, to any person obtaining a copy of this software and +# associated documentation files (the "Software"), to deal in the Software without restriction, including without +# limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the +# Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: +# The above copyright notice and this permission notice shall be included in all copies or substantial portions of +# the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT +# NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT +# SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF +# CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN +# THE SOFTWARE. + +try: + from PyQt5.QtGui import * + from PyQt5.QtCore import * + from PyQt5.QtWidgets import * +except ImportError: + from PyQt4.QtGui import * + from PyQt4.QtCore import * + +#from PyQt4.QtOpenGL import * + +from libs.shape import Shape +from libs.utils import distance + +CURSOR_DEFAULT = Qt.ArrowCursor +CURSOR_POINT = Qt.PointingHandCursor +CURSOR_DRAW = Qt.CrossCursor +CURSOR_MOVE = Qt.ClosedHandCursor +CURSOR_GRAB = Qt.OpenHandCursor + +# class Canvas(QGLWidget): + + +class Canvas(QWidget): + zoomRequest = pyqtSignal(int) + scrollRequest = pyqtSignal(int, int) + newShape = pyqtSignal() + selectionChanged = pyqtSignal(bool) + shapeMoved = pyqtSignal() + drawingPolygon = pyqtSignal(bool) + + CREATE, EDIT = list(range(2)) + _fill_drawing = False # draw shadows + + epsilon = 11.0 + + def __init__(self, *args, **kwargs): + super(Canvas, self).__init__(*args, **kwargs) + # Initialise local state. + self.mode = self.EDIT + self.shapes = [] + self.current = None + self.selectedShape = None # save the selected shape here + self.selectedShapeCopy = None + self.drawingLineColor = QColor(0, 0, 255) + self.drawingRectColor = QColor(0, 0, 255) + self.line = Shape(line_color=self.drawingLineColor) + self.prevPoint = QPointF() + self.offsets = QPointF(), QPointF() + self.scale = 1.0 + self.pixmap = QPixmap() + self.visible = {} + self._hideBackround = False + self.hideBackround = False + self.hShape = None + self.hVertex = None + self._painter = QPainter() + self._cursor = CURSOR_DEFAULT + # Menus: + self.menus = (QMenu(), QMenu()) + # Set widget options. + self.setMouseTracking(True) + self.setFocusPolicy(Qt.WheelFocus) + self.verified = False + self.drawSquare = False + self.fourpoint = True # ADD + self.pointnum = 0 + + #initialisation for panning + self.pan_initial_pos = QPoint() + + def setDrawingColor(self, qColor): + self.drawingLineColor = qColor + self.drawingRectColor = qColor + + def enterEvent(self, ev): + self.overrideCursor(self._cursor) + + def leaveEvent(self, ev): + self.restoreCursor() + + def focusOutEvent(self, ev): + self.restoreCursor() + + def isVisible(self, shape): + return self.visible.get(shape, True) + + def drawing(self): + return self.mode == self.CREATE + + def editing(self): + return self.mode == self.EDIT + + def setEditing(self, value=True): + self.mode = self.EDIT if value else self.CREATE + if not value: # Create + self.unHighlight() + self.deSelectShape() + self.prevPoint = QPointF() + self.repaint() + + def unHighlight(self): + if self.hShape: + self.hShape.highlightClear() + self.hVertex = self.hShape = None + + def selectedVertex(self): + return self.hVertex is not None + + + def mouseMoveEvent(self, ev): + """Update line with last point and current coordinates.""" + pos = self.transformPos(ev.pos()) + + # Update coordinates in status bar if image is opened + window = self.parent().window() + if window.filePath is not None: + self.parent().window().labelCoordinates.setText( + 'X: %d; Y: %d' % (pos.x(), pos.y())) + + # Polygon drawing. + if self.drawing(): + self.overrideCursor(CURSOR_DRAW) # ? + if self.current: + # Display annotation width and height while drawing + currentWidth = abs(self.current[0].x() - pos.x()) + currentHeight = abs(self.current[0].y() - pos.y()) + self.parent().window().labelCoordinates.setText( + 'Width: %d, Height: %d / X: %d; Y: %d' % (currentWidth, currentHeight, pos.x(), pos.y())) + + color = self.drawingLineColor + if self.outOfPixmap(pos): + # Don't allow the user to draw outside the pixmap. + # Clip the coordinates to 0 or max, + # if they are outside the range [0, max] + size = self.pixmap.size() + clipped_x = min(max(0, pos.x()), size.width()) + clipped_y = min(max(0, pos.y()), size.height()) + pos = QPointF(clipped_x, clipped_y) + elif len(self.current) > 1 and self.closeEnough(pos, self.current[0]) and not self.fourpoint: + # Attract line to starting point and colorise to alert the + # user: + pos = self.current[0] + color = self.current.line_color + self.overrideCursor(CURSOR_POINT) + self.current.highlightVertex(0, Shape.NEAR_VERTEX) + elif ( # ADD + len(self.current) > 1 + and self.fourpoint + and self.closeEnough(pos, self.current[0]) + ): + # Attract line to starting point and + # colorise to alert the user. + pos = self.current[0] + self.overrideCursor(CURSOR_POINT) + self.current.highlightVertex(0, Shape.NEAR_VERTEX) + + + if self.drawSquare: + initPos = self.current[0] + minX = initPos.x() + minY = initPos.y() + min_size = min(abs(pos.x() - minX), abs(pos.y() - minY)) + directionX = -1 if pos.x() - minX < 0 else 1 + directionY = -1 if pos.y() - minY < 0 else 1 + self.line[1] = QPointF(minX + directionX * min_size, minY + directionY * min_size) + + elif self.fourpoint: + # self.line[self.pointnum] = pos # OLD + + self.line[0] = self.current[-1] + self.line[1] = pos + + else: + self.line[1] = pos # pos is the mouse's current position + + self.line.line_color = color + self.prevPoint = QPointF() # ? + self.current.highlightClear() + else: + self.prevPoint = pos + self.repaint() + return + + # Polygon copy moving. + if Qt.RightButton & ev.buttons(): + if self.selectedShapeCopy and self.prevPoint: + self.overrideCursor(CURSOR_MOVE) + self.boundedMoveShape(self.selectedShapeCopy, pos) + self.repaint() + elif self.selectedShape: + self.selectedShapeCopy = self.selectedShape.copy() + self.repaint() + return + + # Polygon/Vertex moving. + if Qt.LeftButton & ev.buttons(): + if self.selectedVertex(): + self.boundedMoveVertex(pos) + self.shapeMoved.emit() + self.repaint() + elif self.selectedShape and self.prevPoint: + self.overrideCursor(CURSOR_MOVE) + self.boundedMoveShape(self.selectedShape, pos) + self.shapeMoved.emit() + self.repaint() + else: + #pan + delta_x = pos.x() - self.pan_initial_pos.x() + delta_y = pos.y() - self.pan_initial_pos.y() + self.scrollRequest.emit(delta_x, Qt.Horizontal) + self.scrollRequest.emit(delta_y, Qt.Vertical) + self.update() + return + + # Just hovering over the canvas, 2 posibilities: + # - Highlight shapes + # - Highlight vertex + # Update shape/vertex fill and tooltip value accordingly. + self.setToolTip("Image") + for shape in reversed([s for s in self.shapes if self.isVisible(s)]): + # Look for a nearby vertex to highlight. If that fails, + # check if we happen to be inside a shape. + index = shape.nearestVertex(pos, self.epsilon) + if index is not None: + if self.selectedVertex(): + self.hShape.highlightClear() + self.hVertex, self.hShape = index, shape + shape.highlightVertex(index, shape.MOVE_VERTEX) + self.overrideCursor(CURSOR_POINT) + self.setToolTip("Click & drag to move point") + self.setStatusTip(self.toolTip()) + self.update() + break + elif shape.containsPoint(pos): + if self.selectedVertex(): + self.hShape.highlightClear() + self.hVertex, self.hShape = None, shape + self.setToolTip( + "Click & drag to move shape '%s'" % shape.label) + self.setStatusTip(self.toolTip()) + self.overrideCursor(CURSOR_GRAB) + self.update() + break + else: # Nothing found, clear highlights, reset state. + if self.hShape: + self.hShape.highlightClear() + self.update() + self.hVertex, self.hShape = None, None + self.overrideCursor(CURSOR_DEFAULT) + + def mousePressEvent(self, ev): + pos = self.transformPos(ev.pos()) + + if ev.button() == Qt.LeftButton: + if self.drawing(): + # self.handleDrawing(pos) # OLD + + + if self.current and self.fourpoint: # ADD IF + # Add point to existing shape. + print('Adding points in mousePressEvent is ', self.line[1]) + self.current.addPoint(self.line[1]) + self.line[0] = self.current[-1] + if self.current.isClosed(): + # print('1111') + self.finalise() + elif not self.outOfPixmap(pos): + # Create new shape. + self.current = Shape()# self.current = Shape(shape_type=self.createMode) + self.current.addPoint(pos) + # if self.createMode == "point": + # self.finalise() + # else: + # if self.createMode == "circle": + # self.current.shape_type = "circle" + self.line.points = [pos, pos] + self.setHiding() + self.drawingPolygon.emit(True) + self.update() + + + else: + selection = self.selectShapePoint(pos) + self.prevPoint = pos + + if selection is None: + #pan + QApplication.setOverrideCursor(QCursor(Qt.OpenHandCursor)) + self.pan_initial_pos = pos + + elif ev.button() == Qt.RightButton and self.editing(): + self.selectShapePoint(pos) + self.prevPoint = pos + self.update() + + def mouseReleaseEvent(self, ev): + if ev.button() == Qt.RightButton: + menu = self.menus[bool(self.selectedShapeCopy)] + self.restoreCursor() + if not menu.exec_(self.mapToGlobal(ev.pos()))\ + and self.selectedShapeCopy: + # Cancel the move by deleting the shadow copy. + self.selectedShapeCopy = None + self.repaint() + elif ev.button() == Qt.LeftButton and self.selectedShape: # OLD + if self.selectedVertex(): + self.overrideCursor(CURSOR_POINT) + else: + self.overrideCursor(CURSOR_GRAB) + + + elif ev.button() == Qt.LeftButton and not self.fourpoint: + pos = self.transformPos(ev.pos()) + if self.drawing(): + self.handleDrawing(pos) + else: + #pan + QApplication.restoreOverrideCursor() # ? + + + def endMove(self, copy=False): + assert self.selectedShape and self.selectedShapeCopy + shape = self.selectedShapeCopy + #del shape.fill_color + #del shape.line_color + if copy: + self.shapes.append(shape) + self.selectedShape.selected = False + self.selectedShape = shape + self.repaint() + else: + self.selectedShape.points = [p for p in shape.points] + self.selectedShapeCopy = None + + def hideBackroundShapes(self, value): + self.hideBackround = value + if self.selectedShape: + # Only hide other shapes if there is a current selection. + # Otherwise the user will not be able to select a shape. + self.setHiding(True) + self.repaint() + + def handleDrawing(self, pos): + if self.current and self.current.reachMaxPoints() is False: + if self.fourpoint: + targetPos = self.line[self.pointnum] + self.current.addPoint(targetPos) + print('current points in handleDrawing is ', self.line[self.pointnum]) + self.update() + if self.pointnum == 3: + self.finalise() + + else: # 按住送掉后跳到这里 + initPos = self.current[0] + print('initPos', self.current[0]) + minX = initPos.x() + minY = initPos.y() + targetPos = self.line[1] + maxX = targetPos.x() + maxY = targetPos.y() + self.current.addPoint(QPointF(maxX, minY)) + self.current.addPoint(targetPos) + self.current.addPoint(QPointF(minX, maxY)) + self.finalise() + + elif not self.outOfPixmap(pos): + print('release') + self.current = Shape() + self.current.addPoint(pos) + self.line.points = [pos, pos] + self.setHiding() + self.drawingPolygon.emit(True) + self.update() + + def setHiding(self, enable=True): + self._hideBackround = self.hideBackround if enable else False + + def canCloseShape(self): + return self.drawing() and self.current and len(self.current) > 2 + + def mouseDoubleClickEvent(self, ev): + # We need at least 4 points here, since the mousePress handler + # adds an extra one before this handler is called. + if self.canCloseShape() and len(self.current) > 3: + if not self.fourpoint: + self.current.popPoint() + self.finalise() + + def selectShape(self, shape): + self.deSelectShape() + shape.selected = True + self.selectedShape = shape + self.setHiding() + self.selectionChanged.emit(True) + self.update() + + def selectShapePoint(self, point): + """Select the first shape created which contains this point.""" + self.deSelectShape() + if self.selectedVertex(): # A vertex is marked for selection. + index, shape = self.hVertex, self.hShape + shape.highlightVertex(index, shape.MOVE_VERTEX) + self.selectShape(shape) + return self.hVertex + for shape in reversed(self.shapes): + if self.isVisible(shape) and shape.containsPoint(point): + self.selectShape(shape) + self.calculateOffsets(shape, point) + return self.selectedShape + return None + + def calculateOffsets(self, shape, point): + rect = shape.boundingRect() + x1 = rect.x() - point.x() + y1 = rect.y() - point.y() + x2 = (rect.x() + rect.width()) - point.x() + y2 = (rect.y() + rect.height()) - point.y() + self.offsets = QPointF(x1, y1), QPointF(x2, y2) + + def snapPointToCanvas(self, x, y): + """ + Moves a point x,y to within the boundaries of the canvas. + :return: (x,y,snapped) where snapped is True if x or y were changed, False if not. + """ + if x < 0 or x > self.pixmap.width() or y < 0 or y > self.pixmap.height(): + x = max(x, 0) + y = max(y, 0) + x = min(x, self.pixmap.width()) + y = min(y, self.pixmap.height()) + return x, y, True + + return x, y, False + + def boundedMoveVertex(self, pos): + index, shape = self.hVertex, self.hShape + point = shape[index] + if self.outOfPixmap(pos): + size = self.pixmap.size() + clipped_x = min(max(0, pos.x()), size.width()) + clipped_y = min(max(0, pos.y()), size.height()) + pos = QPointF(clipped_x, clipped_y) + + if self.drawSquare: + opposite_point_index = (index + 2) % 4 + opposite_point = shape[opposite_point_index] + + min_size = min(abs(pos.x() - opposite_point.x()), abs(pos.y() - opposite_point.y())) + directionX = -1 if pos.x() - opposite_point.x() < 0 else 1 + directionY = -1 if pos.y() - opposite_point.y() < 0 else 1 + shiftPos = QPointF(opposite_point.x() + directionX * min_size - point.x(), + opposite_point.y() + directionY * min_size - point.y()) + else: + shiftPos = pos - point + + shape.moveVertexBy(index, shiftPos) + + lindex = (index + 1) % 4 + rindex = (index + 3) % 4 + lshift = None + rshift = None + if index % 2 == 0: + rshift = QPointF(shiftPos.x(), 0) + lshift = QPointF(0, shiftPos.y()) + else: + lshift = QPointF(shiftPos.x(), 0) + rshift = QPointF(0, shiftPos.y()) + shape.moveVertexBy(rindex, rshift) + shape.moveVertexBy(lindex, lshift) + + def boundedMoveShape(self, shape, pos): + if self.outOfPixmap(pos): + return False # No need to move + o1 = pos + self.offsets[0] + if self.outOfPixmap(o1): + pos -= QPointF(min(0, o1.x()), min(0, o1.y())) + o2 = pos + self.offsets[1] + if self.outOfPixmap(o2): + pos += QPointF(min(0, self.pixmap.width() - o2.x()), + min(0, self.pixmap.height() - o2.y())) + # The next line tracks the new position of the cursor + # relative to the shape, but also results in making it + # a bit "shaky" when nearing the border and allows it to + # go outside of the shape's area for some reason. XXX + #self.calculateOffsets(self.selectedShape, pos) + dp = pos - self.prevPoint + if dp: + shape.moveBy(dp) + self.prevPoint = pos + return True + return False + + def deSelectShape(self): + if self.selectedShape: + self.selectedShape.selected = False + self.selectedShape = None + self.setHiding(False) + self.selectionChanged.emit(False) + self.update() + + def deleteSelected(self): + if self.selectedShape: + shape = self.selectedShape + self.shapes.remove(self.selectedShape) + self.selectedShape = None + self.update() + return shape + + def copySelectedShape(self): + if self.selectedShape: + shape = self.selectedShape.copy() + self.deSelectShape() + self.shapes.append(shape) + shape.selected = True + self.selectedShape = shape + self.boundedShiftShape(shape) + return shape + + def boundedShiftShape(self, shape): + # Try to move in one direction, and if it fails in another. + # Give up if both fail. + point = shape[0] + offset = QPointF(2.0, 2.0) + self.calculateOffsets(shape, point) + self.prevPoint = point + if not self.boundedMoveShape(shape, point - offset): + self.boundedMoveShape(shape, point + offset) + + def paintEvent(self, event): + if not self.pixmap: + return super(Canvas, self).paintEvent(event) + + p = self._painter + p.begin(self) + p.setRenderHint(QPainter.Antialiasing) + p.setRenderHint(QPainter.HighQualityAntialiasing) + p.setRenderHint(QPainter.SmoothPixmapTransform) + + p.scale(self.scale, self.scale) + p.translate(self.offsetToCenter()) + + p.drawPixmap(0, 0, self.pixmap) + Shape.scale = self.scale + for shape in self.shapes: + if (shape.selected or not self._hideBackround) and self.isVisible(shape): + shape.fill = shape.selected or shape == self.hShape + shape.paint(p) + if self.current: + self.current.paint(p) + self.line.paint(p) + if self.selectedShapeCopy: + self.selectedShapeCopy.paint(p) + + # Paint rect + if self.current is not None and len(self.line) == 2 and not self.fourpoint: + # print('Drawing rect') + leftTop = self.line[0] + rightBottom = self.line[1] + rectWidth = rightBottom.x() - leftTop.x() + rectHeight = rightBottom.y() - leftTop.y() + p.setPen(self.drawingRectColor) + brush = QBrush(Qt.BDiagPattern) + p.setBrush(brush) + p.drawRect(leftTop.x(), leftTop.y(), rectWidth, rectHeight) + + + # ADD: + if ( + self.fillDrawing() + and self.fourpoint + and self.current is not None + and len(self.current.points) >= 2 + ): + print('paint event') + drawing_shape = self.current.copy() + drawing_shape.addPoint(self.line[1]) + drawing_shape.fill = True + drawing_shape.paint(p) + + if self.drawing() and not self.prevPoint.isNull() and not self.outOfPixmap(self.prevPoint): + p.setPen(QColor(0, 0, 0)) + p.drawLine(self.prevPoint.x(), 0, self.prevPoint.x(), self.pixmap.height()) + p.drawLine(0, self.prevPoint.y(), self.pixmap.width(), self.prevPoint.y()) + + self.setAutoFillBackground(True) + if self.verified: + pal = self.palette() + pal.setColor(self.backgroundRole(), QColor(184, 239, 38, 128)) + self.setPalette(pal) + else: + pal = self.palette() + pal.setColor(self.backgroundRole(), QColor(232, 232, 232, 255)) + self.setPalette(pal) + + p.end() + + def fillDrawing(self): + return self._fill_drawing + + def transformPos(self, point): + """Convert from widget-logical coordinates to painter-logical coordinates.""" + return point / self.scale - self.offsetToCenter() + + def offsetToCenter(self): + s = self.scale + area = super(Canvas, self).size() + w, h = self.pixmap.width() * s, self.pixmap.height() * s + aw, ah = area.width(), area.height() + x = (aw - w) / (2 * s) if aw > w else 0 + y = (ah - h) / (2 * s) if ah > h else 0 + return QPointF(x, y) + + def outOfPixmap(self, p): + w, h = self.pixmap.width(), self.pixmap.height() + return not (0 <= p.x() <= w and 0 <= p.y() <= h) + + def finalise(self): + assert self.current + if self.current.points[0] == self.current.points[-1]: + # print('finalse') + self.current = None + self.drawingPolygon.emit(False) + self.update() + return + + self.current.close() + self.shapes.append(self.current) + self.current = None + self.setHiding(False) + self.newShape.emit() + self.update() + + def closeEnough(self, p1, p2): + #d = distance(p1 - p2) + #m = (p1-p2).manhattanLength() + # print "d %.2f, m %d, %.2f" % (d, m, d - m) + return distance(p1 - p2) < self.epsilon + + # These two, along with a call to adjustSize are required for the + # scroll area. + def sizeHint(self): + return self.minimumSizeHint() + + def minimumSizeHint(self): + if self.pixmap: + return self.scale * self.pixmap.size() + return super(Canvas, self).minimumSizeHint() + + def wheelEvent(self, ev): + qt_version = 4 if hasattr(ev, "delta") else 5 + if qt_version == 4: + if ev.orientation() == Qt.Vertical: + v_delta = ev.delta() + h_delta = 0 + else: + h_delta = ev.delta() + v_delta = 0 + else: + delta = ev.angleDelta() + h_delta = delta.x() + v_delta = delta.y() + + mods = ev.modifiers() + if Qt.ControlModifier == int(mods) and v_delta: + self.zoomRequest.emit(v_delta) + else: + v_delta and self.scrollRequest.emit(v_delta, Qt.Vertical) + h_delta and self.scrollRequest.emit(h_delta, Qt.Horizontal) + ev.accept() + + def keyPressEvent(self, ev): + key = ev.key() + if key == Qt.Key_Escape and self.current: + print('ESC press') + self.current = None + self.drawingPolygon.emit(False) + self.update() + elif key == Qt.Key_Return and self.canCloseShape(): + self.finalise() + elif key == Qt.Key_Left and self.selectedShape: + self.moveOnePixel('Left') + elif key == Qt.Key_Right and self.selectedShape: + self.moveOnePixel('Right') + elif key == Qt.Key_Up and self.selectedShape: + self.moveOnePixel('Up') + elif key == Qt.Key_Down and self.selectedShape: + self.moveOnePixel('Down') + + def moveOnePixel(self, direction): + # print(self.selectedShape.points) + if direction == 'Left' and not self.moveOutOfBound(QPointF(-1.0, 0)): + # print("move Left one pixel") + self.selectedShape.points[0] += QPointF(-1.0, 0) + self.selectedShape.points[1] += QPointF(-1.0, 0) + self.selectedShape.points[2] += QPointF(-1.0, 0) + self.selectedShape.points[3] += QPointF(-1.0, 0) + elif direction == 'Right' and not self.moveOutOfBound(QPointF(1.0, 0)): + # print("move Right one pixel") + self.selectedShape.points[0] += QPointF(1.0, 0) + self.selectedShape.points[1] += QPointF(1.0, 0) + self.selectedShape.points[2] += QPointF(1.0, 0) + self.selectedShape.points[3] += QPointF(1.0, 0) + elif direction == 'Up' and not self.moveOutOfBound(QPointF(0, -1.0)): + # print("move Up one pixel") + self.selectedShape.points[0] += QPointF(0, -1.0) + self.selectedShape.points[1] += QPointF(0, -1.0) + self.selectedShape.points[2] += QPointF(0, -1.0) + self.selectedShape.points[3] += QPointF(0, -1.0) + elif direction == 'Down' and not self.moveOutOfBound(QPointF(0, 1.0)): + # print("move Down one pixel") + self.selectedShape.points[0] += QPointF(0, 1.0) + self.selectedShape.points[1] += QPointF(0, 1.0) + self.selectedShape.points[2] += QPointF(0, 1.0) + self.selectedShape.points[3] += QPointF(0, 1.0) + self.shapeMoved.emit() + self.repaint() + + def moveOutOfBound(self, step): + points = [p1+p2 for p1, p2 in zip(self.selectedShape.points, [step]*4)] + return True in map(self.outOfPixmap, points) + + def setLastLabel(self, text, line_color = None, fill_color = None): + assert text + self.shapes[-1].label = text + if line_color: + self.shapes[-1].line_color = line_color + + if fill_color: + self.shapes[-1].fill_color = fill_color + + return self.shapes[-1] + + def undoLastLine(self): + assert self.shapes + self.current = self.shapes.pop() + self.current.setOpen() + self.line.points = [self.current[-1], self.current[0]] + self.drawingPolygon.emit(True) + + def resetAllLines(self): + assert self.shapes + self.current = self.shapes.pop() + self.current.setOpen() + self.line.points = [self.current[-1], self.current[0]] + self.drawingPolygon.emit(True) + self.current = None + self.drawingPolygon.emit(False) + self.update() + + def loadPixmap(self, pixmap): + self.pixmap = pixmap + self.shapes = [] + self.repaint() # 这函数在哪 + + def loadShapes(self, shapes): + self.shapes = list(shapes) + self.current = None + self.repaint() + + def setShapeVisible(self, shape, value): + self.visible[shape] = value + self.repaint() + + def currentCursor(self): + cursor = QApplication.overrideCursor() + if cursor is not None: + cursor = cursor.shape() + return cursor + + def overrideCursor(self, cursor): + self._cursor = cursor + if self.currentCursor() is None: + QApplication.setOverrideCursor(cursor) + else: + QApplication.changeOverrideCursor(cursor) + + def restoreCursor(self): + QApplication.restoreOverrideCursor() + + def resetState(self): + self.restoreCursor() + self.pixmap = None + self.update() + + def setDrawingShapeToSquare(self, status): + self.drawSquare = status diff --git a/PPOCRLabel/libs/colorDialog.py b/PPOCRLabel/libs/colorDialog.py new file mode 100644 index 0000000000..c70ff76549 --- /dev/null +++ b/PPOCRLabel/libs/colorDialog.py @@ -0,0 +1,49 @@ +# Copyright (c) <2015-Present> Tzutalin +# Copyright (C) 2013 MIT, Computer Science and Artificial Intelligence Laboratory. Bryan Russell, Antonio Torralba, +# William T. Freeman. Permission is hereby granted, free of charge, to any person obtaining a copy of this software and +# associated documentation files (the "Software"), to deal in the Software without restriction, including without +# limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the +# Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: +# The above copyright notice and this permission notice shall be included in all copies or substantial portions of +# the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT +# NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT +# SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF +# CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN +# THE SOFTWARE. +try: + from PyQt5.QtGui import * + from PyQt5.QtCore import * + from PyQt5.QtWidgets import QColorDialog, QDialogButtonBox +except ImportError: + from PyQt4.QtGui import * + from PyQt4.QtCore import * + +BB = QDialogButtonBox + + +class ColorDialog(QColorDialog): + + def __init__(self, parent=None): + super(ColorDialog, self).__init__(parent) + self.setOption(QColorDialog.ShowAlphaChannel) + # The Mac native dialog does not support our restore button. + self.setOption(QColorDialog.DontUseNativeDialog) + # Add a restore defaults button. + # The default is set at invocation time, so that it + # works across dialogs for different elements. + self.default = None + self.bb = self.layout().itemAt(1).widget() + self.bb.addButton(BB.RestoreDefaults) + self.bb.clicked.connect(self.checkRestore) + + def getColor(self, value=None, title=None, default=None): + self.default = default + if title: + self.setWindowTitle(title) + if value: + self.setCurrentColor(value) + return self.currentColor() if self.exec_() else None + + def checkRestore(self, button): + if self.bb.buttonRole(button) & BB.ResetRole and self.default: + self.setCurrentColor(self.default) diff --git a/PPOCRLabel/libs/constants.py b/PPOCRLabel/libs/constants.py new file mode 100644 index 0000000000..58c8222ec5 --- /dev/null +++ b/PPOCRLabel/libs/constants.py @@ -0,0 +1,31 @@ +# Copyright (c) <2015-Present> Tzutalin +# Copyright (C) 2013 MIT, Computer Science and Artificial Intelligence Laboratory. Bryan Russell, Antonio Torralba, +# William T. Freeman. Permission is hereby granted, free of charge, to any person obtaining a copy of this software and +# associated documentation files (the "Software"), to deal in the Software without restriction, including without +# limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the +# Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: +# The above copyright notice and this permission notice shall be included in all copies or substantial portions of +# the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT +# NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT +# SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF +# CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN +# THE SOFTWARE. +SETTING_FILENAME = 'filename' +SETTING_RECENT_FILES = 'recentFiles' +SETTING_WIN_SIZE = 'window/size' +SETTING_WIN_POSE = 'window/position' +SETTING_WIN_GEOMETRY = 'window/geometry' +SETTING_LINE_COLOR = 'line/color' +SETTING_FILL_COLOR = 'fill/color' +SETTING_ADVANCE_MODE = 'advanced' +SETTING_WIN_STATE = 'window/state' +SETTING_SAVE_DIR = 'savedir' +SETTING_PAINT_LABEL = 'paintlabel' +SETTING_LAST_OPEN_DIR = 'lastOpenDir' +SETTING_AUTO_SAVE = 'autosave' +SETTING_SINGLE_CLASS = 'singleclass' +FORMAT_PASCALVOC='PascalVOC' +FORMAT_YOLO='YOLO' +SETTING_DRAW_SQUARE = 'draw/square' +SETTING_LABEL_FILE_FORMAT= 'labelFileFormat' +DEFAULT_ENCODING = 'utf-8' diff --git a/PPOCRLabel/libs/create_ml_io.py b/PPOCRLabel/libs/create_ml_io.py new file mode 100644 index 0000000000..a2123b265b --- /dev/null +++ b/PPOCRLabel/libs/create_ml_io.py @@ -0,0 +1,143 @@ +# Copyright (c) <2015-Present> Tzutalin +# Copyright (C) 2013 MIT, Computer Science and Artificial Intelligence Laboratory. Bryan Russell, Antonio Torralba, +# William T. Freeman. Permission is hereby granted, free of charge, to any person obtaining a copy of this software and +# associated documentation files (the "Software"), to deal in the Software without restriction, including without +# limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the +# Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: +# The above copyright notice and this permission notice shall be included in all copies or substantial portions of +# the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT +# NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT +# SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF +# CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN +# THE SOFTWARE. +#!/usr/bin/env python +# -*- coding: utf8 -*- +import json +from pathlib import Path + +from libs.constants import DEFAULT_ENCODING +import os + +JSON_EXT = '.json' +ENCODE_METHOD = DEFAULT_ENCODING + + +class CreateMLWriter: + def __init__(self, foldername, filename, imgsize, shapes, outputfile, databasesrc='Unknown', localimgpath=None): + self.foldername = foldername + self.filename = filename + self.databasesrc = databasesrc + self.imgsize = imgsize + self.boxlist = [] + self.localimgpath = localimgpath + self.verified = False + self.shapes = shapes + self.outputfile = outputfile + + def write(self): + if os.path.isfile(self.outputfile): + with open(self.outputfile, "r") as file: + input_data = file.read() + outputdict = json.loads(input_data) + else: + outputdict = [] + + outputimagedict = { + "image": self.filename, + "annotations": [] + } + + for shape in self.shapes: + points = shape["points"] + + x1 = points[0][0] + y1 = points[0][1] + x2 = points[1][0] + y2 = points[2][1] + + height, width, x, y = self.calculate_coordinates(x1, x2, y1, y2) + + shapedict = { + "label": shape["label"], + "coordinates": { + "x": x, + "y": y, + "width": width, + "height": height + } + } + outputimagedict["annotations"].append(shapedict) + + # check if image already in output + exists = False + for i in range(0, len(outputdict)): + if outputdict[i]["image"] == outputimagedict["image"]: + exists = True + outputdict[i] = outputimagedict + break + + if not exists: + outputdict.append(outputimagedict) + + Path(self.outputfile).write_text(json.dumps(outputdict), ENCODE_METHOD) + + def calculate_coordinates(self, x1, x2, y1, y2): + if x1 < x2: + xmin = x1 + xmax = x2 + else: + xmin = x2 + xmax = x1 + if y1 < y2: + ymin = y1 + ymax = y2 + else: + ymin = y2 + ymax = y1 + width = xmax - xmin + if width < 0: + width = width * -1 + height = ymax - ymin + # x and y from center of rect + x = xmin + width / 2 + y = ymin + height / 2 + return height, width, x, y + + +class CreateMLReader: + def __init__(self, jsonpath, filepath): + self.jsonpath = jsonpath + self.shapes = [] + self.verified = False + self.filename = filepath.split("/")[-1:][0] + try: + self.parse_json() + except ValueError: + print("JSON decoding failed") + + def parse_json(self): + with open(self.jsonpath, "r") as file: + inputdata = file.read() + + outputdict = json.loads(inputdata) + self.verified = True + + if len(self.shapes) > 0: + self.shapes = [] + for image in outputdict: + if image["image"] == self.filename: + for shape in image["annotations"]: + self.add_shape(shape["label"], shape["coordinates"]) + + def add_shape(self, label, bndbox): + xmin = bndbox["x"] - (bndbox["width"] / 2) + ymin = bndbox["y"] - (bndbox["height"] / 2) + + xmax = bndbox["x"] + (bndbox["width"] / 2) + ymax = bndbox["y"] + (bndbox["height"] / 2) + + points = [(xmin, ymin), (xmax, ymin), (xmax, ymax), (xmin, ymax)] + self.shapes.append((label, points, None, None, True)) + + def get_shapes(self): + return self.shapes diff --git a/PPOCRLabel/libs/hashableQListWidgetItem.py b/PPOCRLabel/libs/hashableQListWidgetItem.py new file mode 100644 index 0000000000..95c496ff56 --- /dev/null +++ b/PPOCRLabel/libs/hashableQListWidgetItem.py @@ -0,0 +1,40 @@ +# Copyright (c) <2015-Present> Tzutalin +# Copyright (C) 2013 MIT, Computer Science and Artificial Intelligence Laboratory. Bryan Russell, Antonio Torralba, +# William T. Freeman. Permission is hereby granted, free of charge, to any person obtaining a copy of this software and +# associated documentation files (the "Software"), to deal in the Software without restriction, including without +# limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the +# Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: +# The above copyright notice and this permission notice shall be included in all copies or substantial portions of +# the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT +# NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT +# SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF +# CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN +# THE SOFTWARE. +#!/usr/bin/env python +# -*- coding: utf-8 -*- +import sys +try: + from PyQt5.QtGui import * + from PyQt5.QtCore import * + from PyQt5.QtWidgets import * +except ImportError: + # needed for py3+qt4 + # Ref: + # http://pyqt.sourceforge.net/Docs/PyQt4/incompatible_apis.html + # http://stackoverflow.com/questions/21217399/pyqt4-qtcore-qvariant-object-instead-of-a-string + if sys.version_info.major >= 3: + import sip + sip.setapi('QVariant', 2) + from PyQt4.QtGui import * + from PyQt4.QtCore import * + +# PyQt5: TypeError: unhashable type: 'QListWidgetItem' + + +class HashableQListWidgetItem(QListWidgetItem): + + def __init__(self, *args): + super(HashableQListWidgetItem, self).__init__(*args) + + def __hash__(self): + return hash(id(self)) diff --git a/PPOCRLabel/libs/labelDialog.py b/PPOCRLabel/libs/labelDialog.py new file mode 100644 index 0000000000..57071d77b5 --- /dev/null +++ b/PPOCRLabel/libs/labelDialog.py @@ -0,0 +1,107 @@ +# Copyright (c) <2015-Present> Tzutalin +# Copyright (C) 2013 MIT, Computer Science and Artificial Intelligence Laboratory. Bryan Russell, Antonio Torralba, +# William T. Freeman. Permission is hereby granted, free of charge, to any person obtaining a copy of this software and +# associated documentation files (the "Software"), to deal in the Software without restriction, including without +# limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the +# Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: +# The above copyright notice and this permission notice shall be included in all copies or substantial portions of +# the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT +# NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT +# SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF +# CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN +# THE SOFTWARE. +try: + from PyQt5.QtGui import * + from PyQt5.QtCore import * + from PyQt5.QtWidgets import * +except ImportError: + from PyQt4.QtGui import * + from PyQt4.QtCore import * + +from libs.utils import newIcon, labelValidator + +BB = QDialogButtonBox + + +class LabelDialog(QDialog): + + def __init__(self, text="Enter object label", parent=None, listItem=None): + super(LabelDialog, self).__init__(parent) + + self.edit = QLineEdit() # OLD + # self.edit = QTextEdit() + self.edit.setText(text) + # self.edit.setValidator(labelValidator()) # 验证有效性 + self.edit.editingFinished.connect(self.postProcess) + + model = QStringListModel() + model.setStringList(listItem) + completer = QCompleter() + completer.setModel(model) + self.edit.setCompleter(completer) + + layout = QVBoxLayout() + layout.addWidget(self.edit) + self.buttonBox = bb = BB(BB.Ok | BB.Cancel, Qt.Horizontal, self) + bb.button(BB.Ok).setIcon(newIcon('done')) + bb.button(BB.Cancel).setIcon(newIcon('undo')) + bb.accepted.connect(self.validate) + bb.rejected.connect(self.reject) + layout.addWidget(bb) + + # if listItem is not None and len(listItem) > 0: + # self.listWidget = QListWidget(self) + # for item in listItem: + # self.listWidget.addItem(item) + # self.listWidget.itemClicked.connect(self.listItemClick) + # self.listWidget.itemDoubleClicked.connect(self.listItemDoubleClick) + # layout.addWidget(self.listWidget) + + self.setLayout(layout) + + def validate(self): + try: + if self.edit.text().trimmed(): + self.accept() + except AttributeError: + # PyQt5: AttributeError: 'str' object has no attribute 'trimmed' + if self.edit.text().strip(): + self.accept() + + def postProcess(self): + try: + self.edit.setText(self.edit.text().trimmed()) + # print(self.edit.text()) + except AttributeError: + # PyQt5: AttributeError: 'str' object has no attribute 'trimmed' + self.edit.setText(self.edit.text()) + print(self.edit.text()) + + def popUp(self, text='', move=True): + self.edit.setText(text) + self.edit.setSelection(0, len(text)) + self.edit.setFocus(Qt.PopupFocusReason) + if move: + cursor_pos = QCursor.pos() + parent_bottomRight = self.parentWidget().geometry() + max_x = parent_bottomRight.x() + parent_bottomRight.width() - self.sizeHint().width() + max_y = parent_bottomRight.y() + parent_bottomRight.height() - self.sizeHint().height() + max_global = self.parentWidget().mapToGlobal(QPoint(max_x, max_y)) + if cursor_pos.x() > max_global.x(): + cursor_pos.setX(max_global.x()) + if cursor_pos.y() > max_global.y(): + cursor_pos.setY(max_global.y()) + self.move(cursor_pos) + return self.edit.text() if self.exec_() else None + + def listItemClick(self, tQListWidgetItem): + try: + text = tQListWidgetItem.text().trimmed() + except AttributeError: + # PyQt5: AttributeError: 'str' object has no attribute 'trimmed' + text = tQListWidgetItem.text().strip() + self.edit.setText(text) + + def listItemDoubleClick(self, tQListWidgetItem): + self.listItemClick(tQListWidgetItem) + self.validate() diff --git a/PPOCRLabel/libs/resources.py b/PPOCRLabel/libs/resources.py new file mode 100644 index 0000000000..7213294fa3 --- /dev/null +++ b/PPOCRLabel/libs/resources.py @@ -0,0 +1,11109 @@ +# -*- coding: utf-8 -*- + +# Resource object code +# +# Created by: The Resource Compiler for PyQt5 (Qt v5.15.1) +# +# WARNING! 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qInitResources(): + QtCore.qRegisterResourceData(rcc_version, qt_resource_struct, qt_resource_name, qt_resource_data) + +def qCleanupResources(): + QtCore.qUnregisterResourceData(rcc_version, qt_resource_struct, qt_resource_name, qt_resource_data) + +qInitResources() diff --git a/PPOCRLabel/libs/settings.py b/PPOCRLabel/libs/settings.py new file mode 100644 index 0000000000..7f9a4fdda6 --- /dev/null +++ b/PPOCRLabel/libs/settings.py @@ -0,0 +1,60 @@ +# Copyright (c) <2015-Present> Tzutalin +# Copyright (C) 2013 MIT, Computer Science and Artificial Intelligence Laboratory. Bryan Russell, Antonio Torralba, +# William T. Freeman. Permission is hereby granted, free of charge, to any person obtaining a copy of this software and +# associated documentation files (the "Software"), to deal in the Software without restriction, including without +# limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the +# Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: +# The above copyright notice and this permission notice shall be included in all copies or substantial portions of +# the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT +# NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT +# SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF +# CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN +# THE SOFTWARE. + +import pickle +import os +import sys + + +class Settings(object): + def __init__(self): + # Be default, the home will be in the same folder as labelImg + home = os.path.expanduser("~") + self.data = {} + # self.path = os.path.join(home, '.labelImgSettings.pkl') + self.path = os.path.join(home, '.autoOCRSettings.pkl') + + def __setitem__(self, key, value): + self.data[key] = value + + def __getitem__(self, key): + return self.data[key] + + def get(self, key, default=None): + if key in self.data: + return self.data[key] + return default + + def save(self): + if self.path: + with open(self.path, 'wb') as f: + pickle.dump(self.data, f, pickle.HIGHEST_PROTOCOL) + return True + return False + + def load(self): + try: + if os.path.exists(self.path): + with open(self.path, 'rb') as f: + self.data = pickle.load(f) + return True + except: + print('Loading setting failed') + return False + + def reset(self): + if os.path.exists(self.path): + os.remove(self.path) + print('Remove setting pkl file ${0}'.format(self.path)) + self.data = {} + self.path = None diff --git a/PPOCRLabel/libs/shape.py b/PPOCRLabel/libs/shape.py new file mode 100644 index 0000000000..2770bac1df --- /dev/null +++ b/PPOCRLabel/libs/shape.py @@ -0,0 +1,217 @@ +# Copyright (c) <2015-Present> Tzutalin +# Copyright (C) 2013 MIT, Computer Science and Artificial Intelligence Laboratory. Bryan Russell, Antonio Torralba, +# William T. Freeman. Permission is hereby granted, free of charge, to any person obtaining a copy of this software and +# associated documentation files (the "Software"), to deal in the Software without restriction, including without +# limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the +# Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: +# The above copyright notice and this permission notice shall be included in all copies or substantial portions of +# the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT +# NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT +# SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF +# CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN +# THE SOFTWARE. +#!/usr/bin/python +# -*- coding: utf-8 -*- + + +try: + from PyQt5.QtGui import * + from PyQt5.QtCore import * +except ImportError: + from PyQt4.QtGui import * + from PyQt4.QtCore import * + +from libs.utils import distance +import sys + +DEFAULT_LINE_COLOR = QColor(0, 255, 0, 128) +DEFAULT_FILL_COLOR = QColor(255, 0, 0, 128) +DEFAULT_SELECT_LINE_COLOR = QColor(255, 255, 255) +DEFAULT_SELECT_FILL_COLOR = QColor(0, 128, 255, 155) +DEFAULT_VERTEX_FILL_COLOR = QColor(0, 255, 0, 255) +DEFAULT_HVERTEX_FILL_COLOR = QColor(255, 0, 0) +MIN_Y_LABEL = 10 + + +class Shape(object): + P_SQUARE, P_ROUND = range(2) + + MOVE_VERTEX, NEAR_VERTEX = range(2) + + # The following class variables influence the drawing + # of _all_ shape objects. + line_color = DEFAULT_LINE_COLOR + fill_color = DEFAULT_FILL_COLOR + select_line_color = DEFAULT_SELECT_LINE_COLOR + select_fill_color = DEFAULT_SELECT_FILL_COLOR + vertex_fill_color = DEFAULT_VERTEX_FILL_COLOR + hvertex_fill_color = DEFAULT_HVERTEX_FILL_COLOR + point_type = P_ROUND + point_size = 8 + scale = 1.0 + + def __init__(self, label=None, line_color=None, difficult=False, paintLabel=False): + self.label = label + self.points = [] + self.fill = False + self.selected = False + self.difficult = difficult + self.paintLabel = paintLabel + + self._highlightIndex = None + self._highlightMode = self.NEAR_VERTEX + self._highlightSettings = { + self.NEAR_VERTEX: (4, self.P_ROUND), + self.MOVE_VERTEX: (1.5, self.P_SQUARE), + } + + self._closed = False + + if line_color is not None: + # Override the class line_color attribute + # with an object attribute. Currently this + # is used for drawing the pending line a different color. + self.line_color = line_color + + def close(self): + self._closed = True + + def reachMaxPoints(self): + if len(self.points) >= 4: + return True + return False + + def addPoint(self, point): + if not self.reachMaxPoints(): + self.points.append(point) + + def popPoint(self): + if self.points: + return self.points.pop() + return None + + def isClosed(self): + return self._closed + + def setOpen(self): + self._closed = False + + def paint(self, painter): + if self.points: + color = self.select_line_color if self.selected else self.line_color + pen = QPen(color) + # Try using integer sizes for smoother drawing(?) + pen.setWidth(max(1, int(round(2.0 / self.scale)))) + painter.setPen(pen) + + line_path = QPainterPath() + vrtx_path = QPainterPath() + + line_path.moveTo(self.points[0]) + # Uncommenting the following line will draw 2 paths + # for the 1st vertex, and make it non-filled, which + # may be desirable. + #self.drawVertex(vrtx_path, 0) + + for i, p in enumerate(self.points): + line_path.lineTo(p) + self.drawVertex(vrtx_path, i) + if self.isClosed(): + line_path.lineTo(self.points[0]) + + painter.drawPath(line_path) + painter.drawPath(vrtx_path) + painter.fillPath(vrtx_path, self.vertex_fill_color) + + # Draw text at the top-left + if self.paintLabel: + min_x = sys.maxsize + min_y = sys.maxsize + for point in self.points: + min_x = min(min_x, point.x()) + min_y = min(min_y, point.y()) + if min_x != sys.maxsize and min_y != sys.maxsize: + font = QFont() + font.setPointSize(8) + font.setBold(True) + painter.setFont(font) + if(self.label == None): + self.label = "" + if(min_y < MIN_Y_LABEL): + min_y += MIN_Y_LABEL + painter.drawText(min_x, min_y, self.label) + + if self.fill: + color = self.select_fill_color if self.selected else self.fill_color + painter.fillPath(line_path, color) + + def drawVertex(self, path, i): + d = self.point_size / self.scale + shape = self.point_type + point = self.points[i] + if i == self._highlightIndex: + size, shape = self._highlightSettings[self._highlightMode] + d *= size + if self._highlightIndex is not None: + self.vertex_fill_color = self.hvertex_fill_color + else: + self.vertex_fill_color = Shape.vertex_fill_color + if shape == self.P_SQUARE: + path.addRect(point.x() - d / 2, point.y() - d / 2, d, d) + elif shape == self.P_ROUND: + path.addEllipse(point, d / 2.0, d / 2.0) + else: + assert False, "unsupported vertex shape" + + def nearestVertex(self, point, epsilon): + for i, p in enumerate(self.points): + if distance(p - point) <= epsilon: + return i + return None + + def containsPoint(self, point): + return self.makePath().contains(point) + + def makePath(self): + path = QPainterPath(self.points[0]) + for p in self.points[1:]: + path.lineTo(p) + return path + + def boundingRect(self): + return self.makePath().boundingRect() + + def moveBy(self, offset): + self.points = [p + offset for p in self.points] + + def moveVertexBy(self, i, offset): + self.points[i] = self.points[i] + offset + + def highlightVertex(self, i, action): + self._highlightIndex = i + self._highlightMode = action + + def highlightClear(self): + self._highlightIndex = None + + def copy(self): + shape = Shape("%s" % self.label) + shape.points = [p for p in self.points] + shape.fill = self.fill + shape.selected = self.selected + shape._closed = self._closed + if self.line_color != Shape.line_color: + shape.line_color = self.line_color + if self.fill_color != Shape.fill_color: + shape.fill_color = self.fill_color + shape.difficult = self.difficult + return shape + + def __len__(self): + return len(self.points) + + def __getitem__(self, key): + return self.points[key] + + def __setitem__(self, key, value): + self.points[key] = value diff --git a/PPOCRLabel/libs/stringBundle.py b/PPOCRLabel/libs/stringBundle.py new file mode 100644 index 0000000000..2417104425 --- /dev/null +++ b/PPOCRLabel/libs/stringBundle.py @@ -0,0 +1,86 @@ +# Copyright (c) <2015-Present> Tzutalin +# Copyright (C) 2013 MIT, Computer Science and Artificial Intelligence Laboratory. Bryan Russell, Antonio Torralba, +# William T. Freeman. Permission is hereby granted, free of charge, to any person obtaining a copy of this software and +# associated documentation files (the "Software"), to deal in the Software without restriction, including without +# limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the +# Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: +# The above copyright notice and this permission notice shall be included in all copies or substantial portions of +# the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT +# NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT +# SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF +# CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN +# THE SOFTWARE. + +#!/usr/bin/env python +# -*- coding: utf-8 -*- +import re +import os +import sys +import locale +from libs.ustr import ustr + +try: + from PyQt5.QtCore import * +except ImportError: + if sys.version_info.major >= 3: + import sip + sip.setapi('QVariant', 2) + from PyQt4.QtCore import * + + +class StringBundle: + + __create_key = object() + + def __init__(self, create_key, localeStr): + assert(create_key == StringBundle.__create_key), "StringBundle must be created using StringBundle.getBundle" + self.idToMessage = {} + paths = self.__createLookupFallbackList(localeStr) + for path in paths: + self.__loadBundle(path) + + @classmethod + def getBundle(cls, localeStr=None): + if localeStr is None: + try: + localeStr = locale.getlocale()[0] if locale.getlocale() and len( + locale.getlocale()) > 0 else os.getenv('LANG') + except: + print('Invalid locale') + localeStr = 'en' + + return StringBundle(cls.__create_key, localeStr) + + def getString(self, stringId): + assert(stringId in self.idToMessage), "Missing string id : " + stringId + return self.idToMessage[stringId] + + def __createLookupFallbackList(self, localeStr): + resultPaths = [] + basePath = ":/strings" + resultPaths.append(basePath) + if localeStr is not None: + # Don't follow standard BCP47. Simple fallback + tags = re.split('[^a-zA-Z]', localeStr) + for tag in tags: + lastPath = resultPaths[-1] + resultPaths.append(lastPath + '-' + tag) + + return resultPaths + + def __loadBundle(self, path): + PROP_SEPERATOR = '=' + f = QFile(path) + if f.exists(): + if f.open(QIODevice.ReadOnly | QFile.Text): + text = QTextStream(f) + text.setCodec("UTF-8") + + while not text.atEnd(): + line = ustr(text.readLine()) + key_value = line.split(PROP_SEPERATOR) + key = key_value[0].strip() + value = PROP_SEPERATOR.join(key_value[1:]).strip().strip('"') + self.idToMessage[key] = value + + f.close() diff --git a/PPOCRLabel/libs/toolBar.py b/PPOCRLabel/libs/toolBar.py new file mode 100644 index 0000000000..9a63929ae9 --- /dev/null +++ b/PPOCRLabel/libs/toolBar.py @@ -0,0 +1,51 @@ +# Copyright (c) <2015-Present> Tzutalin +# Copyright (C) 2013 MIT, Computer Science and Artificial Intelligence Laboratory. Bryan Russell, Antonio Torralba, +# William T. Freeman. Permission is hereby granted, free of charge, to any person obtaining a copy of this software and +# associated documentation files (the "Software"), to deal in the Software without restriction, including without +# limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the +# Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: +# The above copyright notice and this permission notice shall be included in all copies or substantial portions of +# the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT +# NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT +# SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF +# CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN +# THE SOFTWARE. +try: + from PyQt5.QtGui import * + from PyQt5.QtCore import * + from PyQt5.QtWidgets import * +except ImportError: + from PyQt4.QtGui import * + from PyQt4.QtCore import * + + +class ToolBar(QToolBar): + + def __init__(self, title): + super(ToolBar, self).__init__(title) + layout = self.layout() + m = (0, 0, 0, 0) + layout.setSpacing(0) + layout.setContentsMargins(*m) + self.setContentsMargins(*m) + self.setWindowFlags(self.windowFlags() | Qt.FramelessWindowHint) + + def addAction(self, action): + if isinstance(action, QWidgetAction): + return super(ToolBar, self).addAction(action) + btn = ToolButton() + btn.setDefaultAction(action) + btn.setToolButtonStyle(self.toolButtonStyle()) + self.addWidget(btn) + + +class ToolButton(QToolButton): + """ToolBar companion class which ensures all buttons have the same size.""" + minSize = (60, 60) + + def minimumSizeHint(self): + ms = super(ToolButton, self).minimumSizeHint() + w1, h1 = ms.width(), ms.height() + w2, h2 = self.minSize + ToolButton.minSize = max(w1, w2), max(h1, h2) + return QSize(*ToolButton.minSize) diff --git a/PPOCRLabel/libs/ustr.py b/PPOCRLabel/libs/ustr.py new file mode 100644 index 0000000000..b35cf5d3ff --- /dev/null +++ b/PPOCRLabel/libs/ustr.py @@ -0,0 +1,29 @@ +# Copyright (c) <2015-Present> Tzutalin +# Copyright (C) 2013 MIT, Computer Science and Artificial Intelligence Laboratory. Bryan Russell, Antonio Torralba, +# William T. Freeman. Permission is hereby granted, free of charge, to any person obtaining a copy of this software and +# associated documentation files (the "Software"), to deal in the Software without restriction, including without +# limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the +# Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: +# The above copyright notice and this permission notice shall be included in all copies or substantial portions of +# the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT +# NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT +# SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF +# CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN +# THE SOFTWARE. +import sys +from libs.constants import DEFAULT_ENCODING + +def ustr(x): + '''py2/py3 unicode helper''' + + if sys.version_info < (3, 0, 0): + from PyQt4.QtCore import QString + if type(x) == str: + return x.decode(DEFAULT_ENCODING) + if type(x) == QString: + #https://blog.csdn.net/friendan/article/details/51088476 + #https://blog.csdn.net/xxm524/article/details/74937308 + return unicode(x.toUtf8(), DEFAULT_ENCODING, 'ignore') + return x + else: + return x diff --git a/PPOCRLabel/libs/utils.py b/PPOCRLabel/libs/utils.py new file mode 100644 index 0000000000..cb1c92e7a9 --- /dev/null +++ b/PPOCRLabel/libs/utils.py @@ -0,0 +1,182 @@ +# Copyright (c) <2015-Present> Tzutalin +# Copyright (C) 2013 MIT, Computer Science and Artificial Intelligence Laboratory. Bryan Russell, Antonio Torralba, +# William T. Freeman. Permission is hereby granted, free of charge, to any person obtaining a copy of this software and +# associated documentation files (the "Software"), to deal in the Software without restriction, including without +# limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the +# Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: +# The above copyright notice and this permission notice shall be included in all copies or substantial portions of +# the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT +# NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT +# SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF +# CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN +# THE SOFTWARE. +from math import sqrt +from libs.ustr import ustr +import hashlib +import re +import sys +import cv2 +import numpy as np + +try: + from PyQt5.QtGui import * + from PyQt5.QtCore import * + from PyQt5.QtWidgets import * +except ImportError: + from PyQt4.QtGui import * + from PyQt4.QtCore import * + + +def newIcon(icon, iconSize=None): + if iconSize is not None: + return QIcon(QIcon(':/' + icon).pixmap(iconSize,iconSize)) + else: + return QIcon(':/' + icon) + + +def newButton(text, icon=None, slot=None): + b = QPushButton(text) + if icon is not None: + b.setIcon(newIcon(icon)) + if slot is not None: + b.clicked.connect(slot) + return b + + +def newAction(parent, text, slot=None, shortcut=None, icon=None, + tip=None, checkable=False, enabled=True, iconSize=None): + """Create a new action and assign callbacks, shortcuts, etc.""" + a = QAction(text, parent) + if icon is not None: + if iconSize is not None: + a.setIcon(newIcon(icon, iconSize)) + else: + a.setIcon(newIcon(icon)) + if shortcut is not None: + if isinstance(shortcut, (list, tuple)): + a.setShortcuts(shortcut) + else: + a.setShortcut(shortcut) + if tip is not None: + a.setToolTip(tip) + a.setStatusTip(tip) + if slot is not None: + a.triggered.connect(slot) + if checkable: + a.setCheckable(True) + a.setEnabled(enabled) + return a + + +def addActions(widget, actions): + for action in actions: + if action is None: + widget.addSeparator() + elif isinstance(action, QMenu): + widget.addMenu(action) + else: + widget.addAction(action) + + +def labelValidator(): + return QRegExpValidator(QRegExp(r'^[^ \t].+'), None) + + +class struct(object): + + def __init__(self, **kwargs): + self.__dict__.update(kwargs) + + +def distance(p): + return sqrt(p.x() * p.x() + p.y() * p.y()) + + +def fmtShortcut(text): + mod, key = text.split('+', 1) + return '%s+%s' % (mod, key) + + +def generateColorByText(text): + s = ustr(text) + hashCode = int(hashlib.sha256(s.encode('utf-8')).hexdigest(), 16) + r = int((hashCode / 255) % 255) + g = int((hashCode / 65025) % 255) + b = int((hashCode / 16581375) % 255) + return QColor(r, g, b, 100) + +def have_qstring(): + '''p3/qt5 get rid of QString wrapper as py3 has native unicode str type''' + return not (sys.version_info.major >= 3 or QT_VERSION_STR.startswith('5.')) + +def util_qt_strlistclass(): + return QStringList if have_qstring() else list + +def natural_sort(list, key=lambda s:s): + """ + Sort the list into natural alphanumeric order. + """ + def get_alphanum_key_func(key): + convert = lambda text: int(text) if text.isdigit() else text + return lambda s: [convert(c) for c in re.split('([0-9]+)', key(s))] + sort_key = get_alphanum_key_func(key) + list.sort(key=sort_key) + + +def get_rotate_crop_image(img, points): + + try: + img_crop_width = int( + max( + np.linalg.norm(points[0] - points[1]), + np.linalg.norm(points[2] - points[3]))) + img_crop_height = int( + max( + np.linalg.norm(points[0] - points[3]), + np.linalg.norm(points[1] - points[2]))) + pts_std = np.float32([[0, 0], [img_crop_width, 0], + [img_crop_width, img_crop_height], + [0, img_crop_height]]) + M = cv2.getPerspectiveTransform(points, pts_std) + dst_img = cv2.warpPerspective( + img, + M, (img_crop_width, img_crop_height), + borderMode=cv2.BORDER_REPLICATE, + flags=cv2.INTER_CUBIC) + dst_img_height, dst_img_width = dst_img.shape[0:2] + if dst_img_height * 1.0 / dst_img_width >= 1.5: + dst_img = np.rot90(dst_img) + return dst_img + except Exception as e: + print(e) + +def stepsInfo(lang='en'): + if lang == 'ch': + msg = "1. 安装与运行:使用上述命令安装与运行程序。\n" \ + "2. 打开文件夹:在菜单栏点击 “文件” - 打开目录 选择待标记图片的文件夹.\n"\ + "3. 自动标注:点击 ”自动标注“,使用PPOCR超轻量模型对图片文件名前图片状态为 “X” 的图片进行自动标注。\n" \ + "4. 手动标注:点击 “矩形标注”(推荐直接在英文模式下点击键盘中的 “W”),用户可对当前图片中模型未检出的部分进行手动" \ + "绘制标记框。点击键盘P,则使用四点标注模式(或点击“编辑” - “四点标注”),用户依次点击4个点后,双击左键表示标注完成。\n" \ + "5. 标记框绘制完成后,用户点击 “确认”,检测框会先被预分配一个 “待识别” 标签。\n" \ + "6. 重新识别:将图片中的所有检测画绘制/调整完成后,点击 “重新识别”,PPOCR模型会对当前图片中的**所有检测框**重新识别。\n" \ + "7. 内容更改:双击识别结果,对不准确的识别结果进行手动更改。\n" \ + "8. 保存:点击 “保存”,图片状态切换为 “√”,跳转至下一张。\n" \ + "9. 删除:点击 “删除图像”,图片将会被删除至回收站。\n" \ + "10. 标注结果:关闭应用程序或切换文件路径后,手动保存过的标签将会被存放在所打开图片文件夹下的" \ + "*Label.txt*中。在菜单栏点击 “PaddleOCR” - 保存识别结果后,会将此类图片的识别训练数据保存在*crop_img*文件夹下," \ + "识别标签保存在*rec_gt.txt*中。\n" + else: + msg = "1. Build and launch using the instructions above.\n" \ + "2. Click 'Open Dir' in Menu/File to select the folder of the picture.\n"\ + "3. Click 'Auto recognition', use PPOCR model to automatically annotate images which marked with 'X' before the file name."\ + "4. Create Box:\n"\ + "4.1 Click 'Create RectBox' or press 'W' in English keyboard mode to draw a new rectangle detection box. Click and release left mouse to select a region to annotate the text area.\n"\ + "4.2 Press 'P' to enter four-point labeling mode which enables you to create any four-point shape by clicking four points with the left mouse button in succession and DOUBLE CLICK the left mouse as the signal of labeling completion.\n"\ + "5. After the marking frame is drawn, the user clicks 'OK', and the detection frame will be pre-assigned a TEMPORARY label.\n"\ + "6. Click re-Recognition, model will rewrite ALL recognition results in ALL detection box.\n"\ + "7. Double click the result in 'recognition result' list to manually change inaccurate recognition results.\n"\ + "8. Click 'Save', the image status will switch to '√',then the program automatically jump to the next.\n"\ + "9. Click 'Delete Image' and the image will be deleted to the recycle bin.\n"\ + "10. Labeling result: After closing the application or switching the file path, the manually saved label will be stored in *Label.txt* under the opened picture folder.\n"\ + " Click PaddleOCR-Save Recognition Results in the menu bar, the recognition training data of such pictures will be saved in the *crop_img* folder, and the recognition label will be saved in *rec_gt.txt*.\n" + return msg \ No newline at end of file diff --git a/PPOCRLabel/libs/zoomWidget.py b/PPOCRLabel/libs/zoomWidget.py new file mode 100644 index 0000000000..4512d2ab4f --- /dev/null +++ b/PPOCRLabel/libs/zoomWidget.py @@ -0,0 +1,38 @@ +# Copyright (c) <2015-Present> Tzutalin +# Copyright (C) 2013 MIT, Computer Science and Artificial Intelligence Laboratory. Bryan Russell, Antonio Torralba, +# William T. Freeman. Permission is hereby granted, free of charge, to any person obtaining a copy of this software and +# associated documentation files (the "Software"), to deal in the Software without restriction, including without +# limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the +# Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: +# The above copyright notice and this permission notice shall be included in all copies or substantial portions of +# the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT +# NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT +# SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF +# CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN +# THE SOFTWARE. +try: + from PyQt5.QtGui import * + from PyQt5.QtCore import * + from PyQt5.QtWidgets import * +except ImportError: + from PyQt4.QtGui import * + from PyQt4.QtCore import * + + +class ZoomWidget(QSpinBox): + + def __init__(self, value=100): + super(ZoomWidget, self).__init__() + self.setButtonSymbols(QAbstractSpinBox.NoButtons) + self.setRange(1, 500) + self.setSuffix(' %') + self.setValue(value) + self.setToolTip(u'Zoom Level') + self.setStatusTip(self.toolTip()) + self.setAlignment(Qt.AlignCenter) + + def minimumSizeHint(self): + height = super(ZoomWidget, self).minimumSizeHint().height() + fm = QFontMetrics(self.font()) + width = fm.width(str(self.maximum())) + return QSize(width, height) diff --git a/PPOCRLabel/requirements/requirements-linux-python3.txt b/PPOCRLabel/requirements/requirements-linux-python3.txt new file mode 100644 index 0000000000..787a7fda11 --- /dev/null +++ b/PPOCRLabel/requirements/requirements-linux-python3.txt @@ -0,0 +1,2 @@ +pyqt5==5.10.1 +lxml==4.2.4 diff --git a/PPOCRLabel/resources.qrc b/PPOCRLabel/resources.qrc new file mode 100644 index 0000000000..7b1179d882 --- /dev/null +++ b/PPOCRLabel/resources.qrc @@ -0,0 +1,39 @@ + + + +resources/icons/help.png +resources/icons/app.png +resources/icons/Auto.png +resources/icons/reRec.png +resources/icons/expert2.png +resources/icons/done.png +resources/icons/file.png +resources/icons/labels.png +resources/icons/objects.png +resources/icons/close.png +resources/icons/fit-width.png +resources/icons/fit-window.png +resources/icons/undo.png +resources/icons/eye.png +resources/icons/quit.png +resources/icons/copy.png +resources/icons/edit.png +resources/icons/open.png +resources/icons/save.png +resources/icons/format_voc.png +resources/icons/format_yolo.png +resources/icons/save-as.png +resources/icons/color.png +resources/icons/color_line.png +resources/icons/zoom.png +resources/icons/zoom-in.png +resources/icons/zoom-out.png +resources/icons/cancel.png +resources/icons/next.png +resources/icons/prev.png +resources/icons/resetall.png +resources/icons/verify.png +resources/strings/strings.properties +resources/strings/strings-zh-CN.properties + + diff --git a/PPOCRLabel/resources/icons/Auto.png b/PPOCRLabel/resources/icons/Auto.png new file mode 100644 index 0000000000..3c04bc896a Binary files /dev/null and b/PPOCRLabel/resources/icons/Auto.png differ diff --git a/PPOCRLabel/resources/icons/app.icns b/PPOCRLabel/resources/icons/app.icns new file mode 100644 index 0000000000..9409991b4c Binary files /dev/null and b/PPOCRLabel/resources/icons/app.icns differ diff --git a/PPOCRLabel/resources/icons/app.png b/PPOCRLabel/resources/icons/app.png new file mode 100644 index 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b/PPOCRLabel/resources/icons/zoom-out.png differ diff --git a/PPOCRLabel/resources/icons/zoom.png b/PPOCRLabel/resources/icons/zoom.png new file mode 100644 index 0000000000..8265f27840 Binary files /dev/null and b/PPOCRLabel/resources/icons/zoom.png differ diff --git a/PPOCRLabel/resources/strings/strings-zh-CN.properties b/PPOCRLabel/resources/strings/strings-zh-CN.properties new file mode 100644 index 0000000000..c99497084a --- /dev/null +++ b/PPOCRLabel/resources/strings/strings-zh-CN.properties @@ -0,0 +1,98 @@ +saveAsDetail=將标签保存到其他文件 +changeSaveDir=改变存放目录 +openFile=打开文件 +shapeLineColorDetail=更改线条颜色 +resetAll=重置界面与保存地址 +crtBox=矩形标注 +crtBoxDetail=创建一个新的区块 +dupBoxDetail=复制区块 +verifyImg=验证图像 +zoominDetail=放大 +verifyImgDetail=验证图像 +saveDetail=保存标签文件 +openFileDetail=打开图像文件 +fitWidthDetail=调整宽度适应到窗口宽度 +tutorial=PaddleOCR地址 +editLabel=编辑标签 +openAnnotationDetail=打开标签文件 +quit=退出 +shapeFillColorDetail=更改填充颜色 +closeCurDetail=关闭当前文件 +closeCur=关闭文件 +deleteImg=删除图像 +deleteImgDetail=删除当前图像 +fitWin=调整到窗口大小 +delBox=删除选择的区块 +boxLineColorDetail=选择线框颜色 +originalsize=原始大小 +resetAllDetail=重置所有设定 +zoomoutDetail=放大画面 +save=确认 +saveAs=另存为 +fitWinDetail=缩放到当前窗口大小 +openDir=打开目录 +copyPrevBounding=复制当前图像中的上一个边界框 +showHide=显示/隐藏标签 +changeSaveFormat=更改存储格式 +shapeFillColor=填充颜色 +quitApp=退出程序 +dupBox=复制区块 +delBoxDetail=删除区块 +zoomin=放大画面 +info=信息 +openAnnotation=开启标签 +prevImgDetail=上一个图像 +fitWidth=缩放到跟当前画面一样宽 +zoomout=缩小画面 +changeSavedAnnotationDir=更改保存标签文件的预设目录 +nextImgDetail=下一个图像 +originalsizeDetail=放大到原始大小 +prevImg=上一张 +tutorialDetail=显示示范内容 +shapeLineColor=形状线条颜色 +boxLineColor=区块线条颜色 +editLabelDetail=修改当前所选的区块颜色 +nextImg=下一张 +useDefaultLabel=使用预设标签 +useDifficult=有难度的 +boxLabelText=区块的标签 +labels=标签 +autoSaveMode=自动保存模式 +singleClsMode=单一类别模式 +displayLabel=显示类别 +fileList=文件列表 +files=文件 +advancedMode=专家模式 +advancedModeDetail=切换到专家模式 +showAllBoxDetail=显示所有区块 +hideAllBoxDetail=隐藏所有区块 +annoPanel=标注面板 +anno=标注 +addNewBbox=新框 +reLabel=重标注 +choosemodel=选择模型 +tipchoosemodel=选择OCR模型 +ImageResize=图片缩放 +IR=图片缩放 +autoRecognition=自动标注 +reRecognition=重新识别 +mfile=文件 +medit=编辑 +mview=视图 +mhelp=帮助 +iconList=缩略图 +detectionBoxposition=检测框位置 +recognitionResult=识别结果 +creatPolygon=四点标注 +drawSquares=正方形标注 +saveRec=保存识别结果 +tempLabel=待识别 +steps=操作步骤 +choseModelLg=选择模型语言 +cancel=取消 +ok=确认 +autolabeling=自动标注中 +hideBox=隐藏所有标注 +showBox=显示所有标注 +saveLabel=保存标记结果 +singleRe=重识别此区块 \ No newline at end of file diff --git a/PPOCRLabel/resources/strings/strings.properties b/PPOCRLabel/resources/strings/strings.properties new file mode 100644 index 0000000000..0caf5890da --- /dev/null +++ b/PPOCRLabel/resources/strings/strings.properties @@ -0,0 +1,98 @@ +openFile=Open +openFileDetail=Open image or label file +quit=Quit +quitApp=Quit application +openDir=Open Dir +copyPrevBounding=Copy previous Bounding Boxes in the current image +changeSavedAnnotationDir=Change default saved Annotation dir +openAnnotation=Open Annotation +openAnnotationDetail=Open an annotation file +changeSaveDir=Change Save Dir +nextImg=Next Image +nextImgDetail=Open the next Image +prevImg=Prev Image +prevImgDetail=Open the previous Image +verifyImg=Verify Image +verifyImgDetail=Verify Image +save=Check +saveDetail=Save the labels to a file +changeSaveFormat=Change save format +saveAs=Save As +saveAsDetail=Save the labels to a different file +closeCur=Close +closeCurDetail=Close the current file +deleteImg=Delete current image +deleteImgDetail=Delete the current image +resetAll=Reset Interface and Save Dir +resetAllDetail=Reset All +boxLineColor=Box Line Color +boxLineColorDetail=Choose Box line color +crtBox=Create RectBox +crtBoxDetail=Draw a new box +delBox=Delete RectBox +delBoxDetail=Remove the box +dupBox=Duplicate RectBox +dupBoxDetail=Create a duplicate of the selected box +tutorial=PaddleOCR url +tutorialDetail=Show demo +info=Information +zoomin=Zoom In +zoominDetail=Increase zoom level +zoomout=Zoom Out +zoomoutDetail=Decrease zoom level +originalsize=Original size +originalsizeDetail=Zoom to original size +fitWin=Fit Window +fitWinDetail=Zoom follows window size +fitWidth=Fit Width +fitWidthDetail=Zoom follows window width +editLabel=Edit Label +editLabelDetail=Modify the label of the selected Box +shapeLineColor=Shape Line Color +shapeLineColorDetail=Change the line color for this specific shape +shapeFillColor=Shape Fill Color +shapeFillColorDetail=Change the fill color for this specific shape +showHide=Show/Hide Label Panel +useDefaultLabel=Use default label +useDifficult=Difficult +boxLabelText=Box Labels +labels=Labels +autoSaveMode=Auto Save mode +singleClsMode=Single Class Mode +displayLabel=Display Labels +fileList=File List +files=Files +advancedMode=Advanced Mode +advancedModeDetail=Swtich to advanced mode +showAllBoxDetail=Show all bounding boxes +hideAllBoxDetail=Hide all bounding boxes +annoPanel=anno Panel +anno=anno +addNewBbox=new bbox +reLabel=reLabel +choosemodel=Choose OCR model +tipchoosemodel=Choose OCR model from dir +ImageResize=Image Resize +IR=Image Resize +autoRecognition=Auto Recognition +reRecognition=Re-recognition +mfile=File +medit=Eidt +mview=View +mhelp=Help +iconList=Icon List +detectionBoxposition=Detection box position +recognitionResult=Recognition result +creatPolygon=Create Quadrilateral +drawSquares=Draw Squares +saveRec=Save Recognition Result +tempLabel=TEMPORARY +steps=Steps +choseModelLg=Choose Model Language +cancel=Cancel +ok=OK +autolabeling=Automatic Labeling +hideBox=Hide All Box +showBox=Show All Box +saveLabel=Save Label +singleRe=Re-recognition RectBox \ No newline at end of file diff --git a/PPOCRLabel/setup.cfg b/PPOCRLabel/setup.cfg new file mode 100644 index 0000000000..3b273b63db --- /dev/null +++ b/PPOCRLabel/setup.cfg @@ -0,0 +1,8 @@ +[bumpversion] +commit = True +tag = True + +[bumpversion:file:setup.py] + +[bdist_wheel] +universal = 1 diff --git a/PPOCRLabel/setup.py b/PPOCRLabel/setup.py new file mode 100644 index 0000000000..008514fd77 --- /dev/null +++ b/PPOCRLabel/setup.py @@ -0,0 +1,139 @@ +# Copyright (c) <2015-Present> Tzutalin +# Copyright (C) 2013 MIT, Computer Science and Artificial Intelligence Laboratory. Bryan Russell, Antonio Torralba, +# William T. Freeman. Permission is hereby granted, free of charge, to any person obtaining a copy of this software and +# associated documentation files (the "Software"), to deal in the Software without restriction, including without +# limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the +# Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: +# The above copyright notice and this permission notice shall be included in all copies or substantial portions of +# the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT +# NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT +# SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF +# CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN +# THE SOFTWARE. + +#!/usr/bin/env python +# -*- coding: utf-8 -*- + +from setuptools import setup, find_packages, Command +from sys import platform as _platform +from shutil import rmtree +import sys +import os + +here = os.path.abspath(os.path.dirname(__file__)) +NAME = 'labelImg' +REQUIRES_PYTHON = '>=3.0.0' +REQUIRED_DEP = ['pyqt5', 'lxml'] +about = {} + +with open(os.path.join(here, 'libs', '__init__.py')) as f: + exec(f.read(), about) + +with open('README.rst') as readme_file: + readme = readme_file.read() + +with open('HISTORY.rst') as history_file: + history = history_file.read() + + +# OS specific settings +SET_REQUIRES = [] +if _platform == "linux" or _platform == "linux2": + # linux + print('linux') +elif _platform == "darwin": + # MAC OS X + SET_REQUIRES.append('py2app') + +required_packages = find_packages() +required_packages.append('labelImg') + +APP = [NAME + '.py'] +OPTIONS = { + 'argv_emulation': True, + 'iconfile': 'resources/icons/app.icns' +} + +class UploadCommand(Command): + """Support setup.py upload.""" + + description=readme + '\n\n' + history, + + user_options = [] + + @staticmethod + def status(s): + """Prints things in bold.""" + print('\033[1m{0}\033[0m'.format(s)) + + def initialize_options(self): + pass + + def finalize_options(self): + pass + + def run(self): + try: + self.status('Removing previous builds…') + rmtree(os.path.join(here, 'dist')) + except OSError: + self.status('Fail to remove previous builds..') + pass + + self.status('Building Source and Wheel (universal) distribution…') + os.system( + '{0} setup.py sdist bdist_wheel --universal'.format(sys.executable)) + + self.status('Uploading the package to PyPI via Twine…') + os.system('twine upload dist/*') + + self.status('Pushing git tags…') + os.system('git tag -d v{0}'.format(about['__version__'])) + os.system('git tag v{0}'.format(about['__version__'])) + # os.system('git push --tags') + + sys.exit() + + +setup( + app=APP, + name=NAME, + version=about['__version__'], + description="LabelImg is a graphical image annotation tool and label object bounding boxes in images", + long_description=readme + '\n\n' + history, + author="TzuTa Lin", + author_email='tzu.ta.lin@gmail.com', + url='https://github.com/tzutalin/labelImg', + python_requires=REQUIRES_PYTHON, + package_dir={'labelImg': '.'}, + packages=required_packages, + entry_points={ + 'console_scripts': [ + 'labelImg=labelImg.labelImg:main' + ] + }, + include_package_data=True, + install_requires=REQUIRED_DEP, + license="MIT license", + zip_safe=False, + keywords='labelImg labelTool development annotation deeplearning', + classifiers=[ + 'Development Status :: 5 - Production/Stable', + 'Intended Audience :: Developers', + 'License :: OSI Approved :: MIT License', + 'Natural Language :: English', + 'Programming Language :: Python :: 3', + 'Programming Language :: Python :: 3.3', + 'Programming Language :: Python :: 3.4', + 'Programming Language :: Python :: 3.5', + 'Programming Language :: Python :: 3.6', + 'Programming Language :: Python :: 3.7', + ], + package_data={'data/predefined_classes.txt': ['data/predefined_classes.txt']}, + options={'py2app': OPTIONS}, + setup_requires=SET_REQUIRES, + # $ setup.py publish support. + cmdclass={ + 'upload': UploadCommand, + } +) diff --git a/README.md b/README.md index 3243f3ce24..9bb055cd42 100644 --- a/README.md +++ b/README.md @@ -1,209 +1,185 @@ -[English](README_en.md) | 简体中文 - -## 简介 -PaddleOCR旨在打造一套丰富、领先、且实用的OCR工具库,助力使用者训练出更好的模型,并应用落地。 - -**近期更新** -- 2020.8.26 更新OCR相关的84个常见问题及解答,具体参考[FAQ](./doc/doc_ch/FAQ.md) -- 2020.8.24 支持通过whl包安装使用PaddleOCR,具体参考[Paddleocr Package使用说明](./doc/doc_ch/whl.md) -- 2020.8.21 更新8月18日B站直播课回放和PPT,课节2,易学易用的OCR工具大礼包,[获取地址](https://aistudio.baidu.com/aistudio/education/group/info/1519) -- 2020.8.16 开源文本检测算法[SAST](https://arxiv.org/abs/1908.05498)和文本识别算法[SRN](https://arxiv.org/abs/2003.12294) -- 2020.7.23 发布7月21日B站直播课回放和PPT,课节1,PaddleOCR开源大礼包全面解读,[获取地址](https://aistudio.baidu.com/aistudio/course/introduce/1519) -- 2020.7.15 添加基于EasyEdge和Paddle-Lite的移动端DEMO,支持iOS和Android系统 -- [more](./doc/doc_ch/update.md) +English | [简体中文](README_ch.md) + +## Introduction +PaddleOCR aims to create multilingual, awesome, leading, and practical OCR tools that help users train better models and apply them into practice. + +## Notice +PaddleOCR supports both dynamic graph and static graph programming paradigm +- Dynamic graph: dygraph branch (default), **supported by paddle 2.0rc1+ ([installation](./doc/doc_en/installation_en.md))** +- Static graph: develop branch + +**Recent updates** +- 2020.12.15 update Data synthesis tool, i.e., [Style-Text](./StyleText/README.md),easy to synthesize a large number of images which are similar to the target scene image. +- 2020.11.25 Update a new data annotation tool, i.e., [PPOCRLabel](./PPOCRLabel/README.md), which is helpful to improve the labeling efficiency. Moreover, the labeling results can be used in training of the PP-OCR system directly. +- 2020.9.22 Update the PP-OCR technical article, https://arxiv.org/abs/2009.09941 +- [more](./doc/doc_en/update_en.md) + +## Features +- PPOCR series of high-quality pre-trained models, comparable to commercial effects + - Ultra lightweight ppocr_mobile series models: detection (3.0M) + direction classifier (1.4M) + recognition (5.0M) = 9.4M + - General ppocr_server series models: detection (47.1M) + direction classifier (1.4M) + recognition (94.9M) = 143.4M + - Support Chinese, English, and digit recognition, vertical text recognition, and long text recognition + - Support multi-language recognition: Korean, Japanese, German, French +- Rich toolkits related to the OCR areas + - Semi-automatic data annotation tool, i.e., PPOCRLabel: support fast and efficient data annotation + - Data synthesis tool, i.e., Style-Text: easy to synthesize a large number of images which are similar to the target scene image +- Support user-defined training, provides rich predictive inference deployment solutions +- Support PIP installation, easy to use +- Support Linux, Windows, MacOS and other systems + +## Visualization +
+ + +
-## 特性 -- 超轻量级中文OCR模型,总模型仅8.6M - - 单模型支持中英文数字组合识别、竖排文本识别、长文本识别 - - 检测模型DB(4.1M)+识别模型CRNN(4.5M) -- 实用通用中文OCR模型 -- 多种预测推理部署方案,包括服务部署和端侧部署 -- 多种文本检测训练算法,EAST、DB、SAST -- 多种文本识别训练算法,Rosetta、CRNN、STAR-Net、RARE、SRN -- 可运行于Linux、Windows、MacOS等多种系统 +The above pictures are the visualizations of the general ppocr_server model. For more effect pictures, please see [More visualizations](./doc/doc_en/visualization_en.md). -## 快速体验 + +## Community +- Scan the QR code below with your Wechat, you can access to official technical exchange group. Look forward to your participation.
- +
-上图是超轻量级中文OCR模型效果展示,更多效果图请见[效果展示页面](./doc/doc_ch/visualization.md)。 -- 超轻量级中文OCR在线体验地址:https://www.paddlepaddle.org.cn/hub/scene/ocr -- 移动端DEMO体验(基于EasyEdge和Paddle-Lite, 支持iOS和Android系统):[安装包二维码获取地址](https://ai.baidu.com/easyedge/app/openSource?from=paddlelite) +## Quick Experience + +You can also quickly experience the ultra-lightweight OCR : [Online Experience](https://www.paddlepaddle.org.cn/hub/scene/ocr) - Android手机也可以扫描下面二维码安装体验。 +Mobile DEMO experience (based on EasyEdge and Paddle-Lite, supports iOS and Android systems): [Sign in to the website to obtain the QR code for installing the App](https://ai.baidu.com/easyedge/app/openSource?from=paddlelite) + + Also, you can scan the QR code below to install the App (**Android support only**)
- -## 中文OCR模型列表 - -|模型名称|模型简介|检测模型地址|识别模型地址|支持空格的识别模型地址| -|-|-|-|-|-| -|chinese_db_crnn_mobile|超轻量级中文OCR模型|[inference模型](https://paddleocr.bj.bcebos.com/ch_models/ch_det_mv3_db_infer.tar) / [预训练模型](https://paddleocr.bj.bcebos.com/ch_models/ch_det_mv3_db.tar)|[inference模型](https://paddleocr.bj.bcebos.com/ch_models/ch_rec_mv3_crnn_infer.tar) / [预训练模型](https://paddleocr.bj.bcebos.com/ch_models/ch_rec_mv3_crnn.tar)|[inference模型](https://paddleocr.bj.bcebos.com/ch_models/ch_rec_mv3_crnn_enhance_infer.tar) / [预训练模型](https://paddleocr.bj.bcebos.com/ch_models/ch_rec_mv3_crnn_enhance.tar) -|chinese_db_crnn_server|通用中文OCR模型|[inference模型](https://paddleocr.bj.bcebos.com/ch_models/ch_det_r50_vd_db_infer.tar) / [预训练模型](https://paddleocr.bj.bcebos.com/ch_models/ch_det_r50_vd_db.tar)|[inference模型](https://paddleocr.bj.bcebos.com/ch_models/ch_rec_r34_vd_crnn_infer.tar) / [预训练模型](https://paddleocr.bj.bcebos.com/ch_models/ch_rec_r34_vd_crnn.tar)|[inference模型](https://paddleocr.bj.bcebos.com/ch_models/ch_rec_r34_vd_crnn_enhance_infer.tar) / [预训练模型](https://paddleocr.bj.bcebos.com/ch_models/ch_rec_r34_vd_crnn_enhance.tar) - -## 文档教程 -- [快速安装](./doc/doc_ch/installation.md) -- [中文OCR模型快速使用](./doc/doc_ch/quickstart.md) -- 算法介绍 - - [文本检测](#文本检测算法) - - [文本识别](#文本识别算法) -- 模型训练/评估 - - [文本检测](./doc/doc_ch/detection.md) - - [文本识别](./doc/doc_ch/recognition.md) - - [yml参数配置文件介绍](./doc/doc_ch/config.md) - - [中文OCR训练预测技巧](./doc/doc_ch/tricks.md) -- 预测部署 - - [基于Python预测引擎推理](./doc/doc_ch/inference.md) - - [基于C++预测引擎推理](./deploy/cpp_infer/readme.md) - - [服务化部署](./doc/doc_ch/serving.md) - - [端侧部署](./deploy/lite/readme.md) - - 模型量化压缩(coming soon) - - [Benchmark](./doc/doc_ch/benchmark.md) -- 数据集 - - [通用中英文OCR数据集](./doc/doc_ch/datasets.md) - - [手写中文OCR数据集](./doc/doc_ch/handwritten_datasets.md) - - [垂类多语言OCR数据集](./doc/doc_ch/vertical_and_multilingual_datasets.md) - - [常用数据标注工具](./doc/doc_ch/data_annotation.md) - - [常用数据合成工具](./doc/doc_ch/data_synthesis.md) -- 效果展示 - - [超轻量级中文OCR效果展示](#超轻量级中文OCR效果展示) - - [通用中文OCR效果展示](#通用中文OCR效果展示) - - [支持空格的中文OCR效果展示](#支持空格的中文OCR效果展示) -- FAQ - - [【精选】OCR精选10个问题](./doc/doc_ch/FAQ.md) - - [【理论篇】OCR通用21个问题](./doc/doc_ch/FAQ.md) - - [【实战篇】PaddleOCR实战53个问题](./doc/doc_ch/FAQ.md) -- [技术交流群](#欢迎加入PaddleOCR技术交流群) -- [参考文献](./doc/doc_ch/reference.md) -- [许可证书](#许可证书) -- [贡献代码](#贡献代码) - - -## 算法介绍 - -### 1.文本检测算法 - -PaddleOCR开源的文本检测算法列表: -- [x] EAST([paper](https://arxiv.org/abs/1704.03155)) -- [x] DB([paper](https://arxiv.org/abs/1911.08947)) -- [x] SAST([paper](https://arxiv.org/abs/1908.05498))(百度自研) - -在ICDAR2015文本检测公开数据集上,算法效果如下: - -|模型|骨干网络|precision|recall|Hmean|下载链接| -|-|-|-|-|-|-| -|EAST|ResNet50_vd|88.18%|85.51%|86.82%|[下载链接](https://paddleocr.bj.bcebos.com/det_r50_vd_east.tar)| -|EAST|MobileNetV3|81.67%|79.83%|80.74%|[下载链接](https://paddleocr.bj.bcebos.com/det_mv3_east.tar)| -|DB|ResNet50_vd|83.79%|80.65%|82.19%|[下载链接](https://paddleocr.bj.bcebos.com/det_r50_vd_db.tar)| -|DB|MobileNetV3|75.92%|73.18%|74.53%|[下载链接](https://paddleocr.bj.bcebos.com/det_mv3_db.tar)| -|SAST|ResNet50_vd|92.18%|82.96%|87.33%|[下载链接](https://paddleocr.bj.bcebos.com/SAST/sast_r50_vd_icdar2015.tar)| - -在Total-text文本检测公开数据集上,算法效果如下: - -|模型|骨干网络|precision|recall|Hmean|下载链接| -|-|-|-|-|-|-| -|SAST|ResNet50_vd|88.74%|79.80%|84.03%|[下载链接](https://paddleocr.bj.bcebos.com/SAST/sast_r50_vd_total_text.tar)| - -**说明:** SAST模型训练额外加入了icdar2013、icdar2017、COCO-Text、ArT等公开数据集进行调优。PaddleOCR用到的经过整理格式的英文公开数据集下载:[百度云地址](https://pan.baidu.com/s/12cPnZcVuV1zn5DOd4mqjVw) (提取码: 2bpi) - - -使用[LSVT](https://github.com/PaddlePaddle/PaddleOCR/blob/develop/doc/doc_ch/datasets.md#1icdar2019-lsvt)街景数据集共3w张数据,训练中文检测模型的相关配置和预训练文件如下: - -|模型|骨干网络|配置文件|预训练模型| -|-|-|-|-| -|超轻量中文模型|MobileNetV3|det_mv3_db.yml|[下载链接](https://paddleocr.bj.bcebos.com/ch_models/ch_det_mv3_db.tar)| -|通用中文OCR模型|ResNet50_vd|det_r50_vd_db.yml|[下载链接](https://paddleocr.bj.bcebos.com/ch_models/ch_det_r50_vd_db.tar)| - -* 注: 上述DB模型的训练和评估,需设置后处理参数box_thresh=0.6,unclip_ratio=1.5,使用不同数据集、不同模型训练,可调整这两个参数进行优化 - -PaddleOCR文本检测算法的训练和使用请参考文档教程中[模型训练/评估中的文本检测部分](./doc/doc_ch/detection.md)。 - - -### 2.文本识别算法 - -PaddleOCR开源的文本识别算法列表: -- [x] CRNN([paper](https://arxiv.org/abs/1507.05717)) -- [x] Rosetta([paper](https://arxiv.org/abs/1910.05085)) -- [x] STAR-Net([paper](http://www.bmva.org/bmvc/2016/papers/paper043/index.html)) -- [x] RARE([paper](https://arxiv.org/abs/1603.03915v1)) -- [x] SRN([paper](https://arxiv.org/abs/2003.12294))(百度自研) - -参考[DTRB](https://arxiv.org/abs/1904.01906)文字识别训练和评估流程,使用MJSynth和SynthText两个文字识别数据集训练,在IIIT, SVT, IC03, IC13, IC15, SVTP, CUTE数据集上进行评估,算法效果如下: - -|模型|骨干网络|Avg Accuracy|模型存储命名|下载链接| -|-|-|-|-|-| -|Rosetta|Resnet34_vd|80.24%|rec_r34_vd_none_none_ctc|[下载链接](https://paddleocr.bj.bcebos.com/rec_r34_vd_none_none_ctc.tar)| -|Rosetta|MobileNetV3|78.16%|rec_mv3_none_none_ctc|[下载链接](https://paddleocr.bj.bcebos.com/rec_mv3_none_none_ctc.tar)| -|CRNN|Resnet34_vd|82.20%|rec_r34_vd_none_bilstm_ctc|[下载链接](https://paddleocr.bj.bcebos.com/rec_r34_vd_none_bilstm_ctc.tar)| -|CRNN|MobileNetV3|79.37%|rec_mv3_none_bilstm_ctc|[下载链接](https://paddleocr.bj.bcebos.com/rec_mv3_none_bilstm_ctc.tar)| -|STAR-Net|Resnet34_vd|83.93%|rec_r34_vd_tps_bilstm_ctc|[下载链接](https://paddleocr.bj.bcebos.com/rec_r34_vd_tps_bilstm_ctc.tar)| -|STAR-Net|MobileNetV3|81.56%|rec_mv3_tps_bilstm_ctc|[下载链接](https://paddleocr.bj.bcebos.com/rec_mv3_tps_bilstm_ctc.tar)| -|RARE|Resnet34_vd|84.90%|rec_r34_vd_tps_bilstm_attn|[下载链接](https://paddleocr.bj.bcebos.com/rec_r34_vd_tps_bilstm_attn.tar)| -|RARE|MobileNetV3|83.32%|rec_mv3_tps_bilstm_attn|[下载链接](https://paddleocr.bj.bcebos.com/rec_mv3_tps_bilstm_attn.tar)| -|SRN|Resnet50_vd_fpn|88.33%|rec_r50fpn_vd_none_srn|[下载链接](https://paddleocr.bj.bcebos.com/SRN/rec_r50fpn_vd_none_srn.tar)| - -**说明:** SRN模型使用了数据扰动方法对上述提到对两个训练集进行增广,增广后的数据可以在[百度网盘](https://pan.baidu.com/s/1-HSZ-ZVdqBF2HaBZ5pRAKA)上下载,提取码: y3ry。 -原始论文使用两阶段训练平均精度为89.74%,PaddleOCR中使用one-stage训练,平均精度为88.33%。两种预训练权重均在[下载链接](https://paddleocr.bj.bcebos.com/SRN/rec_r50fpn_vd_none_srn.tar)中。 - -使用[LSVT](https://github.com/PaddlePaddle/PaddleOCR/blob/develop/doc/doc_ch/datasets.md#1icdar2019-lsvt)街景数据集根据真值将图crop出来30w数据,进行位置校准。此外基于LSVT语料生成500w合成数据训练中文模型,相关配置和预训练文件如下: - -|模型|骨干网络|配置文件|预训练模型| -|-|-|-|-| -|超轻量中文模型|MobileNetV3|rec_chinese_lite_train.yml|[下载链接](https://paddleocr.bj.bcebos.com/ch_models/ch_rec_mv3_crnn.tar)| -|通用中文OCR模型|Resnet34_vd|rec_chinese_common_train.yml|[下载链接](https://paddleocr.bj.bcebos.com/ch_models/ch_rec_r34_vd_crnn.tar)| - -PaddleOCR文本识别算法的训练和使用请参考文档教程中[模型训练/评估中的文本识别部分](./doc/doc_ch/recognition.md)。 - -## 效果展示 - - -### 1.超轻量级中文OCR效果展示 [more](./doc/doc_ch/visualization.md) +- [**OCR Quick Start**](./doc/doc_en/quickstart_en.md) + + + + +## PP-OCR 2.0 series model list(Update on Dec 15) +**Note** : Compared with [models 1.1](https://github.com/PaddlePaddle/PaddleOCR/blob/develop/doc/doc_en/models_list_en.md), which are trained with static graph programming paradigm, models 2.0 are the dynamic graph trained version and achieve close performance. + +| Model introduction | Model name | Recommended scene | Detection model | Direction classifier | Recognition model | +| ------------------------------------------------------------ | ---------------------------- | ----------------- | ------------------------------------------------------------ | ------------------------------------------------------------ | ------------------------------------------------------------ | +| Chinese and English ultra-lightweight OCR model (9.4M) | ch_ppocr_mobile_v2.0_xx | Mobile & server |[inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_infer.tar) / [pre-trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_train.tar)|[inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar) / [pre-trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_train.tar) |[inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_infer.tar) / [pre-trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_pre.tar) | +| Chinese and English general OCR model (143.4M) | ch_ppocr_server_v2.0_xx | Server |[inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_det_infer.tar) / [pre-trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_det_train.tar) |[inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar) / [pre-trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_traingit.tar) |[inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_rec_infer.tar) / [pre-trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_rec_pre.tar) | + + +For more model downloads (including multiple languages), please refer to [PP-OCR v2.0 series model downloads](./doc/doc_en/models_list_en.md). + +For a new language request, please refer to [Guideline for new language_requests](#language_requests). + +## Tutorials +- [Installation](./doc/doc_en/installation_en.md) +- [Quick Start](./doc/doc_en/quickstart_en.md) +- [Code Structure](./doc/doc_en/tree_en.md) +- Algorithm Introduction + - [Text Detection Algorithm](./doc/doc_en/algorithm_overview_en.md) + - [Text Recognition Algorithm](./doc/doc_en/algorithm_overview_en.md) + - [PP-OCR Pipeline](#PP-OCR-Pipeline) +- Model Training/Evaluation + - [Text Detection](./doc/doc_en/detection_en.md) + - [Text Recognition](./doc/doc_en/recognition_en.md) + - [Direction Classification](./doc/doc_en/angle_class_en.md) + - [Yml Configuration](./doc/doc_en/config_en.md) +- Inference and Deployment + - [Quick Inference Based on PIP](./doc/doc_en/whl_en.md) + - [Python Inference](./doc/doc_en/inference_en.md) + - [C++ Inference](./deploy/cpp_infer/readme_en.md) + - [Serving](./deploy/hubserving/readme_en.md) + - [Mobile](https://github.com/PaddlePaddle/PaddleOCR/blob/develop/deploy/lite/readme_en.md) + - [Benchmark](./doc/doc_en/benchmark_en.md) +- Data Annotation and Synthesis + - [Semi-automatic Annotation Tool: PPOCRLabel](./PPOCRLabel/README.md) + - [Data Synthesis Tool: Style-Text](./StyleText/README.md) + - [Other Data Annotation Tools](./doc/doc_en/data_annotation_en.md) + - [Other Data Synthesis Tools](./doc/doc_en/data_synthesis_en.md) +- Datasets + - [General OCR Datasets(Chinese/English)](./doc/doc_en/datasets_en.md) + - [HandWritten_OCR_Datasets(Chinese)](./doc/doc_en/handwritten_datasets_en.md) + - [Various OCR Datasets(multilingual)](./doc/doc_en/vertical_and_multilingual_datasets_en.md) +- [Visualization](#Visualization) +- [New language requests](#language_requests) +- [FAQ](./doc/doc_en/FAQ_en.md) +- [Community](#Community) +- [References](./doc/doc_en/reference_en.md) +- [License](#LICENSE) +- [Contribution](#CONTRIBUTION) + + + + + +## PP-OCR Pipeline
- +
- -### 2.通用中文OCR效果展示 [more](./doc/doc_ch/visualization.md) +PP-OCR is a practical ultra-lightweight OCR system. It is mainly composed of three parts: DB text detection[2], detection frame correction and CRNN text recognition[7]. The system adopts 19 effective strategies from 8 aspects including backbone network selection and adjustment, prediction head design, data augmentation, learning rate transformation strategy, regularization parameter selection, pre-training model use, and automatic model tailoring and quantization to optimize and slim down the models of each module. The final results are an ultra-lightweight Chinese and English OCR model with an overall size of 3.5M and a 2.8M English digital OCR model. For more details, please refer to the PP-OCR technical article (https://arxiv.org/abs/2009.09941). Besides, The implementation of the FPGM Pruner [8] and PACT quantization [9] is based on [PaddleSlim](https://github.com/PaddlePaddle/PaddleSlim). + +## Visualization [more](./doc/doc_en/visualization_en.md) +- Chinese OCR model
- + + + +
- -### 3.支持空格的中文OCR效果展示 [more](./doc/doc_ch/visualization.md) - +- English OCR model
- +
- -## 欢迎加入PaddleOCR技术交流群 -请扫描下面二维码,完成问卷填写,获取加群二维码和OCR方向的炼丹秘籍 - +- Multilingual OCR model
- + +
- -## 许可证书 -本项目的发布受Apache 2.0 license许可认证。 - - -## 贡献代码 -我们非常欢迎你为PaddleOCR贡献代码,也十分感谢你的反馈。 - -- 非常感谢 [Khanh Tran](https://github.com/xxxpsyduck) 和 [Karl Horky](https://github.com/karlhorky) 贡献修改英文文档 -- 非常感谢 [zhangxin](https://github.com/ZhangXinNan)([Blog](https://blog.csdn.net/sdlypyzq)) 贡献新的可视化方式、添加.gitgnore、处理手动设置PYTHONPATH环境变量的问题 -- 非常感谢 [lyl120117](https://github.com/lyl120117) 贡献打印网络结构的代码 -- 非常感谢 [xiangyubo](https://github.com/xiangyubo) 贡献手写中文OCR数据集 -- 非常感谢 [authorfu](https://github.com/authorfu) 贡献Android和[xiadeye](https://github.com/xiadeye) 贡献IOS的demo代码 -- 非常感谢 [BeyondYourself](https://github.com/BeyondYourself) 给PaddleOCR提了很多非常棒的建议,并简化了PaddleOCR的部分代码风格。 -- 非常感谢 [tangmq](https://gitee.com/tangmq) 给PaddleOCR增加Docker化部署服务,支持快速发布可调用的Restful API服务。 + + +## Guideline for new language requests + +If you want to request a new language support, a PR with 2 following files are needed: + +1. In folder [ppocr/utils/dict](./ppocr/utils/dict), +it is necessary to submit the dict text to this path and name it with `{language}_dict.txt` that contains a list of all characters. Please see the format example from other files in that folder. + +2. In folder [ppocr/utils/corpus](./ppocr/utils/corpus), +it is necessary to submit the corpus to this path and name it with `{language}_corpus.txt` that contains a list of words in your language. +Maybe, 50000 words per language is necessary at least. +Of course, the more, the better. + +If your language has unique elements, please tell me in advance within any way, such as useful links, wikipedia and so on. + +More details, please refer to [Multilingual OCR Development Plan](https://github.com/PaddlePaddle/PaddleOCR/issues/1048). + + + +## License +This project is released under Apache 2.0 license + + +## Contribution +We welcome all the contributions to PaddleOCR and appreciate for your feedback very much. + +- Many thanks to [Khanh Tran](https://github.com/xxxpsyduck) and [Karl Horky](https://github.com/karlhorky) for contributing and revising the English documentation. +- Many thanks to [zhangxin](https://github.com/ZhangXinNan) for contributing the new visualize function、add .gitgnore and discard set PYTHONPATH manually. +- Many thanks to [lyl120117](https://github.com/lyl120117) for contributing the code for printing the network structure. +- Thanks [xiangyubo](https://github.com/xiangyubo) for contributing the handwritten Chinese OCR datasets. +- Thanks [authorfu](https://github.com/authorfu) for contributing Android demo and [xiadeye](https://github.com/xiadeye) contributing iOS demo, respectively. +- Thanks [BeyondYourself](https://github.com/BeyondYourself) for contributing many great suggestions and simplifying part of the code style. +- Thanks [tangmq](https://gitee.com/tangmq) for contributing Dockerized deployment services to PaddleOCR and supporting the rapid release of callable Restful API services. +- Thanks [lijinhan](https://github.com/lijinhan) for contributing a new way, i.e., java SpringBoot, to achieve the request for the Hubserving deployment. +- Thanks [Mejans](https://github.com/Mejans) for contributing the Occitan corpus and character set. +- Thanks [LKKlein](https://github.com/LKKlein) for contributing a new deploying package with the Golang program language. +- Thanks [Evezerest](https://github.com/Evezerest), [ninetailskim](https://github.com/ninetailskim), [edencfc](https://github.com/edencfc), [BeyondYourself](https://github.com/BeyondYourself) and [1084667371](https://github.com/1084667371) for contributing a new data annotation tool, i.e., PPOCRLabel。 diff --git a/README_ch.md b/README_ch.md new file mode 100755 index 0000000000..b1cb778b57 --- /dev/null +++ b/README_ch.md @@ -0,0 +1,160 @@ +[English](README.md) | 简体中文 + +## 简介 +PaddleOCR旨在打造一套丰富、领先、且实用的OCR工具库,助力使用者训练出更好的模型,并应用落地。 +## 注意 +PaddleOCR同时支持动态图与静态图两种编程范式 +- 动态图版本:dygraph分支(默认),需将paddle版本升级至2.0rc1+([快速安装](./doc/doc_ch/installation.md)) +- 静态图版本:develop分支 + +**近期更新** +- 2020.12.15 更新数据合成工具[Style-Text](./StyleText/README_ch.md),可以批量合成大量与目标场景类似的图像,在多个场景验证,效果明显提升。 +- 2020.12.14 [FAQ](./doc/doc_ch/FAQ.md)新增5个高频问题,总数127个,每周一都会更新,欢迎大家持续关注。 +- 2020.11.25 更新半自动标注工具[PPOCRLabel](./PPOCRLabel/README_ch.md),辅助开发者高效完成标注任务,输出格式与PP-OCR训练任务完美衔接。 +- 2020.9.22 更新PP-OCR技术文章,https://arxiv.org/abs/2009.09941 +- [More](./doc/doc_ch/update.md) + + + +## 特性 + +- PPOCR系列高质量预训练模型,准确的识别效果 + - 超轻量ppocr_mobile移动端系列:检测(3.0M)+方向分类器(1.4M)+ 识别(5.0M)= 9.4M + - 通用ppocr_server系列:检测(47.1M)+方向分类器(1.4M)+ 识别(94.9M)= 143.4M + - 支持中英文数字组合识别、竖排文本识别、长文本识别 + - 支持多语言识别:韩语、日语、德语、法语 +- 丰富易用的OCR相关工具组件 + - 半自动数据标注工具PPOCRLabel:支持快速高效的数据标注 + - 数据合成工具Style-Text:批量合成大量与目标场景类似的图像 +- 支持用户自定义训练,提供丰富的预测推理部署方案 +- 支持PIP快速安装使用 +- 可运行于Linux、Windows、MacOS等多种系统 + +## 效果展示 + +
+ + +
+ +上图是通用ppocr_server模型效果展示,更多效果图请见[效果展示页面](./doc/doc_ch/visualization.md)。 + + +## 欢迎加入PaddleOCR技术交流群 +- 微信扫描二维码加入官方交流群,获得更高效的问题答疑,与各行各业开发者充分交流,期待您的加入。 + +
+ +
+ +## 快速体验 +- PC端:超轻量级中文OCR在线体验地址:https://www.paddlepaddle.org.cn/hub/scene/ocr + +- 移动端:[安装包DEMO下载地址](https://ai.baidu.com/easyedge/app/openSource?from=paddlelite)(基于EasyEdge和Paddle-Lite, 支持iOS和Android系统),Android手机也可以直接扫描下面二维码安装体验。 + + +
+ +
+ +- 代码体验:从[快速安装](./doc/doc_ch/quickstart.md) 开始 + + +## PP-OCR 2.0系列模型列表(更新中) +**说明** :2.0版模型和[1.1版模型](https://github.com/PaddlePaddle/PaddleOCR/blob/develop/doc/doc_ch/models_list.md)的主要区别在于动态图训练vs.静态图训练,模型性能上无明显差距。 +| 模型简介 | 模型名称 |推荐场景 | 检测模型 | 方向分类器 | 识别模型 | +| ------------ | --------------- | ----------------|---- | ---------- | -------- | +| 中英文超轻量OCR模型(9.4M) | ch_ppocr_mobile_v2.0_xx |移动端&服务器端|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_infer.tar) / [预训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_train.tar)|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar) / [预训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_train.tar) |[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_infer.tar) / [预训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_pre.tar) | +| 中英文通用OCR模型(143.4M) |ch_ppocr_server_v2.0_xx|服务器端 |[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_det_infer.tar) / [预训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_det_train.tar) |[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar) / [预训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_train.tar) |[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_rec_infer.tar) / [预训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_rec_pre.tar) | + +更多模型下载(包括多语言),可以参考[PP-OCR v2.0 系列模型下载](./doc/doc_ch/models_list.md) + +## 文档教程 +- [快速安装](./doc/doc_ch/installation.md) +- [中文OCR模型快速使用](./doc/doc_ch/quickstart.md) +- [代码组织结构](./doc/doc_ch/tree.md) +- 算法介绍 + - [文本检测](./doc/doc_ch/algorithm_overview.md) + - [文本识别](./doc/doc_ch/algorithm_overview.md) + - [PP-OCR Pipline](#PP-OCR) +- 模型训练/评估 + - [文本检测](./doc/doc_ch/detection.md) + - [文本识别](./doc/doc_ch/recognition.md) + - [方向分类器](./doc/doc_ch/angle_class.md) + - [yml参数配置文件介绍](./doc/doc_ch/config.md) +- 预测部署 + - [基于pip安装whl包快速推理](./doc/doc_ch/whl.md) + - [基于Python脚本预测引擎推理](./doc/doc_ch/inference.md) + - [基于C++预测引擎推理](./deploy/cpp_infer/readme.md) + - [服务化部署](./deploy/hubserving/readme.md) + - [端侧部署](https://github.com/PaddlePaddle/PaddleOCR/blob/develop/deploy/lite/readme.md) + - [Benchmark](./doc/doc_ch/benchmark.md) +- 数据集 + - [通用中英文OCR数据集](./doc/doc_ch/datasets.md) + - [手写中文OCR数据集](./doc/doc_ch/handwritten_datasets.md) + - [垂类多语言OCR数据集](./doc/doc_ch/vertical_and_multilingual_datasets.md) +- 数据标注与合成 + - [半自动标注工具PPOCRLabel](./PPOCRLabel/README_ch.md) + - [数据合成工具Style-Text](./StyleText/README_ch.md) + - [其它数据标注工具](./doc/doc_ch/data_annotation.md) + - [其它数据合成工具](./doc/doc_ch/data_synthesis.md) +- [效果展示](#效果展示) +- FAQ + - [【精选】OCR精选10个问题](./doc/doc_ch/FAQ.md) + - [【理论篇】OCR通用30个问题](./doc/doc_ch/FAQ.md) + - [【实战篇】PaddleOCR实战84个问题](./doc/doc_ch/FAQ.md) +- [技术交流群](#欢迎加入PaddleOCR技术交流群) +- [参考文献](./doc/doc_ch/reference.md) +- [许可证书](#许可证书) +- [贡献代码](#贡献代码) + + + +## PP-OCR Pipline +
+ +
+ +PP-OCR是一个实用的超轻量OCR系统。主要由DB文本检测[2]、检测框矫正和CRNN文本识别三部分组成[7]。该系统从骨干网络选择和调整、预测头部的设计、数据增强、学习率变换策略、正则化参数选择、预训练模型使用以及模型自动裁剪量化8个方面,采用19个有效策略,对各个模块的模型进行效果调优和瘦身,最终得到整体大小为3.5M的超轻量中英文OCR和2.8M的英文数字OCR。更多细节请参考PP-OCR技术方案 https://arxiv.org/abs/2009.09941 。其中FPGM裁剪器[8]和PACT量化[9]的实现可以参考[PaddleSlim](https://github.com/PaddlePaddle/PaddleSlim)。 + + +## 效果展示 [more](./doc/doc_ch/visualization.md) +- 中文模型 +
+ + + + +
+ +- 英文模型 +
+ +
+ +- 其他语言模型 +
+ + +
+ + + +## 许可证书 +本项目的发布受Apache 2.0 license许可认证。 + + +## 贡献代码 +我们非常欢迎你为PaddleOCR贡献代码,也十分感谢你的反馈。 + + +- 非常感谢 [Khanh Tran](https://github.com/xxxpsyduck) 和 [Karl Horky](https://github.com/karlhorky) 贡献修改英文文档 +- 非常感谢 [zhangxin](https://github.com/ZhangXinNan)([Blog](https://blog.csdn.net/sdlypyzq)) 贡献新的可视化方式、添加.gitgnore、处理手动设置PYTHONPATH环境变量的问题 +- 非常感谢 [lyl120117](https://github.com/lyl120117) 贡献打印网络结构的代码 +- 非常感谢 [xiangyubo](https://github.com/xiangyubo) 贡献手写中文OCR数据集 +- 非常感谢 [authorfu](https://github.com/authorfu) 贡献Android和[xiadeye](https://github.com/xiadeye) 贡献IOS的demo代码 +- 非常感谢 [BeyondYourself](https://github.com/BeyondYourself) 给PaddleOCR提了很多非常棒的建议,并简化了PaddleOCR的部分代码风格。 +- 非常感谢 [tangmq](https://gitee.com/tangmq) 给PaddleOCR增加Docker化部署服务,支持快速发布可调用的Restful API服务。 +- 非常感谢 [lijinhan](https://github.com/lijinhan) 给PaddleOCR增加java SpringBoot 调用OCR Hubserving接口完成对OCR服务化部署的使用。 +- 非常感谢 [Mejans](https://github.com/Mejans) 给PaddleOCR增加新语言奥克西坦语Occitan的字典和语料。 +- 非常感谢 [Evezerest](https://github.com/Evezerest), [ninetailskim](https://github.com/ninetailskim), [edencfc](https://github.com/edencfc), [BeyondYourself](https://github.com/BeyondYourself), [1084667371](https://github.com/1084667371) 贡献了PPOCRLabel的完整代码。 diff --git a/README_en.md b/README_en.md deleted file mode 100644 index 37250da2cd..0000000000 --- a/README_en.md +++ /dev/null @@ -1,231 +0,0 @@ -English | [简体中文](README.md) - -## Introduction -PaddleOCR aims to create rich, leading, and practical OCR tools that help users train better models and apply them into practice. - -**Recent updates** -- 2020.8.24 Support the use of PaddleOCR through whl package installation,pelease refer [PaddleOCR Package](https://github.com/PaddlePaddle/PaddleOCR/blob/develop/doc/doc_en/whl_en.md) -- 2020.8.16, Release text detection algorithm [SAST](https://arxiv.org/abs/1908.05498) and text recognition algorithm [SRN](https://arxiv.org/abs/2003.12294) -- 2020.7.23, Release the playback and PPT of live class on BiliBili station, PaddleOCR Introduction, [address](https://aistudio.baidu.com/aistudio/course/introduce/1519) -- 2020.7.15, Add mobile App demo , support both iOS and Android ( based on easyedge and Paddle Lite) -- 2020.7.15, Improve the deployment ability, add the C + + inference , serving deployment. In addition, the benchmarks of the ultra-lightweight OCR model are provided. -- 2020.7.15, Add several related datasets, data annotation and synthesis tools. -- [more](./doc/doc_en/update_en.md) - -## Features -- Ultra-lightweight OCR model, total model size is only 8.6M - - Single model supports Chinese/English numbers combination recognition, vertical text recognition, long text recognition - - Detection model DB (4.1M) + recognition model CRNN (4.5M) -- Various text detection algorithms: EAST, DB -- Various text recognition algorithms: Rosetta, CRNN, STAR-Net, RARE -- Support Linux, Windows, macOS and other systems. - -## Visualization - -![](doc/imgs_results/11.jpg) - -![](doc/imgs_results/img_10.jpg) - -[More visualization](./doc/doc_en/visualization_en.md) - -You can also quickly experience the ultra-lightweight OCR : [Online Experience](https://www.paddlepaddle.org.cn/hub/scene/ocr) - -Mobile DEMO experience (based on EasyEdge and Paddle-Lite, supports iOS and Android systems): [Sign in to the website to obtain the QR code for installing the App](https://ai.baidu.com/easyedge/app/openSource?from=paddlelite) - - Also, you can scan the QR code below to install the App (**Android support only**) - -
- -
- -- [**OCR Quick Start**](./doc/doc_en/quickstart_en.md) - - - -### Supported Models: - -|Model Name|Description |Detection Model link|Recognition Model link| Support for space Recognition Model link| -|-|-|-|-|-| -|db_crnn_mobile|ultra-lightweight OCR model|[inference model](https://paddleocr.bj.bcebos.com/ch_models/ch_det_mv3_db_infer.tar) / [pre-trained model](https://paddleocr.bj.bcebos.com/ch_models/ch_det_mv3_db.tar)|[inference model](https://paddleocr.bj.bcebos.com/ch_models/ch_rec_mv3_crnn_infer.tar) / [pre-trained model](https://paddleocr.bj.bcebos.com/ch_models/ch_rec_mv3_crnn.tar)|[inference model](https://paddleocr.bj.bcebos.com/ch_models/ch_rec_mv3_crnn_enhance_infer.tar) / [pre-train model](https://paddleocr.bj.bcebos.com/ch_models/ch_rec_mv3_crnn_enhance.tar) -|db_crnn_server|General OCR model|[inference model](https://paddleocr.bj.bcebos.com/ch_models/ch_det_r50_vd_db_infer.tar) / [pre-trained model](https://paddleocr.bj.bcebos.com/ch_models/ch_det_r50_vd_db.tar)|[inference model](https://paddleocr.bj.bcebos.com/ch_models/ch_rec_r34_vd_crnn_infer.tar) / [pre-trained model](https://paddleocr.bj.bcebos.com/ch_models/ch_rec_r34_vd_crnn.tar)|[inference model](https://paddleocr.bj.bcebos.com/ch_models/ch_rec_r34_vd_crnn_enhance_infer.tar) / [pre-train model](https://paddleocr.bj.bcebos.com/ch_models/ch_rec_r34_vd_crnn_enhance.tar) - - -## Tutorials -- [Installation](./doc/doc_en/installation_en.md) -- [Quick Start](./doc/doc_en/quickstart_en.md) -- Algorithm introduction - - [Text Detection Algorithm](#TEXTDETECTIONALGORITHM) - - [Text Recognition Algorithm](#TEXTRECOGNITIONALGORITHM) - - [END-TO-END OCR Algorithm](#ENDENDOCRALGORITHM) -- Model training/evaluation - - [Text Detection](./doc/doc_en/detection_en.md) - - [Text Recognition](./doc/doc_en/recognition_en.md) - - [Yml Configuration](./doc/doc_en/config_en.md) - - [Tricks](./doc/doc_en/tricks_en.md) -- Deployment - - [Python Inference](./doc/doc_en/inference_en.md) - - [C++ Inference](./deploy/cpp_infer/readme_en.md) - - [Serving](./doc/doc_en/serving_en.md) - - [Mobile](./deploy/lite/readme_en.md) - - Model Quantization and Compression (coming soon) - - [Benchmark](./doc/doc_en/benchmark_en.md) -- Datasets - - [General OCR Datasets(Chinese/English)](./doc/doc_en/datasets_en.md) - - [HandWritten_OCR_Datasets(Chinese)](./doc/doc_en/handwritten_datasets_en.md) - - [Various OCR Datasets(multilingual)](./doc/doc_en/vertical_and_multilingual_datasets_en.md) - - [Data Annotation Tools](./doc/doc_en/data_annotation_en.md) - - [Data Synthesis Tools](./doc/doc_en/data_synthesis_en.md) -- [FAQ](#FAQ) -- Visualization - - [Ultra-lightweight Chinese/English OCR Visualization](#UCOCRVIS) - - [General Chinese/English OCR Visualization](#GeOCRVIS) - - [Chinese/English OCR Visualization (Support Space Recognition )](#SpaceOCRVIS) -- [Community](#Community) -- [References](./doc/doc_en/reference_en.md) -- [License](#LICENSE) -- [Contribution](#CONTRIBUTION) - - -## Text Detection Algorithm - -PaddleOCR open source text detection algorithms list: -- [x] EAST([paper](https://arxiv.org/abs/1704.03155)) -- [x] DB([paper](https://arxiv.org/abs/1911.08947)) -- [x] SAST([paper](https://arxiv.org/abs/1908.05498))(Baidu Self-Research) - -On the ICDAR2015 dataset, the text detection result is as follows: - -|Model|Backbone|precision|recall|Hmean|Download link| -|-|-|-|-|-|-| -|EAST|ResNet50_vd|88.18%|85.51%|86.82%|[Download link](https://paddleocr.bj.bcebos.com/det_r50_vd_east.tar)| -|EAST|MobileNetV3|81.67%|79.83%|80.74%|[Download link](https://paddleocr.bj.bcebos.com/det_mv3_east.tar)| -|DB|ResNet50_vd|83.79%|80.65%|82.19%|[Download link](https://paddleocr.bj.bcebos.com/det_r50_vd_db.tar)| -|DB|MobileNetV3|75.92%|73.18%|74.53%|[Download link](https://paddleocr.bj.bcebos.com/det_mv3_db.tar)| -|SAST|ResNet50_vd|92.18%|82.96%|87.33%|[Download link](https://paddleocr.bj.bcebos.com/SAST/sast_r50_vd_icdar2015.tar)| - -On Total-Text dataset, the text detection result is as follows: - -|Model|Backbone|precision|recall|Hmean|Download link| -|-|-|-|-|-|-| -|SAST|ResNet50_vd|88.74%|79.80%|84.03%|[Download link](https://paddleocr.bj.bcebos.com/SAST/sast_r50_vd_total_text.tar)| - -**Note:** Additional data, like icdar2013, icdar2017, COCO-Text, ArT, was added to the model training of SAST. Download English public dataset in organized format used by PaddleOCR from [Baidu Drive](https://pan.baidu.com/s/12cPnZcVuV1zn5DOd4mqjVw) (download code: 2bpi). - -For use of [LSVT](https://github.com/PaddlePaddle/PaddleOCR/blob/develop/doc/doc_en/datasets_en.md#1-icdar2019-lsvt) street view dataset with a total of 3w training data,the related configuration and pre-trained models for text detection task are as follows: -|Model|Backbone|Configuration file|Pre-trained model| -|-|-|-|-| -|ultra-lightweight OCR model|MobileNetV3|det_mv3_db.yml|[Download link](https://paddleocr.bj.bcebos.com/ch_models/ch_det_mv3_db.tar)| -|General OCR model|ResNet50_vd|det_r50_vd_db.yml|[Download link](https://paddleocr.bj.bcebos.com/ch_models/ch_det_r50_vd_db.tar)| - -* Note: For the training and evaluation of the above DB model, post-processing parameters box_thresh=0.6 and unclip_ratio=1.5 need to be set. If using different datasets and different models for training, these two parameters can be adjusted for better result. - -For the training guide and use of PaddleOCR text detection algorithms, please refer to the document [Text detection model training/evaluation/prediction](./doc/doc_en/detection_en.md) - - -## Text Recognition Algorithm - -PaddleOCR open-source text recognition algorithms list: -- [x] CRNN([paper](https://arxiv.org/abs/1507.05717)) -- [x] Rosetta([paper](https://arxiv.org/abs/1910.05085)) -- [x] STAR-Net([paper](http://www.bmva.org/bmvc/2016/papers/paper043/index.html)) -- [x] RARE([paper](https://arxiv.org/abs/1603.03915v1)) -- [x] SRN([paper](https://arxiv.org/abs/2003.12294))(Baidu Self-Research) - -Refer to [DTRB](https://arxiv.org/abs/1904.01906), the training and evaluation result of these above text recognition (using MJSynth and SynthText for training, evaluate on IIIT, SVT, IC03, IC13, IC15, SVTP, CUTE) is as follow: - -|Model|Backbone|Avg Accuracy|Module combination|Download link| -|-|-|-|-|-| -|Rosetta|Resnet34_vd|80.24%|rec_r34_vd_none_none_ctc|[Download link](https://paddleocr.bj.bcebos.com/rec_r34_vd_none_none_ctc.tar)| -|Rosetta|MobileNetV3|78.16%|rec_mv3_none_none_ctc|[Download link](https://paddleocr.bj.bcebos.com/rec_mv3_none_none_ctc.tar)| -|CRNN|Resnet34_vd|82.20%|rec_r34_vd_none_bilstm_ctc|[Download link](https://paddleocr.bj.bcebos.com/rec_r34_vd_none_bilstm_ctc.tar)| -|CRNN|MobileNetV3|79.37%|rec_mv3_none_bilstm_ctc|[Download link](https://paddleocr.bj.bcebos.com/rec_mv3_none_bilstm_ctc.tar)| -|STAR-Net|Resnet34_vd|83.93%|rec_r34_vd_tps_bilstm_ctc|[Download link](https://paddleocr.bj.bcebos.com/rec_r34_vd_tps_bilstm_ctc.tar)| -|STAR-Net|MobileNetV3|81.56%|rec_mv3_tps_bilstm_ctc|[Download link](https://paddleocr.bj.bcebos.com/rec_mv3_tps_bilstm_ctc.tar)| -|RARE|Resnet34_vd|84.90%|rec_r34_vd_tps_bilstm_attn|[Download link](https://paddleocr.bj.bcebos.com/rec_r34_vd_tps_bilstm_attn.tar)| -|RARE|MobileNetV3|83.32%|rec_mv3_tps_bilstm_attn|[Download link](https://paddleocr.bj.bcebos.com/rec_mv3_tps_bilstm_attn.tar)| -|SRN|Resnet50_vd_fpn|88.33%|rec_r50fpn_vd_none_srn|[Download link](https://paddleocr.bj.bcebos.com/SRN/rec_r50fpn_vd_none_srn.tar)| - -**Note:** SRN model uses data expansion method to expand the two training sets mentioned above, and the expanded data can be downloaded from [Baidu Drive](https://pan.baidu.com/s/1-HSZ-ZVdqBF2HaBZ5pRAKA) (download code: y3ry). - -The average accuracy of the two-stage training in the original paper is 89.74%, and that of one stage training in paddleocr is 88.33%. Both pre-trained weights can be downloaded [here](https://paddleocr.bj.bcebos.com/SRN/rec_r50fpn_vd_none_srn.tar). - -We use [LSVT](https://github.com/PaddlePaddle/PaddleOCR/blob/develop/doc/doc_en/datasets_en.md#1-icdar2019-lsvt) dataset and cropout 30w training data from original photos by using position groundtruth and make some calibration needed. In addition, based on the LSVT corpus, 500w synthetic data is generated to train the model. The related configuration and pre-trained models are as follows: - -|Model|Backbone|Configuration file|Pre-trained model| -|-|-|-|-| -|ultra-lightweight OCR model|MobileNetV3|rec_chinese_lite_train.yml|[Download link](https://paddleocr.bj.bcebos.com/ch_models/ch_rec_mv3_crnn.tar)|[inference model](https://paddleocr.bj.bcebos.com/ch_models/ch_rec_mv3_crnn_enhance_infer.tar) & [pre-trained model](https://paddleocr.bj.bcebos.com/ch_models/ch_rec_mv3_crnn_enhance.tar)| -|General OCR model|Resnet34_vd|rec_chinese_common_train.yml|[Download link](https://paddleocr.bj.bcebos.com/ch_models/ch_rec_r34_vd_crnn.tar)|[inference model](https://paddleocr.bj.bcebos.com/ch_models/ch_rec_r34_vd_crnn_enhance_infer.tar) & [pre-trained model](https://paddleocr.bj.bcebos.com/ch_models/ch_rec_r34_vd_crnn_enhance.tar)| - -Please refer to the document for training guide and use of PaddleOCR text recognition algorithms [Text recognition model training/evaluation/prediction](./doc/doc_en/recognition_en.md) - - -## END-TO-END OCR Algorithm -- [ ] [End2End-PSL](https://arxiv.org/abs/1909.07808)(Baidu Self-Research, coming soon) - -## Visualization - - -### 1.Ultra-lightweight Chinese/English OCR Visualization [more](./doc/doc_en/visualization_en.md) - -
- -
- - -### 2. General Chinese/English OCR Visualization [more](./doc/doc_en/visualization_en.md) - -
- -
- - -### 3.Chinese/English OCR Visualization (Space_support) [more](./doc/doc_en/visualization_en.md) - -
- -
- - - -## FAQ -1. Error when using attention-based recognition model: KeyError: 'predict' - - The inference of recognition model based on attention loss is still being debugged. For Chinese text recognition, it is recommended to choose the recognition model based on CTC loss first. In practice, it is also found that the recognition model based on attention loss is not as effective as the one based on CTC loss. - -2. About inference speed - - When there are a lot of texts in the picture, the prediction time will increase. You can use `--rec_batch_num` to set a smaller prediction batch size. The default value is 30, which can be changed to 10 or other values. - -3. Service deployment and mobile deployment - - It is expected that the service deployment based on Serving and the mobile deployment based on Paddle Lite will be released successively in mid-to-late June. Stay tuned for more updates. - -4. Release time of self-developed algorithm - - Baidu Self-developed algorithms such as SAST, SRN and end2end PSL will be released in June or July. Please be patient. - -[more](./doc/doc_en/FAQ_en.md) - - -## Community -Scan the QR code below with your wechat and completing the questionnaire, you can access to offical technical exchange group. - -
- -
- - -## License -This project is released under Apache 2.0 license - - -## Contribution -We welcome all the contributions to PaddleOCR and appreciate for your feedback very much. - -- Many thanks to [Khanh Tran](https://github.com/xxxpsyduck) and [Karl Horky](https://github.com/karlhorky) for contributing and revising the English documentation. -- Many thanks to [zhangxin](https://github.com/ZhangXinNan) for contributing the new visualize function、add .gitgnore and discard set PYTHONPATH manually. -- Many thanks to [lyl120117](https://github.com/lyl120117) for contributing the code for printing the network structure. -- Thanks [xiangyubo](https://github.com/xiangyubo) for contributing the handwritten Chinese OCR datasets. -- Thanks [authorfu](https://github.com/authorfu) for contributing Android demo and [xiadeye](https://github.com/xiadeye) contributing iOS demo, respectively. -- Thanks [BeyondYourself](https://github.com/BeyondYourself) for contributing many great suggestions and simplifying part of the code style. -- Thanks [tangmq](https://gitee.com/tangmq) for contributing Dockerized deployment services to PaddleOCR and supporting the rapid release of callable Restful API services. diff --git a/StyleText/README.md b/StyleText/README.md new file mode 100644 index 0000000000..697f439c0e --- /dev/null +++ b/StyleText/README.md @@ -0,0 +1,220 @@ +English | [简体中文](README_ch.md) + +## Style Text + +### Contents +- [1. Introduction](#Introduction) +- [2. Preparation](#Preparation) +- [3. Quick Start](#Quick_Start) +- [4. Applications](#Applications) +- [5. Code Structure](#Code_structure) + + + +### Introduction + +
+ +
+ +
+ +
+ + +The Style-Text data synthesis tool is a tool based on Baidu and HUST cooperation research work, "Editing Text in the Wild" [https://arxiv.org/abs/1908.03047](https://arxiv.org/abs/1908.03047). + +Different from the commonly used GAN-based data synthesis tools, the main framework of Style-Text includes: +* (1) Text foreground style transfer module. +* (2) Background extraction module. +* (3) Fusion module. + +After these three steps, you can quickly realize the image text style transfer. The following figure is some results of the data synthesis tool. + +
+ +
+ + + +#### Preparation + +1. Please refer the [QUICK INSTALLATION](../doc/doc_en/installation_en.md) to install PaddlePaddle. Python3 environment is strongly recommended. +2. Download the pretrained models and unzip: + +```bash +cd StyleText +wget https://paddleocr.bj.bcebos.com/dygraph_v2.0/style_text/style_text_models.zip +unzip style_text_models.zip +``` + +If you save the model in another location, please modify the address of the model file in `configs/config.yml`, and you need to modify these three configurations at the same time: + +``` +bg_generator: + pretrain: style_text_rec/bg_generator +... +text_generator: + pretrain: style_text_models/text_generator +... +fusion_generator: + pretrain: style_text_models/fusion_generator +``` + + +### Quick Start + +#### Synthesis single image + +1. You can run `tools/synth_image` and generate the demo image, which is saved in the current folder. + +```python +python3 tools/synth_image.py -c configs/config.yml --style_image examples/style_images/2.jpg --text_corpus PaddleOCR --language en +``` + +* Note 1: The language options is correspond to the corpus. Currently, the tool only supports English, Simplified Chinese and Korean. +* Note 2: Synth-Text is mainly used to generate images for OCR recognition models. + So the height of style images should be around 32 pixels. Images in other sizes may behave poorly. +* Note 3: You can modify `use_gpu` in `configs/config.yml` to determine whether to use GPU for prediction. + + + +For example, enter the following image and corpus `PaddleOCR`. + +
+ +
+ +The result `fake_fusion.jpg` will be generated. + +
+ +
+ +What's more, the medium result `fake_bg.jpg` will also be saved, which is the background output. + +
+ +
+ + +`fake_text.jpg` * `fake_text.jpg` is the generated image with the same font style as `Style Input`. + + +
+ +
+ + +#### Batch synthesis + +In actual application scenarios, it is often necessary to synthesize pictures in batches and add them to the training set. StyleText can use a batch of style pictures and corpus to synthesize data in batches. The synthesis process is as follows: + +1. The referenced dataset can be specifed in `configs/dataset_config.yml`: + + * `Global`: + * `output_dir:`:Output synthesis data path. + * `StyleSampler`: + * `image_home`:style images' folder. + * `label_file`:Style images' file list. If label is provided, then it is the label file path. + * `with_label`:Whether the `label_file` is label file list. + * `CorpusGenerator`: + * `method`:Method of CorpusGenerator,supports `FileCorpus` and `EnNumCorpus`. If `EnNumCorpus` is used,No other configuration is needed,otherwise you need to set `corpus_file` and `language`. + * `language`:Language of the corpus. + * `corpus_file`: Filepath of the corpus. Corpus file should be a text file which will be split by line-endings('\n'). Corpus generator samples one line each time. + + +Example of corpus file: +``` +PaddleOCR +飞桨文字识别 +StyleText +风格文本图像数据合成 +``` + +We provide a general dataset containing Chinese, English and Korean (50,000 images in all) for your trial ([download link](https://paddleocr.bj.bcebos.com/dygraph_v2.0/style_text/chkoen_5w.tar)), some examples are given below : + +
+ +
+ +2. You can run the following command to start synthesis task: + + ``` bash + python3 tools/synth_dataset.py -c configs/dataset_config.yml + ``` + +We also provide example corpus and images in `examples` folder. +
+ + +
+If you run the code above directly, you will get example output data in `output_data` folder. +You will get synthesis images and labels as below: +
+ +
+There will be some cache under the `label` folder. If the program exit unexpectedly, you can find cached labels there. +When the program finish normally, you will find all the labels in `label.txt` which give the final results. + + +### Applications +We take two scenes as examples, which are metal surface English number recognition and general Korean recognition, to illustrate practical cases of using StyleText to synthesize data to improve text recognition. The following figure shows some examples of real scene images and composite images: + +
+ +
+ + +After adding the above synthetic data for training, the accuracy of the recognition model is improved, which is shown in the following table: + + +| Scenario | Characters | Raw Data | Test Data | Only Use Raw Data
Recognition Accuracy | New Synthetic Data | Simultaneous Use of Synthetic Data
Recognition Accuracy | Index Improvement | +| -------- | ---------- | -------- | -------- | -------------------------- | ------------ | ---------------------- | -------- | +| Metal surface | English and numbers | 2203 | 650 | 0.5938 | 20000 | 0.7546 | 16% | +| Random background | Korean | 5631 | 1230 | 0.3012 | 100000 | 0.5057 | 20% | + + + +### Code Structure + +``` +StyleText +|-- arch // Network module files. +| |-- base_module.py +| |-- decoder.py +| |-- encoder.py +| |-- spectral_norm.py +| `-- style_text_rec.py +|-- configs // Config files. +| |-- config.yml +| `-- dataset_config.yml +|-- engine // Synthesis engines. +| |-- corpus_generators.py // Sample corpus from file or generate random corpus. +| |-- predictors.py // Predict using network. +| |-- style_samplers.py // Sample style images. +| |-- synthesisers.py // Manage other engines to synthesis images. +| |-- text_drawers.py // Generate standard input text images. +| `-- writers.py // Write synthesis images and labels into files. +|-- examples // Example files. +| |-- corpus +| | `-- example.txt +| |-- image_list.txt +| `-- style_images +| |-- 1.jpg +| `-- 2.jpg +|-- fonts // Font files. +| |-- ch_standard.ttf +| |-- en_standard.ttf +| `-- ko_standard.ttf +|-- tools // Program entrance. +| |-- __init__.py +| |-- synth_dataset.py // Synthesis dataset. +| `-- synth_image.py // Synthesis image. +`-- utils // Module of basic functions. + |-- config.py + |-- load_params.py + |-- logging.py + |-- math_functions.py + `-- sys_funcs.py +``` diff --git a/StyleText/README_ch.md b/StyleText/README_ch.md new file mode 100644 index 0000000000..ca7f712248 --- /dev/null +++ b/StyleText/README_ch.md @@ -0,0 +1,205 @@ +简体中文 | [English](README.md) + +## Style Text + + +### 目录 +- [一、工具简介](#工具简介) +- [二、环境配置](#环境配置) +- [三、快速上手](#快速上手) +- [四、应用案例](#应用案例) +- [五、代码结构](#代码结构) + + +### 一、工具简介 +
+ +
+ +
+ +
+ + +Style-Text数据合成工具是基于百度和华科合作研发的文本编辑算法《Editing Text in the Wild》https://arxiv.org/abs/1908.03047 + +不同于常用的基于GAN的数据合成工具,Style-Text主要框架包括:1.文本前景风格迁移模块 2.背景抽取模块 3.融合模块。经过这样三步,就可以迅速实现图像文本风格迁移。下图是一些该数据合成工具效果图。 + +
+ +
+ + +### 二、环境配置 + +1. 参考[快速安装](../doc/doc_ch/installation.md),安装PaddleOCR。 +2. 进入`StyleText`目录,下载模型,并解压: + +```bash +cd StyleText +wget https://paddleocr.bj.bcebos.com/dygraph_v2.0/style_text/style_text_models.zip +unzip style_text_models.zip +``` + +如果您将模型保存再其他位置,请在`configs/config.yml`中修改模型文件的地址,修改时需要同时修改这三个配置: + +``` +bg_generator: + pretrain: style_text_models/bg_generator +... +text_generator: + pretrain: style_text_models/text_generator +... +fusion_generator: + pretrain: style_text_models/fusion_generator +``` + + +### 三、快速上手 + +#### 合成单张图 +输入一张风格图和一段文字语料,运行tools/synth_image,合成单张图片,结果图像保存在当前目录下: + +```python +python3 tools/synth_image.py -c configs/config.yml --style_image examples/style_images/2.jpg --text_corpus PaddleOCR --language en +``` +* 注1:语言选项和语料相对应,目前该工具只支持英文、简体中文和韩语。 +* 注2:Style-Text生成的数据主要应用于OCR识别场景。基于当前PaddleOCR识别模型的设计,我们主要支持高度在32左右的风格图像。 + 如果输入图像尺寸相差过多,效果可能不佳。 +* 注3:可以通过修改配置文件中的`use_gpu`(true或者false)参数来决定是否使用GPU进行预测。 + + +例如,输入如下图片和语料"PaddleOCR": + +
+ +
+ +生成合成数据`fake_fusion.jpg`: +
+ +
+ +除此之外,程序还会生成并保存中间结果`fake_bg.jpg`:为风格参考图去掉文字后的背景; + +
+ +
+ +`fake_text.jpg`:是用提供的字符串,仿照风格参考图中文字的风格,生成在灰色背景上的文字图片。 + +
+ +
+ +#### 批量合成 +在实际应用场景中,经常需要批量合成图片,补充到训练集中。Style-Text可以使用一批风格图片和语料,批量合成数据。合成过程如下: + +1. 在`configs/dataset_config.yml`中配置目标场景风格图像和语料的路径,具体如下: + + * `Global`: + * `output_dir:`:保存合成数据的目录。 + * `StyleSampler`: + * `image_home`:风格图片目录; + * `label_file`:风格图片路径列表文件,如果所用数据集有label,则label_file为label文件路径; + * `with_label`:标志`label_file`是否为label文件。 + * `CorpusGenerator`: + * `method`:语料生成方法,目前有`FileCorpus`和`EnNumCorpus`可选。如果使用`EnNumCorpus`,则不需要填写其他配置,否则需要修改`corpus_file`和`language`; + * `language`:语料的语种; + * `corpus_file`: 语料文件路径。语料文件应使用文本文件。语料生成器首先会将语料按行切分,之后每次随机选取一行。 + + 语料文件格式示例: + ``` + PaddleOCR + 飞桨文字识别 + StyleText + 风格文本图像数据合成 + ... + ``` + + Style-Text也提供了一批中英韩5万张通用场景数据用作文本风格图像,便于合成场景丰富的文本图像,下图给出了一些示例。 + + 中英韩5万张通用场景数据: [下载地址](https://paddleocr.bj.bcebos.com/dygraph_v2.0/style_text/chkoen_5w.tar) + +
+ +
+ +2. 运行`tools/synth_dataset`合成数据: + + ``` bash + python tools/synth_dataset.py -c configs/dataset_config.yml + ``` + 我们在examples目录下提供了样例图片和语料。 +
+ + +
+ + 直接运行上述命令,可以在output_data中产生样例输出,包括图片和用于训练识别模型的标注文件: +
+ +
+ + 其中label目录下的标注文件为程序运行过程中产生的缓存,如果程序在中途异常终止,可以使用缓存的标注文件。 + 如果程序正常运行完毕,则会在output_data下生成label.txt,为最终的标注结果。 + + +### 四、应用案例 +下面以金属表面英文数字识别和通用韩语识别两个场景为例,说明使用Style-Text合成数据,来提升文本识别效果的实际案例。下图给出了一些真实场景图像和合成图像的示例: + +
+ +
+ +在添加上述合成数据进行训练后,识别模型的效果提升,如下表所示: + +| 场景 | 字符 | 原始数据 | 测试数据 | 只使用原始数据
识别准确率 | 新增合成数据 | 同时使用合成数据
识别准确率 | 指标提升 | +| -------- | ---------- | -------- | -------- | -------------------------- | ------------ | ---------------------- | -------- | +| 金属表面 | 英文和数字 | 2203 | 650 | 0.5938 | 20000 | 0.7546 | 16% | +| 随机背景 | 韩语 | 5631 | 1230 | 0.3012 | 100000 | 0.5057 | 20% | + + + +### 五、代码结构 + +``` +StyleText +|-- arch // 网络结构定义文件 +| |-- base_module.py +| |-- decoder.py +| |-- encoder.py +| |-- spectral_norm.py +| `-- style_text_rec.py +|-- configs // 配置文件 +| |-- config.yml +| `-- dataset_config.yml +|-- engine // 数据合成引擎 +| |-- corpus_generators.py // 从文本采样或随机生成语料 +| |-- predictors.py // 调用网络生成数据 +| |-- style_samplers.py // 采样风格图片 +| |-- synthesisers.py // 调度各个模块,合成数据 +| |-- text_drawers.py // 生成标准文字图片,用作输入 +| `-- writers.py // 将合成的图片和标签写入本地目录 +|-- examples // 示例文件 +| |-- corpus +| | `-- example.txt +| |-- image_list.txt +| `-- style_images +| |-- 1.jpg +| `-- 2.jpg +|-- fonts // 字体文件 +| |-- ch_standard.ttf +| |-- en_standard.ttf +| `-- ko_standard.ttf +|-- tools // 程序入口 +| |-- __init__.py +| |-- synth_dataset.py // 批量合成数据 +| `-- synth_image.py // 合成单张图片 +`-- utils // 其他基础功能模块 + |-- config.py + |-- load_params.py + |-- logging.py + |-- math_functions.py + `-- sys_funcs.py +``` diff --git a/StyleText/__init__.py b/StyleText/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/StyleText/arch/__init__.py b/StyleText/arch/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/StyleText/arch/base_module.py b/StyleText/arch/base_module.py new file mode 100644 index 0000000000..da2b6b834c --- /dev/null +++ b/StyleText/arch/base_module.py @@ -0,0 +1,255 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import paddle +import paddle.nn as nn + +from arch.spectral_norm import spectral_norm + + +class CBN(nn.Layer): + def __init__(self, + name, + in_channels, + out_channels, + kernel_size, + stride=1, + padding=0, + dilation=1, + groups=1, + use_bias=False, + norm_layer=None, + act=None, + act_attr=None): + super(CBN, self).__init__() + if use_bias: + bias_attr = paddle.ParamAttr(name=name + "_bias") + else: + bias_attr = None + self._conv = paddle.nn.Conv2D( + in_channels=in_channels, + out_channels=out_channels, + kernel_size=kernel_size, + stride=stride, + padding=padding, + dilation=dilation, + groups=groups, + weight_attr=paddle.ParamAttr(name=name + "_weights"), + bias_attr=bias_attr) + if norm_layer: + self._norm_layer = getattr(paddle.nn, norm_layer)( + num_features=out_channels, name=name + "_bn") + else: + self._norm_layer = None + if act: + if act_attr: + self._act = getattr(paddle.nn, act)(**act_attr, + name=name + "_" + act) + else: + self._act = getattr(paddle.nn, act)(name=name + "_" + act) + else: + self._act = None + + def forward(self, x): + out = self._conv(x) + if self._norm_layer: + out = self._norm_layer(out) + if self._act: + out = self._act(out) + return out + + +class SNConv(nn.Layer): + def __init__(self, + name, + in_channels, + out_channels, + kernel_size, + stride=1, + padding=0, + dilation=1, + groups=1, + use_bias=False, + norm_layer=None, + act=None, + act_attr=None): + super(SNConv, self).__init__() + if use_bias: + bias_attr = paddle.ParamAttr(name=name + "_bias") + else: + bias_attr = None + self._sn_conv = spectral_norm( + paddle.nn.Conv2D( + in_channels=in_channels, + out_channels=out_channels, + kernel_size=kernel_size, + stride=stride, + padding=padding, + dilation=dilation, + groups=groups, + weight_attr=paddle.ParamAttr(name=name + "_weights"), + bias_attr=bias_attr)) + if norm_layer: + self._norm_layer = getattr(paddle.nn, norm_layer)( + num_features=out_channels, name=name + "_bn") + else: + self._norm_layer = None + if act: + if act_attr: + self._act = getattr(paddle.nn, act)(**act_attr, + name=name + "_" + act) + else: + self._act = getattr(paddle.nn, act)(name=name + "_" + act) + else: + self._act = None + + def forward(self, x): + out = self._sn_conv(x) + if self._norm_layer: + out = self._norm_layer(out) + if self._act: + out = self._act(out) + return out + + +class SNConvTranspose(nn.Layer): + def __init__(self, + name, + in_channels, + out_channels, + kernel_size, + stride=1, + padding=0, + output_padding=0, + dilation=1, + groups=1, + use_bias=False, + norm_layer=None, + act=None, + act_attr=None): + super(SNConvTranspose, self).__init__() + if use_bias: + bias_attr = paddle.ParamAttr(name=name + "_bias") + else: + bias_attr = None + self._sn_conv_transpose = spectral_norm( + paddle.nn.Conv2DTranspose( + in_channels=in_channels, + out_channels=out_channels, + kernel_size=kernel_size, + stride=stride, + padding=padding, + output_padding=output_padding, + dilation=dilation, + groups=groups, + weight_attr=paddle.ParamAttr(name=name + "_weights"), + bias_attr=bias_attr)) + if norm_layer: + self._norm_layer = getattr(paddle.nn, norm_layer)( + num_features=out_channels, name=name + "_bn") + else: + self._norm_layer = None + if act: + if act_attr: + self._act = getattr(paddle.nn, act)(**act_attr, + name=name + "_" + act) + else: + self._act = getattr(paddle.nn, act)(name=name + "_" + act) + else: + self._act = None + + def forward(self, x): + out = self._sn_conv_transpose(x) + if self._norm_layer: + out = self._norm_layer(out) + if self._act: + out = self._act(out) + return out + + +class MiddleNet(nn.Layer): + def __init__(self, name, in_channels, mid_channels, out_channels, + use_bias): + super(MiddleNet, self).__init__() + self._sn_conv1 = SNConv( + name=name + "_sn_conv1", + in_channels=in_channels, + out_channels=mid_channels, + kernel_size=1, + use_bias=use_bias, + norm_layer=None, + act=None) + self._pad2d = nn.Pad2D(padding=[1, 1, 1, 1], mode="replicate") + self._sn_conv2 = SNConv( + name=name + "_sn_conv2", + in_channels=mid_channels, + out_channels=mid_channels, + kernel_size=3, + use_bias=use_bias) + self._sn_conv3 = SNConv( + name=name + "_sn_conv3", + in_channels=mid_channels, + out_channels=out_channels, + kernel_size=1, + use_bias=use_bias) + + def forward(self, x): + + sn_conv1 = self._sn_conv1.forward(x) + pad_2d = self._pad2d.forward(sn_conv1) + sn_conv2 = self._sn_conv2.forward(pad_2d) + sn_conv3 = self._sn_conv3.forward(sn_conv2) + return sn_conv3 + + +class ResBlock(nn.Layer): + def __init__(self, name, channels, norm_layer, use_dropout, use_dilation, + use_bias): + super(ResBlock, self).__init__() + if use_dilation: + padding_mat = [1, 1, 1, 1] + else: + padding_mat = [0, 0, 0, 0] + self._pad1 = nn.Pad2D(padding_mat, mode="replicate") + + self._sn_conv1 = SNConv( + name=name + "_sn_conv1", + in_channels=channels, + out_channels=channels, + kernel_size=3, + padding=0, + norm_layer=norm_layer, + use_bias=use_bias, + act="ReLU", + act_attr=None) + if use_dropout: + self._dropout = nn.Dropout(0.5) + else: + self._dropout = None + self._pad2 = nn.Pad2D([1, 1, 1, 1], mode="replicate") + self._sn_conv2 = SNConv( + name=name + "_sn_conv2", + in_channels=channels, + out_channels=channels, + kernel_size=3, + norm_layer=norm_layer, + use_bias=use_bias, + act="ReLU", + act_attr=None) + + def forward(self, x): + pad1 = self._pad1.forward(x) + sn_conv1 = self._sn_conv1.forward(pad1) + pad2 = self._pad2.forward(sn_conv1) + sn_conv2 = self._sn_conv2.forward(pad2) + return sn_conv2 + x diff --git a/StyleText/arch/decoder.py b/StyleText/arch/decoder.py new file mode 100644 index 0000000000..36f07c5998 --- /dev/null +++ b/StyleText/arch/decoder.py @@ -0,0 +1,251 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import paddle +import paddle.nn as nn + +from arch.base_module import SNConv, SNConvTranspose, ResBlock + + +class Decoder(nn.Layer): + def __init__(self, name, encode_dim, out_channels, use_bias, norm_layer, + act, act_attr, conv_block_dropout, conv_block_num, + conv_block_dilation, out_conv_act, out_conv_act_attr): + super(Decoder, self).__init__() + conv_blocks = [] + for i in range(conv_block_num): + conv_blocks.append( + ResBlock( + name="{}_conv_block_{}".format(name, i), + channels=encode_dim * 8, + norm_layer=norm_layer, + use_dropout=conv_block_dropout, + use_dilation=conv_block_dilation, + use_bias=use_bias)) + self.conv_blocks = nn.Sequential(*conv_blocks) + self._up1 = SNConvTranspose( + name=name + "_up1", + in_channels=encode_dim * 8, + out_channels=encode_dim * 4, + kernel_size=3, + stride=2, + padding=1, + output_padding=1, + use_bias=use_bias, + norm_layer=norm_layer, + act=act, + act_attr=act_attr) + self._up2 = SNConvTranspose( + name=name + "_up2", + in_channels=encode_dim * 4, + out_channels=encode_dim * 2, + kernel_size=3, + stride=2, + padding=1, + output_padding=1, + use_bias=use_bias, + norm_layer=norm_layer, + act=act, + act_attr=act_attr) + self._up3 = SNConvTranspose( + name=name + "_up3", + in_channels=encode_dim * 2, + out_channels=encode_dim, + kernel_size=3, + stride=2, + padding=1, + output_padding=1, + use_bias=use_bias, + norm_layer=norm_layer, + act=act, + act_attr=act_attr) + self._pad2d = paddle.nn.Pad2D([1, 1, 1, 1], mode="replicate") + self._out_conv = SNConv( + name=name + "_out_conv", + in_channels=encode_dim, + out_channels=out_channels, + kernel_size=3, + use_bias=use_bias, + norm_layer=None, + act=out_conv_act, + act_attr=out_conv_act_attr) + + def forward(self, x): + if isinstance(x, (list, tuple)): + x = paddle.concat(x, axis=1) + output_dict = dict() + output_dict["conv_blocks"] = self.conv_blocks.forward(x) + output_dict["up1"] = self._up1.forward(output_dict["conv_blocks"]) + output_dict["up2"] = self._up2.forward(output_dict["up1"]) + output_dict["up3"] = self._up3.forward(output_dict["up2"]) + output_dict["pad2d"] = self._pad2d.forward(output_dict["up3"]) + output_dict["out_conv"] = self._out_conv.forward(output_dict["pad2d"]) + return output_dict + + +class DecoderUnet(nn.Layer): + def __init__(self, name, encode_dim, out_channels, use_bias, norm_layer, + act, act_attr, conv_block_dropout, conv_block_num, + conv_block_dilation, out_conv_act, out_conv_act_attr): + super(DecoderUnet, self).__init__() + conv_blocks = [] + for i in range(conv_block_num): + conv_blocks.append( + ResBlock( + name="{}_conv_block_{}".format(name, i), + channels=encode_dim * 8, + norm_layer=norm_layer, + use_dropout=conv_block_dropout, + use_dilation=conv_block_dilation, + use_bias=use_bias)) + self._conv_blocks = nn.Sequential(*conv_blocks) + self._up1 = SNConvTranspose( + name=name + "_up1", + in_channels=encode_dim * 8, + out_channels=encode_dim * 4, + kernel_size=3, + stride=2, + padding=1, + output_padding=1, + use_bias=use_bias, + norm_layer=norm_layer, + act=act, + act_attr=act_attr) + self._up2 = SNConvTranspose( + name=name + "_up2", + in_channels=encode_dim * 8, + out_channels=encode_dim * 2, + kernel_size=3, + stride=2, + padding=1, + output_padding=1, + use_bias=use_bias, + norm_layer=norm_layer, + act=act, + act_attr=act_attr) + self._up3 = SNConvTranspose( + name=name + "_up3", + in_channels=encode_dim * 4, + out_channels=encode_dim, + kernel_size=3, + stride=2, + padding=1, + output_padding=1, + use_bias=use_bias, + norm_layer=norm_layer, + act=act, + act_attr=act_attr) + self._pad2d = paddle.nn.Pad2D([1, 1, 1, 1], mode="replicate") + self._out_conv = SNConv( + name=name + "_out_conv", + in_channels=encode_dim, + out_channels=out_channels, + kernel_size=3, + use_bias=use_bias, + norm_layer=None, + act=out_conv_act, + act_attr=out_conv_act_attr) + + def forward(self, x, y, feature2, feature1): + output_dict = dict() + output_dict["conv_blocks"] = self._conv_blocks( + paddle.concat( + (x, y), axis=1)) + output_dict["up1"] = self._up1.forward(output_dict["conv_blocks"]) + output_dict["up2"] = self._up2.forward( + paddle.concat( + (output_dict["up1"], feature2), axis=1)) + output_dict["up3"] = self._up3.forward( + paddle.concat( + (output_dict["up2"], feature1), axis=1)) + output_dict["pad2d"] = self._pad2d.forward(output_dict["up3"]) + output_dict["out_conv"] = self._out_conv.forward(output_dict["pad2d"]) + return output_dict + + +class SingleDecoder(nn.Layer): + def __init__(self, name, encode_dim, out_channels, use_bias, norm_layer, + act, act_attr, conv_block_dropout, conv_block_num, + conv_block_dilation, out_conv_act, out_conv_act_attr): + super(SingleDecoder, self).__init__() + conv_blocks = [] + for i in range(conv_block_num): + conv_blocks.append( + ResBlock( + name="{}_conv_block_{}".format(name, i), + channels=encode_dim * 4, + norm_layer=norm_layer, + use_dropout=conv_block_dropout, + use_dilation=conv_block_dilation, + use_bias=use_bias)) + self._conv_blocks = nn.Sequential(*conv_blocks) + self._up1 = SNConvTranspose( + name=name + "_up1", + in_channels=encode_dim * 4, + out_channels=encode_dim * 4, + kernel_size=3, + stride=2, + padding=1, + output_padding=1, + use_bias=use_bias, + norm_layer=norm_layer, + act=act, + act_attr=act_attr) + self._up2 = SNConvTranspose( + name=name + "_up2", + in_channels=encode_dim * 8, + out_channels=encode_dim * 2, + kernel_size=3, + stride=2, + padding=1, + output_padding=1, + use_bias=use_bias, + norm_layer=norm_layer, + act=act, + act_attr=act_attr) + self._up3 = SNConvTranspose( + name=name + "_up3", + in_channels=encode_dim * 4, + out_channels=encode_dim, + kernel_size=3, + stride=2, + padding=1, + output_padding=1, + use_bias=use_bias, + norm_layer=norm_layer, + act=act, + act_attr=act_attr) + self._pad2d = paddle.nn.Pad2D([1, 1, 1, 1], mode="replicate") + self._out_conv = SNConv( + name=name + "_out_conv", + in_channels=encode_dim, + out_channels=out_channels, + kernel_size=3, + use_bias=use_bias, + norm_layer=None, + act=out_conv_act, + act_attr=out_conv_act_attr) + + def forward(self, x, feature2, feature1): + output_dict = dict() + output_dict["conv_blocks"] = self._conv_blocks.forward(x) + output_dict["up1"] = self._up1.forward(output_dict["conv_blocks"]) + output_dict["up2"] = self._up2.forward( + paddle.concat( + (output_dict["up1"], feature2), axis=1)) + output_dict["up3"] = self._up3.forward( + paddle.concat( + (output_dict["up2"], feature1), axis=1)) + output_dict["pad2d"] = self._pad2d.forward(output_dict["up3"]) + output_dict["out_conv"] = self._out_conv.forward(output_dict["pad2d"]) + return output_dict diff --git a/StyleText/arch/encoder.py b/StyleText/arch/encoder.py new file mode 100644 index 0000000000..b884cda293 --- /dev/null +++ b/StyleText/arch/encoder.py @@ -0,0 +1,186 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import paddle +import paddle.nn as nn + +from arch.base_module import SNConv, SNConvTranspose, ResBlock + + +class Encoder(nn.Layer): + def __init__(self, name, in_channels, encode_dim, use_bias, norm_layer, + act, act_attr, conv_block_dropout, conv_block_num, + conv_block_dilation): + super(Encoder, self).__init__() + self._pad2d = paddle.nn.Pad2D([3, 3, 3, 3], mode="replicate") + self._in_conv = SNConv( + name=name + "_in_conv", + in_channels=in_channels, + out_channels=encode_dim, + kernel_size=7, + use_bias=use_bias, + norm_layer=norm_layer, + act=act, + act_attr=act_attr) + self._down1 = SNConv( + name=name + "_down1", + in_channels=encode_dim, + out_channels=encode_dim * 2, + kernel_size=3, + stride=2, + padding=1, + use_bias=use_bias, + norm_layer=norm_layer, + act=act, + act_attr=act_attr) + self._down2 = SNConv( + name=name + "_down2", + in_channels=encode_dim * 2, + out_channels=encode_dim * 4, + kernel_size=3, + stride=2, + padding=1, + use_bias=use_bias, + norm_layer=norm_layer, + act=act, + act_attr=act_attr) + self._down3 = SNConv( + name=name + "_down3", + in_channels=encode_dim * 4, + out_channels=encode_dim * 4, + kernel_size=3, + stride=2, + padding=1, + use_bias=use_bias, + norm_layer=norm_layer, + act=act, + act_attr=act_attr) + conv_blocks = [] + for i in range(conv_block_num): + conv_blocks.append( + ResBlock( + name="{}_conv_block_{}".format(name, i), + channels=encode_dim * 4, + norm_layer=norm_layer, + use_dropout=conv_block_dropout, + use_dilation=conv_block_dilation, + use_bias=use_bias)) + self._conv_blocks = nn.Sequential(*conv_blocks) + + def forward(self, x): + out_dict = dict() + x = self._pad2d(x) + out_dict["in_conv"] = self._in_conv.forward(x) + out_dict["down1"] = self._down1.forward(out_dict["in_conv"]) + out_dict["down2"] = self._down2.forward(out_dict["down1"]) + out_dict["down3"] = self._down3.forward(out_dict["down2"]) + out_dict["res_blocks"] = self._conv_blocks.forward(out_dict["down3"]) + return out_dict + + +class EncoderUnet(nn.Layer): + def __init__(self, name, in_channels, encode_dim, use_bias, norm_layer, + act, act_attr): + super(EncoderUnet, self).__init__() + self._pad2d = paddle.nn.Pad2D([3, 3, 3, 3], mode="replicate") + self._in_conv = SNConv( + name=name + "_in_conv", + in_channels=in_channels, + out_channels=encode_dim, + kernel_size=7, + use_bias=use_bias, + norm_layer=norm_layer, + act=act, + act_attr=act_attr) + self._down1 = SNConv( + name=name + "_down1", + in_channels=encode_dim, + out_channels=encode_dim * 2, + kernel_size=3, + stride=2, + padding=1, + use_bias=use_bias, + norm_layer=norm_layer, + act=act, + act_attr=act_attr) + self._down2 = SNConv( + name=name + "_down2", + in_channels=encode_dim * 2, + out_channels=encode_dim * 2, + kernel_size=3, + stride=2, + padding=1, + use_bias=use_bias, + norm_layer=norm_layer, + act=act, + act_attr=act_attr) + self._down3 = SNConv( + name=name + "_down3", + in_channels=encode_dim * 2, + out_channels=encode_dim * 2, + kernel_size=3, + stride=2, + padding=1, + use_bias=use_bias, + norm_layer=norm_layer, + act=act, + act_attr=act_attr) + self._down4 = SNConv( + name=name + "_down4", + in_channels=encode_dim * 2, + out_channels=encode_dim * 2, + kernel_size=3, + stride=2, + padding=1, + use_bias=use_bias, + norm_layer=norm_layer, + act=act, + act_attr=act_attr) + self._up1 = SNConvTranspose( + name=name + "_up1", + in_channels=encode_dim * 2, + out_channels=encode_dim * 2, + kernel_size=3, + stride=2, + padding=1, + use_bias=use_bias, + norm_layer=norm_layer, + act=act, + act_attr=act_attr) + self._up2 = SNConvTranspose( + name=name + "_up2", + in_channels=encode_dim * 4, + out_channels=encode_dim * 4, + kernel_size=3, + stride=2, + padding=1, + use_bias=use_bias, + norm_layer=norm_layer, + act=act, + act_attr=act_attr) + + def forward(self, x): + output_dict = dict() + x = self._pad2d(x) + output_dict['in_conv'] = self._in_conv.forward(x) + output_dict['down1'] = self._down1.forward(output_dict['in_conv']) + output_dict['down2'] = self._down2.forward(output_dict['down1']) + output_dict['down3'] = self._down3.forward(output_dict['down2']) + output_dict['down4'] = self._down4.forward(output_dict['down3']) + output_dict['up1'] = self._up1.forward(output_dict['down4']) + output_dict['up2'] = self._up2.forward( + paddle.concat( + (output_dict['down3'], output_dict['up1']), axis=1)) + output_dict['concat'] = paddle.concat( + (output_dict['down2'], output_dict['up2']), axis=1) + return output_dict diff --git a/StyleText/arch/spectral_norm.py b/StyleText/arch/spectral_norm.py new file mode 100644 index 0000000000..21d0afc8d4 --- /dev/null +++ b/StyleText/arch/spectral_norm.py @@ -0,0 +1,150 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import paddle +import paddle.nn as nn +import paddle.nn.functional as F + + +def normal_(x, mean=0., std=1.): + temp_value = paddle.normal(mean, std, shape=x.shape) + x.set_value(temp_value) + return x + + +class SpectralNorm(object): + def __init__(self, name='weight', n_power_iterations=1, dim=0, eps=1e-12): + self.name = name + self.dim = dim + if n_power_iterations <= 0: + raise ValueError('Expected n_power_iterations to be positive, but ' + 'got n_power_iterations={}'.format( + n_power_iterations)) + self.n_power_iterations = n_power_iterations + self.eps = eps + + def reshape_weight_to_matrix(self, weight): + weight_mat = weight + if self.dim != 0: + # transpose dim to front + weight_mat = weight_mat.transpose([ + self.dim, + * [d for d in range(weight_mat.dim()) if d != self.dim] + ]) + + height = weight_mat.shape[0] + + return weight_mat.reshape([height, -1]) + + def compute_weight(self, module, do_power_iteration): + weight = getattr(module, self.name + '_orig') + u = getattr(module, self.name + '_u') + v = getattr(module, self.name + '_v') + weight_mat = self.reshape_weight_to_matrix(weight) + + if do_power_iteration: + with paddle.no_grad(): + for _ in range(self.n_power_iterations): + v.set_value( + F.normalize( + paddle.matmul( + weight_mat, + u, + transpose_x=True, + transpose_y=False), + axis=0, + epsilon=self.eps, )) + + u.set_value( + F.normalize( + paddle.matmul(weight_mat, v), + axis=0, + epsilon=self.eps, )) + if self.n_power_iterations > 0: + u = u.clone() + v = v.clone() + + sigma = paddle.dot(u, paddle.mv(weight_mat, v)) + weight = weight / sigma + return weight + + def remove(self, module): + with paddle.no_grad(): + weight = self.compute_weight(module, do_power_iteration=False) + delattr(module, self.name) + delattr(module, self.name + '_u') + delattr(module, self.name + '_v') + delattr(module, self.name + '_orig') + + module.add_parameter(self.name, weight.detach()) + + def __call__(self, module, inputs): + setattr( + module, + self.name, + self.compute_weight( + module, do_power_iteration=module.training)) + + @staticmethod + def apply(module, name, n_power_iterations, dim, eps): + for k, hook in module._forward_pre_hooks.items(): + if isinstance(hook, SpectralNorm) and hook.name == name: + raise RuntimeError( + "Cannot register two spectral_norm hooks on " + "the same parameter {}".format(name)) + + fn = SpectralNorm(name, n_power_iterations, dim, eps) + weight = module._parameters[name] + + with paddle.no_grad(): + weight_mat = fn.reshape_weight_to_matrix(weight) + h, w = weight_mat.shape + + # randomly initialize u and v + u = module.create_parameter([h]) + u = normal_(u, 0., 1.) + v = module.create_parameter([w]) + v = normal_(v, 0., 1.) + u = F.normalize(u, axis=0, epsilon=fn.eps) + v = F.normalize(v, axis=0, epsilon=fn.eps) + + # delete fn.name form parameters, otherwise you can not set attribute + del module._parameters[fn.name] + module.add_parameter(fn.name + "_orig", weight) + # still need to assign weight back as fn.name because all sorts of + # things may assume that it exists, e.g., when initializing weights. + # However, we can't directly assign as it could be an Parameter and + # gets added as a parameter. Instead, we register weight * 1.0 as a plain + # attribute. + setattr(module, fn.name, weight * 1.0) + module.register_buffer(fn.name + "_u", u) + module.register_buffer(fn.name + "_v", v) + + module.register_forward_pre_hook(fn) + return fn + + +def spectral_norm(module, + name='weight', + n_power_iterations=1, + eps=1e-12, + dim=None): + + if dim is None: + if isinstance(module, (nn.Conv1DTranspose, nn.Conv2DTranspose, + nn.Conv3DTranspose, nn.Linear)): + dim = 1 + else: + dim = 0 + SpectralNorm.apply(module, name, n_power_iterations, dim, eps) + return module diff --git a/StyleText/arch/style_text_rec.py b/StyleText/arch/style_text_rec.py new file mode 100644 index 0000000000..599927ce3e --- /dev/null +++ b/StyleText/arch/style_text_rec.py @@ -0,0 +1,285 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import paddle +import paddle.nn as nn + +from arch.base_module import MiddleNet, ResBlock +from arch.encoder import Encoder +from arch.decoder import Decoder, DecoderUnet, SingleDecoder +from utils.load_params import load_dygraph_pretrain +from utils.logging import get_logger + + +class StyleTextRec(nn.Layer): + def __init__(self, config): + super(StyleTextRec, self).__init__() + self.logger = get_logger() + self.text_generator = TextGenerator(config["Predictor"][ + "text_generator"]) + self.bg_generator = BgGeneratorWithMask(config["Predictor"][ + "bg_generator"]) + self.fusion_generator = FusionGeneratorSimple(config["Predictor"][ + "fusion_generator"]) + bg_generator_pretrain = config["Predictor"]["bg_generator"]["pretrain"] + text_generator_pretrain = config["Predictor"]["text_generator"][ + "pretrain"] + fusion_generator_pretrain = config["Predictor"]["fusion_generator"][ + "pretrain"] + load_dygraph_pretrain( + self.bg_generator, + self.logger, + path=bg_generator_pretrain, + load_static_weights=False) + load_dygraph_pretrain( + self.text_generator, + self.logger, + path=text_generator_pretrain, + load_static_weights=False) + load_dygraph_pretrain( + self.fusion_generator, + self.logger, + path=fusion_generator_pretrain, + load_static_weights=False) + + def forward(self, style_input, text_input): + text_gen_output = self.text_generator.forward(style_input, text_input) + fake_text = text_gen_output["fake_text"] + fake_sk = text_gen_output["fake_sk"] + bg_gen_output = self.bg_generator.forward(style_input) + bg_encode_feature = bg_gen_output["bg_encode_feature"] + bg_decode_feature1 = bg_gen_output["bg_decode_feature1"] + bg_decode_feature2 = bg_gen_output["bg_decode_feature2"] + fake_bg = bg_gen_output["fake_bg"] + + fusion_gen_output = self.fusion_generator.forward(fake_text, fake_bg) + fake_fusion = fusion_gen_output["fake_fusion"] + return { + "fake_fusion": fake_fusion, + "fake_text": fake_text, + "fake_sk": fake_sk, + "fake_bg": fake_bg, + } + + +class TextGenerator(nn.Layer): + def __init__(self, config): + super(TextGenerator, self).__init__() + name = config["module_name"] + encode_dim = config["encode_dim"] + norm_layer = config["norm_layer"] + conv_block_dropout = config["conv_block_dropout"] + conv_block_num = config["conv_block_num"] + conv_block_dilation = config["conv_block_dilation"] + if norm_layer == "InstanceNorm2D": + use_bias = True + else: + use_bias = False + self.encoder_text = Encoder( + name=name + "_encoder_text", + in_channels=3, + encode_dim=encode_dim, + use_bias=use_bias, + norm_layer=norm_layer, + act="ReLU", + act_attr=None, + conv_block_dropout=conv_block_dropout, + conv_block_num=conv_block_num, + conv_block_dilation=conv_block_dilation) + self.encoder_style = Encoder( + name=name + "_encoder_style", + in_channels=3, + encode_dim=encode_dim, + use_bias=use_bias, + norm_layer=norm_layer, + act="ReLU", + act_attr=None, + conv_block_dropout=conv_block_dropout, + conv_block_num=conv_block_num, + conv_block_dilation=conv_block_dilation) + self.decoder_text = Decoder( + name=name + "_decoder_text", + encode_dim=encode_dim, + out_channels=int(encode_dim / 2), + use_bias=use_bias, + norm_layer=norm_layer, + act="ReLU", + act_attr=None, + conv_block_dropout=conv_block_dropout, + conv_block_num=conv_block_num, + conv_block_dilation=conv_block_dilation, + out_conv_act="Tanh", + out_conv_act_attr=None) + self.decoder_sk = Decoder( + name=name + "_decoder_sk", + encode_dim=encode_dim, + out_channels=1, + use_bias=use_bias, + norm_layer=norm_layer, + act="ReLU", + act_attr=None, + conv_block_dropout=conv_block_dropout, + conv_block_num=conv_block_num, + conv_block_dilation=conv_block_dilation, + out_conv_act="Sigmoid", + out_conv_act_attr=None) + + self.middle = MiddleNet( + name=name + "_middle_net", + in_channels=int(encode_dim / 2) + 1, + mid_channels=encode_dim, + out_channels=3, + use_bias=use_bias) + + def forward(self, style_input, text_input): + style_feature = self.encoder_style.forward(style_input)["res_blocks"] + text_feature = self.encoder_text.forward(text_input)["res_blocks"] + fake_c_temp = self.decoder_text.forward([text_feature, + style_feature])["out_conv"] + fake_sk = self.decoder_sk.forward([text_feature, + style_feature])["out_conv"] + fake_text = self.middle(paddle.concat((fake_c_temp, fake_sk), axis=1)) + return {"fake_sk": fake_sk, "fake_text": fake_text} + + +class BgGeneratorWithMask(nn.Layer): + def __init__(self, config): + super(BgGeneratorWithMask, self).__init__() + name = config["module_name"] + encode_dim = config["encode_dim"] + norm_layer = config["norm_layer"] + conv_block_dropout = config["conv_block_dropout"] + conv_block_num = config["conv_block_num"] + conv_block_dilation = config["conv_block_dilation"] + self.output_factor = config.get("output_factor", 1.0) + + if norm_layer == "InstanceNorm2D": + use_bias = True + else: + use_bias = False + + self.encoder_bg = Encoder( + name=name + "_encoder_bg", + in_channels=3, + encode_dim=encode_dim, + use_bias=use_bias, + norm_layer=norm_layer, + act="ReLU", + act_attr=None, + conv_block_dropout=conv_block_dropout, + conv_block_num=conv_block_num, + conv_block_dilation=conv_block_dilation) + + self.decoder_bg = SingleDecoder( + name=name + "_decoder_bg", + encode_dim=encode_dim, + out_channels=3, + use_bias=use_bias, + norm_layer=norm_layer, + act="ReLU", + act_attr=None, + conv_block_dropout=conv_block_dropout, + conv_block_num=conv_block_num, + conv_block_dilation=conv_block_dilation, + out_conv_act="Tanh", + out_conv_act_attr=None) + + self.decoder_mask = Decoder( + name=name + "_decoder_mask", + encode_dim=encode_dim // 2, + out_channels=1, + use_bias=use_bias, + norm_layer=norm_layer, + act="ReLU", + act_attr=None, + conv_block_dropout=conv_block_dropout, + conv_block_num=conv_block_num, + conv_block_dilation=conv_block_dilation, + out_conv_act="Sigmoid", + out_conv_act_attr=None) + + self.middle = MiddleNet( + name=name + "_middle_net", + in_channels=3 + 1, + mid_channels=encode_dim, + out_channels=3, + use_bias=use_bias) + + def forward(self, style_input): + encode_bg_output = self.encoder_bg(style_input) + decode_bg_output = self.decoder_bg(encode_bg_output["res_blocks"], + encode_bg_output["down2"], + encode_bg_output["down1"]) + + fake_c_temp = decode_bg_output["out_conv"] + fake_bg_mask = self.decoder_mask.forward(encode_bg_output[ + "res_blocks"])["out_conv"] + fake_bg = self.middle( + paddle.concat( + (fake_c_temp, fake_bg_mask), axis=1)) + return { + "bg_encode_feature": encode_bg_output["res_blocks"], + "bg_decode_feature1": decode_bg_output["up1"], + "bg_decode_feature2": decode_bg_output["up2"], + "fake_bg": fake_bg, + "fake_bg_mask": fake_bg_mask, + } + + +class FusionGeneratorSimple(nn.Layer): + def __init__(self, config): + super(FusionGeneratorSimple, self).__init__() + name = config["module_name"] + encode_dim = config["encode_dim"] + norm_layer = config["norm_layer"] + conv_block_dropout = config["conv_block_dropout"] + conv_block_dilation = config["conv_block_dilation"] + if norm_layer == "InstanceNorm2D": + use_bias = True + else: + use_bias = False + + self._conv = nn.Conv2D( + in_channels=6, + out_channels=encode_dim, + kernel_size=3, + stride=1, + padding=1, + groups=1, + weight_attr=paddle.ParamAttr(name=name + "_conv_weights"), + bias_attr=False) + + self._res_block = ResBlock( + name="{}_conv_block".format(name), + channels=encode_dim, + norm_layer=norm_layer, + use_dropout=conv_block_dropout, + use_dilation=conv_block_dilation, + use_bias=use_bias) + + self._reduce_conv = nn.Conv2D( + in_channels=encode_dim, + out_channels=3, + kernel_size=3, + stride=1, + padding=1, + groups=1, + weight_attr=paddle.ParamAttr(name=name + "_reduce_conv_weights"), + bias_attr=False) + + def forward(self, fake_text, fake_bg): + fake_concat = paddle.concat((fake_text, fake_bg), axis=1) + fake_concat_tmp = self._conv(fake_concat) + output_res = self._res_block(fake_concat_tmp) + fake_fusion = self._reduce_conv(output_res) + return {"fake_fusion": fake_fusion} diff --git a/StyleText/configs/config.yml b/StyleText/configs/config.yml new file mode 100644 index 0000000000..3b10b3d276 --- /dev/null +++ b/StyleText/configs/config.yml @@ -0,0 +1,54 @@ +Global: + output_num: 10 + output_dir: output_data + use_gpu: false + image_height: 32 + image_width: 320 +TextDrawer: + fonts: + en: fonts/en_standard.ttf + ch: fonts/ch_standard.ttf + ko: fonts/ko_standard.ttf +Predictor: + method: StyleTextRecPredictor + algorithm: StyleTextRec + scale: 0.00392156862745098 + mean: + - 0.5 + - 0.5 + - 0.5 + std: + - 0.5 + - 0.5 + - 0.5 + expand_result: false + bg_generator: + pretrain: style_text_models/bg_generator + module_name: bg_generator + generator_type: BgGeneratorWithMask + encode_dim: 64 + norm_layer: null + conv_block_num: 4 + conv_block_dropout: false + conv_block_dilation: true + output_factor: 1.05 + text_generator: + pretrain: style_text_models/text_generator + module_name: text_generator + generator_type: TextGenerator + encode_dim: 64 + norm_layer: InstanceNorm2D + conv_block_num: 4 + conv_block_dropout: false + conv_block_dilation: true + fusion_generator: + pretrain: style_text_models/fusion_generator + module_name: fusion_generator + generator_type: FusionGeneratorSimple + encode_dim: 64 + norm_layer: null + conv_block_num: 4 + conv_block_dropout: false + conv_block_dilation: true +Writer: + method: SimpleWriter diff --git a/StyleText/configs/dataset_config.yml b/StyleText/configs/dataset_config.yml new file mode 100644 index 0000000000..aa4ec69b8c --- /dev/null +++ b/StyleText/configs/dataset_config.yml @@ -0,0 +1,64 @@ +Global: + output_num: 10 + output_dir: output_data + use_gpu: false + image_height: 32 + image_width: 320 + standard_font: fonts/en_standard.ttf +TextDrawer: + fonts: + en: fonts/en_standard.ttf + ch: fonts/ch_standard.ttf + ko: fonts/ko_standard.ttf +StyleSampler: + method: DatasetSampler + image_home: examples + label_file: examples/image_list.txt + with_label: true +CorpusGenerator: + method: FileCorpus + language: ch + corpus_file: examples/corpus/example.txt +Predictor: + method: StyleTextRecPredictor + algorithm: StyleTextRec + scale: 0.00392156862745098 + mean: + - 0.5 + - 0.5 + - 0.5 + std: + - 0.5 + - 0.5 + - 0.5 + expand_result: false + bg_generator: + pretrain: style_text_models/bg_generator + module_name: bg_generator + generator_type: BgGeneratorWithMask + encode_dim: 64 + norm_layer: null + conv_block_num: 4 + conv_block_dropout: false + conv_block_dilation: true + output_factor: 1.05 + text_generator: + pretrain: style_text_models/text_generator + module_name: text_generator + generator_type: TextGenerator + encode_dim: 64 + norm_layer: InstanceNorm2D + conv_block_num: 4 + conv_block_dropout: false + conv_block_dilation: true + fusion_generator: + pretrain: style_text_models/fusion_generator + module_name: fusion_generator + generator_type: FusionGeneratorSimple + encode_dim: 64 + norm_layer: null + conv_block_num: 4 + conv_block_dropout: false + conv_block_dilation: true +Writer: + method: SimpleWriter diff --git a/StyleText/doc/images/1.png b/StyleText/doc/images/1.png new file mode 100644 index 0000000000..8f7574ba2f Binary files /dev/null and b/StyleText/doc/images/1.png differ diff --git a/StyleText/doc/images/10.png b/StyleText/doc/images/10.png new file mode 100644 index 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mode 100644 index 0000000000..e69de29bb2 diff --git a/StyleText/engine/corpus_generators.py b/StyleText/engine/corpus_generators.py new file mode 100644 index 0000000000..186d15f36d --- /dev/null +++ b/StyleText/engine/corpus_generators.py @@ -0,0 +1,66 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import random + +from utils.logging import get_logger + + +class FileCorpus(object): + def __init__(self, config): + self.logger = get_logger() + self.logger.info("using FileCorpus") + + self.char_list = " 0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz" + + corpus_file = config["CorpusGenerator"]["corpus_file"] + self.language = config["CorpusGenerator"]["language"] + with open(corpus_file, 'r') as f: + corpus_raw = f.read() + self.corpus_list = corpus_raw.split("\n")[:-1] + assert len(self.corpus_list) > 0 + random.shuffle(self.corpus_list) + self.index = 0 + + def generate(self, corpus_length=0): + if self.index >= len(self.corpus_list): + self.index = 0 + random.shuffle(self.corpus_list) + corpus = self.corpus_list[self.index] + if corpus_length != 0: + corpus = corpus[0:corpus_length] + if corpus_length > len(corpus): + self.logger.warning("generated corpus is shorter than expected.") + self.index += 1 + return self.language, corpus + + +class EnNumCorpus(object): + def __init__(self, config): + self.logger = get_logger() + self.logger.info("using NumberCorpus") + self.num_list = "0123456789" + self.en_char_list = "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz" + self.height = config["Global"]["image_height"] + self.max_width = config["Global"]["image_width"] + + def generate(self, corpus_length=0): + corpus = "" + if corpus_length == 0: + corpus_length = random.randint(5, 15) + for i in range(corpus_length): + if random.random() < 0.2: + corpus += "{}".format(random.choice(self.en_char_list)) + else: + corpus += "{}".format(random.choice(self.num_list)) + return "en", corpus diff --git a/StyleText/engine/predictors.py b/StyleText/engine/predictors.py new file mode 100644 index 0000000000..a1ba21f1b6 --- /dev/null +++ b/StyleText/engine/predictors.py @@ -0,0 +1,116 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import numpy as np +import cv2 +import math +import paddle + +from arch import style_text_rec +from utils.sys_funcs import check_gpu +from utils.logging import get_logger + + +class StyleTextRecPredictor(object): + def __init__(self, config): + algorithm = config['Predictor']['algorithm'] + assert algorithm in ["StyleTextRec" + ], "Generator {} not supported.".format(algorithm) + use_gpu = config["Global"]['use_gpu'] + check_gpu(use_gpu) + paddle.set_device('gpu' if use_gpu else 'cpu') + self.logger = get_logger() + self.generator = getattr(style_text_rec, algorithm)(config) + self.height = config["Global"]["image_height"] + self.width = config["Global"]["image_width"] + self.scale = config["Predictor"]["scale"] + self.mean = config["Predictor"]["mean"] + self.std = config["Predictor"]["std"] + self.expand_result = config["Predictor"]["expand_result"] + + def predict(self, style_input, text_input): + style_input = self.rep_style_input(style_input, text_input) + tensor_style_input = self.preprocess(style_input) + tensor_text_input = self.preprocess(text_input) + style_text_result = self.generator.forward(tensor_style_input, + tensor_text_input) + fake_fusion = self.postprocess(style_text_result["fake_fusion"]) + fake_text = self.postprocess(style_text_result["fake_text"]) + fake_sk = self.postprocess(style_text_result["fake_sk"]) + fake_bg = self.postprocess(style_text_result["fake_bg"]) + bbox = self.get_text_boundary(fake_text) + if bbox: + left, right, top, bottom = bbox + fake_fusion = fake_fusion[top:bottom, left:right, :] + fake_text = fake_text[top:bottom, left:right, :] + fake_sk = fake_sk[top:bottom, left:right, :] + fake_bg = fake_bg[top:bottom, left:right, :] + + # fake_fusion = self.crop_by_text(img_fake_fusion, img_fake_text) + return { + "fake_fusion": fake_fusion, + "fake_text": fake_text, + "fake_sk": fake_sk, + "fake_bg": fake_bg, + } + + def preprocess(self, img): + img = (img.astype('float32') * self.scale - self.mean) / self.std + img_height, img_width, channel = img.shape + assert channel == 3, "Please use an rgb image." + ratio = img_width / float(img_height) + if math.ceil(self.height * ratio) > self.width: + resized_w = self.width + else: + resized_w = int(math.ceil(self.height * ratio)) + img = cv2.resize(img, (resized_w, self.height)) + + new_img = np.zeros([self.height, self.width, 3]).astype('float32') + new_img[:, 0:resized_w, :] = img + img = new_img.transpose((2, 0, 1)) + img = img[np.newaxis, :, :, :] + return paddle.to_tensor(img) + + def postprocess(self, tensor): + img = tensor.numpy()[0] + img = img.transpose((1, 2, 0)) + img = (img * self.std + self.mean) / self.scale + img = np.maximum(img, 0.0) + img = np.minimum(img, 255.0) + img = img.astype('uint8') + return img + + def rep_style_input(self, style_input, text_input): + rep_num = int(1.2 * (text_input.shape[1] / text_input.shape[0]) / + (style_input.shape[1] / style_input.shape[0])) + 1 + style_input = np.tile(style_input, reps=[1, rep_num, 1]) + max_width = int(self.width / self.height * style_input.shape[0]) + style_input = style_input[:, :max_width, :] + return style_input + + def get_text_boundary(self, text_img): + img_height = text_img.shape[0] + img_width = text_img.shape[1] + bounder = 3 + text_canny_img = cv2.Canny(text_img, 10, 20) + edge_num_h = text_canny_img.sum(axis=0) + no_zero_list_h = np.where(edge_num_h > 0)[0] + edge_num_w = text_canny_img.sum(axis=1) + no_zero_list_w = np.where(edge_num_w > 0)[0] + if len(no_zero_list_h) == 0 or len(no_zero_list_w) == 0: + return None + left = max(no_zero_list_h[0] - bounder, 0) + right = min(no_zero_list_h[-1] + bounder, img_width) + top = max(no_zero_list_w[0] - bounder, 0) + bottom = min(no_zero_list_w[-1] + bounder, img_height) + return [left, right, top, bottom] diff --git a/StyleText/engine/style_samplers.py b/StyleText/engine/style_samplers.py new file mode 100644 index 0000000000..e171d58db7 --- /dev/null +++ b/StyleText/engine/style_samplers.py @@ -0,0 +1,62 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import numpy as np +import random +import cv2 + + +class DatasetSampler(object): + def __init__(self, config): + self.image_home = config["StyleSampler"]["image_home"] + label_file = config["StyleSampler"]["label_file"] + self.dataset_with_label = config["StyleSampler"]["with_label"] + self.height = config["Global"]["image_height"] + self.index = 0 + with open(label_file, "r") as f: + label_raw = f.read() + self.path_label_list = label_raw.split("\n")[:-1] + assert len(self.path_label_list) > 0 + random.shuffle(self.path_label_list) + + def sample(self): + if self.index >= len(self.path_label_list): + random.shuffle(self.path_label_list) + self.index = 0 + if self.dataset_with_label: + path_label = self.path_label_list[self.index] + rel_image_path, label = path_label.split('\t') + else: + rel_image_path = self.path_label_list[self.index] + label = None + img_path = "{}/{}".format(self.image_home, rel_image_path) + image = cv2.imread(img_path) + origin_height = image.shape[0] + ratio = self.height / origin_height + width = int(image.shape[1] * ratio) + height = int(image.shape[0] * ratio) + image = cv2.resize(image, (width, height)) + + self.index += 1 + if label: + return {"image": image, "label": label} + else: + return {"image": image} + + +def duplicate_image(image, width): + image_width = image.shape[1] + dup_num = width // image_width + 1 + image = np.tile(image, reps=[1, dup_num, 1]) + cropped_image = image[:, :width, :] + return cropped_image diff --git a/StyleText/engine/synthesisers.py b/StyleText/engine/synthesisers.py new file mode 100644 index 0000000000..177e3e049a --- /dev/null +++ b/StyleText/engine/synthesisers.py @@ -0,0 +1,71 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import os + +from utils.config import ArgsParser, load_config, override_config +from utils.logging import get_logger +from engine import style_samplers, corpus_generators, text_drawers, predictors, writers + + +class ImageSynthesiser(object): + def __init__(self): + self.FLAGS = ArgsParser().parse_args() + self.config = load_config(self.FLAGS.config) + self.config = override_config(self.config, options=self.FLAGS.override) + self.output_dir = self.config["Global"]["output_dir"] + if not os.path.exists(self.output_dir): + os.mkdir(self.output_dir) + self.logger = get_logger( + log_file='{}/predict.log'.format(self.output_dir)) + + self.text_drawer = text_drawers.StdTextDrawer(self.config) + + predictor_method = self.config["Predictor"]["method"] + assert predictor_method is not None + self.predictor = getattr(predictors, predictor_method)(self.config) + + def synth_image(self, corpus, style_input, language="en"): + corpus, text_input = self.text_drawer.draw_text(corpus, language) + synth_result = self.predictor.predict(style_input, text_input) + return synth_result + + +class DatasetSynthesiser(ImageSynthesiser): + def __init__(self): + super(DatasetSynthesiser, self).__init__() + self.tag = self.FLAGS.tag + self.output_num = self.config["Global"]["output_num"] + corpus_generator_method = self.config["CorpusGenerator"]["method"] + self.corpus_generator = getattr(corpus_generators, + corpus_generator_method)(self.config) + + style_sampler_method = self.config["StyleSampler"]["method"] + assert style_sampler_method is not None + self.style_sampler = style_samplers.DatasetSampler(self.config) + self.writer = writers.SimpleWriter(self.config, self.tag) + + def synth_dataset(self): + for i in range(self.output_num): + style_data = self.style_sampler.sample() + style_input = style_data["image"] + corpus_language, text_input_label = self.corpus_generator.generate( + ) + text_input_label, text_input = self.text_drawer.draw_text( + text_input_label, corpus_language) + + synth_result = self.predictor.predict(style_input, text_input) + fake_fusion = synth_result["fake_fusion"] + self.writer.save_image(fake_fusion, text_input_label) + self.writer.save_label() + self.writer.merge_label() diff --git a/StyleText/engine/text_drawers.py b/StyleText/engine/text_drawers.py new file mode 100644 index 0000000000..8aaac06ec5 --- /dev/null +++ b/StyleText/engine/text_drawers.py @@ -0,0 +1,57 @@ +from PIL import Image, ImageDraw, ImageFont +import numpy as np +from utils.logging import get_logger + + +class StdTextDrawer(object): + def __init__(self, config): + self.logger = get_logger() + self.max_width = config["Global"]["image_width"] + self.char_list = " 0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz" + self.height = config["Global"]["image_height"] + self.font_dict = {} + self.load_fonts(config["TextDrawer"]["fonts"]) + self.support_languages = list(self.font_dict) + + def load_fonts(self, fonts_config): + for language in fonts_config: + font_path = fonts_config[language] + font_height = self.get_valid_height(font_path) + font = ImageFont.truetype(font_path, font_height) + self.font_dict[language] = font + + def get_valid_height(self, font_path): + font = ImageFont.truetype(font_path, self.height - 4) + _, font_height = font.getsize(self.char_list) + if font_height <= self.height - 4: + return self.height - 4 + else: + return int((self.height - 4)**2 / font_height) + + def draw_text(self, corpus, language="en", crop=True): + if language not in self.support_languages: + self.logger.warning( + "language {} not supported, use en instead.".format(language)) + language = "en" + if crop: + width = min(self.max_width, len(corpus) * self.height) + 4 + else: + width = len(corpus) * self.height + 4 + bg = Image.new("RGB", (width, self.height), color=(127, 127, 127)) + draw = ImageDraw.Draw(bg) + + char_x = 2 + font = self.font_dict[language] + for i, char_i in enumerate(corpus): + char_size = font.getsize(char_i)[0] + draw.text((char_x, 2), char_i, fill=(0, 0, 0), font=font) + char_x += char_size + if char_x >= width: + corpus = corpus[0:i + 1] + self.logger.warning("corpus length exceed limit: {}".format( + corpus)) + break + + text_input = np.array(bg).astype(np.uint8) + text_input = text_input[:, 0:char_x, :] + return corpus, text_input diff --git a/StyleText/engine/writers.py b/StyleText/engine/writers.py new file mode 100644 index 0000000000..0df75e7234 --- /dev/null +++ b/StyleText/engine/writers.py @@ -0,0 +1,71 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import os +import cv2 +import glob + +from utils.logging import get_logger + + +class SimpleWriter(object): + def __init__(self, config, tag): + self.logger = get_logger() + self.output_dir = config["Global"]["output_dir"] + self.counter = 0 + self.label_dict = {} + self.tag = tag + self.label_file_index = 0 + + def save_image(self, image, text_input_label): + image_home = os.path.join(self.output_dir, "images", self.tag) + if not os.path.exists(image_home): + os.makedirs(image_home) + + image_path = os.path.join(image_home, "{}.png".format(self.counter)) + # todo support continue synth + cv2.imwrite(image_path, image) + self.logger.info("generate image: {}".format(image_path)) + + image_name = os.path.join(self.tag, "{}.png".format(self.counter)) + self.label_dict[image_name] = text_input_label + + self.counter += 1 + if not self.counter % 100: + self.save_label() + + def save_label(self): + label_raw = "" + label_home = os.path.join(self.output_dir, "label") + if not os.path.exists(label_home): + os.mkdir(label_home) + for image_path in self.label_dict: + label = self.label_dict[image_path] + label_raw += "{}\t{}\n".format(image_path, label) + label_file_path = os.path.join(label_home, + "{}_label.txt".format(self.tag)) + with open(label_file_path, "w") as f: + f.write(label_raw) + self.label_file_index += 1 + + def merge_label(self): + label_raw = "" + label_file_regex = os.path.join(self.output_dir, "label", + "*_label.txt") + label_file_list = glob.glob(label_file_regex) + for label_file_i in label_file_list: + with open(label_file_i, "r") as f: + label_raw += f.read() + label_file_path = os.path.join(self.output_dir, "label.txt") + with open(label_file_path, "w") as f: + f.write(label_raw) diff --git a/StyleText/examples/corpus/example.txt b/StyleText/examples/corpus/example.txt new file mode 100644 index 0000000000..93ba35af3b --- /dev/null +++ b/StyleText/examples/corpus/example.txt @@ -0,0 +1,2 @@ +Paddle +飞桨文字识别 diff --git a/StyleText/examples/image_list.txt b/StyleText/examples/image_list.txt new file mode 100644 index 0000000000..b07be03535 --- /dev/null +++ b/StyleText/examples/image_list.txt @@ -0,0 +1,2 @@ +style_images/1.jpg NEATNESS +style_images/2.jpg 锁店君和宾馆 diff --git a/StyleText/examples/style_images/1.jpg b/StyleText/examples/style_images/1.jpg new file mode 100644 index 0000000000..4da7838e5d Binary files /dev/null and b/StyleText/examples/style_images/1.jpg differ diff --git a/StyleText/examples/style_images/2.jpg b/StyleText/examples/style_images/2.jpg new file mode 100644 index 0000000000..0ab932b1d9 Binary files /dev/null and b/StyleText/examples/style_images/2.jpg differ diff --git a/StyleText/fonts/ch_standard.ttf b/StyleText/fonts/ch_standard.ttf new file mode 100755 index 0000000000..cdb7fa5907 Binary files /dev/null and b/StyleText/fonts/ch_standard.ttf differ diff --git a/StyleText/fonts/en_standard.ttf b/StyleText/fonts/en_standard.ttf new file mode 100755 index 0000000000..2e31d02424 Binary files /dev/null and b/StyleText/fonts/en_standard.ttf differ diff --git a/StyleText/fonts/ko_standard.ttf b/StyleText/fonts/ko_standard.ttf new file mode 100755 index 0000000000..982bd879c2 Binary files /dev/null and b/StyleText/fonts/ko_standard.ttf differ diff --git a/StyleText/tools/__init__.py b/StyleText/tools/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/ppocr/modeling/stns/__init__.py b/StyleText/tools/synth_dataset.py old mode 100755 new mode 100644 similarity index 55% rename from ppocr/modeling/stns/__init__.py rename to StyleText/tools/synth_dataset.py index abf198b97e..a75f7f393b --- a/ppocr/modeling/stns/__init__.py +++ b/StyleText/tools/synth_dataset.py @@ -1,4 +1,4 @@ -# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. @@ -11,3 +11,21 @@ # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. + +import os +import sys + +__dir__ = os.path.dirname(os.path.abspath(__file__)) +sys.path.append(__dir__) +sys.path.append(os.path.abspath(os.path.join(__dir__, '..'))) + +from engine.synthesisers import DatasetSynthesiser + + +def synth_dataset(): + dataset_synthesiser = DatasetSynthesiser() + dataset_synthesiser.synth_dataset() + + +if __name__ == '__main__': + synth_dataset() diff --git a/StyleText/tools/synth_image.py b/StyleText/tools/synth_image.py new file mode 100644 index 0000000000..cbc3118675 --- /dev/null +++ b/StyleText/tools/synth_image.py @@ -0,0 +1,82 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import os +import cv2 +import sys +import glob + +__dir__ = os.path.dirname(os.path.abspath(__file__)) +sys.path.append(__dir__) +sys.path.append(os.path.abspath(os.path.join(__dir__, '..'))) + +from utils.config import ArgsParser +from engine.synthesisers import ImageSynthesiser + + +def synth_image(): + args = ArgsParser().parse_args() + image_synthesiser = ImageSynthesiser() + style_image_path = args.style_image + img = cv2.imread(style_image_path) + text_corpus = args.text_corpus + language = args.language + + synth_result = image_synthesiser.synth_image(text_corpus, img, language) + fake_fusion = synth_result["fake_fusion"] + fake_text = synth_result["fake_text"] + fake_bg = synth_result["fake_bg"] + cv2.imwrite("fake_fusion.jpg", fake_fusion) + cv2.imwrite("fake_text.jpg", fake_text) + cv2.imwrite("fake_bg.jpg", fake_bg) + + +def batch_synth_images(): + image_synthesiser = ImageSynthesiser() + + corpus_file = "../StyleTextRec_data/test_20201208/test_text_list.txt" + style_data_dir = "../StyleTextRec_data/test_20201208/style_images/" + save_path = "./output_data/" + corpus_list = [] + with open(corpus_file, "rb") as fin: + lines = fin.readlines() + for line in lines: + substr = line.decode("utf-8").strip("\n").split("\t") + corpus_list.append(substr) + style_img_list = glob.glob("{}/*.jpg".format(style_data_dir)) + corpus_num = len(corpus_list) + style_img_num = len(style_img_list) + for cno in range(corpus_num): + for sno in range(style_img_num): + corpus, lang = corpus_list[cno] + style_img_path = style_img_list[sno] + img = cv2.imread(style_img_path) + synth_result = image_synthesiser.synth_image(corpus, img, lang) + fake_fusion = synth_result["fake_fusion"] + fake_text = synth_result["fake_text"] + fake_bg = synth_result["fake_bg"] + for tp in range(2): + if tp == 0: + prefix = "%s/c%d_s%d_" % (save_path, cno, sno) + else: + prefix = "%s/s%d_c%d_" % (save_path, sno, cno) + cv2.imwrite("%s_fake_fusion.jpg" % prefix, fake_fusion) + cv2.imwrite("%s_fake_text.jpg" % prefix, fake_text) + cv2.imwrite("%s_fake_bg.jpg" % prefix, fake_bg) + cv2.imwrite("%s_input_style.jpg" % prefix, img) + print(cno, corpus_num, sno, style_img_num) + + +if __name__ == '__main__': + # batch_synth_images() + synth_image() diff --git a/StyleText/utils/__init__.py b/StyleText/utils/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/StyleText/utils/config.py b/StyleText/utils/config.py new file mode 100644 index 0000000000..b2f8a618a8 --- /dev/null +++ b/StyleText/utils/config.py @@ -0,0 +1,224 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import yaml +import os +from argparse import ArgumentParser, RawDescriptionHelpFormatter + + +def override(dl, ks, v): + """ + Recursively replace dict of list + + Args: + dl(dict or list): dict or list to be replaced + ks(list): list of keys + v(str): value to be replaced + """ + + def str2num(v): + try: + return eval(v) + except Exception: + return v + + assert isinstance(dl, (list, dict)), ("{} should be a list or a dict") + assert len(ks) > 0, ('lenght of keys should larger than 0') + if isinstance(dl, list): + k = str2num(ks[0]) + if len(ks) == 1: + assert k < len(dl), ('index({}) out of range({})'.format(k, dl)) + dl[k] = str2num(v) + else: + override(dl[k], ks[1:], v) + else: + if len(ks) == 1: + #assert ks[0] in dl, ('{} is not exist in {}'.format(ks[0], dl)) + if not ks[0] in dl: + logger.warning('A new filed ({}) detected!'.format(ks[0], dl)) + dl[ks[0]] = str2num(v) + else: + assert ks[0] in dl, ( + '({}) doesn\'t exist in {}, a new dict field is invalid'. + format(ks[0], dl)) + override(dl[ks[0]], ks[1:], v) + + +def override_config(config, options=None): + """ + Recursively override the config + + Args: + config(dict): dict to be replaced + options(list): list of pairs(key0.key1.idx.key2=value) + such as: [ + 'topk=2', + 'VALID.transforms.1.ResizeImage.resize_short=300' + ] + + Returns: + config(dict): replaced config + """ + if options is not None: + for opt in options: + assert isinstance(opt, str), ( + "option({}) should be a str".format(opt)) + assert "=" in opt, ( + "option({}) should contain a =" + "to distinguish between key and value".format(opt)) + pair = opt.split('=') + assert len(pair) == 2, ("there can be only a = in the option") + key, value = pair + keys = key.split('.') + override(config, keys, value) + + return config + + +class ArgsParser(ArgumentParser): + def __init__(self): + super(ArgsParser, self).__init__( + formatter_class=RawDescriptionHelpFormatter) + self.add_argument("-c", "--config", help="configuration file to use") + self.add_argument( + "-t", "--tag", default="0", help="tag for marking worker") + self.add_argument( + '-o', + '--override', + action='append', + default=[], + help='config options to be overridden') + self.add_argument( + "--style_image", default="examples/style_images/1.jpg", help="tag for marking worker") + self.add_argument( + "--text_corpus", default="PaddleOCR", help="tag for marking worker") + self.add_argument( + "--language", default="en", help="tag for marking worker") + + def parse_args(self, argv=None): + args = super(ArgsParser, self).parse_args(argv) + assert args.config is not None, \ + "Please specify --config=configure_file_path." + return args + + +def load_config(file_path): + """ + Load config from yml/yaml file. + Args: + file_path (str): Path of the config file to be loaded. + Returns: config + """ + ext = os.path.splitext(file_path)[1] + assert ext in ['.yml', '.yaml'], "only support yaml files for now" + with open(file_path, 'rb') as f: + config = yaml.load(f, Loader=yaml.Loader) + + return config + + +def gen_config(): + base_config = { + "Global": { + "algorithm": "SRNet", + "use_gpu": True, + "start_epoch": 1, + "stage1_epoch_num": 100, + "stage2_epoch_num": 100, + "log_smooth_window": 20, + "print_batch_step": 2, + "save_model_dir": "./output/SRNet", + "use_visualdl": False, + "save_epoch_step": 10, + "vgg_pretrain": "./pretrained/VGG19_pretrained", + "vgg_load_static_pretrain": True + }, + "Architecture": { + "model_type": "data_aug", + "algorithm": "SRNet", + "net_g": { + "name": "srnet_net_g", + "encode_dim": 64, + "norm": "batch", + "use_dropout": False, + "init_type": "xavier", + "init_gain": 0.02, + "use_dilation": 1 + }, + # input_nc, ndf, netD, + # n_layers_D=3, norm='instance', use_sigmoid=False, init_type='normal', init_gain=0.02, gpu_id='cuda:0' + "bg_discriminator": { + "name": "srnet_bg_discriminator", + "input_nc": 6, + "ndf": 64, + "netD": "basic", + "norm": "none", + "init_type": "xavier", + }, + "fusion_discriminator": { + "name": "srnet_fusion_discriminator", + "input_nc": 6, + "ndf": 64, + "netD": "basic", + "norm": "none", + "init_type": "xavier", + } + }, + "Loss": { + "lamb": 10, + "perceptual_lamb": 1, + "muvar_lamb": 50, + "style_lamb": 500 + }, + "Optimizer": { + "name": "Adam", + "learning_rate": { + "name": "lambda", + "lr": 0.0002, + "lr_decay_iters": 50 + }, + "beta1": 0.5, + "beta2": 0.999, + }, + "Train": { + "batch_size_per_card": 8, + "num_workers_per_card": 4, + "dataset": { + "delimiter": "\t", + "data_dir": "/", + "label_file": "tmp/label.txt", + "transforms": [{ + "DecodeImage": { + "to_rgb": True, + "to_np": False, + "channel_first": False + } + }, { + "NormalizeImage": { + "scale": 1. / 255., + "mean": [0.485, 0.456, 0.406], + "std": [0.229, 0.224, 0.225], + "order": None + } + }, { + "ToCHWImage": None + }] + } + } + } + with open("config.yml", "w") as f: + yaml.dump(base_config, f) + + +if __name__ == '__main__': + gen_config() diff --git a/StyleText/utils/load_params.py b/StyleText/utils/load_params.py new file mode 100644 index 0000000000..be0561363e --- /dev/null +++ b/StyleText/utils/load_params.py @@ -0,0 +1,27 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import os +import paddle + +__all__ = ['load_dygraph_pretrain'] + + +def load_dygraph_pretrain(model, logger, path=None, load_static_weights=False): + if not os.path.exists(path + '.pdparams'): + raise ValueError("Model pretrain path {} does not " + "exists.".format(path)) + param_state_dict = paddle.load(path + '.pdparams') + model.set_state_dict(param_state_dict) + logger.info("load pretrained model from {}".format(path)) + return diff --git a/StyleText/utils/logging.py b/StyleText/utils/logging.py new file mode 100644 index 0000000000..f700fe26bc --- /dev/null +++ b/StyleText/utils/logging.py @@ -0,0 +1,65 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import os +import sys +import logging +import functools +import paddle.distributed as dist + +logger_initialized = {} + + +@functools.lru_cache() +def get_logger(name='srnet', log_file=None, log_level=logging.INFO): + """Initialize and get a logger by name. + If the logger has not been initialized, this method will initialize the + logger by adding one or two handlers, otherwise the initialized logger will + be directly returned. During initialization, a StreamHandler will always be + added. If `log_file` is specified a FileHandler will also be added. + Args: + name (str): Logger name. + log_file (str | None): The log filename. If specified, a FileHandler + will be added to the logger. + log_level (int): The logger level. Note that only the process of + rank 0 is affected, and other processes will set the level to + "Error" thus be silent most of the time. + Returns: + logging.Logger: The expected logger. + """ + logger = logging.getLogger(name) + if name in logger_initialized: + return logger + for logger_name in logger_initialized: + if name.startswith(logger_name): + return logger + + formatter = logging.Formatter( + '[%(asctime)s] %(name)s %(levelname)s: %(message)s', + datefmt="%Y/%m/%d %H:%M:%S") + + stream_handler = logging.StreamHandler(stream=sys.stdout) + stream_handler.setFormatter(formatter) + logger.addHandler(stream_handler) + if log_file is not None and dist.get_rank() == 0: + log_file_folder = os.path.split(log_file)[0] + os.makedirs(log_file_folder, exist_ok=True) + file_handler = logging.FileHandler(log_file, 'a') + file_handler.setFormatter(formatter) + logger.addHandler(file_handler) + if dist.get_rank() == 0: + logger.setLevel(log_level) + else: + logger.setLevel(logging.ERROR) + logger_initialized[name] = True + return logger diff --git a/StyleText/utils/math_functions.py b/StyleText/utils/math_functions.py new file mode 100644 index 0000000000..3dc8d9160f --- /dev/null +++ b/StyleText/utils/math_functions.py @@ -0,0 +1,45 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import paddle + + +def compute_mean_covariance(img): + batch_size = img.shape[0] + channel_num = img.shape[1] + height = img.shape[2] + width = img.shape[3] + num_pixels = height * width + + # batch_size * channel_num * 1 * 1 + mu = img.mean(2, keepdim=True).mean(3, keepdim=True) + + # batch_size * channel_num * num_pixels + img_hat = img - mu.expand_as(img) + img_hat = img_hat.reshape([batch_size, channel_num, num_pixels]) + # batch_size * num_pixels * channel_num + img_hat_transpose = img_hat.transpose([0, 2, 1]) + # batch_size * channel_num * channel_num + covariance = paddle.bmm(img_hat, img_hat_transpose) + covariance = covariance / num_pixels + + return mu, covariance + + +def dice_coefficient(y_true_cls, y_pred_cls, training_mask): + eps = 1e-5 + intersection = paddle.sum(y_true_cls * y_pred_cls * training_mask) + union = paddle.sum(y_true_cls * training_mask) + paddle.sum( + y_pred_cls * training_mask) + eps + loss = 1. - (2 * intersection / union) + return loss diff --git a/StyleText/utils/sys_funcs.py b/StyleText/utils/sys_funcs.py new file mode 100644 index 0000000000..203d91d836 --- /dev/null +++ b/StyleText/utils/sys_funcs.py @@ -0,0 +1,67 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import sys +import os +import errno +import paddle + + +def get_check_global_params(mode): + check_params = [ + 'use_gpu', 'max_text_length', 'image_shape', 'image_shape', + 'character_type', 'loss_type' + ] + if mode == "train_eval": + check_params = check_params + [ + 'train_batch_size_per_card', 'test_batch_size_per_card' + ] + elif mode == "test": + check_params = check_params + ['test_batch_size_per_card'] + return check_params + + +def check_gpu(use_gpu): + """ + Log error and exit when set use_gpu=true in paddlepaddle + cpu version. + """ + err = "Config use_gpu cannot be set as true while you are " \ + "using paddlepaddle cpu version ! \nPlease try: \n" \ + "\t1. Install paddlepaddle-gpu to run model on GPU \n" \ + "\t2. Set use_gpu as false in config file to run " \ + "model on CPU" + if use_gpu: + try: + if not paddle.is_compiled_with_cuda(): + print(err) + sys.exit(1) + except: + print("Fail to check gpu state.") + sys.exit(1) + + +def _mkdir_if_not_exist(path, logger): + """ + mkdir if not exists, ignore the exception when multiprocess mkdir together + """ + if not os.path.exists(path): + try: + os.makedirs(path) + except OSError as e: + if e.errno == errno.EEXIST and os.path.isdir(path): + logger.warning( + 'be happy if some process has already created {}'.format( + path)) + else: + raise OSError('Failed to mkdir {}'.format(path)) diff --git a/configs/cls/cls_mv3.yml b/configs/cls/cls_mv3.yml new file mode 100644 index 0000000000..b165bc4830 --- /dev/null +++ b/configs/cls/cls_mv3.yml @@ -0,0 +1,96 @@ +Global: + use_gpu: true + epoch_num: 100 + log_smooth_window: 20 + print_batch_step: 10 + save_model_dir: ./output/cls/mv3/ + save_epoch_step: 3 + # evaluation is run every 5000 iterations after the 4000th iteration + eval_batch_step: [0, 1000] + # if pretrained_model is saved in static mode, load_static_weights must set to True + cal_metric_during_train: True + pretrained_model: + checkpoints: + save_inference_dir: + use_visualdl: False + infer_img: doc/imgs_words_en/word_10.png + label_list: ['0','180'] + +Architecture: + model_type: cls + algorithm: CLS + Transform: + Backbone: + name: MobileNetV3 + scale: 0.35 + model_name: small + Neck: + Head: + name: ClsHead + class_dim: 2 + +Loss: + name: ClsLoss + +Optimizer: + name: Adam + beta1: 0.9 + beta2: 0.999 + lr: + name: Cosine + learning_rate: 0.001 + regularizer: + name: 'L2' + factor: 0 + +PostProcess: + name: ClsPostProcess + +Metric: + name: ClsMetric + main_indicator: acc + +Train: + dataset: + name: SimpleDataSet + data_dir: ./train_data/cls + label_file_list: + - ./train_data/cls/train.txt + transforms: + - DecodeImage: # load image + img_mode: BGR + channel_first: False + - ClsLabelEncode: # Class handling label + - RecAug: + use_tia: False + - RandAugment: + - ClsResizeImg: + image_shape: [3, 48, 192] + - KeepKeys: + keep_keys: ['image', 'label'] # dataloader will return list in this order + loader: + shuffle: True + batch_size_per_card: 512 + drop_last: True + num_workers: 8 + +Eval: + dataset: + name: SimpleDataSet + data_dir: ./train_data/cls + label_file_list: + - ./train_data/cls/test.txt + transforms: + - DecodeImage: # load image + img_mode: BGR + channel_first: False + - ClsLabelEncode: # Class handling label + - ClsResizeImg: + image_shape: [3, 48, 192] + - KeepKeys: + keep_keys: ['image', 'label'] # dataloader will return list in this order + loader: + shuffle: False + drop_last: False + batch_size_per_card: 512 + num_workers: 4 \ No newline at end of file diff --git a/configs/det/ch_ppocr_v2.0/ch_det_mv3_db_v2.0.yml b/configs/det/ch_ppocr_v2.0/ch_det_mv3_db_v2.0.yml new file mode 100644 index 0000000000..fd88495928 --- /dev/null +++ b/configs/det/ch_ppocr_v2.0/ch_det_mv3_db_v2.0.yml @@ -0,0 +1,134 @@ +Global: + use_gpu: true + epoch_num: 1200 + log_smooth_window: 20 + print_batch_step: 2 + save_model_dir: ./output/ch_db_mv3/ + save_epoch_step: 1200 + # evaluation is run every 5000 iterations after the 4000th iteration + eval_batch_step: [3000, 2000] + # if pretrained_model is saved in static mode, load_static_weights must set to True + load_static_weights: True + cal_metric_during_train: False + pretrained_model: ./pretrain_models/MobileNetV3_large_x0_5_pretrained + checkpoints: + save_inference_dir: + use_visualdl: False + infer_img: doc/imgs_en/img_10.jpg + save_res_path: ./output/det_db/predicts_db.txt + +Architecture: + model_type: det + algorithm: DB + Transform: + Backbone: + name: MobileNetV3 + scale: 0.5 + model_name: large + disable_se: True + Neck: + name: DBFPN + out_channels: 96 + Head: + name: DBHead + k: 50 + +Loss: + name: DBLoss + balance_loss: true + main_loss_type: DiceLoss + alpha: 5 + beta: 10 + ohem_ratio: 3 + +Optimizer: + name: Adam + beta1: 0.9 + beta2: 0.999 + lr: + name: Cosine + learning_rate: 0.001 + warmup_epoch: 2 + regularizer: + name: 'L2' + factor: 0 + +PostProcess: + name: DBPostProcess + thresh: 0.3 + box_thresh: 0.6 + max_candidates: 1000 + unclip_ratio: 1.5 + +Metric: + name: DetMetric + main_indicator: hmean + +Train: + dataset: + name: SimpleDataSet + data_dir: ./train_data/icdar2015/text_localization/ + label_file_list: + - ./train_data/icdar2015/text_localization/train_icdar2015_label.txt + ratio_list: [1.0] + transforms: + - DecodeImage: # load image + img_mode: BGR + channel_first: False + - DetLabelEncode: # Class handling label + - IaaAugment: + augmenter_args: + - { 'type': Fliplr, 'args': { 'p': 0.5 } } + - { 'type': Affine, 'args': { 'rotate': [-10, 10] } } + - { 'type': Resize, 'args': { 'size': [0.5, 3] } } + - EastRandomCropData: + size: [960, 960] + max_tries: 50 + keep_ratio: true + - MakeBorderMap: + shrink_ratio: 0.4 + thresh_min: 0.3 + thresh_max: 0.7 + - MakeShrinkMap: + shrink_ratio: 0.4 + min_text_size: 8 + - NormalizeImage: + scale: 1./255. + mean: [0.485, 0.456, 0.406] + std: [0.229, 0.224, 0.225] + order: 'hwc' + - ToCHWImage: + - KeepKeys: + keep_keys: ['image', 'threshold_map', 'threshold_mask', 'shrink_map', 'shrink_mask'] # the order of the dataloader list + loader: + shuffle: True + drop_last: False + batch_size_per_card: 8 + num_workers: 4 + +Eval: + dataset: + name: SimpleDataSet + data_dir: ./train_data/icdar2015/text_localization/ + label_file_list: + - ./train_data/icdar2015/text_localization/test_icdar2015_label.txt + transforms: + - DecodeImage: # load image + img_mode: BGR + channel_first: False + - DetLabelEncode: # Class handling label + - DetResizeForTest: +# image_shape: [736, 1280] + - NormalizeImage: + scale: 1./255. + mean: [0.485, 0.456, 0.406] + std: [0.229, 0.224, 0.225] + order: 'hwc' + - ToCHWImage: + - KeepKeys: + keep_keys: ['image', 'shape', 'polys', 'ignore_tags'] + loader: + shuffle: False + drop_last: False + batch_size_per_card: 1 # must be 1 + num_workers: 2 diff --git a/configs/det/ch_ppocr_v2.0/ch_det_res18_db_v2.0.yml b/configs/det/ch_ppocr_v2.0/ch_det_res18_db_v2.0.yml new file mode 100644 index 0000000000..2694601254 --- /dev/null +++ b/configs/det/ch_ppocr_v2.0/ch_det_res18_db_v2.0.yml @@ -0,0 +1,133 @@ +Global: + use_gpu: true + epoch_num: 1200 + log_smooth_window: 20 + print_batch_step: 2 + save_model_dir: ./output/ch_db_res18/ + save_epoch_step: 1200 + # evaluation is run every 5000 iterations after the 4000th iteration + eval_batch_step: [3000, 2000] + # if pretrained_model is saved in static mode, load_static_weights must set to True + load_static_weights: True + cal_metric_during_train: False + pretrained_model: ./pretrain_models/ResNet18_vd_pretrained + checkpoints: + save_inference_dir: + use_visualdl: False + infer_img: doc/imgs_en/img_10.jpg + save_res_path: ./output/det_db/predicts_db.txt + +Architecture: + model_type: det + algorithm: DB + Transform: + Backbone: + name: ResNet + layers: 18 + disable_se: True + Neck: + name: DBFPN + out_channels: 256 + Head: + name: DBHead + k: 50 + +Loss: + name: DBLoss + balance_loss: true + main_loss_type: DiceLoss + alpha: 5 + beta: 10 + ohem_ratio: 3 + +Optimizer: + name: Adam + beta1: 0.9 + beta2: 0.999 + lr: + name: Cosine + learning_rate: 0.001 + warmup_epoch: 2 + regularizer: + name: 'L2' + factor: 0 + +PostProcess: + name: DBPostProcess + thresh: 0.3 + box_thresh: 0.6 + max_candidates: 1000 + unclip_ratio: 1.5 + +Metric: + name: DetMetric + main_indicator: hmean + +Train: + dataset: + name: SimpleDataSet + data_dir: ./train_data/icdar2015/text_localization/ + label_file_list: + - ./train_data/icdar2015/text_localization/train_icdar2015_label.txt + ratio_list: [1.0] + transforms: + - DecodeImage: # load image + img_mode: BGR + channel_first: False + - DetLabelEncode: # Class handling label + - IaaAugment: + augmenter_args: + - { 'type': Fliplr, 'args': { 'p': 0.5 } } + - { 'type': Affine, 'args': { 'rotate': [-10, 10] } } + - { 'type': Resize, 'args': { 'size': [0.5, 3] } } + - EastRandomCropData: + size: [960, 960] + max_tries: 50 + keep_ratio: true + - MakeBorderMap: + shrink_ratio: 0.4 + thresh_min: 0.3 + thresh_max: 0.7 + - MakeShrinkMap: + shrink_ratio: 0.4 + min_text_size: 8 + - NormalizeImage: + scale: 1./255. + mean: [0.485, 0.456, 0.406] + std: [0.229, 0.224, 0.225] + order: 'hwc' + - ToCHWImage: + - KeepKeys: + keep_keys: ['image', 'threshold_map', 'threshold_mask', 'shrink_map', 'shrink_mask'] # the order of the dataloader list + loader: + shuffle: True + drop_last: False + batch_size_per_card: 8 + num_workers: 4 + +Eval: + dataset: + name: SimpleDataSet + data_dir: ./train_data/icdar2015/text_localization/ + label_file_list: + - ./train_data/icdar2015/text_localization/test_icdar2015_label.txt + transforms: + - DecodeImage: # load image + img_mode: BGR + channel_first: False + - DetLabelEncode: # Class handling label + - DetResizeForTest: +# image_shape: [736, 1280] + - NormalizeImage: + scale: 1./255. + mean: [0.485, 0.456, 0.406] + std: [0.229, 0.224, 0.225] + order: 'hwc' + - ToCHWImage: + - KeepKeys: + keep_keys: ['image', 'shape', 'polys', 'ignore_tags'] + loader: + shuffle: False + drop_last: False + batch_size_per_card: 1 # must be 1 + num_workers: 2 diff --git a/configs/det/det_db_icdar15_reader.yml b/configs/det/det_db_icdar15_reader.yml deleted file mode 100755 index 0f99257b53..0000000000 --- a/configs/det/det_db_icdar15_reader.yml +++ /dev/null @@ -1,22 +0,0 @@ -TrainReader: - reader_function: ppocr.data.det.dataset_traversal,TrainReader - process_function: ppocr.data.det.db_process,DBProcessTrain - num_workers: 8 - img_set_dir: ./train_data/icdar2015/text_localization/ - label_file_path: ./train_data/icdar2015/text_localization/train_icdar2015_label.txt - -EvalReader: - reader_function: ppocr.data.det.dataset_traversal,EvalTestReader - process_function: ppocr.data.det.db_process,DBProcessTest - img_set_dir: ./train_data/icdar2015/text_localization/ - label_file_path: ./train_data/icdar2015/text_localization/test_icdar2015_label.txt - test_image_shape: [736, 1280] - -TestReader: - reader_function: ppocr.data.det.dataset_traversal,EvalTestReader - process_function: ppocr.data.det.db_process,DBProcessTest - infer_img: - img_set_dir: ./train_data/icdar2015/text_localization/ - label_file_path: ./train_data/icdar2015/text_localization/test_icdar2015_label.txt - test_image_shape: [736, 1280] - do_eval: True diff --git a/configs/det/det_east_icdar15_reader.yml b/configs/det/det_east_icdar15_reader.yml deleted file mode 100755 index 060ed4dd38..0000000000 --- a/configs/det/det_east_icdar15_reader.yml +++ /dev/null @@ -1,23 +0,0 @@ -TrainReader: - reader_function: ppocr.data.det.dataset_traversal,TrainReader - process_function: ppocr.data.det.east_process,EASTProcessTrain - num_workers: 8 - img_set_dir: ./train_data/icdar2015/text_localization/ - label_file_path: ./train_data/icdar2015/text_localization/train_icdar2015_label.txt - background_ratio: 0.125 - min_crop_side_ratio: 0.1 - min_text_size: 10 - -EvalReader: - reader_function: ppocr.data.det.dataset_traversal,EvalTestReader - process_function: ppocr.data.det.east_process,EASTProcessTest - img_set_dir: ./train_data/icdar2015/text_localization/ - label_file_path: ./train_data/icdar2015/text_localization/test_icdar2015_label.txt - -TestReader: - reader_function: ppocr.data.det.dataset_traversal,EvalTestReader - process_function: ppocr.data.det.east_process,EASTProcessTest - infer_img: - img_set_dir: ./train_data/icdar2015/text_localization/ - label_file_path: ./train_data/icdar2015/text_localization/test_icdar2015_label.txt - do_eval: True diff --git a/configs/det/det_mv3_db.yml b/configs/det/det_mv3_db.yml old mode 100755 new mode 100644 index caa7bd4fa0..5c8a092342 --- a/configs/det/det_mv3_db.yml +++ b/configs/det/det_mv3_db.yml @@ -1,39 +1,39 @@ Global: - algorithm: DB use_gpu: true epoch_num: 1200 log_smooth_window: 20 - print_batch_step: 2 - save_model_dir: ./output/det_db/ - save_epoch_step: 200 - # evaluation is run every 5000 iterations after the 4000th iteration - eval_batch_step: [4000, 5000] - train_batch_size_per_card: 16 - test_batch_size_per_card: 16 - image_shape: [3, 640, 640] - reader_yml: ./configs/det/det_db_icdar15_reader.yml - pretrain_weights: ./pretrain_models/MobileNetV3_large_x0_5_pretrained/ + print_batch_step: 10 + save_model_dir: ./output/db_mv3/ + save_epoch_step: 1200 + # evaluation is run every 2000 iterations + eval_batch_step: [0, 2000] + # if pretrained_model is saved in static mode, load_static_weights must set to True + load_static_weights: True + cal_metric_during_train: False + pretrained_model: ./pretrain_models/MobileNetV3_large_x0_5_pretrained checkpoints: - save_res_path: ./output/det_db/predicts_db.txt save_inference_dir: - -Architecture: - function: ppocr.modeling.architectures.det_model,DetModel - -Backbone: - function: ppocr.modeling.backbones.det_mobilenet_v3,MobileNetV3 - scale: 0.5 - model_name: large + use_visualdl: False + infer_img: doc/imgs_en/img_10.jpg + save_res_path: ./output/det_db/predicts_db.txt -Head: - function: ppocr.modeling.heads.det_db_head,DBHead - model_name: large - k: 50 - inner_channels: 96 - out_channels: 2 +Architecture: + model_type: det + algorithm: DB + Transform: + Backbone: + name: MobileNetV3 + scale: 0.5 + model_name: large + Neck: + name: DBFPN + out_channels: 256 + Head: + name: DBHead + k: 50 Loss: - function: ppocr.modeling.losses.det_db_loss,DBLoss + name: DBLoss balance_loss: true main_loss_type: DiceLoss alpha: 5 @@ -41,14 +41,91 @@ Loss: ohem_ratio: 3 Optimizer: - function: ppocr.optimizer,AdamDecay - base_lr: 0.001 + name: Adam beta1: 0.9 beta2: 0.999 + lr: + learning_rate: 0.001 + regularizer: + name: 'L2' + factor: 0 PostProcess: - function: ppocr.postprocess.db_postprocess,DBPostProcess + name: DBPostProcess thresh: 0.3 - box_thresh: 0.7 + box_thresh: 0.6 max_candidates: 1000 - unclip_ratio: 2.0 + unclip_ratio: 1.5 + +Metric: + name: DetMetric + main_indicator: hmean + +Train: + dataset: + name: SimpleDataSet + data_dir: ./train_data/icdar2015/text_localization/ + label_file_list: + - ./train_data/icdar2015/text_localization/train_icdar2015_label.txt + ratio_list: [0.5] + transforms: + - DecodeImage: # load image + img_mode: BGR + channel_first: False + - DetLabelEncode: # Class handling label + - IaaAugment: + augmenter_args: + - { 'type': Fliplr, 'args': { 'p': 0.5 } } + - { 'type': Affine, 'args': { 'rotate': [-10, 10] } } + - { 'type': Resize, 'args': { 'size': [0.5, 3] } } + - EastRandomCropData: + size: [640, 640] + max_tries: 50 + keep_ratio: true + - MakeBorderMap: + shrink_ratio: 0.4 + thresh_min: 0.3 + thresh_max: 0.7 + - MakeShrinkMap: + shrink_ratio: 0.4 + min_text_size: 8 + - NormalizeImage: + scale: 1./255. + mean: [0.485, 0.456, 0.406] + std: [0.229, 0.224, 0.225] + order: 'hwc' + - ToCHWImage: + - KeepKeys: + keep_keys: ['image', 'threshold_map', 'threshold_mask', 'shrink_map', 'shrink_mask'] # the order of the dataloader list + loader: + shuffle: True + drop_last: False + batch_size_per_card: 16 + num_workers: 8 + +Eval: + dataset: + name: SimpleDataSet + data_dir: ./train_data/icdar2015/text_localization/ + label_file_list: + - ./train_data/icdar2015/text_localization/test_icdar2015_label.txt + transforms: + - DecodeImage: # load image + img_mode: BGR + channel_first: False + - DetLabelEncode: # Class handling label + - DetResizeForTest: + image_shape: [736, 1280] + - NormalizeImage: + scale: 1./255. + mean: [0.485, 0.456, 0.406] + std: [0.229, 0.224, 0.225] + order: 'hwc' + - ToCHWImage: + - KeepKeys: + keep_keys: ['image', 'shape', 'polys', 'ignore_tags'] + loader: + shuffle: False + drop_last: False + batch_size_per_card: 1 # must be 1 + num_workers: 8 \ No newline at end of file diff --git a/configs/det/det_mv3_east.yml b/configs/det/det_mv3_east.yml old mode 100755 new mode 100644 index 67b82fffff..05581a761c --- a/configs/det/det_mv3_east.yml +++ b/configs/det/det_mv3_east.yml @@ -1,45 +1,111 @@ Global: - algorithm: EAST use_gpu: true - epoch_num: 100000 + epoch_num: 10000 log_smooth_window: 20 - print_batch_step: 5 - save_model_dir: ./output/det_east/ - save_epoch_step: 200 - eval_batch_step: [5000, 5000] - train_batch_size_per_card: 16 - test_batch_size_per_card: 16 - image_shape: [3, 512, 512] - reader_yml: ./configs/det/det_east_icdar15_reader.yml - pretrain_weights: ./pretrain_models/MobileNetV3_large_x0_5_pretrained/ - checkpoints: - save_res_path: ./output/det_east/predicts_east.txt + print_batch_step: 2 + save_model_dir: ./output/east_mv3/ + save_epoch_step: 1000 + # evaluation is run every 5000 iterations after the 4000th iteration + eval_batch_step: [4000, 5000] + # if pretrained_model is saved in static mode, load_static_weights must set to True + load_static_weights: True + cal_metric_during_train: False + pretrained_model: ./pretrain_models/MobileNetV3_large_x0_5_pretrained + checkpoints: save_inference_dir: - -Architecture: - function: ppocr.modeling.architectures.det_model,DetModel + use_visualdl: False + infer_img: + save_res_path: ./output/det_east/predicts_east.txt -Backbone: - function: ppocr.modeling.backbones.det_mobilenet_v3,MobileNetV3 - scale: 0.5 - model_name: large +Architecture: + model_type: det + algorithm: EAST + Transform: + Backbone: + name: MobileNetV3 + scale: 0.5 + model_name: large + Neck: + name: EASTFPN + model_name: small + Head: + name: EASTHead + model_name: small -Head: - function: ppocr.modeling.heads.det_east_head,EASTHead - model_name: small - Loss: - function: ppocr.modeling.losses.det_east_loss,EASTLoss - + name: EASTLoss + Optimizer: - function: ppocr.optimizer,AdamDecay - base_lr: 0.001 + name: Adam beta1: 0.9 beta2: 0.999 + lr: + # name: Cosine + learning_rate: 0.001 + # warmup_epoch: 0 + regularizer: + name: 'L2' + factor: 0 PostProcess: - function: ppocr.postprocess.east_postprocess,EASTPostPocess + name: EASTPostProcess score_thresh: 0.8 cover_thresh: 0.1 nms_thresh: 0.2 - + +Metric: + name: DetMetric + main_indicator: hmean + +Train: + dataset: + name: SimpleDataSet + data_dir: ./train_data/icdar2015/text_localization/ + label_file_list: + - ./train_data/icdar2015/text_localization/train_icdar2015_label.txt + ratio_list: [1.0] + transforms: + - DecodeImage: # load image + img_mode: BGR + channel_first: False + - DetLabelEncode: # Class handling label + - EASTProcessTrain: + image_shape: [512, 512] + background_ratio: 0.125 + min_crop_side_ratio: 0.1 + min_text_size: 10 + - KeepKeys: + keep_keys: ['image', 'score_map', 'geo_map', 'training_mask'] # dataloader will return list in this order + loader: + shuffle: True + drop_last: False + batch_size_per_card: 16 + num_workers: 8 + +Eval: + dataset: + name: SimpleDataSet + data_dir: ./train_data/icdar2015/text_localization/ + label_file_list: + - ./train_data/icdar2015/text_localization/test_icdar2015_label.txt + transforms: + - DecodeImage: # load image + img_mode: BGR + channel_first: False + - DetLabelEncode: # Class handling label + - DetResizeForTest: + limit_side_len: 2400 + limit_type: max + - NormalizeImage: + scale: 1./255. + mean: [0.485, 0.456, 0.406] + std: [0.229, 0.224, 0.225] + order: 'hwc' + - ToCHWImage: + - KeepKeys: + keep_keys: ['image', 'shape', 'polys', 'ignore_tags'] + loader: + shuffle: False + drop_last: False + batch_size_per_card: 1 # must be 1 + num_workers: 2 \ No newline at end of file diff --git a/configs/det/det_r50_vd_db.yml b/configs/det/det_r50_vd_db.yml old mode 100755 new mode 100644 index 9a3b77e7ce..f1188fe357 --- a/configs/det/det_r50_vd_db.yml +++ b/configs/det/det_r50_vd_db.yml @@ -1,37 +1,38 @@ Global: - algorithm: DB use_gpu: true epoch_num: 1200 log_smooth_window: 20 - print_batch_step: 2 - save_model_dir: ./output/det_db/ - save_epoch_step: 200 - eval_batch_step: [5000, 5000] - train_batch_size_per_card: 8 - test_batch_size_per_card: 16 - image_shape: [3, 640, 640] - reader_yml: ./configs/det/det_db_icdar15_reader.yml - pretrain_weights: ./pretrain_models/ResNet50_vd_ssld_pretrained/ - save_res_path: ./output/det_db/predicts_db.txt + print_batch_step: 10 + save_model_dir: ./output/det_r50_vd/ + save_epoch_step: 1200 + # evaluation is run every 2000 iterations + eval_batch_step: [0,2000] + # if pretrained_model is saved in static mode, load_static_weights must set to True + load_static_weights: True + cal_metric_during_train: False + pretrained_model: ./pretrain_models/ResNet50_vd_ssld_pretrained checkpoints: save_inference_dir: + use_visualdl: False + infer_img: doc/imgs_en/img_10.jpg + save_res_path: ./output/det_db/predicts_db.txt Architecture: - function: ppocr.modeling.architectures.det_model,DetModel - -Backbone: - function: ppocr.modeling.backbones.det_resnet_vd,ResNet - layers: 50 - -Head: - function: ppocr.modeling.heads.det_db_head,DBHead - model_name: large - k: 50 - inner_channels: 256 - out_channels: 2 + model_type: det + algorithm: DB + Transform: + Backbone: + name: ResNet + layers: 50 + Neck: + name: DBFPN + out_channels: 256 + Head: + name: DBHead + k: 50 Loss: - function: ppocr.modeling.losses.det_db_loss,DBLoss + name: DBLoss balance_loss: true main_loss_type: DiceLoss alpha: 5 @@ -39,15 +40,91 @@ Loss: ohem_ratio: 3 Optimizer: - function: ppocr.optimizer,AdamDecay - base_lr: 0.001 + name: Adam beta1: 0.9 beta2: 0.999 + lr: + learning_rate: 0.001 + regularizer: + name: 'L2' + factor: 0 PostProcess: - function: ppocr.postprocess.db_postprocess,DBPostProcess + name: DBPostProcess thresh: 0.3 box_thresh: 0.7 max_candidates: 1000 unclip_ratio: 1.5 - + +Metric: + name: DetMetric + main_indicator: hmean + +Train: + dataset: + name: SimpleDataSet + data_dir: ./train_data/icdar2015/text_localization/ + label_file_list: + - ./train_data/icdar2015/text_localization/train_icdar2015_label.txt + ratio_list: [0.5] + transforms: + - DecodeImage: # load image + img_mode: BGR + channel_first: False + - DetLabelEncode: # Class handling label + - IaaAugment: + augmenter_args: + - { 'type': Fliplr, 'args': { 'p': 0.5 } } + - { 'type': Affine, 'args': { 'rotate': [-10, 10] } } + - { 'type': Resize, 'args': { 'size': [0.5, 3] } } + - EastRandomCropData: + size: [640, 640] + max_tries: 50 + keep_ratio: true + - MakeBorderMap: + shrink_ratio: 0.4 + thresh_min: 0.3 + thresh_max: 0.7 + - MakeShrinkMap: + shrink_ratio: 0.4 + min_text_size: 8 + - NormalizeImage: + scale: 1./255. + mean: [0.485, 0.456, 0.406] + std: [0.229, 0.224, 0.225] + order: 'hwc' + - ToCHWImage: + - KeepKeys: + keep_keys: ['image', 'threshold_map', 'threshold_mask', 'shrink_map', 'shrink_mask'] # the order of the dataloader list + loader: + shuffle: True + drop_last: False + batch_size_per_card: 16 + num_workers: 8 + +Eval: + dataset: + name: SimpleDataSet + data_dir: ./train_data/icdar2015/text_localization/ + label_file_list: + - ./train_data/icdar2015/text_localization/test_icdar2015_label.txt + transforms: + - DecodeImage: # load image + img_mode: BGR + channel_first: False + - DetLabelEncode: # Class handling label + - DetResizeForTest: + image_shape: [736, 1280] + - NormalizeImage: + scale: 1./255. + mean: [0.485, 0.456, 0.406] + std: [0.229, 0.224, 0.225] + order: 'hwc' + - ToCHWImage: + - KeepKeys: + keep_keys: ['image', 'shape', 'polys', 'ignore_tags'] + loader: + shuffle: False + drop_last: False + batch_size_per_card: 1 # must be 1 + num_workers: 8 \ No newline at end of file diff --git a/configs/det/det_r50_vd_east.yml b/configs/det/det_r50_vd_east.yml old mode 100755 new mode 100644 index 8d86819937..b8fe55d4ac --- a/configs/det/det_r50_vd_east.yml +++ b/configs/det/det_r50_vd_east.yml @@ -1,44 +1,110 @@ Global: - algorithm: EAST use_gpu: true - epoch_num: 100000 + epoch_num: 10000 log_smooth_window: 20 - print_batch_step: 5 - save_model_dir: ./output/det_east/ - save_epoch_step: 200 - eval_batch_step: [5000, 5000] - train_batch_size_per_card: 8 - test_batch_size_per_card: 16 - image_shape: [3, 512, 512] - reader_yml: ./configs/det/det_east_icdar15_reader.yml - pretrain_weights: ./pretrain_models/ResNet50_vd_ssld_pretrained/ - save_res_path: ./output/det_east/predicts_east.txt - checkpoints: + print_batch_step: 2 + save_model_dir: ./output/east_r50_vd/ + save_epoch_step: 1000 + # evaluation is run every 5000 iterations after the 4000th iteration + eval_batch_step: [4000, 5000] + # if pretrained_model is saved in static mode, load_static_weights must set to True + load_static_weights: True + cal_metric_during_train: False + pretrained_model: ./pretrain_models/ResNet50_vd_pretrained/ + checkpoints: save_inference_dir: + use_visualdl: False + infer_img: + save_res_path: ./output/det_east/predicts_east.txt Architecture: - function: ppocr.modeling.architectures.det_model,DetModel - -Backbone: - function: ppocr.modeling.backbones.det_resnet_vd,ResNet - layers: 50 + model_type: det + algorithm: EAST + Transform: + Backbone: + name: ResNet + layers: 50 + Neck: + name: EASTFPN + model_name: large + Head: + name: EASTHead + model_name: large -Head: - function: ppocr.modeling.heads.det_east_head,EASTHead - model_name: large - Loss: - function: ppocr.modeling.losses.det_east_loss,EASTLoss - + name: EASTLoss + Optimizer: - function: ppocr.optimizer,AdamDecay - base_lr: 0.001 + name: Adam beta1: 0.9 beta2: 0.999 + lr: + # name: Cosine + learning_rate: 0.001 + # warmup_epoch: 0 + regularizer: + name: 'L2' + factor: 0 PostProcess: - function: ppocr.postprocess.east_postprocess,EASTPostPocess + name: EASTPostProcess score_thresh: 0.8 cover_thresh: 0.1 nms_thresh: 0.2 - + +Metric: + name: DetMetric + main_indicator: hmean + +Train: + dataset: + name: SimpleDataSet + data_dir: ./train_data/icdar2015/text_localization/ + label_file_list: + - ./train_data/icdar2015/text_localization/train_icdar2015_label.txt + ratio_list: [1.0] + transforms: + - DecodeImage: # load image + img_mode: BGR + channel_first: False + - DetLabelEncode: # Class handling label + - EASTProcessTrain: + image_shape: [512, 512] + background_ratio: 0.125 + min_crop_side_ratio: 0.1 + min_text_size: 10 + - KeepKeys: + keep_keys: ['image', 'score_map', 'geo_map', 'training_mask'] # dataloader will return list in this order + loader: + shuffle: True + drop_last: False + batch_size_per_card: 8 + num_workers: 8 + +Eval: + dataset: + name: SimpleDataSet + data_dir: ./train_data/icdar2015/text_localization/ + label_file_list: + - ./train_data/icdar2015/text_localization/test_icdar2015_label.txt + transforms: + - DecodeImage: # load image + img_mode: BGR + channel_first: False + - DetLabelEncode: # Class handling label + - DetResizeForTest: + limit_side_len: 2400 + limit_type: max + - NormalizeImage: + scale: 1./255. + mean: [0.485, 0.456, 0.406] + std: [0.229, 0.224, 0.225] + order: 'hwc' + - ToCHWImage: + - KeepKeys: + keep_keys: ['image', 'shape', 'polys', 'ignore_tags'] + loader: + shuffle: False + drop_last: False + batch_size_per_card: 1 # must be 1 + num_workers: 2 \ No newline at end of file diff --git a/configs/det/det_r50_vd_sast_icdar15.yml b/configs/det/det_r50_vd_sast_icdar15.yml old mode 100644 new mode 100755 index f1ecd61dc8..a989bc8fc7 --- a/configs/det/det_r50_vd_sast_icdar15.yml +++ b/configs/det/det_r50_vd_sast_icdar15.yml @@ -1,50 +1,110 @@ Global: - algorithm: SAST use_gpu: true - epoch_num: 2000 + epoch_num: 5000 log_smooth_window: 20 print_batch_step: 2 - save_model_dir: ./output/det_sast/ - save_epoch_step: 20 - eval_batch_step: 5000 - train_batch_size_per_card: 8 - test_batch_size_per_card: 8 - image_shape: [3, 512, 512] - reader_yml: ./configs/det/det_sast_icdar15_reader.yml - pretrain_weights: ./pretrain_models/ResNet50_vd_ssld_pretrained/ - save_res_path: ./output/det_sast/predicts_sast.txt + save_model_dir: ./output/sast_r50_vd_ic15/ + save_epoch_step: 1000 + # evaluation is run every 5000 iterations after the 4000th iteration + eval_batch_step: [4000, 5000] + # if pretrained_model is saved in static mode, load_static_weights must set to True + load_static_weights: True + cal_metric_during_train: False + pretrained_model: ./pretrain_models/ResNet50_vd_ssld_pretrained/ checkpoints: save_inference_dir: + use_visualdl: False + infer_img: + save_res_path: ./output/sast_r50_vd_ic15/predicts_sast.txt Architecture: - function: ppocr.modeling.architectures.det_model,DetModel - -Backbone: - function: ppocr.modeling.backbones.det_resnet_vd_sast,ResNet - layers: 50 - -Head: - function: ppocr.modeling.heads.det_sast_head,SASTHead - model_name: large - only_fpn_up: False -# with_cab: False - with_cab: True + model_type: det + algorithm: SAST + Transform: + Backbone: + name: ResNet_SAST + layers: 50 + Neck: + name: SASTFPN + with_cab: True + Head: + name: SASTHead Loss: - function: ppocr.modeling.losses.det_sast_loss,SASTLoss - + name: SASTLoss + Optimizer: - function: ppocr.optimizer,RMSProp - base_lr: 0.001 - decay: - function: piecewise_decay - boundaries: [30000, 50000, 80000, 100000, 150000] - decay_rate: 0.3 + name: Adam + beta1: 0.9 + beta2: 0.999 + lr: + # name: Cosine + learning_rate: 0.001 + # warmup_epoch: 0 + regularizer: + name: 'L2' + factor: 0 PostProcess: - function: ppocr.postprocess.sast_postprocess,SASTPostProcess + name: SASTPostProcess score_thresh: 0.5 sample_pts_num: 2 nms_thresh: 0.2 expand_scale: 1.0 - shrink_ratio_of_width: 0.3 \ No newline at end of file + shrink_ratio_of_width: 0.3 + +Metric: + name: DetMetric + main_indicator: hmean + +Train: + dataset: + name: SimpleDataSet + data_dir: ./train_data/ + label_file_list: [./train_data/icdar2013/train_label_json.txt, ./train_data/icdar2015/train_label_json.txt, ./train_data/icdar17_mlt_latin/train_label_json.txt, ./train_data/coco_text_icdar_4pts/train_label_json.txt] + ratio_list: [0.1, 0.45, 0.3, 0.15] + transforms: + - DecodeImage: # load image + img_mode: BGR + channel_first: False + - DetLabelEncode: # Class handling label + - SASTProcessTrain: + image_shape: [512, 512] + min_crop_side_ratio: 0.3 + min_crop_size: 24 + min_text_size: 4 + max_text_size: 512 + - KeepKeys: + keep_keys: ['image', 'score_map', 'border_map', 'training_mask', 'tvo_map', 'tco_map'] # dataloader will return list in this order + loader: + shuffle: True + drop_last: False + batch_size_per_card: 4 + num_workers: 4 + +Eval: + dataset: + name: SimpleDataSet + data_dir: ./train_data/icdar2015/text_localization/ + label_file_list: + - ./train_data/icdar2015/text_localization/test_icdar2015_label.txt + transforms: + - DecodeImage: # load image + img_mode: BGR + channel_first: False + - DetLabelEncode: # Class handling label + - DetResizeForTest: + resize_long: 1536 + - NormalizeImage: + scale: 1./255. + mean: [0.485, 0.456, 0.406] + std: [0.229, 0.224, 0.225] + order: 'hwc' + - ToCHWImage: + - KeepKeys: + keep_keys: ['image', 'shape', 'polys', 'ignore_tags'] + loader: + shuffle: False + drop_last: False + batch_size_per_card: 1 # must be 1 + num_workers: 2 \ No newline at end of file diff --git a/configs/det/det_r50_vd_sast_totaltext.yml b/configs/det/det_r50_vd_sast_totaltext.yml old mode 100644 new mode 100755 index ec42ce6d4b..a92f1b6e53 --- a/configs/det/det_r50_vd_sast_totaltext.yml +++ b/configs/det/det_r50_vd_sast_totaltext.yml @@ -1,50 +1,110 @@ Global: - algorithm: SAST use_gpu: true - epoch_num: 2000 + epoch_num: 5000 log_smooth_window: 20 print_batch_step: 2 - save_model_dir: ./output/det_sast/ - save_epoch_step: 20 - eval_batch_step: 5000 - train_batch_size_per_card: 8 - test_batch_size_per_card: 1 - image_shape: [3, 512, 512] - reader_yml: ./configs/det/det_sast_totaltext_reader.yml - pretrain_weights: ./pretrain_models/ResNet50_vd_ssld_pretrained/ - save_res_path: ./output/det_sast/predicts_sast.txt - checkpoints: + save_model_dir: ./output/sast_r50_vd_tt/ + save_epoch_step: 1000 + # evaluation is run every 5000 iterations after the 4000th iteration + eval_batch_step: [4000, 5000] + # if pretrained_model is saved in static mode, load_static_weights must set to True + load_static_weights: True + cal_metric_during_train: False + pretrained_model: ./pretrain_models/ResNet50_vd_ssld_pretrained/ + checkpoints: save_inference_dir: + use_visualdl: False + infer_img: + save_res_path: ./output/sast_r50_vd_tt/predicts_sast.txt Architecture: - function: ppocr.modeling.architectures.det_model,DetModel - -Backbone: - function: ppocr.modeling.backbones.det_resnet_vd_sast,ResNet - layers: 50 - -Head: - function: ppocr.modeling.heads.det_sast_head,SASTHead - model_name: large - only_fpn_up: False - # with_cab: False - with_cab: True + model_type: det + algorithm: SAST + Transform: + Backbone: + name: ResNet_SAST + layers: 50 + Neck: + name: SASTFPN + with_cab: True + Head: + name: SASTHead Loss: - function: ppocr.modeling.losses.det_sast_loss,SASTLoss - + name: SASTLoss + Optimizer: - function: ppocr.optimizer,RMSProp - base_lr: 0.001 - decay: - function: piecewise_decay - boundaries: [30000, 50000, 80000, 100000, 150000] - decay_rate: 0.3 + name: Adam + beta1: 0.9 + beta2: 0.999 + lr: + # name: Cosine + learning_rate: 0.001 + # warmup_epoch: 0 + regularizer: + name: 'L2' + factor: 0 PostProcess: - function: ppocr.postprocess.sast_postprocess,SASTPostProcess + name: SASTPostProcess score_thresh: 0.5 sample_pts_num: 6 nms_thresh: 0.2 expand_scale: 1.2 - shrink_ratio_of_width: 0.2 \ No newline at end of file + shrink_ratio_of_width: 0.2 + +Metric: + name: DetMetric + main_indicator: hmean + +Train: + dataset: + name: SimpleDataSet + data_dir: ./train_data/ + label_file_list: [./train_data/art_latin_icdar_14pt/train_no_tt_test/train_label_json.txt, ./train_data/total_text_icdar_14pt/train_label_json.txt] + data_ratio_list: [0.5, 0.5] + transforms: + - DecodeImage: # load image + img_mode: BGR + channel_first: False + - DetLabelEncode: # Class handling label + - SASTProcessTrain: + image_shape: [512, 512] + min_crop_side_ratio: 0.3 + min_crop_size: 24 + min_text_size: 4 + max_text_size: 512 + - KeepKeys: + keep_keys: ['image', 'score_map', 'border_map', 'training_mask', 'tvo_map', 'tco_map'] # dataloader will return list in this order + loader: + shuffle: True + drop_last: False + batch_size_per_card: 4 + num_workers: 4 + +Eval: + dataset: + name: SimpleDataSet + data_dir: ./train_data/ + label_file_list: + - ./train_data/total_text_icdar_14pt/test_label_json.txt + transforms: + - DecodeImage: # load image + img_mode: BGR + channel_first: False + - DetLabelEncode: # Class handling label + - DetResizeForTest: + resize_long: 768 + - NormalizeImage: + scale: 1./255. + mean: [0.485, 0.456, 0.406] + std: [0.229, 0.224, 0.225] + order: 'hwc' + - ToCHWImage: + - KeepKeys: + keep_keys: ['image', 'shape', 'polys', 'ignore_tags'] + loader: + shuffle: False + drop_last: False + batch_size_per_card: 1 # must be 1 + num_workers: 2 \ No newline at end of file diff --git a/configs/det/det_sast_icdar15_reader.yml b/configs/det/det_sast_icdar15_reader.yml deleted file mode 100644 index ee45a85da7..0000000000 --- a/configs/det/det_sast_icdar15_reader.yml +++ /dev/null @@ -1,24 +0,0 @@ -TrainReader: - reader_function: ppocr.data.det.dataset_traversal,TrainReader - process_function: ppocr.data.det.sast_process,SASTProcessTrain - num_workers: 8 - img_set_dir: ./train_data/ - label_file_path: [./train_data/icdar2013/train_label_json.txt, ./train_data/icdar2015/train_label_json.txt, ./train_data/icdar17_mlt_latin/train_label_json.txt, ./train_data/coco_text_icdar_4pts/train_label_json.txt] - data_ratio_list: [0.1, 0.45, 0.3, 0.15] - min_crop_side_ratio: 0.3 - min_crop_size: 24 - min_text_size: 4 - max_text_size: 512 - -EvalReader: - reader_function: ppocr.data.det.dataset_traversal,EvalTestReader - process_function: ppocr.data.det.sast_process,SASTProcessTest - img_set_dir: ./train_data/icdar2015/text_localization/ - label_file_path: ./train_data/icdar2015/text_localization/test_icdar2015_label.txt - max_side_len: 1536 - -TestReader: - reader_function: ppocr.data.det.dataset_traversal,EvalTestReader - process_function: ppocr.data.det.sast_process,SASTProcessTest - infer_img: ./train_data/icdar2015/text_localization/ch4_test_images/img_11.jpg - max_side_len: 1536 diff --git a/configs/det/det_sast_totaltext_reader.yml b/configs/det/det_sast_totaltext_reader.yml deleted file mode 100644 index 92503d9f0e..0000000000 --- a/configs/det/det_sast_totaltext_reader.yml +++ /dev/null @@ -1,24 +0,0 @@ -TrainReader: - reader_function: ppocr.data.det.dataset_traversal,TrainReader - process_function: ppocr.data.det.sast_process,SASTProcessTrain - num_workers: 8 - img_set_dir: ./train_data/ - label_file_path: [./train_data/art_latin_icdar_14pt/train_no_tt_test/train_label_json.txt, ./train_data/total_text_icdar_14pt/train_label_json.txt] - data_ratio_list: [0.5, 0.5] - min_crop_side_ratio: 0.3 - min_crop_size: 24 - min_text_size: 4 - max_text_size: 512 - -EvalReader: - reader_function: ppocr.data.det.dataset_traversal,EvalTestReader - process_function: ppocr.data.det.sast_process,SASTProcessTest - img_set_dir: ./train_data/ - label_file_path: ./train_data/total_text_icdar_14pt/test_label_json.txt - max_side_len: 768 - -TestReader: - reader_function: ppocr.data.det.dataset_traversal,EvalTestReader - process_function: ppocr.data.det.sast_process,SASTProcessTest - infer_img: ./train_data/afs/total_text/Images/Test/img623.jpg - max_side_len: 768 diff --git a/configs/rec/ch_ppocr_v2.0/rec_chinese_common_train_v2.0.yml b/configs/rec/ch_ppocr_v2.0/rec_chinese_common_train_v2.0.yml new file mode 100644 index 0000000000..1db3e1cb86 --- /dev/null +++ b/configs/rec/ch_ppocr_v2.0/rec_chinese_common_train_v2.0.yml @@ -0,0 +1,100 @@ +Global: + use_gpu: true + epoch_num: 500 + log_smooth_window: 20 + print_batch_step: 10 + save_model_dir: ./output/rec_chinese_common_v2.0 + save_epoch_step: 3 + # evaluation is run every 5000 iterations after the 4000th iteration + eval_batch_step: [0, 2000] + # if pretrained_model is saved in static mode, load_static_weights must set to True + cal_metric_during_train: True + pretrained_model: + checkpoints: + save_inference_dir: + use_visualdl: False + infer_img: doc/imgs_words/ch/word_1.jpg + # for data or label process + character_dict_path: ppocr/utils/ppocr_keys_v1.txt + character_type: ch + max_text_length: 25 + infer_mode: False + use_space_char: True + + +Optimizer: + name: Adam + beta1: 0.9 + beta2: 0.999 + lr: + name: Cosine + learning_rate: 0.001 + regularizer: + name: 'L2' + factor: 0.00004 + +Architecture: + model_type: rec + algorithm: CRNN + Transform: + Backbone: + name: ResNet + layers: 34 + Neck: + name: SequenceEncoder + encoder_type: rnn + hidden_size: 256 + Head: + name: CTCHead + fc_decay: 0.00004 + +Loss: + name: CTCLoss + +PostProcess: + name: CTCLabelDecode + +Metric: + name: RecMetric + main_indicator: acc + +Train: + dataset: + name: SimpleDataSet + data_dir: ./train_data/ + label_file_list: ["./train_data/train_list.txt"] + transforms: + - DecodeImage: # load image + img_mode: BGR + channel_first: False + - RecAug: + - CTCLabelEncode: # Class handling label + - RecResizeImg: + image_shape: [3, 32, 320] + - KeepKeys: + keep_keys: ['image', 'label', 'length'] # dataloader will return list in this order + loader: + shuffle: True + batch_size_per_card: 256 + drop_last: True + num_workers: 8 + +Eval: + dataset: + name: SimpleDataSet + data_dir: ./train_data/ + label_file_list: ["./train_data/val_list.txt"] + transforms: + - DecodeImage: # load image + img_mode: BGR + channel_first: False + - CTCLabelEncode: # Class handling label + - RecResizeImg: + image_shape: [3, 32, 320] + - KeepKeys: + keep_keys: ['image', 'label', 'length'] # dataloader will return list in this order + loader: + shuffle: False + drop_last: False + batch_size_per_card: 256 + num_workers: 8 diff --git a/configs/rec/ch_ppocr_v2.0/rec_chinese_lite_train_v2.0.yml b/configs/rec/ch_ppocr_v2.0/rec_chinese_lite_train_v2.0.yml new file mode 100644 index 0000000000..dc9d650f30 --- /dev/null +++ b/configs/rec/ch_ppocr_v2.0/rec_chinese_lite_train_v2.0.yml @@ -0,0 +1,102 @@ +Global: + use_gpu: true + epoch_num: 500 + log_smooth_window: 20 + print_batch_step: 10 + save_model_dir: ./output/rec_chinese_lite_v2.0 + save_epoch_step: 3 + # evaluation is run every 5000 iterations after the 4000th iteration + eval_batch_step: [0, 2000] + # if pretrained_model is saved in static mode, load_static_weights must set to True + cal_metric_during_train: True + pretrained_model: + checkpoints: + save_inference_dir: + use_visualdl: False + infer_img: doc/imgs_words/ch/word_1.jpg + # for data or label process + character_dict_path: ppocr/utils/ppocr_keys_v1.txt + character_type: ch + max_text_length: 25 + infer_mode: False + use_space_char: True + + +Optimizer: + name: Adam + beta1: 0.9 + beta2: 0.999 + lr: + name: Cosine + learning_rate: 0.001 + regularizer: + name: 'L2' + factor: 0.00001 + +Architecture: + model_type: rec + algorithm: CRNN + Transform: + Backbone: + name: MobileNetV3 + scale: 0.5 + model_name: small + small_stride: [1, 2, 2, 2] + Neck: + name: SequenceEncoder + encoder_type: rnn + hidden_size: 48 + Head: + name: CTCHead + fc_decay: 0.00001 + +Loss: + name: CTCLoss + +PostProcess: + name: CTCLabelDecode + +Metric: + name: RecMetric + main_indicator: acc + +Train: + dataset: + name: SimpleDataSet + data_dir: ./train_data/ + label_file_list: ["./train_data/train_list.txt"] + transforms: + - DecodeImage: # load image + img_mode: BGR + channel_first: False + - RecAug: + - CTCLabelEncode: # Class handling label + - RecResizeImg: + image_shape: [3, 32, 320] + - KeepKeys: + keep_keys: ['image', 'label', 'length'] # dataloader will return list in this order + loader: + shuffle: True + batch_size_per_card: 256 + drop_last: True + num_workers: 8 + +Eval: + dataset: + name: SimpleDataSet + data_dir: ./train_data + label_file_list: ["./train_data/val_list.txt"] + transforms: + - DecodeImage: # load image + img_mode: BGR + channel_first: False + - CTCLabelEncode: # Class handling label + - RecResizeImg: + image_shape: [3, 32, 320] + - KeepKeys: + keep_keys: ['image', 'label', 'length'] # dataloader will return list in this order + loader: + shuffle: False + drop_last: False + batch_size_per_card: 256 + num_workers: 8 diff --git a/configs/rec/multi_language/rec_en_number_lite_train.yml b/configs/rec/multi_language/rec_en_number_lite_train.yml new file mode 100644 index 0000000000..cee0512114 --- /dev/null +++ b/configs/rec/multi_language/rec_en_number_lite_train.yml @@ -0,0 +1,102 @@ +Global: + use_gpu: True + epoch_num: 500 + log_smooth_window: 20 + print_batch_step: 10 + save_model_dir: ./output/rec_en_number_lite + save_epoch_step: 3 + # evaluation is run every 5000 iterations after the 4000th iteration + eval_batch_step: [0, 2000] + # if pretrained_model is saved in static mode, load_static_weights must set to True + cal_metric_during_train: True + pretrained_model: + checkpoints: + save_inference_dir: + use_visualdl: False + infer_img: + # for data or label process + character_dict_path: ppocr/utils/dict/en_dict.txt + character_type: ch + max_text_length: 25 + infer_mode: False + use_space_char: False + + +Optimizer: + name: Adam + beta1: 0.9 + beta2: 0.999 + lr: + name: Cosine + learning_rate: 0.001 + regularizer: + name: 'L2' + factor: 0.00001 + +Architecture: + model_type: rec + algorithm: CRNN + Transform: + Backbone: + name: MobileNetV3 + scale: 0.5 + model_name: small + small_stride: [1, 2, 2, 2] + Neck: + name: SequenceEncoder + encoder_type: rnn + hidden_size: 48 + Head: + name: CTCHead + fc_decay: 0.00001 + +Loss: + name: CTCLoss + +PostProcess: + name: CTCLabelDecode + +Metric: + name: RecMetric + main_indicator: acc + +Train: + dataset: + name: SimpleDataSet + data_dir: ./train_data/ + label_file_list: ["./train_data/train_list.txt"] + transforms: + - DecodeImage: # load image + img_mode: BGR + channel_first: False + - RecAug: + - CTCLabelEncode: # Class handling label + - RecResizeImg: + image_shape: [3, 32, 320] + - KeepKeys: + keep_keys: ['image', 'label', 'length'] # dataloader will return list in this order + loader: + shuffle: True + batch_size_per_card: 256 + drop_last: True + num_workers: 8 + +Eval: + dataset: + name: SimpleDataSet + data_dir: ./train_data/ + label_file_list: ["./train_data/eval_list.txt"] + transforms: + - DecodeImage: # load image + img_mode: BGR + channel_first: False + - CTCLabelEncode: # Class handling label + - RecResizeImg: + image_shape: [3, 32, 320] + - KeepKeys: + keep_keys: ['image', 'label', 'length'] # dataloader will return list in this order + loader: + shuffle: False + drop_last: False + batch_size_per_card: 256 + num_workers: 8 diff --git a/configs/rec/multi_language/rec_french_lite_train.yml b/configs/rec/multi_language/rec_french_lite_train.yml new file mode 100644 index 0000000000..63378d38a0 --- /dev/null +++ b/configs/rec/multi_language/rec_french_lite_train.yml @@ -0,0 +1,102 @@ +Global: + use_gpu: True + epoch_num: 500 + log_smooth_window: 20 + print_batch_step: 10 + save_model_dir: ./output/rec_french_lite + save_epoch_step: 3 + # evaluation is run every 5000 iterations after the 4000th iteration + eval_batch_step: [0, 2000] + # if pretrained_model is saved in static mode, load_static_weights must set to True + cal_metric_during_train: True + pretrained_model: + checkpoints: + save_inference_dir: + use_visualdl: False + infer_img: + # for data or label process + character_dict_path: ppocr/utils/dict/french_dict.txt + character_type: french + max_text_length: 25 + infer_mode: False + use_space_char: False + + +Optimizer: + name: Adam + beta1: 0.9 + beta2: 0.999 + lr: + name: Cosine + learning_rate: 0.001 + regularizer: + name: 'L2' + factor: 0.00001 + +Architecture: + model_type: rec + algorithm: CRNN + Transform: + Backbone: + name: MobileNetV3 + scale: 0.5 + model_name: small + small_stride: [1, 2, 2, 2] + Neck: + name: SequenceEncoder + encoder_type: rnn + hidden_size: 48 + Head: + name: CTCHead + fc_decay: 0.00001 + +Loss: + name: CTCLoss + +PostProcess: + name: CTCLabelDecode + +Metric: + name: RecMetric + main_indicator: acc + +Train: + dataset: + name: SimpleDataSet + data_dir: ./train_data/ + label_file_list: ["./train_data/train_list.txt"] + transforms: + - DecodeImage: # load image + img_mode: BGR + channel_first: False + - RecAug: + - CTCLabelEncode: # Class handling label + - RecResizeImg: + image_shape: [3, 32, 320] + - KeepKeys: + keep_keys: ['image', 'label', 'length'] # dataloader will return list in this order + loader: + shuffle: True + batch_size_per_card: 256 + drop_last: True + num_workers: 8 + +Eval: + dataset: + name: SimpleDataSet + data_dir: ./train_data/ + label_file_list: ["./train_data/eval_list.txt"] + transforms: + - DecodeImage: # load image + img_mode: BGR + channel_first: False + - CTCLabelEncode: # Class handling label + - RecResizeImg: + image_shape: [3, 32, 320] + - KeepKeys: + keep_keys: ['image', 'label', 'length'] # dataloader will return list in this order + loader: + shuffle: False + drop_last: False + batch_size_per_card: 256 + num_workers: 8 diff --git a/configs/rec/multi_language/rec_german_lite_train.yml b/configs/rec/multi_language/rec_german_lite_train.yml new file mode 100644 index 0000000000..1651510c5e --- /dev/null +++ b/configs/rec/multi_language/rec_german_lite_train.yml @@ -0,0 +1,102 @@ +Global: + use_gpu: True + epoch_num: 500 + log_smooth_window: 20 + print_batch_step: 10 + save_model_dir: ./output/rec_german_lite + save_epoch_step: 3 + # evaluation is run every 5000 iterations after the 4000th iteration + eval_batch_step: [0, 2000] + # if pretrained_model is saved in static mode, load_static_weights must set to True + cal_metric_during_train: True + pretrained_model: + checkpoints: + save_inference_dir: + use_visualdl: False + infer_img: + # for data or label process + character_dict_path: ppocr/utils/dict/german_dict.txt + character_type: german + max_text_length: 25 + infer_mode: False + use_space_char: False + + +Optimizer: + name: Adam + beta1: 0.9 + beta2: 0.999 + lr: + name: Cosine + learning_rate: 0.001 + regularizer: + name: 'L2' + factor: 0.00001 + +Architecture: + model_type: rec + algorithm: CRNN + Transform: + Backbone: + name: MobileNetV3 + scale: 0.5 + model_name: small + small_stride: [1, 2, 2, 2] + Neck: + name: SequenceEncoder + encoder_type: rnn + hidden_size: 48 + Head: + name: CTCHead + fc_decay: 0.00001 + +Loss: + name: CTCLoss + +PostProcess: + name: CTCLabelDecode + +Metric: + name: RecMetric + main_indicator: acc + +Train: + dataset: + name: SimpleDataSet + data_dir: ./train_data/ + label_file_list: ["./train_data/train_list.txt"] + transforms: + - DecodeImage: # load image + img_mode: BGR + channel_first: False + - RecAug: + - CTCLabelEncode: # Class handling label + - RecResizeImg: + image_shape: [3, 32, 320] + - KeepKeys: + keep_keys: ['image', 'label', 'length'] # dataloader will return list in this order + loader: + shuffle: True + batch_size_per_card: 256 + drop_last: True + num_workers: 8 + +Eval: + dataset: + name: SimpleDataSet + data_dir: ./train_data/ + label_file_list: ["./train_data/eval_list.txt"] + transforms: + - DecodeImage: # load image + img_mode: BGR + channel_first: False + - CTCLabelEncode: # Class handling label + - RecResizeImg: + image_shape: [3, 32, 320] + - KeepKeys: + keep_keys: ['image', 'label', 'length'] # dataloader will return list in this order + loader: + shuffle: False + drop_last: False + batch_size_per_card: 256 + num_workers: 8 diff --git a/configs/rec/multi_language/rec_japan_lite_train.yml b/configs/rec/multi_language/rec_japan_lite_train.yml new file mode 100644 index 0000000000..bb47584edb --- /dev/null +++ b/configs/rec/multi_language/rec_japan_lite_train.yml @@ -0,0 +1,102 @@ +Global: + use_gpu: True + epoch_num: 500 + log_smooth_window: 20 + print_batch_step: 10 + save_model_dir: ./output/rec_japan_lite + save_epoch_step: 3 + # evaluation is run every 5000 iterations after the 4000th iteration + eval_batch_step: [0, 2000] + # if pretrained_model is saved in static mode, load_static_weights must set to True + cal_metric_during_train: True + pretrained_model: + checkpoints: + save_inference_dir: + use_visualdl: False + infer_img: + # for data or label process + character_dict_path: ppocr/utils/dict/japan_dict.txt + character_type: japan + max_text_length: 25 + infer_mode: False + use_space_char: False + + +Optimizer: + name: Adam + beta1: 0.9 + beta2: 0.999 + lr: + name: Cosine + learning_rate: 0.001 + regularizer: + name: 'L2' + factor: 0.00001 + +Architecture: + model_type: rec + algorithm: CRNN + Transform: + Backbone: + name: MobileNetV3 + scale: 0.5 + model_name: small + small_stride: [1, 2, 2, 2] + Neck: + name: SequenceEncoder + encoder_type: rnn + hidden_size: 48 + Head: + name: CTCHead + fc_decay: 0.00001 + +Loss: + name: CTCLoss + +PostProcess: + name: CTCLabelDecode + +Metric: + name: RecMetric + main_indicator: acc + +Train: + dataset: + name: SimpleDataSet + data_dir: ./train_data/ + label_file_list: ["./train_data/train_list.txt"] + transforms: + - DecodeImage: # load image + img_mode: BGR + channel_first: False + - RecAug: + - CTCLabelEncode: # Class handling label + - RecResizeImg: + image_shape: [3, 32, 320] + - KeepKeys: + keep_keys: ['image', 'label', 'length'] # dataloader will return list in this order + loader: + shuffle: True + batch_size_per_card: 256 + drop_last: True + num_workers: 8 + +Eval: + dataset: + name: SimpleDataSet + data_dir: ./train_data/ + label_file_list: ["./train_data/eval_list.txt"] + transforms: + - DecodeImage: # load image + img_mode: BGR + channel_first: False + - CTCLabelEncode: # Class handling label + - RecResizeImg: + image_shape: [3, 32, 320] + - KeepKeys: + keep_keys: ['image', 'label', 'length'] # dataloader will return list in this order + loader: + shuffle: False + drop_last: False + batch_size_per_card: 256 + num_workers: 8 diff --git a/configs/rec/multi_language/rec_korean_lite_train.yml b/configs/rec/multi_language/rec_korean_lite_train.yml new file mode 100644 index 0000000000..77f15524f7 --- /dev/null +++ b/configs/rec/multi_language/rec_korean_lite_train.yml @@ -0,0 +1,102 @@ +Global: + use_gpu: True + epoch_num: 500 + log_smooth_window: 20 + print_batch_step: 10 + save_model_dir: ./output/rec_korean_lite + save_epoch_step: 3 + # evaluation is run every 5000 iterations after the 4000th iteration + eval_batch_step: [0, 2000] + # if pretrained_model is saved in static mode, load_static_weights must set to True + cal_metric_during_train: True + pretrained_model: + checkpoints: + save_inference_dir: + use_visualdl: False + infer_img: + # for data or label process + character_dict_path: ppocr/utils/dict/korean_dict.txt + character_type: korean + max_text_length: 25 + infer_mode: False + use_space_char: False + + +Optimizer: + name: Adam + beta1: 0.9 + beta2: 0.999 + lr: + name: Cosine + learning_rate: 0.001 + regularizer: + name: 'L2' + factor: 0.00001 + +Architecture: + model_type: rec + algorithm: CRNN + Transform: + Backbone: + name: MobileNetV3 + scale: 0.5 + model_name: small + small_stride: [1, 2, 2, 2] + Neck: + name: SequenceEncoder + encoder_type: rnn + hidden_size: 48 + Head: + name: CTCHead + fc_decay: 0.00001 + +Loss: + name: CTCLoss + +PostProcess: + name: CTCLabelDecode + +Metric: + name: RecMetric + main_indicator: acc + +Train: + dataset: + name: SimpleDataSet + data_dir: ./train_data/ + label_file_list: ["./train_data/train_list.txt"] + transforms: + - DecodeImage: # load image + img_mode: BGR + channel_first: False + - RecAug: + - CTCLabelEncode: # Class handling label + - RecResizeImg: + image_shape: [3, 32, 320] + - KeepKeys: + keep_keys: ['image', 'label', 'length'] # dataloader will return list in this order + loader: + shuffle: True + batch_size_per_card: 256 + drop_last: True + num_workers: 8 + +Eval: + dataset: + name: SimpleDataSet + data_dir: ./train_data/ + label_file_list: ["./train_data/eval_list.txt"] + transforms: + - DecodeImage: # load image + img_mode: BGR + channel_first: False + - CTCLabelEncode: # Class handling label + - RecResizeImg: + image_shape: [3, 32, 320] + - KeepKeys: + keep_keys: ['image', 'label', 'length'] # dataloader will return list in this order + loader: + shuffle: False + drop_last: False + batch_size_per_card: 256 + num_workers: 8 diff --git a/configs/rec/rec_benchmark_reader.yml b/configs/rec/rec_benchmark_reader.yml deleted file mode 100755 index 524f2f68ba..0000000000 --- a/configs/rec/rec_benchmark_reader.yml +++ /dev/null @@ -1,12 +0,0 @@ -TrainReader: - reader_function: ppocr.data.rec.dataset_traversal,LMDBReader - num_workers: 8 - lmdb_sets_dir: ./train_data/data_lmdb_release/training/ - -EvalReader: - reader_function: ppocr.data.rec.dataset_traversal,LMDBReader - lmdb_sets_dir: ./train_data/data_lmdb_release/validation/ - -TestReader: - reader_function: ppocr.data.rec.dataset_traversal,LMDBReader - lmdb_sets_dir: ./train_data/data_lmdb_release/evaluation/ diff --git a/configs/rec/rec_chinese_common_train.yml b/configs/rec/rec_chinese_common_train.yml deleted file mode 100644 index 0d897459e0..0000000000 --- a/configs/rec/rec_chinese_common_train.yml +++ /dev/null @@ -1,45 +0,0 @@ -Global: - algorithm: CRNN - use_gpu: true - epoch_num: 3000 - log_smooth_window: 20 - print_batch_step: 10 - save_model_dir: ./output/rec_CRNN - save_epoch_step: 3 - eval_batch_step: 2000 - train_batch_size_per_card: 128 - test_batch_size_per_card: 128 - image_shape: [3, 32, 320] - max_text_length: 25 - character_type: ch - character_dict_path: ./ppocr/utils/ppocr_keys_v1.txt - loss_type: ctc - distort: false - use_space_char: false - reader_yml: ./configs/rec/rec_chinese_reader.yml - pretrain_weights: - checkpoints: - save_inference_dir: - infer_img: - -Architecture: - function: ppocr.modeling.architectures.rec_model,RecModel - -Backbone: - function: ppocr.modeling.backbones.rec_resnet_vd,ResNet - layers: 34 - -Head: - function: ppocr.modeling.heads.rec_ctc_head,CTCPredict - encoder_type: rnn - SeqRNN: - hidden_size: 256 - -Loss: - function: ppocr.modeling.losses.rec_ctc_loss,CTCLoss - -Optimizer: - function: ppocr.optimizer,AdamDecay - base_lr: 0.0005 - beta1: 0.9 - beta2: 0.999 diff --git a/configs/rec/rec_chinese_lite_train.yml b/configs/rec/rec_chinese_lite_train.yml deleted file mode 100755 index 95a39a3b4d..0000000000 --- a/configs/rec/rec_chinese_lite_train.yml +++ /dev/null @@ -1,46 +0,0 @@ -Global: - algorithm: CRNN - use_gpu: true - epoch_num: 3000 - log_smooth_window: 20 - print_batch_step: 10 - save_model_dir: ./output/rec_CRNN - save_epoch_step: 3 - eval_batch_step: 2000 - train_batch_size_per_card: 256 - test_batch_size_per_card: 256 - image_shape: [3, 32, 320] - max_text_length: 25 - character_type: ch - character_dict_path: ./ppocr/utils/ppocr_keys_v1.txt - loss_type: ctc - distort: false - use_space_char: false - reader_yml: ./configs/rec/rec_chinese_reader.yml - pretrain_weights: - checkpoints: - save_inference_dir: - infer_img: - -Architecture: - function: ppocr.modeling.architectures.rec_model,RecModel - -Backbone: - function: ppocr.modeling.backbones.rec_mobilenet_v3,MobileNetV3 - scale: 0.5 - model_name: small - -Head: - function: ppocr.modeling.heads.rec_ctc_head,CTCPredict - encoder_type: rnn - SeqRNN: - hidden_size: 48 - -Loss: - function: ppocr.modeling.losses.rec_ctc_loss,CTCLoss - -Optimizer: - function: ppocr.optimizer,AdamDecay - base_lr: 0.0005 - beta1: 0.9 - beta2: 0.999 diff --git a/configs/rec/rec_chinese_reader.yml b/configs/rec/rec_chinese_reader.yml deleted file mode 100755 index a44efd9911..0000000000 --- a/configs/rec/rec_chinese_reader.yml +++ /dev/null @@ -1,13 +0,0 @@ -TrainReader: - reader_function: ppocr.data.rec.dataset_traversal,SimpleReader - num_workers: 8 - img_set_dir: ./train_data - label_file_path: ./train_data/rec_gt_train.txt - -EvalReader: - reader_function: ppocr.data.rec.dataset_traversal,SimpleReader - img_set_dir: ./train_data - label_file_path: ./train_data/rec_gt_test.txt - -TestReader: - reader_function: ppocr.data.rec.dataset_traversal,SimpleReader diff --git a/configs/rec/rec_icdar15_reader.yml b/configs/rec/rec_icdar15_reader.yml deleted file mode 100755 index 322d5f25e0..0000000000 --- a/configs/rec/rec_icdar15_reader.yml +++ /dev/null @@ -1,13 +0,0 @@ -TrainReader: - reader_function: ppocr.data.rec.dataset_traversal,SimpleReader - num_workers: 8 - img_set_dir: ./train_data/ic15_data - label_file_path: ./train_data/ic15_data/rec_gt_train.txt - -EvalReader: - reader_function: ppocr.data.rec.dataset_traversal,SimpleReader - img_set_dir: ./train_data/ic15_data - label_file_path: ./train_data/ic15_data/rec_gt_test.txt - -TestReader: - reader_function: ppocr.data.rec.dataset_traversal,SimpleReader diff --git a/configs/rec/rec_icdar15_train.yml b/configs/rec/rec_icdar15_train.yml old mode 100755 new mode 100644 index 98a38e7477..3de0ce7741 --- a/configs/rec/rec_icdar15_train.yml +++ b/configs/rec/rec_icdar15_train.yml @@ -1,49 +1,98 @@ Global: - algorithm: CRNN use_gpu: true - epoch_num: 1000 + epoch_num: 72 log_smooth_window: 20 print_batch_step: 10 - save_model_dir: ./output/rec_CRNN - save_epoch_step: 300 - eval_batch_step: 500 - train_batch_size_per_card: 256 - test_batch_size_per_card: 256 - image_shape: [3, 32, 100] - max_text_length: 25 - character_type: en - loss_type: ctc - distort: true - debug: false - reader_yml: ./configs/rec/rec_icdar15_reader.yml - pretrain_weights: ./pretrain_models/rec_mv3_none_bilstm_ctc/best_accuracy + save_model_dir: ./output/rec/ic15/ + save_epoch_step: 3 + # evaluation is run every 2000 iterations + eval_batch_step: [0, 2000] + # if pretrained_model is saved in static mode, load_static_weights must set to True + cal_metric_during_train: True + pretrained_model: checkpoints: save_inference_dir: - infer_img: - -Architecture: - function: ppocr.modeling.architectures.rec_model,RecModel + use_visualdl: False + infer_img: doc/imgs_words_en/word_10.png + # for data or label process + character_dict_path: ppocr/utils/ic15_dict.txt + character_type: ch + max_text_length: 25 + infer_mode: False + use_space_char: False -Backbone: - function: ppocr.modeling.backbones.rec_mobilenet_v3,MobileNetV3 - scale: 0.5 - model_name: large +Optimizer: + name: Adam + beta1: 0.9 + beta2: 0.999 + lr: + learning_rate: 0.0005 + regularizer: + name: 'L2' + factor: 0 -Head: - function: ppocr.modeling.heads.rec_ctc_head,CTCPredict - encoder_type: rnn - SeqRNN: +Architecture: + model_type: rec + algorithm: CRNN + Transform: + Backbone: + name: MobileNetV3 + scale: 0.5 + model_name: large + Neck: + name: SequenceEncoder + encoder_type: rnn hidden_size: 96 - + Head: + name: CTCHead + fc_decay: 0 + Loss: - function: ppocr.modeling.losses.rec_ctc_loss,CTCLoss + name: CTCLoss -Optimizer: - function: ppocr.optimizer,AdamDecay - base_lr: 0.0005 - beta1: 0.9 - beta2: 0.999 - decay: - function: cosine_decay - step_each_epoch: 20 - total_epoch: 1000 +PostProcess: + name: CTCLabelDecode + +Metric: + name: RecMetric + main_indicator: acc + +Train: + dataset: + name: SimpleDataSet + data_dir: ./train_data/ + label_file_list: ["./train_data/train_list.txt"] + transforms: + - DecodeImage: # load image + img_mode: BGR + channel_first: False + - CTCLabelEncode: # Class handling label + - RecResizeImg: + image_shape: [3, 32, 100] + - KeepKeys: + keep_keys: ['image', 'label', 'length'] # dataloader will return list in this order + loader: + shuffle: True + batch_size_per_card: 256 + drop_last: True + num_workers: 8 + +Eval: + dataset: + name: SimpleDataSet + data_dir: ./train_data/ + label_file_list: ["./train_data/train_list.txt"] + transforms: + - DecodeImage: # load image + img_mode: BGR + channel_first: False + - CTCLabelEncode: # Class handling label + - RecResizeImg: + image_shape: [3, 32, 100] + - KeepKeys: + keep_keys: ['image', 'label', 'length'] # dataloader will return list in this order + loader: + shuffle: False + drop_last: False + batch_size_per_card: 256 + num_workers: 4 diff --git a/configs/rec/rec_mv3_none_bilstm_ctc.yml b/configs/rec/rec_mv3_none_bilstm_ctc.yml old mode 100755 new mode 100644 index d2e096fb1c..38f1e8691e --- a/configs/rec/rec_mv3_none_bilstm_ctc.yml +++ b/configs/rec/rec_mv3_none_bilstm_ctc.yml @@ -1,43 +1,96 @@ Global: - algorithm: CRNN use_gpu: true epoch_num: 72 log_smooth_window: 20 print_batch_step: 10 - save_model_dir: output/rec_CRNN + save_model_dir: ./output/rec/mv3_none_bilstm_ctc/ save_epoch_step: 3 - eval_batch_step: 2000 - train_batch_size_per_card: 256 - test_batch_size_per_card: 256 - image_shape: [3, 32, 100] - max_text_length: 25 - character_type: en - loss_type: ctc - reader_yml: ./configs/rec/rec_benchmark_reader.yml - pretrain_weights: + # evaluation is run every 2000 iterations + eval_batch_step: [0, 2000] + # if pretrained_model is saved in static mode, load_static_weights must set to True + cal_metric_during_train: True + pretrained_model: checkpoints: save_inference_dir: - infer_img: - -Architecture: - function: ppocr.modeling.architectures.rec_model,RecModel - -Backbone: - function: ppocr.modeling.backbones.rec_mobilenet_v3,MobileNetV3 - scale: 0.5 - model_name: large - -Head: - function: ppocr.modeling.heads.rec_ctc_head,CTCPredict - encoder_type: rnn - SeqRNN: - hidden_size: 96 - -Loss: - function: ppocr.modeling.losses.rec_ctc_loss,CTCLoss + use_visualdl: False + infer_img: doc/imgs_words_en/word_10.png + # for data or label process + character_dict_path: + character_type: en + max_text_length: 25 + infer_mode: False + use_space_char: False Optimizer: - function: ppocr.optimizer,AdamDecay - base_lr: 0.001 + name: Adam beta1: 0.9 beta2: 0.999 + lr: + learning_rate: 0.0005 + regularizer: + name: 'L2' + factor: 0 + +Architecture: + model_type: rec + algorithm: CRNN + Transform: + Backbone: + name: MobileNetV3 + scale: 0.5 + model_name: large + Neck: + name: SequenceEncoder + encoder_type: rnn + hidden_size: 96 + Head: + name: CTCHead + fc_decay: 0 + +Loss: + name: CTCLoss + +PostProcess: + name: CTCLabelDecode + +Metric: + name: RecMetric + main_indicator: acc + +Train: + dataset: + name: LMDBDateSet + data_dir: ./train_data/data_lmdb_release/training/ + transforms: + - DecodeImage: # load image + img_mode: BGR + channel_first: False + - CTCLabelEncode: # Class handling label + - RecResizeImg: + image_shape: [3, 32, 100] + - KeepKeys: + keep_keys: ['image', 'label', 'length'] # dataloader will return list in this order + loader: + shuffle: False + batch_size_per_card: 256 + drop_last: True + num_workers: 8 + +Eval: + dataset: + name: LMDBDateSet + data_dir: ./train_data/data_lmdb_release/validation/ + transforms: + - DecodeImage: # load image + img_mode: BGR + channel_first: False + - CTCLabelEncode: # Class handling label + - RecResizeImg: + image_shape: [3, 32, 100] + - KeepKeys: + keep_keys: ['image', 'label', 'length'] # dataloader will return list in this order + loader: + shuffle: False + drop_last: False + batch_size_per_card: 256 + num_workers: 4 diff --git a/configs/rec/rec_mv3_none_none_ctc.yml b/configs/rec/rec_mv3_none_none_ctc.yml old mode 100755 new mode 100644 index ceec09ce6f..33079ad48c --- a/configs/rec/rec_mv3_none_none_ctc.yml +++ b/configs/rec/rec_mv3_none_none_ctc.yml @@ -1,41 +1,95 @@ Global: - algorithm: Rosetta - use_gpu: true + use_gpu: True epoch_num: 72 log_smooth_window: 20 print_batch_step: 10 - save_model_dir: output/rec_Rosetta + save_model_dir: ./output/rec/mv3_none_none_ctc/ save_epoch_step: 3 - eval_batch_step: 2000 - train_batch_size_per_card: 256 - test_batch_size_per_card: 256 - image_shape: [3, 32, 100] - max_text_length: 25 - character_type: en - loss_type: ctc - reader_yml: ./configs/rec/rec_benchmark_reader.yml - pretrain_weights: + # evaluation is run every 2000 iterations + eval_batch_step: [0, 2000] + # if pretrained_model is saved in static mode, load_static_weights must set to True + cal_metric_during_train: True + pretrained_model: checkpoints: save_inference_dir: - infer_img: + use_visualdl: False + infer_img: doc/imgs_words_en/word_10.png + # for data or label process + character_dict_path: + character_type: en + max_text_length: 25 + infer_mode: False + use_space_char: False -Architecture: - function: ppocr.modeling.architectures.rec_model,RecModel +Optimizer: + name: Adam + beta1: 0.9 + beta2: 0.999 + lr: + learning_rate: 0.0005 + regularizer: + name: 'L2' + factor: 0 -Backbone: - function: ppocr.modeling.backbones.rec_mobilenet_v3,MobileNetV3 - scale: 0.5 - model_name: large +Architecture: + model_type: rec + algorithm: Rosetta + Transform: + Backbone: + name: MobileNetV3 + scale: 0.5 + model_name: large + Neck: + name: SequenceEncoder + encoder_type: reshape + Head: + name: CTCHead + fc_decay: 0.0004 -Head: - function: ppocr.modeling.heads.rec_ctc_head,CTCPredict - encoder_type: reshape - Loss: - function: ppocr.modeling.losses.rec_ctc_loss,CTCLoss + name: CTCLoss -Optimizer: - function: ppocr.optimizer,AdamDecay - base_lr: 0.001 - beta1: 0.9 - beta2: 0.999 +PostProcess: + name: CTCLabelDecode + +Metric: + name: RecMetric + main_indicator: acc + +Train: + dataset: + name: LMDBDateSet + data_dir: ./train_data/data_lmdb_release/training/ + transforms: + - DecodeImage: # load image + img_mode: BGR + channel_first: False + - CTCLabelEncode: # Class handling label + - RecResizeImg: + image_shape: [3, 32, 100] + - KeepKeys: + keep_keys: ['image', 'label', 'length'] # dataloader will return list in this order + loader: + shuffle: False + batch_size_per_card: 256 + drop_last: True + num_workers: 8 + +Eval: + dataset: + name: LMDBDateSet + data_dir: ./train_data/data_lmdb_release/validation/ + transforms: + - DecodeImage: # load image + img_mode: BGR + channel_first: False + - CTCLabelEncode: # Class handling label + - RecResizeImg: + image_shape: [3, 32, 100] + - KeepKeys: + keep_keys: ['image', 'label', 'length'] # dataloader will return list in this order + loader: + shuffle: False + drop_last: False + batch_size_per_card: 256 + num_workers: 8 diff --git a/configs/rec/rec_mv3_tps_bilstm_attn.yml b/configs/rec/rec_mv3_tps_bilstm_attn.yml deleted file mode 100755 index 7fc4f67994..0000000000 --- a/configs/rec/rec_mv3_tps_bilstm_attn.yml +++ /dev/null @@ -1,54 +0,0 @@ -Global: - algorithm: RARE - use_gpu: true - epoch_num: 72 - log_smooth_window: 20 - print_batch_step: 10 - save_model_dir: output/rec_RARE - save_epoch_step: 3 - eval_batch_step: 2000 - train_batch_size_per_card: 256 - test_batch_size_per_card: 256 - image_shape: [3, 32, 100] - max_text_length: 25 - character_type: en - loss_type: attention - tps: true - reader_yml: ./configs/rec/rec_benchmark_reader.yml - pretrain_weights: - checkpoints: - save_inference_dir: - infer_img: - - -Architecture: - function: ppocr.modeling.architectures.rec_model,RecModel - -TPS: - function: ppocr.modeling.stns.tps,TPS - num_fiducial: 20 - loc_lr: 0.1 - model_name: small - -Backbone: - function: ppocr.modeling.backbones.rec_mobilenet_v3,MobileNetV3 - scale: 0.5 - model_name: large - -Head: - function: ppocr.modeling.heads.rec_attention_head,AttentionPredict - encoder_type: rnn - SeqRNN: - hidden_size: 96 - Attention: - decoder_size: 96 - word_vector_dim: 96 - -Loss: - function: ppocr.modeling.losses.rec_attention_loss,AttentionLoss - -Optimizer: - function: ppocr.optimizer,AdamDecay - base_lr: 0.001 - beta1: 0.9 - beta2: 0.999 diff --git a/configs/rec/rec_mv3_tps_bilstm_ctc.yml b/configs/rec/rec_mv3_tps_bilstm_ctc.yml old mode 100755 new mode 100644 index 4b9660bcde..08f68939d4 --- a/configs/rec/rec_mv3_tps_bilstm_ctc.yml +++ b/configs/rec/rec_mv3_tps_bilstm_ctc.yml @@ -1,51 +1,100 @@ Global: - algorithm: STARNet use_gpu: true epoch_num: 72 log_smooth_window: 20 print_batch_step: 10 - save_model_dir: output/rec_STARNet + save_model_dir: ./output/rec/mv3_tps_bilstm_ctc/ save_epoch_step: 3 - eval_batch_step: 2000 - train_batch_size_per_card: 256 - test_batch_size_per_card: 256 - image_shape: [3, 32, 100] - max_text_length: 25 - character_type: en - loss_type: ctc - tps: true - reader_yml: ./configs/rec/rec_benchmark_reader.yml - pretrain_weights: + # evaluation is run every 2000 iterations + eval_batch_step: [0, 2000] + # if pretrained_model is saved in static mode, load_static_weights must set to True + cal_metric_during_train: True + pretrained_model: checkpoints: save_inference_dir: - infer_img: + use_visualdl: False + infer_img: doc/imgs_words_en/word_10.png + # for data or label process + character_dict_path: + character_type: en + max_text_length: 25 + infer_mode: False + use_space_char: False - -Architecture: - function: ppocr.modeling.architectures.rec_model,RecModel +Optimizer: + name: Adam + beta1: 0.9 + beta2: 0.999 + lr: + learning_rate: 0.0005 + regularizer: + name: 'L2' + factor: 0 -TPS: - function: ppocr.modeling.stns.tps,TPS - num_fiducial: 20 - loc_lr: 0.1 - model_name: small - -Backbone: - function: ppocr.modeling.backbones.rec_mobilenet_v3,MobileNetV3 - scale: 0.5 - model_name: large - -Head: - function: ppocr.modeling.heads.rec_ctc_head,CTCPredict - encoder_type: rnn - SeqRNN: +Architecture: + model_type: rec + algorithm: STARNet + Transform: + name: TPS + num_fiducial: 20 + loc_lr: 0.1 + model_name: small + Backbone: + name: MobileNetV3 + scale: 0.5 + model_name: large + Neck: + name: SequenceEncoder + encoder_type: rnn hidden_size: 96 - + Head: + name: CTCHead + fc_decay: 0.0004 + Loss: - function: ppocr.modeling.losses.rec_ctc_loss,CTCLoss + name: CTCLoss -Optimizer: - function: ppocr.optimizer,AdamDecay - base_lr: 0.001 - beta1: 0.9 - beta2: 0.999 +PostProcess: + name: CTCLabelDecode + +Metric: + name: RecMetric + main_indicator: acc + +Train: + dataset: + name: LMDBDateSet + data_dir: ./train_data/data_lmdb_release/training/ + transforms: + - DecodeImage: # load image + img_mode: BGR + channel_first: False + - CTCLabelEncode: # Class handling label + - RecResizeImg: + image_shape: [3, 32, 100] + - KeepKeys: + keep_keys: ['image', 'label', 'length'] # dataloader will return list in this order + loader: + shuffle: False + batch_size_per_card: 256 + drop_last: True + num_workers: 8 + +Eval: + dataset: + name: LMDBDateSet + data_dir: ./train_data/data_lmdb_release/validation/ + transforms: + - DecodeImage: # load image + img_mode: BGR + channel_first: False + - CTCLabelEncode: # Class handling label + - RecResizeImg: + image_shape: [3, 32, 100] + - KeepKeys: + keep_keys: ['image', 'label', 'length'] # dataloader will return list in this order + loader: + shuffle: False + drop_last: False + batch_size_per_card: 256 + num_workers: 4 diff --git a/configs/rec/rec_r34_vd_none_bilstm_ctc.yml b/configs/rec/rec_r34_vd_none_bilstm_ctc.yml old mode 100755 new mode 100644 index b71e8feae7..4ad2ff89ef --- a/configs/rec/rec_r34_vd_none_bilstm_ctc.yml +++ b/configs/rec/rec_r34_vd_none_bilstm_ctc.yml @@ -1,43 +1,95 @@ Global: - algorithm: CRNN use_gpu: true epoch_num: 72 log_smooth_window: 20 print_batch_step: 10 - save_model_dir: output/rec_CRNN + save_model_dir: ./output/rec/r34_vd_none_bilstm_ctc/ save_epoch_step: 3 - eval_batch_step: 2000 - train_batch_size_per_card: 256 - test_batch_size_per_card: 256 - image_shape: [3, 32, 100] - max_text_length: 25 - character_type: en - loss_type: ctc - reader_yml: ./configs/rec/rec_benchmark_reader.yml - pretrain_weights: + # evaluation is run every 2000 iterations + eval_batch_step: [0, 2000] + # if pretrained_model is saved in static mode, load_static_weights must set to True + cal_metric_during_train: True + pretrained_model: checkpoints: save_inference_dir: - infer_img: + use_visualdl: False + infer_img: doc/imgs_words_en/word_10.png + # for data or label process + character_dict_path: + character_type: en + max_text_length: 25 + infer_mode: False + use_space_char: False +Optimizer: + name: Adam + beta1: 0.9 + beta2: 0.999 + lr: + learning_rate: 0.0005 + regularizer: + name: 'L2' + factor: 0 Architecture: - function: ppocr.modeling.architectures.rec_model,RecModel - -Backbone: - function: ppocr.modeling.backbones.rec_resnet_vd,ResNet - layers: 34 - -Head: - function: ppocr.modeling.heads.rec_ctc_head,CTCPredict - encoder_type: rnn - SeqRNN: + model_type: rec + algorithm: CRNN + Transform: + Backbone: + name: ResNet + layers: 34 + Neck: + name: SequenceEncoder + encoder_type: rnn hidden_size: 256 - + Head: + name: CTCHead + fc_decay: 0 + Loss: - function: ppocr.modeling.losses.rec_ctc_loss,CTCLoss + name: CTCLoss -Optimizer: - function: ppocr.optimizer,AdamDecay - base_lr: 0.001 - beta1: 0.9 - beta2: 0.999 +PostProcess: + name: CTCLabelDecode + +Metric: + name: RecMetric + main_indicator: acc + +Train: + dataset: + name: LMDBDateSet + data_dir: ./train_data/data_lmdb_release/training/ + transforms: + - DecodeImage: # load image + img_mode: BGR + channel_first: False + - CTCLabelEncode: # Class handling label + - RecResizeImg: + image_shape: [3, 32, 100] + - KeepKeys: + keep_keys: ['image', 'label', 'length'] # dataloader will return list in this order + loader: + shuffle: True + batch_size_per_card: 256 + drop_last: True + num_workers: 8 + +Eval: + dataset: + name: LMDBDateSet + data_dir: ./train_data/data_lmdb_release/validation/ + transforms: + - DecodeImage: # load image + img_mode: BGR + channel_first: False + - CTCLabelEncode: # Class handling label + - RecResizeImg: + image_shape: [3, 32, 100] + - KeepKeys: + keep_keys: ['image', 'label', 'length'] # dataloader will return list in this order + loader: + shuffle: False + drop_last: False + batch_size_per_card: 256 + num_workers: 4 diff --git a/configs/rec/rec_r34_vd_none_none_ctc.yml b/configs/rec/rec_r34_vd_none_none_ctc.yml old mode 100755 new mode 100644 index d9c9458d6d..9c1eeb304f --- a/configs/rec/rec_r34_vd_none_none_ctc.yml +++ b/configs/rec/rec_r34_vd_none_none_ctc.yml @@ -1,40 +1,93 @@ Global: - algorithm: Rosetta use_gpu: true epoch_num: 72 log_smooth_window: 20 print_batch_step: 10 - save_model_dir: output/rec_Rosetta + save_model_dir: ./output/rec/r34_vd_none_none_ctc/ save_epoch_step: 3 - eval_batch_step: 2000 - train_batch_size_per_card: 256 - test_batch_size_per_card: 256 - image_shape: [3, 32, 100] - max_text_length: 25 - character_type: en - loss_type: ctc - reader_yml: ./configs/rec/rec_benchmark_reader.yml - pretrain_weights: + # evaluation is run every 2000 iterations + eval_batch_step: [0, 2000] + # if pretrained_model is saved in static mode, load_static_weights must set to True + cal_metric_during_train: True + pretrained_model: checkpoints: save_inference_dir: - infer_img: - -Architecture: - function: ppocr.modeling.architectures.rec_model,RecModel - -Backbone: - function: ppocr.modeling.backbones.rec_resnet_vd,ResNet - layers: 34 - -Head: - function: ppocr.modeling.heads.rec_ctc_head,CTCPredict - encoder_type: reshape - -Loss: - function: ppocr.modeling.losses.rec_ctc_loss,CTCLoss + use_visualdl: False + infer_img: doc/imgs_words_en/word_10.png + # for data or label process + character_dict_path: + character_type: en + max_text_length: 25 + infer_mode: False + use_space_char: False Optimizer: - function: ppocr.optimizer,AdamDecay - base_lr: 0.001 + name: Adam beta1: 0.9 beta2: 0.999 + lr: + learning_rate: 0.0005 + regularizer: + name: 'L2' + factor: 0 + +Architecture: + model_type: rec + algorithm: Rosetta + Backbone: + name: ResNet + layers: 34 + Neck: + name: SequenceEncoder + encoder_type: reshape + Head: + name: CTCHead + fc_decay: 0.0004 + +Loss: + name: CTCLoss + +PostProcess: + name: CTCLabelDecode + +Metric: + name: RecMetric + main_indicator: acc + +Train: + dataset: + name: LMDBDateSet + data_dir: ./train_data/data_lmdb_release/training/ + transforms: + - DecodeImage: # load image + img_mode: BGR + channel_first: False + - CTCLabelEncode: # Class handling label + - RecResizeImg: + image_shape: [3, 32, 100] + - KeepKeys: + keep_keys: ['image', 'label', 'length'] # dataloader will return list in this order + loader: + shuffle: True + batch_size_per_card: 256 + drop_last: True + num_workers: 8 + +Eval: + dataset: + name: LMDBDateSet + data_dir: ./train_data/data_lmdb_release/validation/ + transforms: + - DecodeImage: # load image + img_mode: BGR + channel_first: False + - CTCLabelEncode: # Class handling label + - RecResizeImg: + image_shape: [3, 32, 100] + - KeepKeys: + keep_keys: ['image', 'label', 'length'] # dataloader will return list in this order + loader: + shuffle: False + drop_last: False + batch_size_per_card: 256 + num_workers: 4 diff --git a/configs/rec/rec_r34_vd_tps_bilstm_attn.yml b/configs/rec/rec_r34_vd_tps_bilstm_attn.yml deleted file mode 100755 index dfcd97fad6..0000000000 --- a/configs/rec/rec_r34_vd_tps_bilstm_attn.yml +++ /dev/null @@ -1,53 +0,0 @@ -Global: - algorithm: RARE - use_gpu: true - epoch_num: 72 - log_smooth_window: 20 - print_batch_step: 10 - save_model_dir: output/rec_RARE - save_epoch_step: 3 - eval_batch_step: 2000 - train_batch_size_per_card: 256 - test_batch_size_per_card: 256 - image_shape: [3, 32, 100] - max_text_length: 25 - character_type: en - loss_type: attention - tps: true - reader_yml: ./configs/rec/rec_benchmark_reader.yml - pretrain_weights: - checkpoints: - save_inference_dir: - infer_img: - - -Architecture: - function: ppocr.modeling.architectures.rec_model,RecModel - -TPS: - function: ppocr.modeling.stns.tps,TPS - num_fiducial: 20 - loc_lr: 0.1 - model_name: large - -Backbone: - function: ppocr.modeling.backbones.rec_resnet_vd,ResNet - layers: 34 - -Head: - function: ppocr.modeling.heads.rec_attention_head,AttentionPredict - encoder_type: rnn - SeqRNN: - hidden_size: 256 - Attention: - decoder_size: 128 - word_vector_dim: 128 - -Loss: - function: ppocr.modeling.losses.rec_attention_loss,AttentionLoss - -Optimizer: - function: ppocr.optimizer,AdamDecay - base_lr: 0.001 - beta1: 0.9 - beta2: 0.999 diff --git a/configs/rec/rec_r34_vd_tps_bilstm_ctc.yml b/configs/rec/rec_r34_vd_tps_bilstm_ctc.yml old mode 100755 new mode 100644 index 574a088cc0..aeded4926a --- a/configs/rec/rec_r34_vd_tps_bilstm_ctc.yml +++ b/configs/rec/rec_r34_vd_tps_bilstm_ctc.yml @@ -1,50 +1,99 @@ Global: - algorithm: STARNet use_gpu: true epoch_num: 72 log_smooth_window: 20 print_batch_step: 10 - save_model_dir: output/rec_STARNet + save_model_dir: ./output/rec/r34_vd_tps_bilstm_ctc/ save_epoch_step: 3 - eval_batch_step: 2000 - train_batch_size_per_card: 256 - test_batch_size_per_card: 256 - image_shape: [3, 32, 100] - max_text_length: 25 - character_type: en - loss_type: ctc - tps: true - reader_yml: ./configs/rec/rec_benchmark_reader.yml - pretrain_weights: + # evaluation is run every 2000 iterations + eval_batch_step: [0, 2000] + # if pretrained_model is saved in static mode, load_static_weights must set to True + cal_metric_during_train: True + pretrained_model: checkpoints: save_inference_dir: - infer_img: + use_visualdl: False + infer_img: doc/imgs_words_en/word_10.png + # for data or label process + character_dict_path: + character_type: en + max_text_length: 25 + infer_mode: False + use_space_char: False +Optimizer: + name: Adam + beta1: 0.9 + beta2: 0.999 + lr: + learning_rate: 0.0005 + regularizer: + name: 'L2' + factor: 0 Architecture: - function: ppocr.modeling.architectures.rec_model,RecModel - -TPS: - function: ppocr.modeling.stns.tps,TPS - num_fiducial: 20 - loc_lr: 0.1 - model_name: large - -Backbone: - function: ppocr.modeling.backbones.rec_resnet_vd,ResNet - layers: 34 - -Head: - function: ppocr.modeling.heads.rec_ctc_head,CTCPredict - encoder_type: rnn - SeqRNN: + model_type: rec + algorithm: STARNet + Transform: + name: TPS + num_fiducial: 20 + loc_lr: 0.1 + model_name: small + Backbone: + name: ResNet + layers: 34 + Neck: + name: SequenceEncoder + encoder_type: rnn hidden_size: 256 - + Head: + name: CTCHead + fc_decay: 0 + Loss: - function: ppocr.modeling.losses.rec_ctc_loss,CTCLoss + name: CTCLoss -Optimizer: - function: ppocr.optimizer,AdamDecay - base_lr: 0.001 - beta1: 0.9 - beta2: 0.999 +PostProcess: + name: CTCLabelDecode + +Metric: + name: RecMetric + main_indicator: acc + +Train: + dataset: + name: LMDBDateSet + data_dir: ./train_data/data_lmdb_release/training/ + transforms: + - DecodeImage: # load image + img_mode: BGR + channel_first: False + - CTCLabelEncode: # Class handling label + - RecResizeImg: + image_shape: [3, 32, 100] + - KeepKeys: + keep_keys: ['image', 'label', 'length'] # dataloader will return list in this order + loader: + shuffle: True + batch_size_per_card: 256 + drop_last: True + num_workers: 8 + +Eval: + dataset: + name: LMDBDateSet + data_dir: ./train_data/data_lmdb_release/validation/ + transforms: + - DecodeImage: # load image + img_mode: BGR + channel_first: False + - CTCLabelEncode: # Class handling label + - RecResizeImg: + image_shape: [3, 32, 100] + - KeepKeys: + keep_keys: ['image', 'label', 'length'] # dataloader will return list in this order + loader: + shuffle: False + drop_last: False + batch_size_per_card: 256 + num_workers: 4 diff --git a/configs/rec/rec_r50fpn_vd_none_srn.yml b/configs/rec/rec_r50fpn_vd_none_srn.yml deleted file mode 100755 index 30709e479f..0000000000 --- a/configs/rec/rec_r50fpn_vd_none_srn.yml +++ /dev/null @@ -1,49 +0,0 @@ -Global: - algorithm: SRN - use_gpu: true - epoch_num: 72 - log_smooth_window: 20 - print_batch_step: 10 - save_model_dir: output/rec_pvam_withrotate - save_epoch_step: 1 - eval_batch_step: 8000 - train_batch_size_per_card: 64 - test_batch_size_per_card: 1 - image_shape: [1, 64, 256] - max_text_length: 25 - character_type: en - loss_type: srn - num_heads: 8 - average_window: 0.15 - max_average_window: 15625 - min_average_window: 10000 - reader_yml: ./configs/rec/rec_benchmark_reader.yml - pretrain_weights: - checkpoints: - save_inference_dir: - infer_img: - -Architecture: - function: ppocr.modeling.architectures.rec_model,RecModel - -Backbone: - function: ppocr.modeling.backbones.rec_resnet_fpn,ResNet - layers: 50 - -Head: - function: ppocr.modeling.heads.rec_srn_all_head,SRNPredict - encoder_type: rnn - num_encoder_TUs: 2 - num_decoder_TUs: 4 - hidden_dims: 512 - SeqRNN: - hidden_size: 256 - -Loss: - function: ppocr.modeling.losses.rec_srn_loss,SRNLoss - -Optimizer: - function: ppocr.optimizer,AdamDecay - base_lr: 0.0001 - beta1: 0.9 - beta2: 0.999 diff --git a/deploy/android_demo/.gitignore b/deploy/android_demo/.gitignore deleted file mode 100644 index 93dcb29353..0000000000 --- a/deploy/android_demo/.gitignore +++ /dev/null @@ -1,9 +0,0 @@ -*.iml -.gradle -/local.properties -/.idea/* -.DS_Store -/build -/captures -.externalNativeBuild - diff --git a/deploy/android_demo/README.md b/deploy/android_demo/README.md deleted file mode 100644 index e35e757914..0000000000 --- a/deploy/android_demo/README.md +++ /dev/null @@ -1,19 +0,0 @@ -# 如何快速测试 -### 1. 安装最新版本的Android Studio -可以从https://developer.android.com/studio 下载。本Demo使用是4.0版本Android Studio编写。 - -### 2. 按照NDK 20 以上版本 -Demo测试的时候使用的是NDK 20b版本,20版本以上均可以支持编译成功。 - -如果您是初学者,可以用以下方式安装和测试NDK编译环境。 -点击 File -> New ->New Project, 新建 "Native C++" project - -### 3. 导入项目 -点击 File->New->Import Project..., 然后跟着Android Studio的引导导入 - - -# 获得更多支持 -前往[端计算模型生成平台EasyEdge](https://ai.baidu.com/easyedge/app/open_source_demo?referrerUrl=paddlelite),获得更多开发支持: - -- Demo APP:可使用手机扫码安装,方便手机端快速体验文字识别 -- SDK:模型被封装为适配不同芯片硬件和操作系统SDK,包括完善的接口,方便进行二次开发 diff --git a/deploy/android_demo/app/.gitignore b/deploy/android_demo/app/.gitignore deleted file mode 100644 index 796b96d1c4..0000000000 --- a/deploy/android_demo/app/.gitignore +++ /dev/null @@ -1 +0,0 @@ -/build diff --git a/deploy/android_demo/app/build.gradle b/deploy/android_demo/app/build.gradle deleted file mode 100644 index 5ecb11692c..0000000000 --- a/deploy/android_demo/app/build.gradle +++ /dev/null @@ -1,94 +0,0 @@ -import java.security.MessageDigest - -apply plugin: 'com.android.application' - -android { - compileSdkVersion 29 - defaultConfig { - applicationId "com.baidu.paddle.lite.demo.ocr" - minSdkVersion 23 - targetSdkVersion 29 - versionCode 1 - versionName "1.0" - testInstrumentationRunner "android.support.test.runner.AndroidJUnitRunner" - externalNativeBuild { - cmake { - cppFlags "-std=c++11 -frtti -fexceptions -Wno-format" - arguments '-DANDROID_PLATFORM=android-23', '-DANDROID_STL=c++_shared' ,"-DANDROID_ARM_NEON=TRUE" - } - } - ndk { - // abiFilters "arm64-v8a", "armeabi-v7a" - abiFilters "arm64-v8a", "armeabi-v7a" - ldLibs "jnigraphics" - } - } - buildTypes { - release { - minifyEnabled false - proguardFiles getDefaultProguardFile('proguard-android-optimize.txt'), 'proguard-rules.pro' - } - } - externalNativeBuild { - cmake { - path "src/main/cpp/CMakeLists.txt" - version "3.10.2" - } - } -} - -dependencies { - implementation fileTree(include: ['*.jar'], dir: 'libs') - implementation 'androidx.appcompat:appcompat:1.1.0' - implementation 'androidx.constraintlayout:constraintlayout:1.1.3' - testImplementation 'junit:junit:4.12' - androidTestImplementation 'com.android.support.test:runner:1.0.2' - androidTestImplementation 'com.android.support.test.espresso:espresso-core:3.0.2' -} - -def archives = [ - [ - 'src' : 'https://paddlelite-demo.bj.bcebos.com/libs/android/paddle_lite_libs_v2_6_1.tar.gz', - 'dest': 'PaddleLite' - ], - [ - 'src' : 'https://paddlelite-demo.bj.bcebos.com/libs/android/opencv-4.2.0-android-sdk.tar.gz', - 'dest': 'OpenCV' - ], - [ - 'src' : 'https://paddleocr.bj.bcebos.com/deploy/lite/ocr_v1_for_cpu.tar.gz', - 'dest' : 'src/main/assets/models/ocr_v1_for_cpu' - ] -] - -task downloadAndExtractArchives(type: DefaultTask) { - doFirst { - println "Downloading and extracting archives including libs and models" - } - doLast { - // Prepare cache folder for archives - String cachePath = "cache" - if (!file("${cachePath}").exists()) { - mkdir "${cachePath}" - } - archives.eachWithIndex { archive, index -> - MessageDigest messageDigest = MessageDigest.getInstance('MD5') - messageDigest.update(archive.src.bytes) - String cacheName = new BigInteger(1, messageDigest.digest()).toString(32) - // Download the target archive if not exists - boolean copyFiles = !file("${archive.dest}").exists() - if (!file("${cachePath}/${cacheName}.tar.gz").exists()) { - ant.get(src: archive.src, dest: file("${cachePath}/${cacheName}.tar.gz")) - copyFiles = true; // force to copy files from the latest archive files - } - // Extract the target archive if its dest path does not exists - if (copyFiles) { - copy { - from tarTree("${cachePath}/${cacheName}.tar.gz") - into "${archive.dest}" - } - } - } - } -} -preBuild.dependsOn downloadAndExtractArchives \ No newline at end of file diff --git a/deploy/android_demo/app/proguard-rules.pro b/deploy/android_demo/app/proguard-rules.pro deleted file mode 100644 index f1b424510d..0000000000 --- a/deploy/android_demo/app/proguard-rules.pro +++ /dev/null @@ -1,21 +0,0 @@ -# Add project specific ProGuard rules here. -# You can control the set of applied configuration files using the -# proguardFiles setting in build.gradle. -# -# For more details, see -# http://developer.android.com/guide/developing/tools/proguard.html - -# If your project uses WebView with JS, uncomment the following -# and specify the fully qualified class name to the JavaScript interface -# class: -#-keepclassmembers class fqcn.of.javascript.interface.for.webview { -# public *; -#} - -# Uncomment this to preserve the line number information for -# debugging stack traces. -#-keepattributes SourceFile,LineNumberTable - -# If you keep the line number information, uncomment this to -# hide the original source file name. -#-renamesourcefileattribute SourceFile diff --git a/deploy/android_demo/app/src/androidTest/java/com/baidu/paddle/lite/demo/ocr/ExampleInstrumentedTest.java b/deploy/android_demo/app/src/androidTest/java/com/baidu/paddle/lite/demo/ocr/ExampleInstrumentedTest.java deleted file mode 100644 index 77b179da46..0000000000 --- a/deploy/android_demo/app/src/androidTest/java/com/baidu/paddle/lite/demo/ocr/ExampleInstrumentedTest.java +++ /dev/null @@ -1,26 +0,0 @@ -package com.baidu.paddle.lite.demo.ocr; - -import android.content.Context; -import android.support.test.InstrumentationRegistry; -import android.support.test.runner.AndroidJUnit4; - -import org.junit.Test; -import org.junit.runner.RunWith; - -import static org.junit.Assert.*; - -/** - * Instrumented test, which will execute on an Android device. - * - * @see Testing documentation - */ -@RunWith(AndroidJUnit4.class) -public class ExampleInstrumentedTest { - @Test - public void useAppContext() { - // Context of the app under test. - Context appContext = InstrumentationRegistry.getTargetContext(); - - assertEquals("com.baidu.paddle.lite.demo", appContext.getPackageName()); - } -} diff --git a/deploy/android_demo/app/src/main/AndroidManifest.xml b/deploy/android_demo/app/src/main/AndroidManifest.xml deleted file mode 100644 index 54482b1dcc..0000000000 --- a/deploy/android_demo/app/src/main/AndroidManifest.xml +++ /dev/null @@ -1,39 +0,0 @@ - - - - - - - - - - - - - - - - - - - - - - - - \ No newline at end of file diff --git a/deploy/android_demo/app/src/main/assets/images/5.jpg b/deploy/android_demo/app/src/main/assets/images/5.jpg deleted file mode 100644 index 8517e125c5..0000000000 Binary files a/deploy/android_demo/app/src/main/assets/images/5.jpg and /dev/null differ diff --git a/deploy/android_demo/app/src/main/assets/labels/ppocr_keys_v1.txt b/deploy/android_demo/app/src/main/assets/labels/ppocr_keys_v1.txt deleted file mode 100644 index 84b885d835..0000000000 --- a/deploy/android_demo/app/src/main/assets/labels/ppocr_keys_v1.txt +++ /dev/null @@ -1,6623 +0,0 @@ -' -疗 -绚 -诚 -娇 -溜 -题 -贿 -者 -廖 -更 -纳 -加 -奉 -公 -一 -就 -汴 -计 -与 -路 -房 -原 -妇 -2 -0 -8 -- -7 -其 -> -: -] -, -, -骑 -刈 -全 -消 -昏 -傈 -安 -久 -钟 -嗅 -不 -影 -处 -驽 -蜿 -资 -关 -椤 -地 -瘸 -专 -问 -忖 -票 -嫉 -炎 -韵 -要 -月 -田 -节 -陂 -鄙 -捌 -备 -拳 -伺 -眼 -网 -盎 -大 -傍 -心 -东 -愉 -汇 -蹿 -科 -每 -业 -里 -航 -晏 -字 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documentation: https://d.android.com/studio/projects/add-native-code.html - -# Sets the minimum version of CMake required to build the native library. - -cmake_minimum_required(VERSION 3.4.1) - -# Creates and names a library, sets it as either STATIC or SHARED, and provides -# the relative paths to its source code. You can define multiple libraries, and -# CMake builds them for you. Gradle automatically packages shared libraries with -# your APK. - -set(PaddleLite_DIR "${CMAKE_CURRENT_SOURCE_DIR}/../../../PaddleLite") -include_directories(${PaddleLite_DIR}/cxx/include) - -set(OpenCV_DIR "${CMAKE_CURRENT_SOURCE_DIR}/../../../OpenCV/sdk/native/jni") -message(STATUS "opencv dir: ${OpenCV_DIR}") -find_package(OpenCV REQUIRED) -message(STATUS "OpenCV libraries: ${OpenCV_LIBS}") -include_directories(${OpenCV_INCLUDE_DIRS}) -aux_source_directory(. SOURCES) -set(CMAKE_CXX_FLAGS - "${CMAKE_CXX_FLAGS} -ffast-math -Ofast -Os" - ) -set(CMAKE_CXX_FLAGS - "${CMAKE_CXX_FLAGS} -fvisibility=hidden -fvisibility-inlines-hidden -fdata-sections -ffunction-sections" - ) -set(CMAKE_SHARED_LINKER_FLAGS - "${CMAKE_SHARED_LINKER_FLAGS} -Wl,--gc-sections -Wl,-z,nocopyreloc") - -add_library( - # Sets the name of the library. - Native - # Sets the library as a shared library. - SHARED - # Provides a relative path to your source file(s). - ${SOURCES}) - -find_library( - # Sets the name of the path variable. - log-lib - # Specifies the name of the NDK library that you want CMake to locate. - log) - -add_library( - # Sets the name of the library. - paddle_light_api_shared - # Sets the library as a shared library. - SHARED - # Provides a relative path to your source file(s). - IMPORTED) - -set_target_properties( - # Specifies the target library. - paddle_light_api_shared - # Specifies the parameter you want to define. - PROPERTIES - IMPORTED_LOCATION - ${PaddleLite_DIR}/cxx/libs/${ANDROID_ABI}/libpaddle_light_api_shared.so - # Provides the path to the library you want to import. -) - - -# Specifies libraries CMake should link to your target library. You can link -# multiple libraries, such as libraries you define in this build script, -# prebuilt third-party libraries, or system libraries. - -target_link_libraries( - # Specifies the target library. - Native - paddle_light_api_shared - ${OpenCV_LIBS} - GLESv2 - EGL - jnigraphics - ${log-lib} -) - -add_custom_command( - TARGET Native - POST_BUILD - COMMAND - ${CMAKE_COMMAND} -E copy - ${PaddleLite_DIR}/cxx/libs/${ANDROID_ABI}/libc++_shared.so - ${CMAKE_LIBRARY_OUTPUT_DIRECTORY}/libc++_shared.so) - -add_custom_command( - TARGET Native - POST_BUILD - COMMAND - ${CMAKE_COMMAND} -E copy - ${PaddleLite_DIR}/cxx/libs/${ANDROID_ABI}/libpaddle_light_api_shared.so - ${CMAKE_LIBRARY_OUTPUT_DIRECTORY}/libpaddle_light_api_shared.so) - -add_custom_command( - TARGET Native - POST_BUILD - COMMAND - ${CMAKE_COMMAND} -E copy - ${PaddleLite_DIR}/cxx/libs/${ANDROID_ABI}/libhiai.so - ${CMAKE_LIBRARY_OUTPUT_DIRECTORY}/libhiai.so) - -add_custom_command( - TARGET Native - POST_BUILD - COMMAND - ${CMAKE_COMMAND} -E copy - ${PaddleLite_DIR}/cxx/libs/${ANDROID_ABI}/libhiai_ir.so - ${CMAKE_LIBRARY_OUTPUT_DIRECTORY}/libhiai_ir.so) - -add_custom_command( - TARGET Native - POST_BUILD - COMMAND - ${CMAKE_COMMAND} -E copy - ${PaddleLite_DIR}/cxx/libs/${ANDROID_ABI}/libhiai_ir_build.so - ${CMAKE_LIBRARY_OUTPUT_DIRECTORY}/libhiai_ir_build.so) \ No newline at end of file diff --git a/deploy/android_demo/app/src/main/cpp/common.h b/deploy/android_demo/app/src/main/cpp/common.h deleted file mode 100644 index f3937e9192..0000000000 --- a/deploy/android_demo/app/src/main/cpp/common.h +++ /dev/null @@ -1,48 +0,0 @@ -// -// Created by fu on 4/25/18. -// - -#pragma once -#import -#import - -#ifdef __ANDROID__ - -#include - -#define LOG_TAG "OCR_NDK" - -#define LOGI(...) \ - __android_log_print(ANDROID_LOG_INFO, LOG_TAG, __VA_ARGS__) -#define LOGW(...) \ - __android_log_print(ANDROID_LOG_WARN, LOG_TAG, __VA_ARGS__) -#define LOGE(...) \ - __android_log_print(ANDROID_LOG_ERROR, LOG_TAG, __VA_ARGS__) -#else -#include -#define LOGI(format, ...) \ - fprintf(stdout, "[" LOG_TAG "]" format "\n", ##__VA_ARGS__) -#define LOGW(format, ...) \ - fprintf(stdout, "[" LOG_TAG "]" format "\n", ##__VA_ARGS__) -#define LOGE(format, ...) \ - fprintf(stderr, "[" LOG_TAG "]Error: " format "\n", ##__VA_ARGS__) -#endif - -enum RETURN_CODE { - RETURN_OK = 0 -}; - -enum NET_TYPE{ - NET_OCR = 900100, - NET_OCR_INTERNAL = 991008 -}; - - -template -inline T product(const std::vector &vec) { - if (vec.empty()){ - return 0; - } - return std::accumulate(vec.begin(), vec.end(), 1, std::multiplies()); -} - diff --git a/deploy/android_demo/app/src/main/cpp/native.cpp b/deploy/android_demo/app/src/main/cpp/native.cpp deleted file mode 100644 index 390c594deb..0000000000 --- a/deploy/android_demo/app/src/main/cpp/native.cpp +++ /dev/null @@ -1,115 +0,0 @@ -// -// Created by fujiayi on 2020/7/5. -// - -#include "native.h" -#include "ocr_ppredictor.h" -#include -#include -#include - -static paddle::lite_api::PowerMode str_to_cpu_mode(const std::string &cpu_mode); - -extern "C" -JNIEXPORT jlong JNICALL -Java_com_baidu_paddle_lite_demo_ocr_OCRPredictorNative_init(JNIEnv *env, jobject thiz, - jstring j_det_model_path, - jstring j_rec_model_path, - jint j_thread_num, - jstring j_cpu_mode) { - std::string det_model_path = jstring_to_cpp_string(env, j_det_model_path); - std::string rec_model_path = jstring_to_cpp_string(env, j_rec_model_path); - int thread_num = j_thread_num; - std::string cpu_mode = jstring_to_cpp_string(env, j_cpu_mode); - ppredictor::OCR_Config conf; - conf.thread_num = thread_num; - conf.mode = str_to_cpu_mode(cpu_mode); - ppredictor::OCR_PPredictor *orc_predictor = new ppredictor::OCR_PPredictor{conf}; - orc_predictor->init_from_file(det_model_path, rec_model_path); - return reinterpret_cast(orc_predictor); -} - -/** - * "LITE_POWER_HIGH" convert to paddle::lite_api::LITE_POWER_HIGH - * @param cpu_mode - * @return - */ -static paddle::lite_api::PowerMode str_to_cpu_mode(const std::string &cpu_mode) { - static std::map cpu_mode_map{ - {"LITE_POWER_HIGH", paddle::lite_api::LITE_POWER_HIGH}, - {"LITE_POWER_LOW", paddle::lite_api::LITE_POWER_HIGH}, - {"LITE_POWER_FULL", paddle::lite_api::LITE_POWER_FULL}, - {"LITE_POWER_NO_BIND", paddle::lite_api::LITE_POWER_NO_BIND}, - {"LITE_POWER_RAND_HIGH", paddle::lite_api::LITE_POWER_RAND_HIGH}, - {"LITE_POWER_RAND_LOW", paddle::lite_api::LITE_POWER_RAND_LOW} - }; - std::string upper_key; - std::transform(cpu_mode.cbegin(), cpu_mode.cend(), upper_key.begin(), ::toupper); - auto index = cpu_mode_map.find(upper_key); - if (index == cpu_mode_map.end()) { - LOGE("cpu_mode not found %s", upper_key.c_str()); - return paddle::lite_api::LITE_POWER_HIGH; - } else { - return index->second; - } - -} - -extern "C" -JNIEXPORT jfloatArray JNICALL -Java_com_baidu_paddle_lite_demo_ocr_OCRPredictorNative_forward(JNIEnv *env, jobject thiz, - jlong java_pointer, jfloatArray buf, - jfloatArray ddims, - jobject original_image) { - LOGI("begin to run native forward"); - if (java_pointer == 0) { - LOGE("JAVA pointer is NULL"); - return cpp_array_to_jfloatarray(env, nullptr, 0); - } - cv::Mat origin = bitmap_to_cv_mat(env, original_image); - if (origin.size == 0) { - LOGE("origin bitmap cannot convert to CV Mat"); - return cpp_array_to_jfloatarray(env, nullptr, 0); - } - ppredictor::OCR_PPredictor *ppredictor = (ppredictor::OCR_PPredictor *) java_pointer; - std::vector dims_float_arr = jfloatarray_to_float_vector(env, ddims); - std::vector dims_arr; - dims_arr.resize(dims_float_arr.size()); - std::copy(dims_float_arr.cbegin(), dims_float_arr.cend(), dims_arr.begin()); - - // 这里值有点大,就不调用jfloatarray_to_float_vector了 - int64_t buf_len = (int64_t) env->GetArrayLength(buf); - jfloat *buf_data = env->GetFloatArrayElements(buf, JNI_FALSE); - float *data = (jfloat *) buf_data; - std::vector results = ppredictor->infer_ocr(dims_arr, data, - buf_len, - NET_OCR, origin); - LOGI("infer_ocr finished with boxes %ld", results.size()); - // 这里将std::vector 序列化成 float数组,传输到java层再反序列化 - std::vector float_arr; - for (const ppredictor::OCRPredictResult &r :results) { - float_arr.push_back(r.points.size()); - float_arr.push_back(r.word_index.size()); - float_arr.push_back(r.score); - for (const std::vector &point : r.points) { - float_arr.push_back(point.at(0)); - float_arr.push_back(point.at(1)); - } - for (int index: r.word_index) { - float_arr.push_back(index); - } - } - return cpp_array_to_jfloatarray(env, float_arr.data(), float_arr.size()); -} - -extern "C" -JNIEXPORT void JNICALL -Java_com_baidu_paddle_lite_demo_ocr_OCRPredictorNative_release(JNIEnv *env, jobject thiz, - jlong java_pointer){ - if (java_pointer == 0) { - LOGE("JAVA pointer is NULL"); - return; - } - ppredictor::OCR_PPredictor *ppredictor = (ppredictor::OCR_PPredictor *) java_pointer; - delete ppredictor; -} \ No newline at end of file diff --git a/deploy/android_demo/app/src/main/cpp/native.h b/deploy/android_demo/app/src/main/cpp/native.h deleted file mode 100644 index 1ef6d94924..0000000000 --- a/deploy/android_demo/app/src/main/cpp/native.h +++ /dev/null @@ -1,138 +0,0 @@ -// -// Created by fujiayi on 2020/7/5. -// - -#pragma once - - -#include -#include -#include -#include -#include -#include "common.h" - -inline std::string jstring_to_cpp_string(JNIEnv *env, jstring jstr) { - // In java, a unicode char will be encoded using 2 bytes (utf16). - // so jstring will contain characters utf16. std::string in c++ is - // essentially a string of bytes, not characters, so if we want to - // pass jstring from JNI to c++, we have convert utf16 to bytes. - if (!jstr) { - return ""; - } - const jclass stringClass = env->GetObjectClass(jstr); - const jmethodID getBytes = - env->GetMethodID(stringClass, "getBytes", "(Ljava/lang/String;)[B"); - const jbyteArray stringJbytes = (jbyteArray) env->CallObjectMethod( - jstr, getBytes, env->NewStringUTF("UTF-8")); - - size_t length = (size_t) env->GetArrayLength(stringJbytes); - jbyte *pBytes = env->GetByteArrayElements(stringJbytes, NULL); - - std::string ret = std::string(reinterpret_cast(pBytes), length); - env->ReleaseByteArrayElements(stringJbytes, pBytes, JNI_ABORT); - - env->DeleteLocalRef(stringJbytes); - env->DeleteLocalRef(stringClass); - return ret; -} - -inline jstring cpp_string_to_jstring(JNIEnv *env, std::string str) { - auto *data = str.c_str(); - jclass strClass = env->FindClass("java/lang/String"); - jmethodID strClassInitMethodID = - env->GetMethodID(strClass, "", "([BLjava/lang/String;)V"); - - jbyteArray bytes = env->NewByteArray(strlen(data)); - env->SetByteArrayRegion(bytes, 0, strlen(data), - reinterpret_cast(data)); - - jstring encoding = env->NewStringUTF("UTF-8"); - jstring res = (jstring) ( - env->NewObject(strClass, strClassInitMethodID, bytes, encoding)); - - env->DeleteLocalRef(strClass); - env->DeleteLocalRef(encoding); - env->DeleteLocalRef(bytes); - - return res; -} - -inline jfloatArray cpp_array_to_jfloatarray(JNIEnv *env, const float *buf, - int64_t len) { - if (len == 0) { - return env->NewFloatArray(0); - } - jfloatArray result = env->NewFloatArray(len); - env->SetFloatArrayRegion(result, 0, len, buf); - return result; -} - -inline jintArray cpp_array_to_jintarray(JNIEnv *env, const int *buf, - int64_t len) { - jintArray result = env->NewIntArray(len); - env->SetIntArrayRegion(result, 0, len, buf); - return result; -} - -inline jbyteArray cpp_array_to_jbytearray(JNIEnv *env, const int8_t *buf, - int64_t len) { - jbyteArray result = env->NewByteArray(len); - env->SetByteArrayRegion(result, 0, len, buf); - return result; -} - -inline jlongArray int64_vector_to_jlongarray(JNIEnv *env, - const std::vector &vec) { - jlongArray result = env->NewLongArray(vec.size()); - jlong *buf = new jlong[vec.size()]; - for (size_t i = 0; i < vec.size(); ++i) { - buf[i] = (jlong) vec[i]; - } - env->SetLongArrayRegion(result, 0, vec.size(), buf); - delete[] buf; - return result; -} - -inline std::vector jlongarray_to_int64_vector(JNIEnv *env, - jlongArray data) { - int data_size = env->GetArrayLength(data); - jlong *data_ptr = env->GetLongArrayElements(data, nullptr); - std::vector data_vec(data_ptr, data_ptr + data_size); - env->ReleaseLongArrayElements(data, data_ptr, 0); - return data_vec; -} - -inline std::vector jfloatarray_to_float_vector(JNIEnv *env, - jfloatArray data) { - int data_size = env->GetArrayLength(data); - jfloat *data_ptr = env->GetFloatArrayElements(data, nullptr); - std::vector data_vec(data_ptr, data_ptr + data_size); - env->ReleaseFloatArrayElements(data, data_ptr, 0); - return data_vec; -} - -inline cv::Mat bitmap_to_cv_mat(JNIEnv *env, jobject bitmap) { - AndroidBitmapInfo info; - int result = AndroidBitmap_getInfo(env, bitmap, &info); - if (result != ANDROID_BITMAP_RESULT_SUCCESS) { - LOGE("AndroidBitmap_getInfo failed, result: %d", result); - return cv::Mat{}; - } - if (info.format != ANDROID_BITMAP_FORMAT_RGBA_8888) { - LOGE("Bitmap format is not RGBA_8888 !"); - return cv::Mat{}; - } - unsigned char *srcData = NULL; - AndroidBitmap_lockPixels(env, bitmap, (void **) &srcData); - cv::Mat mat = cv::Mat::zeros(info.height, info.width, CV_8UC4); - memcpy(mat.data, srcData, info.height * info.width * 4); - AndroidBitmap_unlockPixels(env, bitmap); - cv::cvtColor(mat, mat, cv::COLOR_RGBA2BGR); - /** - if (!cv::imwrite("/sdcard/1/copy.jpg", mat)){ - LOGE("Write image failed " ); - } - */ - return mat; -} diff --git a/deploy/android_demo/app/src/main/cpp/ocr_clipper.cpp b/deploy/android_demo/app/src/main/cpp/ocr_clipper.cpp deleted file mode 100644 index d5db347202..0000000000 --- a/deploy/android_demo/app/src/main/cpp/ocr_clipper.cpp +++ /dev/null @@ -1,4629 +0,0 @@ -/******************************************************************************* -* * -* Author : Angus Johnson * -* Version : 6.4.2 * -* Date : 27 February 2017 * -* Website : http://www.angusj.com * -* Copyright : Angus Johnson 2010-2017 * -* * -* License: * -* Use, modification & distribution is subject to Boost Software License Ver 1. * -* http://www.boost.org/LICENSE_1_0.txt * -* * -* Attributions: * -* The code in this library is an extension of Bala Vatti's clipping algorithm: * -* "A generic solution to polygon clipping" * -* Communications of the ACM, Vol 35, Issue 7 (July 1992) pp 56-63. * -* http://portal.acm.org/citation.cfm?id=129906 * -* * -* Computer graphics and geometric modeling: implementation and algorithms * -* By Max K. Agoston * -* Springer; 1 edition (January 4, 2005) * -* http://books.google.com/books?q=vatti+clipping+agoston * -* * -* See also: * -* "Polygon Offsetting by Computing Winding Numbers" * -* Paper no. DETC2005-85513 pp. 565-575 * -* ASME 2005 International Design Engineering Technical Conferences * -* and Computers and Information in Engineering Conference (IDETC/CIE2005) * -* September 24-28, 2005 , Long Beach, California, USA * -* http://www.me.berkeley.edu/~mcmains/pubs/DAC05OffsetPolygon.pdf * -* * -*******************************************************************************/ - -/******************************************************************************* -* * -* This is a translation of the Delphi Clipper library and the naming style * -* used has retained a Delphi flavour. * -* * -*******************************************************************************/ - -#include "ocr_clipper.hpp" -#include -#include -#include -#include -#include -#include -#include -#include - -namespace ClipperLib { - -static double const pi = 3.141592653589793238; -static double const two_pi = pi *2; -static double const def_arc_tolerance = 0.25; - -enum Direction { dRightToLeft, dLeftToRight }; - -static int const Unassigned = -1; //edge not currently 'owning' a solution -static int const Skip = -2; //edge that would otherwise close a path - -#define HORIZONTAL (-1.0E+40) -#define TOLERANCE (1.0e-20) -#define NEAR_ZERO(val) (((val) > -TOLERANCE) && ((val) < TOLERANCE)) - -struct TEdge { - IntPoint Bot; - IntPoint Curr; //current (updated for every new scanbeam) - IntPoint Top; - double Dx; - PolyType PolyTyp; - EdgeSide Side; //side only refers to current side of solution poly - int WindDelta; //1 or -1 depending on winding direction - int WindCnt; - int WindCnt2; //winding count of the opposite polytype - int OutIdx; - TEdge *Next; - TEdge *Prev; - TEdge *NextInLML; - TEdge *NextInAEL; - TEdge *PrevInAEL; - TEdge *NextInSEL; - TEdge *PrevInSEL; -}; - -struct IntersectNode { - TEdge *Edge1; - TEdge *Edge2; - IntPoint Pt; -}; - -struct LocalMinimum { - cInt Y; - TEdge *LeftBound; - TEdge *RightBound; -}; - -struct OutPt; - -//OutRec: contains a path in the clipping solution. Edges in the AEL will -//carry a pointer to an OutRec when they are part of the clipping solution. -struct OutRec { - int Idx; - bool IsHole; - bool IsOpen; - OutRec *FirstLeft; //see comments in clipper.pas - PolyNode *PolyNd; - OutPt *Pts; - OutPt *BottomPt; -}; - -struct OutPt { - int Idx; - IntPoint Pt; - OutPt *Next; - OutPt *Prev; -}; - -struct Join { - OutPt *OutPt1; - OutPt *OutPt2; - IntPoint OffPt; -}; - -struct LocMinSorter -{ - inline bool operator()(const LocalMinimum& locMin1, const LocalMinimum& locMin2) - { - return locMin2.Y < locMin1.Y; - } -}; - -//------------------------------------------------------------------------------ -//------------------------------------------------------------------------------ - -inline cInt Round(double val) -{ - if ((val < 0)) return static_cast(val - 0.5); - else return static_cast(val + 0.5); -} -//------------------------------------------------------------------------------ - -inline cInt Abs(cInt val) -{ - return val < 0 ? -val : val; -} - -//------------------------------------------------------------------------------ -// PolyTree methods ... -//------------------------------------------------------------------------------ - -void PolyTree::Clear() -{ - for (PolyNodes::size_type i = 0; i < AllNodes.size(); ++i) - delete AllNodes[i]; - AllNodes.resize(0); - Childs.resize(0); -} -//------------------------------------------------------------------------------ - -PolyNode* PolyTree::GetFirst() const -{ - if (!Childs.empty()) - return Childs[0]; - else - return 0; -} -//------------------------------------------------------------------------------ - -int PolyTree::Total() const -{ - int result = (int)AllNodes.size(); - //with negative offsets, ignore the hidden outer polygon ... - if (result > 0 && Childs[0] != AllNodes[0]) result--; - return result; -} - -//------------------------------------------------------------------------------ -// PolyNode methods ... -//------------------------------------------------------------------------------ - -PolyNode::PolyNode(): Parent(0), Index(0), m_IsOpen(false) -{ -} -//------------------------------------------------------------------------------ - -int PolyNode::ChildCount() const -{ - return (int)Childs.size(); -} -//------------------------------------------------------------------------------ - -void PolyNode::AddChild(PolyNode& child) -{ - unsigned cnt = (unsigned)Childs.size(); - Childs.push_back(&child); - child.Parent = this; - child.Index = cnt; -} -//------------------------------------------------------------------------------ - -PolyNode* PolyNode::GetNext() const -{ - if (!Childs.empty()) - return Childs[0]; - else - return GetNextSiblingUp(); -} -//------------------------------------------------------------------------------ - -PolyNode* PolyNode::GetNextSiblingUp() const -{ - if (!Parent) //protects against PolyTree.GetNextSiblingUp() - return 0; - else if (Index == Parent->Childs.size() - 1) - return Parent->GetNextSiblingUp(); - else - return Parent->Childs[Index + 1]; -} -//------------------------------------------------------------------------------ - -bool PolyNode::IsHole() const -{ - bool result = true; - PolyNode* node = Parent; - while (node) - { - result = !result; - node = node->Parent; - } - return result; -} -//------------------------------------------------------------------------------ - -bool PolyNode::IsOpen() const -{ - return m_IsOpen; -} -//------------------------------------------------------------------------------ - -#ifndef use_int32 - -//------------------------------------------------------------------------------ -// Int128 class (enables safe math on signed 64bit integers) -// eg Int128 val1((long64)9223372036854775807); //ie 2^63 -1 -// Int128 val2((long64)9223372036854775807); -// Int128 val3 = val1 * val2; -// val3.AsString => "85070591730234615847396907784232501249" (8.5e+37) -//------------------------------------------------------------------------------ - -class Int128 -{ - public: - ulong64 lo; - long64 hi; - - Int128(long64 _lo = 0) - { - lo = (ulong64)_lo; - if (_lo < 0) hi = -1; else hi = 0; - } - - - Int128(const Int128 &val): lo(val.lo), hi(val.hi){} - - Int128(const long64& _hi, const ulong64& _lo): lo(_lo), hi(_hi){} - - Int128& operator = (const long64 &val) - { - lo = (ulong64)val; - if (val < 0) hi = -1; else hi = 0; - return *this; - } - - bool operator == (const Int128 &val) const - {return (hi == val.hi && lo == val.lo);} - - bool operator != (const Int128 &val) const - { return !(*this == val);} - - bool operator > (const Int128 &val) const - { - if (hi != val.hi) - return hi > val.hi; - else - return lo > val.lo; - } - - bool operator < (const Int128 &val) const - { - if (hi != val.hi) - return hi < val.hi; - else - return lo < val.lo; - } - - bool operator >= (const Int128 &val) const - { return !(*this < val);} - - bool operator <= (const Int128 &val) const - { return !(*this > val);} - - Int128& operator += (const Int128 &rhs) - { - hi += rhs.hi; - lo += rhs.lo; - if (lo < rhs.lo) hi++; - return *this; - } - - Int128 operator + (const Int128 &rhs) const - { - Int128 result(*this); - result+= rhs; - return result; - } - - Int128& operator -= (const Int128 &rhs) - { - *this += -rhs; - return *this; - } - - Int128 operator - (const Int128 &rhs) const - { - Int128 result(*this); - result -= rhs; - return result; - } - - Int128 operator-() const //unary negation - { - if (lo == 0) - return Int128(-hi, 0); - else - return Int128(~hi, ~lo + 1); - } - - operator double() const - { - const double shift64 = 18446744073709551616.0; //2^64 - if (hi < 0) - { - if (lo == 0) return (double)hi * shift64; - else return -(double)(~lo + ~hi * shift64); - } - else - return (double)(lo + hi * shift64); - } - -}; -//------------------------------------------------------------------------------ - -Int128 Int128Mul (long64 lhs, long64 rhs) -{ - bool negate = (lhs < 0) != (rhs < 0); - - if (lhs < 0) lhs = -lhs; - ulong64 int1Hi = ulong64(lhs) >> 32; - ulong64 int1Lo = ulong64(lhs & 0xFFFFFFFF); - - if (rhs < 0) rhs = -rhs; - ulong64 int2Hi = ulong64(rhs) >> 32; - ulong64 int2Lo = ulong64(rhs & 0xFFFFFFFF); - - //nb: see comments in clipper.pas - ulong64 a = int1Hi * int2Hi; - ulong64 b = int1Lo * int2Lo; - ulong64 c = int1Hi * int2Lo + int1Lo * int2Hi; - - Int128 tmp; - tmp.hi = long64(a + (c >> 32)); - tmp.lo = long64(c << 32); - tmp.lo += long64(b); - if (tmp.lo < b) tmp.hi++; - if (negate) tmp = -tmp; - return tmp; -}; -#endif - -//------------------------------------------------------------------------------ -// Miscellaneous global functions -//------------------------------------------------------------------------------ - -bool Orientation(const Path &poly) -{ - return Area(poly) >= 0; -} -//------------------------------------------------------------------------------ - -double Area(const Path &poly) -{ - int size = (int)poly.size(); - if (size < 3) return 0; - - double a = 0; - for (int i = 0, j = size -1; i < size; ++i) - { - a += ((double)poly[j].X + poly[i].X) * ((double)poly[j].Y - poly[i].Y); - j = i; - } - return -a * 0.5; -} -//------------------------------------------------------------------------------ - -double Area(const OutPt *op) -{ - const OutPt *startOp = op; - if (!op) return 0; - double a = 0; - do { - a += (double)(op->Prev->Pt.X + op->Pt.X) * (double)(op->Prev->Pt.Y - op->Pt.Y); - op = op->Next; - } while (op != startOp); - return a * 0.5; -} -//------------------------------------------------------------------------------ - -double Area(const OutRec &outRec) -{ - return Area(outRec.Pts); -} -//------------------------------------------------------------------------------ - -bool PointIsVertex(const IntPoint &Pt, OutPt *pp) -{ - OutPt *pp2 = pp; - do - { - if (pp2->Pt == Pt) return true; - pp2 = pp2->Next; - } - while (pp2 != pp); - return false; -} -//------------------------------------------------------------------------------ - -//See "The Point in Polygon Problem for Arbitrary Polygons" by Hormann & Agathos -//http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.88.5498&rep=rep1&type=pdf -int PointInPolygon(const IntPoint &pt, const Path &path) -{ - //returns 0 if false, +1 if true, -1 if pt ON polygon boundary - int result = 0; - size_t cnt = path.size(); - if (cnt < 3) return 0; - IntPoint ip = path[0]; - for(size_t i = 1; i <= cnt; ++i) - { - IntPoint ipNext = (i == cnt ? path[0] : path[i]); - if (ipNext.Y == pt.Y) - { - if ((ipNext.X == pt.X) || (ip.Y == pt.Y && - ((ipNext.X > pt.X) == (ip.X < pt.X)))) return -1; - } - if ((ip.Y < pt.Y) != (ipNext.Y < pt.Y)) - { - if (ip.X >= pt.X) - { - if (ipNext.X > pt.X) result = 1 - result; - else - { - double d = (double)(ip.X - pt.X) * (ipNext.Y - pt.Y) - - (double)(ipNext.X - pt.X) * (ip.Y - pt.Y); - if (!d) return -1; - if ((d > 0) == (ipNext.Y > ip.Y)) result = 1 - result; - } - } else - { - if (ipNext.X > pt.X) - { - double d = (double)(ip.X - pt.X) * (ipNext.Y - pt.Y) - - (double)(ipNext.X - pt.X) * (ip.Y - pt.Y); - if (!d) return -1; - if ((d > 0) == (ipNext.Y > ip.Y)) result = 1 - result; - } - } - } - ip = ipNext; - } - return result; -} -//------------------------------------------------------------------------------ - -int PointInPolygon (const IntPoint &pt, OutPt *op) -{ - //returns 0 if false, +1 if true, -1 if pt ON polygon boundary - int result = 0; - OutPt* startOp = op; - for(;;) - { - if (op->Next->Pt.Y == pt.Y) - { - if ((op->Next->Pt.X == pt.X) || (op->Pt.Y == pt.Y && - ((op->Next->Pt.X > pt.X) == (op->Pt.X < pt.X)))) return -1; - } - if ((op->Pt.Y < pt.Y) != (op->Next->Pt.Y < pt.Y)) - { - if (op->Pt.X >= pt.X) - { - if (op->Next->Pt.X > pt.X) result = 1 - result; - else - { - double d = (double)(op->Pt.X - pt.X) * (op->Next->Pt.Y - pt.Y) - - (double)(op->Next->Pt.X - pt.X) * (op->Pt.Y - pt.Y); - if (!d) return -1; - if ((d > 0) == (op->Next->Pt.Y > op->Pt.Y)) result = 1 - result; - } - } else - { - if (op->Next->Pt.X > pt.X) - { - double d = (double)(op->Pt.X - pt.X) * (op->Next->Pt.Y - pt.Y) - - (double)(op->Next->Pt.X - pt.X) * (op->Pt.Y - pt.Y); - if (!d) return -1; - if ((d > 0) == (op->Next->Pt.Y > op->Pt.Y)) result = 1 - result; - } - } - } - op = op->Next; - if (startOp == op) break; - } - return result; -} -//------------------------------------------------------------------------------ - -bool Poly2ContainsPoly1(OutPt *OutPt1, OutPt *OutPt2) -{ - OutPt* op = OutPt1; - do - { - //nb: PointInPolygon returns 0 if false, +1 if true, -1 if pt on polygon - int res = PointInPolygon(op->Pt, OutPt2); - if (res >= 0) return res > 0; - op = op->Next; - } - while (op != OutPt1); - return true; -} -//---------------------------------------------------------------------- - -bool SlopesEqual(const TEdge &e1, const TEdge &e2, bool UseFullInt64Range) -{ -#ifndef use_int32 - if (UseFullInt64Range) - return Int128Mul(e1.Top.Y - e1.Bot.Y, e2.Top.X - e2.Bot.X) == - Int128Mul(e1.Top.X - e1.Bot.X, e2.Top.Y - e2.Bot.Y); - else -#endif - return (e1.Top.Y - e1.Bot.Y) * (e2.Top.X - e2.Bot.X) == - (e1.Top.X - e1.Bot.X) * (e2.Top.Y - e2.Bot.Y); -} -//------------------------------------------------------------------------------ - -bool SlopesEqual(const IntPoint pt1, const IntPoint pt2, - const IntPoint pt3, bool UseFullInt64Range) -{ -#ifndef use_int32 - if (UseFullInt64Range) - return Int128Mul(pt1.Y-pt2.Y, pt2.X-pt3.X) == Int128Mul(pt1.X-pt2.X, pt2.Y-pt3.Y); - else -#endif - return (pt1.Y-pt2.Y)*(pt2.X-pt3.X) == (pt1.X-pt2.X)*(pt2.Y-pt3.Y); -} -//------------------------------------------------------------------------------ - -bool SlopesEqual(const IntPoint pt1, const IntPoint pt2, - const IntPoint pt3, const IntPoint pt4, bool UseFullInt64Range) -{ -#ifndef use_int32 - if (UseFullInt64Range) - return Int128Mul(pt1.Y-pt2.Y, pt3.X-pt4.X) == Int128Mul(pt1.X-pt2.X, pt3.Y-pt4.Y); - else -#endif - return (pt1.Y-pt2.Y)*(pt3.X-pt4.X) == (pt1.X-pt2.X)*(pt3.Y-pt4.Y); -} -//------------------------------------------------------------------------------ - -inline bool IsHorizontal(TEdge &e) -{ - return e.Dx == HORIZONTAL; -} -//------------------------------------------------------------------------------ - -inline double GetDx(const IntPoint pt1, const IntPoint pt2) -{ - return (pt1.Y == pt2.Y) ? - HORIZONTAL : (double)(pt2.X - pt1.X) / (pt2.Y - pt1.Y); -} -//--------------------------------------------------------------------------- - -inline void SetDx(TEdge &e) -{ - cInt dy = (e.Top.Y - e.Bot.Y); - if (dy == 0) e.Dx = HORIZONTAL; - else e.Dx = (double)(e.Top.X - e.Bot.X) / dy; -} -//--------------------------------------------------------------------------- - -inline void SwapSides(TEdge &Edge1, TEdge &Edge2) -{ - EdgeSide Side = Edge1.Side; - Edge1.Side = Edge2.Side; - Edge2.Side = Side; -} -//------------------------------------------------------------------------------ - -inline void SwapPolyIndexes(TEdge &Edge1, TEdge &Edge2) -{ - int OutIdx = Edge1.OutIdx; - Edge1.OutIdx = Edge2.OutIdx; - Edge2.OutIdx = OutIdx; -} -//------------------------------------------------------------------------------ - -inline cInt TopX(TEdge &edge, const cInt currentY) -{ - return ( currentY == edge.Top.Y ) ? - edge.Top.X : edge.Bot.X + Round(edge.Dx *(currentY - edge.Bot.Y)); -} -//------------------------------------------------------------------------------ - -void IntersectPoint(TEdge &Edge1, TEdge &Edge2, IntPoint &ip) -{ -#ifdef use_xyz - ip.Z = 0; -#endif - - double b1, b2; - if (Edge1.Dx == Edge2.Dx) - { - ip.Y = Edge1.Curr.Y; - ip.X = TopX(Edge1, ip.Y); - return; - } - else if (Edge1.Dx == 0) - { - ip.X = Edge1.Bot.X; - if (IsHorizontal(Edge2)) - ip.Y = Edge2.Bot.Y; - else - { - b2 = Edge2.Bot.Y - (Edge2.Bot.X / Edge2.Dx); - ip.Y = Round(ip.X / Edge2.Dx + b2); - } - } - else if (Edge2.Dx == 0) - { - ip.X = Edge2.Bot.X; - if (IsHorizontal(Edge1)) - ip.Y = Edge1.Bot.Y; - else - { - b1 = Edge1.Bot.Y - (Edge1.Bot.X / Edge1.Dx); - ip.Y = Round(ip.X / Edge1.Dx + b1); - } - } - else - { - b1 = Edge1.Bot.X - Edge1.Bot.Y * Edge1.Dx; - b2 = Edge2.Bot.X - Edge2.Bot.Y * Edge2.Dx; - double q = (b2-b1) / (Edge1.Dx - Edge2.Dx); - ip.Y = Round(q); - if (std::fabs(Edge1.Dx) < std::fabs(Edge2.Dx)) - ip.X = Round(Edge1.Dx * q + b1); - else - ip.X = Round(Edge2.Dx * q + b2); - } - - if (ip.Y < Edge1.Top.Y || ip.Y < Edge2.Top.Y) - { - if (Edge1.Top.Y > Edge2.Top.Y) - ip.Y = Edge1.Top.Y; - else - ip.Y = Edge2.Top.Y; - if (std::fabs(Edge1.Dx) < std::fabs(Edge2.Dx)) - ip.X = TopX(Edge1, ip.Y); - else - ip.X = TopX(Edge2, ip.Y); - } - //finally, don't allow 'ip' to be BELOW curr.Y (ie bottom of scanbeam) ... - if (ip.Y > Edge1.Curr.Y) - { - ip.Y = Edge1.Curr.Y; - //use the more vertical edge to derive X ... - if (std::fabs(Edge1.Dx) > std::fabs(Edge2.Dx)) - ip.X = TopX(Edge2, ip.Y); else - ip.X = TopX(Edge1, ip.Y); - } -} -//------------------------------------------------------------------------------ - -void ReversePolyPtLinks(OutPt *pp) -{ - if (!pp) return; - OutPt *pp1, *pp2; - pp1 = pp; - do { - pp2 = pp1->Next; - pp1->Next = pp1->Prev; - pp1->Prev = pp2; - pp1 = pp2; - } while( pp1 != pp ); -} -//------------------------------------------------------------------------------ - -void DisposeOutPts(OutPt*& pp) -{ - if (pp == 0) return; - pp->Prev->Next = 0; - while( pp ) - { - OutPt *tmpPp = pp; - pp = pp->Next; - delete tmpPp; - } -} -//------------------------------------------------------------------------------ - -inline void InitEdge(TEdge* e, TEdge* eNext, TEdge* ePrev, const IntPoint& Pt) -{ - std::memset(e, 0, sizeof(TEdge)); - e->Next = eNext; - e->Prev = ePrev; - e->Curr = Pt; - e->OutIdx = Unassigned; -} -//------------------------------------------------------------------------------ - -void InitEdge2(TEdge& e, PolyType Pt) -{ - if (e.Curr.Y >= e.Next->Curr.Y) - { - e.Bot = e.Curr; - e.Top = e.Next->Curr; - } else - { - e.Top = e.Curr; - e.Bot = e.Next->Curr; - } - SetDx(e); - e.PolyTyp = Pt; -} -//------------------------------------------------------------------------------ - -TEdge* RemoveEdge(TEdge* e) -{ - //removes e from double_linked_list (but without removing from memory) - e->Prev->Next = e->Next; - e->Next->Prev = e->Prev; - TEdge* result = e->Next; - e->Prev = 0; //flag as removed (see ClipperBase.Clear) - return result; -} -//------------------------------------------------------------------------------ - -inline void ReverseHorizontal(TEdge &e) -{ - //swap horizontal edges' Top and Bottom x's so they follow the natural - //progression of the bounds - ie so their xbots will align with the - //adjoining lower edge. [Helpful in the ProcessHorizontal() method.] - std::swap(e.Top.X, e.Bot.X); -#ifdef use_xyz - std::swap(e.Top.Z, e.Bot.Z); -#endif -} -//------------------------------------------------------------------------------ - -void SwapPoints(IntPoint &pt1, IntPoint &pt2) -{ - IntPoint tmp = pt1; - pt1 = pt2; - pt2 = tmp; -} -//------------------------------------------------------------------------------ - -bool GetOverlapSegment(IntPoint pt1a, IntPoint pt1b, IntPoint pt2a, - IntPoint pt2b, IntPoint &pt1, IntPoint &pt2) -{ - //precondition: segments are Collinear. - if (Abs(pt1a.X - pt1b.X) > Abs(pt1a.Y - pt1b.Y)) - { - if (pt1a.X > pt1b.X) SwapPoints(pt1a, pt1b); - if (pt2a.X > pt2b.X) SwapPoints(pt2a, pt2b); - if (pt1a.X > pt2a.X) pt1 = pt1a; else pt1 = pt2a; - if (pt1b.X < pt2b.X) pt2 = pt1b; else pt2 = pt2b; - return pt1.X < pt2.X; - } else - { - if (pt1a.Y < pt1b.Y) SwapPoints(pt1a, pt1b); - if (pt2a.Y < pt2b.Y) SwapPoints(pt2a, pt2b); - if (pt1a.Y < pt2a.Y) pt1 = pt1a; else pt1 = pt2a; - if (pt1b.Y > pt2b.Y) pt2 = pt1b; else pt2 = pt2b; - return pt1.Y > pt2.Y; - } -} -//------------------------------------------------------------------------------ - -bool FirstIsBottomPt(const OutPt* btmPt1, const OutPt* btmPt2) -{ - OutPt *p = btmPt1->Prev; - while ((p->Pt == btmPt1->Pt) && (p != btmPt1)) p = p->Prev; - double dx1p = std::fabs(GetDx(btmPt1->Pt, p->Pt)); - p = btmPt1->Next; - while ((p->Pt == btmPt1->Pt) && (p != btmPt1)) p = p->Next; - double dx1n = std::fabs(GetDx(btmPt1->Pt, p->Pt)); - - p = btmPt2->Prev; - while ((p->Pt == btmPt2->Pt) && (p != btmPt2)) p = p->Prev; - double dx2p = std::fabs(GetDx(btmPt2->Pt, p->Pt)); - p = btmPt2->Next; - while ((p->Pt == btmPt2->Pt) && (p != btmPt2)) p = p->Next; - double dx2n = std::fabs(GetDx(btmPt2->Pt, p->Pt)); - - if (std::max(dx1p, dx1n) == std::max(dx2p, dx2n) && - std::min(dx1p, dx1n) == std::min(dx2p, dx2n)) - return Area(btmPt1) > 0; //if otherwise identical use orientation - else - return (dx1p >= dx2p && dx1p >= dx2n) || (dx1n >= dx2p && dx1n >= dx2n); -} -//------------------------------------------------------------------------------ - -OutPt* GetBottomPt(OutPt *pp) -{ - OutPt* dups = 0; - OutPt* p = pp->Next; - while (p != pp) - { - if (p->Pt.Y > pp->Pt.Y) - { - pp = p; - dups = 0; - } - else if (p->Pt.Y == pp->Pt.Y && p->Pt.X <= pp->Pt.X) - { - if (p->Pt.X < pp->Pt.X) - { - dups = 0; - pp = p; - } else - { - if (p->Next != pp && p->Prev != pp) dups = p; - } - } - p = p->Next; - } - if (dups) - { - //there appears to be at least 2 vertices at BottomPt so ... - while (dups != p) - { - if (!FirstIsBottomPt(p, dups)) pp = dups; - dups = dups->Next; - while (dups->Pt != pp->Pt) dups = dups->Next; - } - } - return pp; -} -//------------------------------------------------------------------------------ - -bool Pt2IsBetweenPt1AndPt3(const IntPoint pt1, - const IntPoint pt2, const IntPoint pt3) -{ - if ((pt1 == pt3) || (pt1 == pt2) || (pt3 == pt2)) - return false; - else if (pt1.X != pt3.X) - return (pt2.X > pt1.X) == (pt2.X < pt3.X); - else - return (pt2.Y > pt1.Y) == (pt2.Y < pt3.Y); -} -//------------------------------------------------------------------------------ - -bool HorzSegmentsOverlap(cInt seg1a, cInt seg1b, cInt seg2a, cInt seg2b) -{ - if (seg1a > seg1b) std::swap(seg1a, seg1b); - if (seg2a > seg2b) std::swap(seg2a, seg2b); - return (seg1a < seg2b) && (seg2a < seg1b); -} - -//------------------------------------------------------------------------------ -// ClipperBase class methods ... -//------------------------------------------------------------------------------ - -ClipperBase::ClipperBase() //constructor -{ - m_CurrentLM = m_MinimaList.begin(); //begin() == end() here - m_UseFullRange = false; -} -//------------------------------------------------------------------------------ - -ClipperBase::~ClipperBase() //destructor -{ - Clear(); -} -//------------------------------------------------------------------------------ - -void RangeTest(const IntPoint& Pt, bool& useFullRange) -{ - if (useFullRange) - { - if (Pt.X > hiRange || Pt.Y > hiRange || -Pt.X > hiRange || -Pt.Y > hiRange) - throw clipperException("Coordinate outside allowed range"); - } - else if (Pt.X > loRange|| Pt.Y > loRange || -Pt.X > loRange || -Pt.Y > loRange) - { - useFullRange = true; - RangeTest(Pt, useFullRange); - } -} -//------------------------------------------------------------------------------ - -TEdge* FindNextLocMin(TEdge* E) -{ - for (;;) - { - while (E->Bot != E->Prev->Bot || E->Curr == E->Top) E = E->Next; - if (!IsHorizontal(*E) && !IsHorizontal(*E->Prev)) break; - while (IsHorizontal(*E->Prev)) E = E->Prev; - TEdge* E2 = E; - while (IsHorizontal(*E)) E = E->Next; - if (E->Top.Y == E->Prev->Bot.Y) continue; //ie just an intermediate horz. - if (E2->Prev->Bot.X < E->Bot.X) E = E2; - break; - } - return E; -} -//------------------------------------------------------------------------------ - -TEdge* ClipperBase::ProcessBound(TEdge* E, bool NextIsForward) -{ - TEdge *Result = E; - TEdge *Horz = 0; - - if (E->OutIdx == Skip) - { - //if edges still remain in the current bound beyond the skip edge then - //create another LocMin and call ProcessBound once more - if (NextIsForward) - { - while (E->Top.Y == E->Next->Bot.Y) E = E->Next; - //don't include top horizontals when parsing a bound a second time, - //they will be contained in the opposite bound ... - while (E != Result && IsHorizontal(*E)) E = E->Prev; - } - else - { - while (E->Top.Y == E->Prev->Bot.Y) E = E->Prev; - while (E != Result && IsHorizontal(*E)) E = E->Next; - } - - if (E == Result) - { - if (NextIsForward) Result = E->Next; - else Result = E->Prev; - } - else - { - //there are more edges in the bound beyond result starting with E - if (NextIsForward) - E = Result->Next; - else - E = Result->Prev; - MinimaList::value_type locMin; - locMin.Y = E->Bot.Y; - locMin.LeftBound = 0; - locMin.RightBound = E; - E->WindDelta = 0; - Result = ProcessBound(E, NextIsForward); - m_MinimaList.push_back(locMin); - } - return Result; - } - - TEdge *EStart; - - if (IsHorizontal(*E)) - { - //We need to be careful with open paths because this may not be a - //true local minima (ie E may be following a skip edge). - //Also, consecutive horz. edges may start heading left before going right. - if (NextIsForward) - EStart = E->Prev; - else - EStart = E->Next; - if (IsHorizontal(*EStart)) //ie an adjoining horizontal skip edge - { - if (EStart->Bot.X != E->Bot.X && EStart->Top.X != E->Bot.X) - ReverseHorizontal(*E); - } - else if (EStart->Bot.X != E->Bot.X) - ReverseHorizontal(*E); - } - - EStart = E; - if (NextIsForward) - { - while (Result->Top.Y == Result->Next->Bot.Y && Result->Next->OutIdx != Skip) - Result = Result->Next; - if (IsHorizontal(*Result) && Result->Next->OutIdx != Skip) - { - //nb: at the top of a bound, horizontals are added to the bound - //only when the preceding edge attaches to the horizontal's left vertex - //unless a Skip edge is encountered when that becomes the top divide - Horz = Result; - while (IsHorizontal(*Horz->Prev)) Horz = Horz->Prev; - if (Horz->Prev->Top.X > Result->Next->Top.X) Result = Horz->Prev; - } - while (E != Result) - { - E->NextInLML = E->Next; - if (IsHorizontal(*E) && E != EStart && - E->Bot.X != E->Prev->Top.X) ReverseHorizontal(*E); - E = E->Next; - } - if (IsHorizontal(*E) && E != EStart && E->Bot.X != E->Prev->Top.X) - ReverseHorizontal(*E); - Result = Result->Next; //move to the edge just beyond current bound - } else - { - while (Result->Top.Y == Result->Prev->Bot.Y && Result->Prev->OutIdx != Skip) - Result = Result->Prev; - if (IsHorizontal(*Result) && Result->Prev->OutIdx != Skip) - { - Horz = Result; - while (IsHorizontal(*Horz->Next)) Horz = Horz->Next; - if (Horz->Next->Top.X == Result->Prev->Top.X || - Horz->Next->Top.X > Result->Prev->Top.X) Result = Horz->Next; - } - - while (E != Result) - { - E->NextInLML = E->Prev; - if (IsHorizontal(*E) && E != EStart && E->Bot.X != E->Next->Top.X) - ReverseHorizontal(*E); - E = E->Prev; - } - if (IsHorizontal(*E) && E != EStart && E->Bot.X != E->Next->Top.X) - ReverseHorizontal(*E); - Result = Result->Prev; //move to the edge just beyond current bound - } - - return Result; -} -//------------------------------------------------------------------------------ - -bool ClipperBase::AddPath(const Path &pg, PolyType PolyTyp, bool Closed) -{ -#ifdef use_lines - if (!Closed && PolyTyp == ptClip) - throw clipperException("AddPath: Open paths must be subject."); -#else - if (!Closed) - throw clipperException("AddPath: Open paths have been disabled."); -#endif - - int highI = (int)pg.size() -1; - if (Closed) while (highI > 0 && (pg[highI] == pg[0])) --highI; - while (highI > 0 && (pg[highI] == pg[highI -1])) --highI; - if ((Closed && highI < 2) || (!Closed && highI < 1)) return false; - - //create a new edge array ... - TEdge *edges = new TEdge [highI +1]; - - bool IsFlat = true; - //1. Basic (first) edge initialization ... - try - { - edges[1].Curr = pg[1]; - RangeTest(pg[0], m_UseFullRange); - RangeTest(pg[highI], m_UseFullRange); - InitEdge(&edges[0], &edges[1], &edges[highI], pg[0]); - InitEdge(&edges[highI], &edges[0], &edges[highI-1], pg[highI]); - for (int i = highI - 1; i >= 1; --i) - { - RangeTest(pg[i], m_UseFullRange); - InitEdge(&edges[i], &edges[i+1], &edges[i-1], pg[i]); - } - } - catch(...) - { - delete [] edges; - throw; //range test fails - } - TEdge *eStart = &edges[0]; - - //2. Remove duplicate vertices, and (when closed) collinear edges ... - TEdge *E = eStart, *eLoopStop = eStart; - for (;;) - { - //nb: allows matching start and end points when not Closed ... - if (E->Curr == E->Next->Curr && (Closed || E->Next != eStart)) - { - if (E == E->Next) break; - if (E == eStart) eStart = E->Next; - E = RemoveEdge(E); - eLoopStop = E; - continue; - } - if (E->Prev == E->Next) - break; //only two vertices - else if (Closed && - SlopesEqual(E->Prev->Curr, E->Curr, E->Next->Curr, m_UseFullRange) && - (!m_PreserveCollinear || - !Pt2IsBetweenPt1AndPt3(E->Prev->Curr, E->Curr, E->Next->Curr))) - { - //Collinear edges are allowed for open paths but in closed paths - //the default is to merge adjacent collinear edges into a single edge. - //However, if the PreserveCollinear property is enabled, only overlapping - //collinear edges (ie spikes) will be removed from closed paths. - if (E == eStart) eStart = E->Next; - E = RemoveEdge(E); - E = E->Prev; - eLoopStop = E; - continue; - } - E = E->Next; - if ((E == eLoopStop) || (!Closed && E->Next == eStart)) break; - } - - if ((!Closed && (E == E->Next)) || (Closed && (E->Prev == E->Next))) - { - delete [] edges; - return false; - } - - if (!Closed) - { - m_HasOpenPaths = true; - eStart->Prev->OutIdx = Skip; - } - - //3. Do second stage of edge initialization ... - E = eStart; - do - { - InitEdge2(*E, PolyTyp); - E = E->Next; - if (IsFlat && E->Curr.Y != eStart->Curr.Y) IsFlat = false; - } - while (E != eStart); - - //4. Finally, add edge bounds to LocalMinima list ... - - //Totally flat paths must be handled differently when adding them - //to LocalMinima list to avoid endless loops etc ... - if (IsFlat) - { - if (Closed) - { - delete [] edges; - return false; - } - E->Prev->OutIdx = Skip; - MinimaList::value_type locMin; - locMin.Y = E->Bot.Y; - locMin.LeftBound = 0; - locMin.RightBound = E; - locMin.RightBound->Side = esRight; - locMin.RightBound->WindDelta = 0; - for (;;) - { - if (E->Bot.X != E->Prev->Top.X) ReverseHorizontal(*E); - if (E->Next->OutIdx == Skip) break; - E->NextInLML = E->Next; - E = E->Next; - } - m_MinimaList.push_back(locMin); - m_edges.push_back(edges); - return true; - } - - m_edges.push_back(edges); - bool leftBoundIsForward; - TEdge* EMin = 0; - - //workaround to avoid an endless loop in the while loop below when - //open paths have matching start and end points ... - if (E->Prev->Bot == E->Prev->Top) E = E->Next; - - for (;;) - { - E = FindNextLocMin(E); - if (E == EMin) break; - else if (!EMin) EMin = E; - - //E and E.Prev now share a local minima (left aligned if horizontal). - //Compare their slopes to find which starts which bound ... - MinimaList::value_type locMin; - locMin.Y = E->Bot.Y; - if (E->Dx < E->Prev->Dx) - { - locMin.LeftBound = E->Prev; - locMin.RightBound = E; - leftBoundIsForward = false; //Q.nextInLML = Q.prev - } else - { - locMin.LeftBound = E; - locMin.RightBound = E->Prev; - leftBoundIsForward = true; //Q.nextInLML = Q.next - } - - if (!Closed) locMin.LeftBound->WindDelta = 0; - else if (locMin.LeftBound->Next == locMin.RightBound) - locMin.LeftBound->WindDelta = -1; - else locMin.LeftBound->WindDelta = 1; - locMin.RightBound->WindDelta = -locMin.LeftBound->WindDelta; - - E = ProcessBound(locMin.LeftBound, leftBoundIsForward); - if (E->OutIdx == Skip) E = ProcessBound(E, leftBoundIsForward); - - TEdge* E2 = ProcessBound(locMin.RightBound, !leftBoundIsForward); - if (E2->OutIdx == Skip) E2 = ProcessBound(E2, !leftBoundIsForward); - - if (locMin.LeftBound->OutIdx == Skip) - locMin.LeftBound = 0; - else if (locMin.RightBound->OutIdx == Skip) - locMin.RightBound = 0; - m_MinimaList.push_back(locMin); - if (!leftBoundIsForward) E = E2; - } - return true; -} -//------------------------------------------------------------------------------ - -bool ClipperBase::AddPaths(const Paths &ppg, PolyType PolyTyp, bool Closed) -{ - bool result = false; - for (Paths::size_type i = 0; i < ppg.size(); ++i) - if (AddPath(ppg[i], PolyTyp, Closed)) result = true; - return result; -} -//------------------------------------------------------------------------------ - -void ClipperBase::Clear() -{ - DisposeLocalMinimaList(); - for (EdgeList::size_type i = 0; i < m_edges.size(); ++i) - { - TEdge* edges = m_edges[i]; - delete [] edges; - } - m_edges.clear(); - m_UseFullRange = false; - m_HasOpenPaths = false; -} -//------------------------------------------------------------------------------ - -void ClipperBase::Reset() -{ - m_CurrentLM = m_MinimaList.begin(); - if (m_CurrentLM == m_MinimaList.end()) return; //ie nothing to process - std::sort(m_MinimaList.begin(), m_MinimaList.end(), LocMinSorter()); - - m_Scanbeam = ScanbeamList(); //clears/resets priority_queue - //reset all edges ... - for (MinimaList::iterator lm = m_MinimaList.begin(); lm != m_MinimaList.end(); ++lm) - { - InsertScanbeam(lm->Y); - TEdge* e = lm->LeftBound; - if (e) - { - e->Curr = e->Bot; - e->Side = esLeft; - e->OutIdx = Unassigned; - } - - e = lm->RightBound; - if (e) - { - e->Curr = e->Bot; - e->Side = esRight; - e->OutIdx = Unassigned; - } - } - m_ActiveEdges = 0; - m_CurrentLM = m_MinimaList.begin(); -} -//------------------------------------------------------------------------------ - -void ClipperBase::DisposeLocalMinimaList() -{ - m_MinimaList.clear(); - m_CurrentLM = m_MinimaList.begin(); -} -//------------------------------------------------------------------------------ - -bool ClipperBase::PopLocalMinima(cInt Y, const LocalMinimum *&locMin) -{ - if (m_CurrentLM == m_MinimaList.end() || (*m_CurrentLM).Y != Y) return false; - locMin = &(*m_CurrentLM); - ++m_CurrentLM; - return true; -} -//------------------------------------------------------------------------------ - -IntRect ClipperBase::GetBounds() -{ - IntRect result; - MinimaList::iterator lm = m_MinimaList.begin(); - if (lm == m_MinimaList.end()) - { - result.left = result.top = result.right = result.bottom = 0; - return result; - } - result.left = lm->LeftBound->Bot.X; - result.top = lm->LeftBound->Bot.Y; - result.right = lm->LeftBound->Bot.X; - result.bottom = lm->LeftBound->Bot.Y; - while (lm != m_MinimaList.end()) - { - //todo - needs fixing for open paths - result.bottom = std::max(result.bottom, lm->LeftBound->Bot.Y); - TEdge* e = lm->LeftBound; - for (;;) { - TEdge* bottomE = e; - while (e->NextInLML) - { - if (e->Bot.X < result.left) result.left = e->Bot.X; - if (e->Bot.X > result.right) result.right = e->Bot.X; - e = e->NextInLML; - } - result.left = std::min(result.left, e->Bot.X); - result.right = std::max(result.right, e->Bot.X); - result.left = std::min(result.left, e->Top.X); - result.right = std::max(result.right, e->Top.X); - result.top = std::min(result.top, e->Top.Y); - if (bottomE == lm->LeftBound) e = lm->RightBound; - else break; - } - ++lm; - } - return result; -} -//------------------------------------------------------------------------------ - -void ClipperBase::InsertScanbeam(const cInt Y) -{ - m_Scanbeam.push(Y); -} -//------------------------------------------------------------------------------ - -bool ClipperBase::PopScanbeam(cInt &Y) -{ - if (m_Scanbeam.empty()) return false; - Y = m_Scanbeam.top(); - m_Scanbeam.pop(); - while (!m_Scanbeam.empty() && Y == m_Scanbeam.top()) { m_Scanbeam.pop(); } // Pop duplicates. - return true; -} -//------------------------------------------------------------------------------ - -void ClipperBase::DisposeAllOutRecs(){ - for (PolyOutList::size_type i = 0; i < m_PolyOuts.size(); ++i) - DisposeOutRec(i); - m_PolyOuts.clear(); -} -//------------------------------------------------------------------------------ - -void ClipperBase::DisposeOutRec(PolyOutList::size_type index) -{ - OutRec *outRec = m_PolyOuts[index]; - if (outRec->Pts) DisposeOutPts(outRec->Pts); - delete outRec; - m_PolyOuts[index] = 0; -} -//------------------------------------------------------------------------------ - -void ClipperBase::DeleteFromAEL(TEdge *e) -{ - TEdge* AelPrev = e->PrevInAEL; - TEdge* AelNext = e->NextInAEL; - if (!AelPrev && !AelNext && (e != m_ActiveEdges)) return; //already deleted - if (AelPrev) AelPrev->NextInAEL = AelNext; - else m_ActiveEdges = AelNext; - if (AelNext) AelNext->PrevInAEL = AelPrev; - e->NextInAEL = 0; - e->PrevInAEL = 0; -} -//------------------------------------------------------------------------------ - -OutRec* ClipperBase::CreateOutRec() -{ - OutRec* result = new OutRec; - result->IsHole = false; - result->IsOpen = false; - result->FirstLeft = 0; - result->Pts = 0; - result->BottomPt = 0; - result->PolyNd = 0; - m_PolyOuts.push_back(result); - result->Idx = (int)m_PolyOuts.size() - 1; - return result; -} -//------------------------------------------------------------------------------ - -void ClipperBase::SwapPositionsInAEL(TEdge *Edge1, TEdge *Edge2) -{ - //check that one or other edge hasn't already been removed from AEL ... - if (Edge1->NextInAEL == Edge1->PrevInAEL || - Edge2->NextInAEL == Edge2->PrevInAEL) return; - - if (Edge1->NextInAEL == Edge2) - { - TEdge* Next = Edge2->NextInAEL; - if (Next) Next->PrevInAEL = Edge1; - TEdge* Prev = Edge1->PrevInAEL; - if (Prev) Prev->NextInAEL = Edge2; - Edge2->PrevInAEL = Prev; - Edge2->NextInAEL = Edge1; - Edge1->PrevInAEL = Edge2; - Edge1->NextInAEL = Next; - } - else if (Edge2->NextInAEL == Edge1) - { - TEdge* Next = Edge1->NextInAEL; - if (Next) Next->PrevInAEL = Edge2; - TEdge* Prev = Edge2->PrevInAEL; - if (Prev) Prev->NextInAEL = Edge1; - Edge1->PrevInAEL = Prev; - Edge1->NextInAEL = Edge2; - Edge2->PrevInAEL = Edge1; - Edge2->NextInAEL = Next; - } - else - { - TEdge* Next = Edge1->NextInAEL; - TEdge* Prev = Edge1->PrevInAEL; - Edge1->NextInAEL = Edge2->NextInAEL; - if (Edge1->NextInAEL) Edge1->NextInAEL->PrevInAEL = Edge1; - Edge1->PrevInAEL = Edge2->PrevInAEL; - if (Edge1->PrevInAEL) Edge1->PrevInAEL->NextInAEL = Edge1; - Edge2->NextInAEL = Next; - if (Edge2->NextInAEL) Edge2->NextInAEL->PrevInAEL = Edge2; - Edge2->PrevInAEL = Prev; - if (Edge2->PrevInAEL) Edge2->PrevInAEL->NextInAEL = Edge2; - } - - if (!Edge1->PrevInAEL) m_ActiveEdges = Edge1; - else if (!Edge2->PrevInAEL) m_ActiveEdges = Edge2; -} -//------------------------------------------------------------------------------ - -void ClipperBase::UpdateEdgeIntoAEL(TEdge *&e) -{ - if (!e->NextInLML) - throw clipperException("UpdateEdgeIntoAEL: invalid call"); - - e->NextInLML->OutIdx = e->OutIdx; - TEdge* AelPrev = e->PrevInAEL; - TEdge* AelNext = e->NextInAEL; - if (AelPrev) AelPrev->NextInAEL = e->NextInLML; - else m_ActiveEdges = e->NextInLML; - if (AelNext) AelNext->PrevInAEL = e->NextInLML; - e->NextInLML->Side = e->Side; - e->NextInLML->WindDelta = e->WindDelta; - e->NextInLML->WindCnt = e->WindCnt; - e->NextInLML->WindCnt2 = e->WindCnt2; - e = e->NextInLML; - e->Curr = e->Bot; - e->PrevInAEL = AelPrev; - e->NextInAEL = AelNext; - if (!IsHorizontal(*e)) InsertScanbeam(e->Top.Y); -} -//------------------------------------------------------------------------------ - -bool ClipperBase::LocalMinimaPending() -{ - return (m_CurrentLM != m_MinimaList.end()); -} - -//------------------------------------------------------------------------------ -// TClipper methods ... -//------------------------------------------------------------------------------ - -Clipper::Clipper(int initOptions) : ClipperBase() //constructor -{ - m_ExecuteLocked = false; - m_UseFullRange = false; - m_ReverseOutput = ((initOptions & ioReverseSolution) != 0); - m_StrictSimple = ((initOptions & ioStrictlySimple) != 0); - m_PreserveCollinear = ((initOptions & ioPreserveCollinear) != 0); - m_HasOpenPaths = false; -#ifdef use_xyz - m_ZFill = 0; -#endif -} -//------------------------------------------------------------------------------ - -#ifdef use_xyz -void Clipper::ZFillFunction(ZFillCallback zFillFunc) -{ - m_ZFill = zFillFunc; -} -//------------------------------------------------------------------------------ -#endif - -bool Clipper::Execute(ClipType clipType, Paths &solution, PolyFillType fillType) -{ - return Execute(clipType, solution, fillType, fillType); -} -//------------------------------------------------------------------------------ - -bool Clipper::Execute(ClipType clipType, PolyTree &polytree, PolyFillType fillType) -{ - return Execute(clipType, polytree, fillType, fillType); -} -//------------------------------------------------------------------------------ - -bool Clipper::Execute(ClipType clipType, Paths &solution, - PolyFillType subjFillType, PolyFillType clipFillType) -{ - if( m_ExecuteLocked ) return false; - if (m_HasOpenPaths) - throw clipperException("Error: PolyTree struct is needed for open path clipping."); - m_ExecuteLocked = true; - solution.resize(0); - m_SubjFillType = subjFillType; - m_ClipFillType = clipFillType; - m_ClipType = clipType; - m_UsingPolyTree = false; - bool succeeded = ExecuteInternal(); - if (succeeded) BuildResult(solution); - DisposeAllOutRecs(); - m_ExecuteLocked = false; - return succeeded; -} -//------------------------------------------------------------------------------ - -bool Clipper::Execute(ClipType clipType, PolyTree& polytree, - PolyFillType subjFillType, PolyFillType clipFillType) -{ - if( m_ExecuteLocked ) return false; - m_ExecuteLocked = true; - m_SubjFillType = subjFillType; - m_ClipFillType = clipFillType; - m_ClipType = clipType; - m_UsingPolyTree = true; - bool succeeded = ExecuteInternal(); - if (succeeded) BuildResult2(polytree); - DisposeAllOutRecs(); - m_ExecuteLocked = false; - return succeeded; -} -//------------------------------------------------------------------------------ - -void Clipper::FixHoleLinkage(OutRec &outrec) -{ - //skip OutRecs that (a) contain outermost polygons or - //(b) already have the correct owner/child linkage ... - if (!outrec.FirstLeft || - (outrec.IsHole != outrec.FirstLeft->IsHole && - outrec.FirstLeft->Pts)) return; - - OutRec* orfl = outrec.FirstLeft; - while (orfl && ((orfl->IsHole == outrec.IsHole) || !orfl->Pts)) - orfl = orfl->FirstLeft; - outrec.FirstLeft = orfl; -} -//------------------------------------------------------------------------------ - -bool Clipper::ExecuteInternal() -{ - bool succeeded = true; - try { - Reset(); - m_Maxima = MaximaList(); - m_SortedEdges = 0; - - succeeded = true; - cInt botY, topY; - if (!PopScanbeam(botY)) return false; - InsertLocalMinimaIntoAEL(botY); - while (PopScanbeam(topY) || LocalMinimaPending()) - { - ProcessHorizontals(); - ClearGhostJoins(); - if (!ProcessIntersections(topY)) - { - succeeded = false; - break; - } - ProcessEdgesAtTopOfScanbeam(topY); - botY = topY; - InsertLocalMinimaIntoAEL(botY); - } - } - catch(...) - { - succeeded = false; - } - - if (succeeded) - { - //fix orientations ... - for (PolyOutList::size_type i = 0; i < m_PolyOuts.size(); ++i) - { - OutRec *outRec = m_PolyOuts[i]; - if (!outRec->Pts || outRec->IsOpen) continue; - if ((outRec->IsHole ^ m_ReverseOutput) == (Area(*outRec) > 0)) - ReversePolyPtLinks(outRec->Pts); - } - - if (!m_Joins.empty()) JoinCommonEdges(); - - //unfortunately FixupOutPolygon() must be done after JoinCommonEdges() - for (PolyOutList::size_type i = 0; i < m_PolyOuts.size(); ++i) - { - OutRec *outRec = m_PolyOuts[i]; - if (!outRec->Pts) continue; - if (outRec->IsOpen) - FixupOutPolyline(*outRec); - else - FixupOutPolygon(*outRec); - } - - if (m_StrictSimple) DoSimplePolygons(); - } - - ClearJoins(); - ClearGhostJoins(); - return succeeded; -} -//------------------------------------------------------------------------------ - -void Clipper::SetWindingCount(TEdge &edge) -{ - TEdge *e = edge.PrevInAEL; - //find the edge of the same polytype that immediately preceeds 'edge' in AEL - while (e && ((e->PolyTyp != edge.PolyTyp) || (e->WindDelta == 0))) e = e->PrevInAEL; - if (!e) - { - if (edge.WindDelta == 0) - { - PolyFillType pft = (edge.PolyTyp == ptSubject ? m_SubjFillType : m_ClipFillType); - edge.WindCnt = (pft == pftNegative ? -1 : 1); - } - else - edge.WindCnt = edge.WindDelta; - edge.WindCnt2 = 0; - e = m_ActiveEdges; //ie get ready to calc WindCnt2 - } - else if (edge.WindDelta == 0 && m_ClipType != ctUnion) - { - edge.WindCnt = 1; - edge.WindCnt2 = e->WindCnt2; - e = e->NextInAEL; //ie get ready to calc WindCnt2 - } - else if (IsEvenOddFillType(edge)) - { - //EvenOdd filling ... - if (edge.WindDelta == 0) - { - //are we inside a subj polygon ... - bool Inside = true; - TEdge *e2 = e->PrevInAEL; - while (e2) - { - if (e2->PolyTyp == e->PolyTyp && e2->WindDelta != 0) - Inside = !Inside; - e2 = e2->PrevInAEL; - } - edge.WindCnt = (Inside ? 0 : 1); - } - else - { - edge.WindCnt = edge.WindDelta; - } - edge.WindCnt2 = e->WindCnt2; - e = e->NextInAEL; //ie get ready to calc WindCnt2 - } - else - { - //nonZero, Positive or Negative filling ... - if (e->WindCnt * e->WindDelta < 0) - { - //prev edge is 'decreasing' WindCount (WC) toward zero - //so we're outside the previous polygon ... - if (Abs(e->WindCnt) > 1) - { - //outside prev poly but still inside another. - //when reversing direction of prev poly use the same WC - if (e->WindDelta * edge.WindDelta < 0) edge.WindCnt = e->WindCnt; - //otherwise continue to 'decrease' WC ... - else edge.WindCnt = e->WindCnt + edge.WindDelta; - } - else - //now outside all polys of same polytype so set own WC ... - edge.WindCnt = (edge.WindDelta == 0 ? 1 : edge.WindDelta); - } else - { - //prev edge is 'increasing' WindCount (WC) away from zero - //so we're inside the previous polygon ... - if (edge.WindDelta == 0) - edge.WindCnt = (e->WindCnt < 0 ? e->WindCnt - 1 : e->WindCnt + 1); - //if wind direction is reversing prev then use same WC - else if (e->WindDelta * edge.WindDelta < 0) edge.WindCnt = e->WindCnt; - //otherwise add to WC ... - else edge.WindCnt = e->WindCnt + edge.WindDelta; - } - edge.WindCnt2 = e->WindCnt2; - e = e->NextInAEL; //ie get ready to calc WindCnt2 - } - - //update WindCnt2 ... - if (IsEvenOddAltFillType(edge)) - { - //EvenOdd filling ... - while (e != &edge) - { - if (e->WindDelta != 0) - edge.WindCnt2 = (edge.WindCnt2 == 0 ? 1 : 0); - e = e->NextInAEL; - } - } else - { - //nonZero, Positive or Negative filling ... - while ( e != &edge ) - { - edge.WindCnt2 += e->WindDelta; - e = e->NextInAEL; - } - } -} -//------------------------------------------------------------------------------ - -bool Clipper::IsEvenOddFillType(const TEdge& edge) const -{ - if (edge.PolyTyp == ptSubject) - return m_SubjFillType == pftEvenOdd; else - return m_ClipFillType == pftEvenOdd; -} -//------------------------------------------------------------------------------ - -bool Clipper::IsEvenOddAltFillType(const TEdge& edge) const -{ - if (edge.PolyTyp == ptSubject) - return m_ClipFillType == pftEvenOdd; else - return m_SubjFillType == pftEvenOdd; -} -//------------------------------------------------------------------------------ - -bool Clipper::IsContributing(const TEdge& edge) const -{ - PolyFillType pft, pft2; - if (edge.PolyTyp == ptSubject) - { - pft = m_SubjFillType; - pft2 = m_ClipFillType; - } else - { - pft = m_ClipFillType; - pft2 = m_SubjFillType; - } - - switch(pft) - { - case pftEvenOdd: - //return false if a subj line has been flagged as inside a subj polygon - if (edge.WindDelta == 0 && edge.WindCnt != 1) return false; - break; - case pftNonZero: - if (Abs(edge.WindCnt) != 1) return false; - break; - case pftPositive: - if (edge.WindCnt != 1) return false; - break; - default: //pftNegative - if (edge.WindCnt != -1) return false; - } - - switch(m_ClipType) - { - case ctIntersection: - switch(pft2) - { - case pftEvenOdd: - case pftNonZero: - return (edge.WindCnt2 != 0); - case pftPositive: - return (edge.WindCnt2 > 0); - default: - return (edge.WindCnt2 < 0); - } - break; - case ctUnion: - switch(pft2) - { - case pftEvenOdd: - case pftNonZero: - return (edge.WindCnt2 == 0); - case pftPositive: - return (edge.WindCnt2 <= 0); - default: - return (edge.WindCnt2 >= 0); - } - break; - case ctDifference: - if (edge.PolyTyp == ptSubject) - switch(pft2) - { - case pftEvenOdd: - case pftNonZero: - return (edge.WindCnt2 == 0); - case pftPositive: - return (edge.WindCnt2 <= 0); - default: - return (edge.WindCnt2 >= 0); - } - else - switch(pft2) - { - case pftEvenOdd: - case pftNonZero: - return (edge.WindCnt2 != 0); - case pftPositive: - return (edge.WindCnt2 > 0); - default: - return (edge.WindCnt2 < 0); - } - break; - case ctXor: - if (edge.WindDelta == 0) //XOr always contributing unless open - switch(pft2) - { - case pftEvenOdd: - case pftNonZero: - return (edge.WindCnt2 == 0); - case pftPositive: - return (edge.WindCnt2 <= 0); - default: - return (edge.WindCnt2 >= 0); - } - else - return true; - break; - default: - return true; - } -} -//------------------------------------------------------------------------------ - -OutPt* Clipper::AddLocalMinPoly(TEdge *e1, TEdge *e2, const IntPoint &Pt) -{ - OutPt* result; - TEdge *e, *prevE; - if (IsHorizontal(*e2) || ( e1->Dx > e2->Dx )) - { - result = AddOutPt(e1, Pt); - e2->OutIdx = e1->OutIdx; - e1->Side = esLeft; - e2->Side = esRight; - e = e1; - if (e->PrevInAEL == e2) - prevE = e2->PrevInAEL; - else - prevE = e->PrevInAEL; - } else - { - result = AddOutPt(e2, Pt); - e1->OutIdx = e2->OutIdx; - e1->Side = esRight; - e2->Side = esLeft; - e = e2; - if (e->PrevInAEL == e1) - prevE = e1->PrevInAEL; - else - prevE = e->PrevInAEL; - } - - if (prevE && prevE->OutIdx >= 0 && prevE->Top.Y < Pt.Y && e->Top.Y < Pt.Y) - { - cInt xPrev = TopX(*prevE, Pt.Y); - cInt xE = TopX(*e, Pt.Y); - if (xPrev == xE && (e->WindDelta != 0) && (prevE->WindDelta != 0) && - SlopesEqual(IntPoint(xPrev, Pt.Y), prevE->Top, IntPoint(xE, Pt.Y), e->Top, m_UseFullRange)) - { - OutPt* outPt = AddOutPt(prevE, Pt); - AddJoin(result, outPt, e->Top); - } - } - return result; -} -//------------------------------------------------------------------------------ - -void Clipper::AddLocalMaxPoly(TEdge *e1, TEdge *e2, const IntPoint &Pt) -{ - AddOutPt( e1, Pt ); - if (e2->WindDelta == 0) AddOutPt(e2, Pt); - if( e1->OutIdx == e2->OutIdx ) - { - e1->OutIdx = Unassigned; - e2->OutIdx = Unassigned; - } - else if (e1->OutIdx < e2->OutIdx) - AppendPolygon(e1, e2); - else - AppendPolygon(e2, e1); -} -//------------------------------------------------------------------------------ - -void Clipper::AddEdgeToSEL(TEdge *edge) -{ - //SEL pointers in PEdge are reused to build a list of horizontal edges. - //However, we don't need to worry about order with horizontal edge processing. - if( !m_SortedEdges ) - { - m_SortedEdges = edge; - edge->PrevInSEL = 0; - edge->NextInSEL = 0; - } - else - { - edge->NextInSEL = m_SortedEdges; - edge->PrevInSEL = 0; - m_SortedEdges->PrevInSEL = edge; - m_SortedEdges = edge; - } -} -//------------------------------------------------------------------------------ - -bool Clipper::PopEdgeFromSEL(TEdge *&edge) -{ - if (!m_SortedEdges) return false; - edge = m_SortedEdges; - DeleteFromSEL(m_SortedEdges); - return true; -} -//------------------------------------------------------------------------------ - -void Clipper::CopyAELToSEL() -{ - TEdge* e = m_ActiveEdges; - m_SortedEdges = e; - while ( e ) - { - e->PrevInSEL = e->PrevInAEL; - e->NextInSEL = e->NextInAEL; - e = e->NextInAEL; - } -} -//------------------------------------------------------------------------------ - -void Clipper::AddJoin(OutPt *op1, OutPt *op2, const IntPoint OffPt) -{ - Join* j = new Join; - j->OutPt1 = op1; - j->OutPt2 = op2; - j->OffPt = OffPt; - m_Joins.push_back(j); -} -//------------------------------------------------------------------------------ - -void Clipper::ClearJoins() -{ - for (JoinList::size_type i = 0; i < m_Joins.size(); i++) - delete m_Joins[i]; - m_Joins.resize(0); -} -//------------------------------------------------------------------------------ - -void Clipper::ClearGhostJoins() -{ - for (JoinList::size_type i = 0; i < m_GhostJoins.size(); i++) - delete m_GhostJoins[i]; - m_GhostJoins.resize(0); -} -//------------------------------------------------------------------------------ - -void Clipper::AddGhostJoin(OutPt *op, const IntPoint OffPt) -{ - Join* j = new Join; - j->OutPt1 = op; - j->OutPt2 = 0; - j->OffPt = OffPt; - m_GhostJoins.push_back(j); -} -//------------------------------------------------------------------------------ - -void Clipper::InsertLocalMinimaIntoAEL(const cInt botY) -{ - const LocalMinimum *lm; - while (PopLocalMinima(botY, lm)) - { - TEdge* lb = lm->LeftBound; - TEdge* rb = lm->RightBound; - - OutPt *Op1 = 0; - if (!lb) - { - //nb: don't insert LB into either AEL or SEL - InsertEdgeIntoAEL(rb, 0); - SetWindingCount(*rb); - if (IsContributing(*rb)) - Op1 = AddOutPt(rb, rb->Bot); - } - else if (!rb) - { - InsertEdgeIntoAEL(lb, 0); - SetWindingCount(*lb); - if (IsContributing(*lb)) - Op1 = AddOutPt(lb, lb->Bot); - InsertScanbeam(lb->Top.Y); - } - else - { - InsertEdgeIntoAEL(lb, 0); - InsertEdgeIntoAEL(rb, lb); - SetWindingCount( *lb ); - rb->WindCnt = lb->WindCnt; - rb->WindCnt2 = lb->WindCnt2; - if (IsContributing(*lb)) - Op1 = AddLocalMinPoly(lb, rb, lb->Bot); - InsertScanbeam(lb->Top.Y); - } - - if (rb) - { - if (IsHorizontal(*rb)) - { - AddEdgeToSEL(rb); - if (rb->NextInLML) - InsertScanbeam(rb->NextInLML->Top.Y); - } - else InsertScanbeam( rb->Top.Y ); - } - - if (!lb || !rb) continue; - - //if any output polygons share an edge, they'll need joining later ... - if (Op1 && IsHorizontal(*rb) && - m_GhostJoins.size() > 0 && (rb->WindDelta != 0)) - { - for (JoinList::size_type i = 0; i < m_GhostJoins.size(); ++i) - { - Join* jr = m_GhostJoins[i]; - //if the horizontal Rb and a 'ghost' horizontal overlap, then convert - //the 'ghost' join to a real join ready for later ... - if (HorzSegmentsOverlap(jr->OutPt1->Pt.X, jr->OffPt.X, rb->Bot.X, rb->Top.X)) - AddJoin(jr->OutPt1, Op1, jr->OffPt); - } - } - - if (lb->OutIdx >= 0 && lb->PrevInAEL && - lb->PrevInAEL->Curr.X == lb->Bot.X && - lb->PrevInAEL->OutIdx >= 0 && - SlopesEqual(lb->PrevInAEL->Bot, lb->PrevInAEL->Top, lb->Curr, lb->Top, m_UseFullRange) && - (lb->WindDelta != 0) && (lb->PrevInAEL->WindDelta != 0)) - { - OutPt *Op2 = AddOutPt(lb->PrevInAEL, lb->Bot); - AddJoin(Op1, Op2, lb->Top); - } - - if(lb->NextInAEL != rb) - { - - if (rb->OutIdx >= 0 && rb->PrevInAEL->OutIdx >= 0 && - SlopesEqual(rb->PrevInAEL->Curr, rb->PrevInAEL->Top, rb->Curr, rb->Top, m_UseFullRange) && - (rb->WindDelta != 0) && (rb->PrevInAEL->WindDelta != 0)) - { - OutPt *Op2 = AddOutPt(rb->PrevInAEL, rb->Bot); - AddJoin(Op1, Op2, rb->Top); - } - - TEdge* e = lb->NextInAEL; - if (e) - { - while( e != rb ) - { - //nb: For calculating winding counts etc, IntersectEdges() assumes - //that param1 will be to the Right of param2 ABOVE the intersection ... - IntersectEdges(rb , e , lb->Curr); //order important here - e = e->NextInAEL; - } - } - } - - } -} -//------------------------------------------------------------------------------ - -void Clipper::DeleteFromSEL(TEdge *e) -{ - TEdge* SelPrev = e->PrevInSEL; - TEdge* SelNext = e->NextInSEL; - if( !SelPrev && !SelNext && (e != m_SortedEdges) ) return; //already deleted - if( SelPrev ) SelPrev->NextInSEL = SelNext; - else m_SortedEdges = SelNext; - if( SelNext ) SelNext->PrevInSEL = SelPrev; - e->NextInSEL = 0; - e->PrevInSEL = 0; -} -//------------------------------------------------------------------------------ - -#ifdef use_xyz -void Clipper::SetZ(IntPoint& pt, TEdge& e1, TEdge& e2) -{ - if (pt.Z != 0 || !m_ZFill) return; - else if (pt == e1.Bot) pt.Z = e1.Bot.Z; - else if (pt == e1.Top) pt.Z = e1.Top.Z; - else if (pt == e2.Bot) pt.Z = e2.Bot.Z; - else if (pt == e2.Top) pt.Z = e2.Top.Z; - else (*m_ZFill)(e1.Bot, e1.Top, e2.Bot, e2.Top, pt); -} -//------------------------------------------------------------------------------ -#endif - -void Clipper::IntersectEdges(TEdge *e1, TEdge *e2, IntPoint &Pt) -{ - bool e1Contributing = ( e1->OutIdx >= 0 ); - bool e2Contributing = ( e2->OutIdx >= 0 ); - -#ifdef use_xyz - SetZ(Pt, *e1, *e2); -#endif - -#ifdef use_lines - //if either edge is on an OPEN path ... - if (e1->WindDelta == 0 || e2->WindDelta == 0) - { - //ignore subject-subject open path intersections UNLESS they - //are both open paths, AND they are both 'contributing maximas' ... - if (e1->WindDelta == 0 && e2->WindDelta == 0) return; - - //if intersecting a subj line with a subj poly ... - else if (e1->PolyTyp == e2->PolyTyp && - e1->WindDelta != e2->WindDelta && m_ClipType == ctUnion) - { - if (e1->WindDelta == 0) - { - if (e2Contributing) - { - AddOutPt(e1, Pt); - if (e1Contributing) e1->OutIdx = Unassigned; - } - } - else - { - if (e1Contributing) - { - AddOutPt(e2, Pt); - if (e2Contributing) e2->OutIdx = Unassigned; - } - } - } - else if (e1->PolyTyp != e2->PolyTyp) - { - //toggle subj open path OutIdx on/off when Abs(clip.WndCnt) == 1 ... - if ((e1->WindDelta == 0) && abs(e2->WindCnt) == 1 && - (m_ClipType != ctUnion || e2->WindCnt2 == 0)) - { - AddOutPt(e1, Pt); - if (e1Contributing) e1->OutIdx = Unassigned; - } - else if ((e2->WindDelta == 0) && (abs(e1->WindCnt) == 1) && - (m_ClipType != ctUnion || e1->WindCnt2 == 0)) - { - AddOutPt(e2, Pt); - if (e2Contributing) e2->OutIdx = Unassigned; - } - } - return; - } -#endif - - //update winding counts... - //assumes that e1 will be to the Right of e2 ABOVE the intersection - if ( e1->PolyTyp == e2->PolyTyp ) - { - if ( IsEvenOddFillType( *e1) ) - { - int oldE1WindCnt = e1->WindCnt; - e1->WindCnt = e2->WindCnt; - e2->WindCnt = oldE1WindCnt; - } else - { - if (e1->WindCnt + e2->WindDelta == 0 ) e1->WindCnt = -e1->WindCnt; - else e1->WindCnt += e2->WindDelta; - if ( e2->WindCnt - e1->WindDelta == 0 ) e2->WindCnt = -e2->WindCnt; - else e2->WindCnt -= e1->WindDelta; - } - } else - { - if (!IsEvenOddFillType(*e2)) e1->WindCnt2 += e2->WindDelta; - else e1->WindCnt2 = ( e1->WindCnt2 == 0 ) ? 1 : 0; - if (!IsEvenOddFillType(*e1)) e2->WindCnt2 -= e1->WindDelta; - else e2->WindCnt2 = ( e2->WindCnt2 == 0 ) ? 1 : 0; - } - - PolyFillType e1FillType, e2FillType, e1FillType2, e2FillType2; - if (e1->PolyTyp == ptSubject) - { - e1FillType = m_SubjFillType; - e1FillType2 = m_ClipFillType; - } else - { - e1FillType = m_ClipFillType; - e1FillType2 = m_SubjFillType; - } - if (e2->PolyTyp == ptSubject) - { - e2FillType = m_SubjFillType; - e2FillType2 = m_ClipFillType; - } else - { - e2FillType = m_ClipFillType; - e2FillType2 = m_SubjFillType; - } - - cInt e1Wc, e2Wc; - switch (e1FillType) - { - case pftPositive: e1Wc = e1->WindCnt; break; - case pftNegative: e1Wc = -e1->WindCnt; break; - default: e1Wc = Abs(e1->WindCnt); - } - switch(e2FillType) - { - case pftPositive: e2Wc = e2->WindCnt; break; - case pftNegative: e2Wc = -e2->WindCnt; break; - default: e2Wc = Abs(e2->WindCnt); - } - - if ( e1Contributing && e2Contributing ) - { - if ((e1Wc != 0 && e1Wc != 1) || (e2Wc != 0 && e2Wc != 1) || - (e1->PolyTyp != e2->PolyTyp && m_ClipType != ctXor) ) - { - AddLocalMaxPoly(e1, e2, Pt); - } - else - { - AddOutPt(e1, Pt); - AddOutPt(e2, Pt); - SwapSides( *e1 , *e2 ); - SwapPolyIndexes( *e1 , *e2 ); - } - } - else if ( e1Contributing ) - { - if (e2Wc == 0 || e2Wc == 1) - { - AddOutPt(e1, Pt); - SwapSides(*e1, *e2); - SwapPolyIndexes(*e1, *e2); - } - } - else if ( e2Contributing ) - { - if (e1Wc == 0 || e1Wc == 1) - { - AddOutPt(e2, Pt); - SwapSides(*e1, *e2); - SwapPolyIndexes(*e1, *e2); - } - } - else if ( (e1Wc == 0 || e1Wc == 1) && (e2Wc == 0 || e2Wc == 1)) - { - //neither edge is currently contributing ... - - cInt e1Wc2, e2Wc2; - switch (e1FillType2) - { - case pftPositive: e1Wc2 = e1->WindCnt2; break; - case pftNegative : e1Wc2 = -e1->WindCnt2; break; - default: e1Wc2 = Abs(e1->WindCnt2); - } - switch (e2FillType2) - { - case pftPositive: e2Wc2 = e2->WindCnt2; break; - case pftNegative: e2Wc2 = -e2->WindCnt2; break; - default: e2Wc2 = Abs(e2->WindCnt2); - } - - if (e1->PolyTyp != e2->PolyTyp) - { - AddLocalMinPoly(e1, e2, Pt); - } - else if (e1Wc == 1 && e2Wc == 1) - switch( m_ClipType ) { - case ctIntersection: - if (e1Wc2 > 0 && e2Wc2 > 0) - AddLocalMinPoly(e1, e2, Pt); - break; - case ctUnion: - if ( e1Wc2 <= 0 && e2Wc2 <= 0 ) - AddLocalMinPoly(e1, e2, Pt); - break; - case ctDifference: - if (((e1->PolyTyp == ptClip) && (e1Wc2 > 0) && (e2Wc2 > 0)) || - ((e1->PolyTyp == ptSubject) && (e1Wc2 <= 0) && (e2Wc2 <= 0))) - AddLocalMinPoly(e1, e2, Pt); - break; - case ctXor: - AddLocalMinPoly(e1, e2, Pt); - } - else - SwapSides( *e1, *e2 ); - } -} -//------------------------------------------------------------------------------ - -void Clipper::SetHoleState(TEdge *e, OutRec *outrec) -{ - TEdge *e2 = e->PrevInAEL; - TEdge *eTmp = 0; - while (e2) - { - if (e2->OutIdx >= 0 && e2->WindDelta != 0) - { - if (!eTmp) eTmp = e2; - else if (eTmp->OutIdx == e2->OutIdx) eTmp = 0; - } - e2 = e2->PrevInAEL; - } - if (!eTmp) - { - outrec->FirstLeft = 0; - outrec->IsHole = false; - } - else - { - outrec->FirstLeft = m_PolyOuts[eTmp->OutIdx]; - outrec->IsHole = !outrec->FirstLeft->IsHole; - } -} -//------------------------------------------------------------------------------ - -OutRec* GetLowermostRec(OutRec *outRec1, OutRec *outRec2) -{ - //work out which polygon fragment has the correct hole state ... - if (!outRec1->BottomPt) - outRec1->BottomPt = GetBottomPt(outRec1->Pts); - if (!outRec2->BottomPt) - outRec2->BottomPt = GetBottomPt(outRec2->Pts); - OutPt *OutPt1 = outRec1->BottomPt; - OutPt *OutPt2 = outRec2->BottomPt; - if (OutPt1->Pt.Y > OutPt2->Pt.Y) return outRec1; - else if (OutPt1->Pt.Y < OutPt2->Pt.Y) return outRec2; - else if (OutPt1->Pt.X < OutPt2->Pt.X) return outRec1; - else if (OutPt1->Pt.X > OutPt2->Pt.X) return outRec2; - else if (OutPt1->Next == OutPt1) return outRec2; - else if (OutPt2->Next == OutPt2) return outRec1; - else if (FirstIsBottomPt(OutPt1, OutPt2)) return outRec1; - else return outRec2; -} -//------------------------------------------------------------------------------ - -bool OutRec1RightOfOutRec2(OutRec* outRec1, OutRec* outRec2) -{ - do - { - outRec1 = outRec1->FirstLeft; - if (outRec1 == outRec2) return true; - } while (outRec1); - return false; -} -//------------------------------------------------------------------------------ - -OutRec* Clipper::GetOutRec(int Idx) -{ - OutRec* outrec = m_PolyOuts[Idx]; - while (outrec != m_PolyOuts[outrec->Idx]) - outrec = m_PolyOuts[outrec->Idx]; - return outrec; -} -//------------------------------------------------------------------------------ - -void Clipper::AppendPolygon(TEdge *e1, TEdge *e2) -{ - //get the start and ends of both output polygons ... - OutRec *outRec1 = m_PolyOuts[e1->OutIdx]; - OutRec *outRec2 = m_PolyOuts[e2->OutIdx]; - - OutRec *holeStateRec; - if (OutRec1RightOfOutRec2(outRec1, outRec2)) - holeStateRec = outRec2; - else if (OutRec1RightOfOutRec2(outRec2, outRec1)) - holeStateRec = outRec1; - else - holeStateRec = GetLowermostRec(outRec1, outRec2); - - //get the start and ends of both output polygons and - //join e2 poly onto e1 poly and delete pointers to e2 ... - - OutPt* p1_lft = outRec1->Pts; - OutPt* p1_rt = p1_lft->Prev; - OutPt* p2_lft = outRec2->Pts; - OutPt* p2_rt = p2_lft->Prev; - - //join e2 poly onto e1 poly and delete pointers to e2 ... - if( e1->Side == esLeft ) - { - if( e2->Side == esLeft ) - { - //z y x a b c - ReversePolyPtLinks(p2_lft); - p2_lft->Next = p1_lft; - p1_lft->Prev = p2_lft; - p1_rt->Next = p2_rt; - p2_rt->Prev = p1_rt; - outRec1->Pts = p2_rt; - } else - { - //x y z a b c - p2_rt->Next = p1_lft; - p1_lft->Prev = p2_rt; - p2_lft->Prev = p1_rt; - p1_rt->Next = p2_lft; - outRec1->Pts = p2_lft; - } - } else - { - if( e2->Side == esRight ) - { - //a b c z y x - ReversePolyPtLinks(p2_lft); - p1_rt->Next = p2_rt; - p2_rt->Prev = p1_rt; - p2_lft->Next = p1_lft; - p1_lft->Prev = p2_lft; - } else - { - //a b c x y z - p1_rt->Next = p2_lft; - p2_lft->Prev = p1_rt; - p1_lft->Prev = p2_rt; - p2_rt->Next = p1_lft; - } - } - - outRec1->BottomPt = 0; - if (holeStateRec == outRec2) - { - if (outRec2->FirstLeft != outRec1) - outRec1->FirstLeft = outRec2->FirstLeft; - outRec1->IsHole = outRec2->IsHole; - } - outRec2->Pts = 0; - outRec2->BottomPt = 0; - outRec2->FirstLeft = outRec1; - - int OKIdx = e1->OutIdx; - int ObsoleteIdx = e2->OutIdx; - - e1->OutIdx = Unassigned; //nb: safe because we only get here via AddLocalMaxPoly - e2->OutIdx = Unassigned; - - TEdge* e = m_ActiveEdges; - while( e ) - { - if( e->OutIdx == ObsoleteIdx ) - { - e->OutIdx = OKIdx; - e->Side = e1->Side; - break; - } - e = e->NextInAEL; - } - - outRec2->Idx = outRec1->Idx; -} -//------------------------------------------------------------------------------ - -OutPt* Clipper::AddOutPt(TEdge *e, const IntPoint &pt) -{ - if( e->OutIdx < 0 ) - { - OutRec *outRec = CreateOutRec(); - outRec->IsOpen = (e->WindDelta == 0); - OutPt* newOp = new OutPt; - outRec->Pts = newOp; - newOp->Idx = outRec->Idx; - newOp->Pt = pt; - newOp->Next = newOp; - newOp->Prev = newOp; - if (!outRec->IsOpen) - SetHoleState(e, outRec); - e->OutIdx = outRec->Idx; - return newOp; - } else - { - OutRec *outRec = m_PolyOuts[e->OutIdx]; - //OutRec.Pts is the 'Left-most' point & OutRec.Pts.Prev is the 'Right-most' - OutPt* op = outRec->Pts; - - bool ToFront = (e->Side == esLeft); - if (ToFront && (pt == op->Pt)) return op; - else if (!ToFront && (pt == op->Prev->Pt)) return op->Prev; - - OutPt* newOp = new OutPt; - newOp->Idx = outRec->Idx; - newOp->Pt = pt; - newOp->Next = op; - newOp->Prev = op->Prev; - newOp->Prev->Next = newOp; - op->Prev = newOp; - if (ToFront) outRec->Pts = newOp; - return newOp; - } -} -//------------------------------------------------------------------------------ - -OutPt* Clipper::GetLastOutPt(TEdge *e) -{ - OutRec *outRec = m_PolyOuts[e->OutIdx]; - if (e->Side == esLeft) - return outRec->Pts; - else - return outRec->Pts->Prev; -} -//------------------------------------------------------------------------------ - -void Clipper::ProcessHorizontals() -{ - TEdge* horzEdge; - while (PopEdgeFromSEL(horzEdge)) - ProcessHorizontal(horzEdge); -} -//------------------------------------------------------------------------------ - -inline bool IsMinima(TEdge *e) -{ - return e && (e->Prev->NextInLML != e) && (e->Next->NextInLML != e); -} -//------------------------------------------------------------------------------ - -inline bool IsMaxima(TEdge *e, const cInt Y) -{ - return e && e->Top.Y == Y && !e->NextInLML; -} -//------------------------------------------------------------------------------ - -inline bool IsIntermediate(TEdge *e, const cInt Y) -{ - return e->Top.Y == Y && e->NextInLML; -} -//------------------------------------------------------------------------------ - -TEdge *GetMaximaPair(TEdge *e) -{ - if ((e->Next->Top == e->Top) && !e->Next->NextInLML) - return e->Next; - else if ((e->Prev->Top == e->Top) && !e->Prev->NextInLML) - return e->Prev; - else return 0; -} -//------------------------------------------------------------------------------ - -TEdge *GetMaximaPairEx(TEdge *e) -{ - //as GetMaximaPair() but returns 0 if MaxPair isn't in AEL (unless it's horizontal) - TEdge* result = GetMaximaPair(e); - if (result && (result->OutIdx == Skip || - (result->NextInAEL == result->PrevInAEL && !IsHorizontal(*result)))) return 0; - return result; -} -//------------------------------------------------------------------------------ - -void Clipper::SwapPositionsInSEL(TEdge *Edge1, TEdge *Edge2) -{ - if( !( Edge1->NextInSEL ) && !( Edge1->PrevInSEL ) ) return; - if( !( Edge2->NextInSEL ) && !( Edge2->PrevInSEL ) ) return; - - if( Edge1->NextInSEL == Edge2 ) - { - TEdge* Next = Edge2->NextInSEL; - if( Next ) Next->PrevInSEL = Edge1; - TEdge* Prev = Edge1->PrevInSEL; - if( Prev ) Prev->NextInSEL = Edge2; - Edge2->PrevInSEL = Prev; - Edge2->NextInSEL = Edge1; - Edge1->PrevInSEL = Edge2; - Edge1->NextInSEL = Next; - } - else if( Edge2->NextInSEL == Edge1 ) - { - TEdge* Next = Edge1->NextInSEL; - if( Next ) Next->PrevInSEL = Edge2; - TEdge* Prev = Edge2->PrevInSEL; - if( Prev ) Prev->NextInSEL = Edge1; - Edge1->PrevInSEL = Prev; - Edge1->NextInSEL = Edge2; - Edge2->PrevInSEL = Edge1; - Edge2->NextInSEL = Next; - } - else - { - TEdge* Next = Edge1->NextInSEL; - TEdge* Prev = Edge1->PrevInSEL; - Edge1->NextInSEL = Edge2->NextInSEL; - if( Edge1->NextInSEL ) Edge1->NextInSEL->PrevInSEL = Edge1; - Edge1->PrevInSEL = Edge2->PrevInSEL; - if( Edge1->PrevInSEL ) Edge1->PrevInSEL->NextInSEL = Edge1; - Edge2->NextInSEL = Next; - if( Edge2->NextInSEL ) Edge2->NextInSEL->PrevInSEL = Edge2; - Edge2->PrevInSEL = Prev; - if( Edge2->PrevInSEL ) Edge2->PrevInSEL->NextInSEL = Edge2; - } - - if( !Edge1->PrevInSEL ) m_SortedEdges = Edge1; - else if( !Edge2->PrevInSEL ) m_SortedEdges = Edge2; -} -//------------------------------------------------------------------------------ - -TEdge* GetNextInAEL(TEdge *e, Direction dir) -{ - return dir == dLeftToRight ? e->NextInAEL : e->PrevInAEL; -} -//------------------------------------------------------------------------------ - -void GetHorzDirection(TEdge& HorzEdge, Direction& Dir, cInt& Left, cInt& Right) -{ - if (HorzEdge.Bot.X < HorzEdge.Top.X) - { - Left = HorzEdge.Bot.X; - Right = HorzEdge.Top.X; - Dir = dLeftToRight; - } else - { - Left = HorzEdge.Top.X; - Right = HorzEdge.Bot.X; - Dir = dRightToLeft; - } -} -//------------------------------------------------------------------------ - -/******************************************************************************* -* Notes: Horizontal edges (HEs) at scanline intersections (ie at the Top or * -* Bottom of a scanbeam) are processed as if layered. The order in which HEs * -* are processed doesn't matter. HEs intersect with other HE Bot.Xs only [#] * -* (or they could intersect with Top.Xs only, ie EITHER Bot.Xs OR Top.Xs), * -* and with other non-horizontal edges [*]. Once these intersections are * -* processed, intermediate HEs then 'promote' the Edge above (NextInLML) into * -* the AEL. These 'promoted' edges may in turn intersect [%] with other HEs. * -*******************************************************************************/ - -void Clipper::ProcessHorizontal(TEdge *horzEdge) -{ - Direction dir; - cInt horzLeft, horzRight; - bool IsOpen = (horzEdge->WindDelta == 0); - - GetHorzDirection(*horzEdge, dir, horzLeft, horzRight); - - TEdge* eLastHorz = horzEdge, *eMaxPair = 0; - while (eLastHorz->NextInLML && IsHorizontal(*eLastHorz->NextInLML)) - eLastHorz = eLastHorz->NextInLML; - if (!eLastHorz->NextInLML) - eMaxPair = GetMaximaPair(eLastHorz); - - MaximaList::const_iterator maxIt; - MaximaList::const_reverse_iterator maxRit; - if (m_Maxima.size() > 0) - { - //get the first maxima in range (X) ... - if (dir == dLeftToRight) - { - maxIt = m_Maxima.begin(); - while (maxIt != m_Maxima.end() && *maxIt <= horzEdge->Bot.X) maxIt++; - if (maxIt != m_Maxima.end() && *maxIt >= eLastHorz->Top.X) - maxIt = m_Maxima.end(); - } - else - { - maxRit = m_Maxima.rbegin(); - while (maxRit != m_Maxima.rend() && *maxRit > horzEdge->Bot.X) maxRit++; - if (maxRit != m_Maxima.rend() && *maxRit <= eLastHorz->Top.X) - maxRit = m_Maxima.rend(); - } - } - - OutPt* op1 = 0; - - for (;;) //loop through consec. horizontal edges - { - - bool IsLastHorz = (horzEdge == eLastHorz); - TEdge* e = GetNextInAEL(horzEdge, dir); - while(e) - { - - //this code block inserts extra coords into horizontal edges (in output - //polygons) whereever maxima touch these horizontal edges. This helps - //'simplifying' polygons (ie if the Simplify property is set). - if (m_Maxima.size() > 0) - { - if (dir == dLeftToRight) - { - while (maxIt != m_Maxima.end() && *maxIt < e->Curr.X) - { - if (horzEdge->OutIdx >= 0 && !IsOpen) - AddOutPt(horzEdge, IntPoint(*maxIt, horzEdge->Bot.Y)); - maxIt++; - } - } - else - { - while (maxRit != m_Maxima.rend() && *maxRit > e->Curr.X) - { - if (horzEdge->OutIdx >= 0 && !IsOpen) - AddOutPt(horzEdge, IntPoint(*maxRit, horzEdge->Bot.Y)); - maxRit++; - } - } - }; - - if ((dir == dLeftToRight && e->Curr.X > horzRight) || - (dir == dRightToLeft && e->Curr.X < horzLeft)) break; - - //Also break if we've got to the end of an intermediate horizontal edge ... - //nb: Smaller Dx's are to the right of larger Dx's ABOVE the horizontal. - if (e->Curr.X == horzEdge->Top.X && horzEdge->NextInLML && - e->Dx < horzEdge->NextInLML->Dx) break; - - if (horzEdge->OutIdx >= 0 && !IsOpen) //note: may be done multiple times - { -#ifdef use_xyz - if (dir == dLeftToRight) SetZ(e->Curr, *horzEdge, *e); - else SetZ(e->Curr, *e, *horzEdge); -#endif - op1 = AddOutPt(horzEdge, e->Curr); - TEdge* eNextHorz = m_SortedEdges; - while (eNextHorz) - { - if (eNextHorz->OutIdx >= 0 && - HorzSegmentsOverlap(horzEdge->Bot.X, - horzEdge->Top.X, eNextHorz->Bot.X, eNextHorz->Top.X)) - { - OutPt* op2 = GetLastOutPt(eNextHorz); - AddJoin(op2, op1, eNextHorz->Top); - } - eNextHorz = eNextHorz->NextInSEL; - } - AddGhostJoin(op1, horzEdge->Bot); - } - - //OK, so far we're still in range of the horizontal Edge but make sure - //we're at the last of consec. horizontals when matching with eMaxPair - if(e == eMaxPair && IsLastHorz) - { - if (horzEdge->OutIdx >= 0) - AddLocalMaxPoly(horzEdge, eMaxPair, horzEdge->Top); - DeleteFromAEL(horzEdge); - DeleteFromAEL(eMaxPair); - return; - } - - if(dir == dLeftToRight) - { - IntPoint Pt = IntPoint(e->Curr.X, horzEdge->Curr.Y); - IntersectEdges(horzEdge, e, Pt); - } - else - { - IntPoint Pt = IntPoint(e->Curr.X, horzEdge->Curr.Y); - IntersectEdges( e, horzEdge, Pt); - } - TEdge* eNext = GetNextInAEL(e, dir); - SwapPositionsInAEL( horzEdge, e ); - e = eNext; - } //end while(e) - - //Break out of loop if HorzEdge.NextInLML is not also horizontal ... - if (!horzEdge->NextInLML || !IsHorizontal(*horzEdge->NextInLML)) break; - - UpdateEdgeIntoAEL(horzEdge); - if (horzEdge->OutIdx >= 0) AddOutPt(horzEdge, horzEdge->Bot); - GetHorzDirection(*horzEdge, dir, horzLeft, horzRight); - - } //end for (;;) - - if (horzEdge->OutIdx >= 0 && !op1) - { - op1 = GetLastOutPt(horzEdge); - TEdge* eNextHorz = m_SortedEdges; - while (eNextHorz) - { - if (eNextHorz->OutIdx >= 0 && - HorzSegmentsOverlap(horzEdge->Bot.X, - horzEdge->Top.X, eNextHorz->Bot.X, eNextHorz->Top.X)) - { - OutPt* op2 = GetLastOutPt(eNextHorz); - AddJoin(op2, op1, eNextHorz->Top); - } - eNextHorz = eNextHorz->NextInSEL; - } - AddGhostJoin(op1, horzEdge->Top); - } - - if (horzEdge->NextInLML) - { - if(horzEdge->OutIdx >= 0) - { - op1 = AddOutPt( horzEdge, horzEdge->Top); - UpdateEdgeIntoAEL(horzEdge); - if (horzEdge->WindDelta == 0) return; - //nb: HorzEdge is no longer horizontal here - TEdge* ePrev = horzEdge->PrevInAEL; - TEdge* eNext = horzEdge->NextInAEL; - if (ePrev && ePrev->Curr.X == horzEdge->Bot.X && - ePrev->Curr.Y == horzEdge->Bot.Y && ePrev->WindDelta != 0 && - (ePrev->OutIdx >= 0 && ePrev->Curr.Y > ePrev->Top.Y && - SlopesEqual(*horzEdge, *ePrev, m_UseFullRange))) - { - OutPt* op2 = AddOutPt(ePrev, horzEdge->Bot); - AddJoin(op1, op2, horzEdge->Top); - } - else if (eNext && eNext->Curr.X == horzEdge->Bot.X && - eNext->Curr.Y == horzEdge->Bot.Y && eNext->WindDelta != 0 && - eNext->OutIdx >= 0 && eNext->Curr.Y > eNext->Top.Y && - SlopesEqual(*horzEdge, *eNext, m_UseFullRange)) - { - OutPt* op2 = AddOutPt(eNext, horzEdge->Bot); - AddJoin(op1, op2, horzEdge->Top); - } - } - else - UpdateEdgeIntoAEL(horzEdge); - } - else - { - if (horzEdge->OutIdx >= 0) AddOutPt(horzEdge, horzEdge->Top); - DeleteFromAEL(horzEdge); - } -} -//------------------------------------------------------------------------------ - -bool Clipper::ProcessIntersections(const cInt topY) -{ - if( !m_ActiveEdges ) return true; - try { - BuildIntersectList(topY); - size_t IlSize = m_IntersectList.size(); - if (IlSize == 0) return true; - if (IlSize == 1 || FixupIntersectionOrder()) ProcessIntersectList(); - else return false; - } - catch(...) - { - m_SortedEdges = 0; - DisposeIntersectNodes(); - throw clipperException("ProcessIntersections error"); - } - m_SortedEdges = 0; - return true; -} -//------------------------------------------------------------------------------ - -void Clipper::DisposeIntersectNodes() -{ - for (size_t i = 0; i < m_IntersectList.size(); ++i ) - delete m_IntersectList[i]; - m_IntersectList.clear(); -} -//------------------------------------------------------------------------------ - -void Clipper::BuildIntersectList(const cInt topY) -{ - if ( !m_ActiveEdges ) return; - - //prepare for sorting ... - TEdge* e = m_ActiveEdges; - m_SortedEdges = e; - while( e ) - { - e->PrevInSEL = e->PrevInAEL; - e->NextInSEL = e->NextInAEL; - e->Curr.X = TopX( *e, topY ); - e = e->NextInAEL; - } - - //bubblesort ... - bool isModified; - do - { - isModified = false; - e = m_SortedEdges; - while( e->NextInSEL ) - { - TEdge *eNext = e->NextInSEL; - IntPoint Pt; - if(e->Curr.X > eNext->Curr.X) - { - IntersectPoint(*e, *eNext, Pt); - if (Pt.Y < topY) Pt = IntPoint(TopX(*e, topY), topY); - IntersectNode * newNode = new IntersectNode; - newNode->Edge1 = e; - newNode->Edge2 = eNext; - newNode->Pt = Pt; - m_IntersectList.push_back(newNode); - - SwapPositionsInSEL(e, eNext); - isModified = true; - } - else - e = eNext; - } - if( e->PrevInSEL ) e->PrevInSEL->NextInSEL = 0; - else break; - } - while ( isModified ); - m_SortedEdges = 0; //important -} -//------------------------------------------------------------------------------ - - -void Clipper::ProcessIntersectList() -{ - for (size_t i = 0; i < m_IntersectList.size(); ++i) - { - IntersectNode* iNode = m_IntersectList[i]; - { - IntersectEdges( iNode->Edge1, iNode->Edge2, iNode->Pt); - SwapPositionsInAEL( iNode->Edge1 , iNode->Edge2 ); - } - delete iNode; - } - m_IntersectList.clear(); -} -//------------------------------------------------------------------------------ - -bool IntersectListSort(IntersectNode* node1, IntersectNode* node2) -{ - return node2->Pt.Y < node1->Pt.Y; -} -//------------------------------------------------------------------------------ - -inline bool EdgesAdjacent(const IntersectNode &inode) -{ - return (inode.Edge1->NextInSEL == inode.Edge2) || - (inode.Edge1->PrevInSEL == inode.Edge2); -} -//------------------------------------------------------------------------------ - -bool Clipper::FixupIntersectionOrder() -{ - //pre-condition: intersections are sorted Bottom-most first. - //Now it's crucial that intersections are made only between adjacent edges, - //so to ensure this the order of intersections may need adjusting ... - CopyAELToSEL(); - std::sort(m_IntersectList.begin(), m_IntersectList.end(), IntersectListSort); - size_t cnt = m_IntersectList.size(); - for (size_t i = 0; i < cnt; ++i) - { - if (!EdgesAdjacent(*m_IntersectList[i])) - { - size_t j = i + 1; - while (j < cnt && !EdgesAdjacent(*m_IntersectList[j])) j++; - if (j == cnt) return false; - std::swap(m_IntersectList[i], m_IntersectList[j]); - } - SwapPositionsInSEL(m_IntersectList[i]->Edge1, m_IntersectList[i]->Edge2); - } - return true; -} -//------------------------------------------------------------------------------ - -void Clipper::DoMaxima(TEdge *e) -{ - TEdge* eMaxPair = GetMaximaPairEx(e); - if (!eMaxPair) - { - if (e->OutIdx >= 0) - AddOutPt(e, e->Top); - DeleteFromAEL(e); - return; - } - - TEdge* eNext = e->NextInAEL; - while(eNext && eNext != eMaxPair) - { - IntersectEdges(e, eNext, e->Top); - SwapPositionsInAEL(e, eNext); - eNext = e->NextInAEL; - } - - if(e->OutIdx == Unassigned && eMaxPair->OutIdx == Unassigned) - { - DeleteFromAEL(e); - DeleteFromAEL(eMaxPair); - } - else if( e->OutIdx >= 0 && eMaxPair->OutIdx >= 0 ) - { - if (e->OutIdx >= 0) AddLocalMaxPoly(e, eMaxPair, e->Top); - DeleteFromAEL(e); - DeleteFromAEL(eMaxPair); - } -#ifdef use_lines - else if (e->WindDelta == 0) - { - if (e->OutIdx >= 0) - { - AddOutPt(e, e->Top); - e->OutIdx = Unassigned; - } - DeleteFromAEL(e); - - if (eMaxPair->OutIdx >= 0) - { - AddOutPt(eMaxPair, e->Top); - eMaxPair->OutIdx = Unassigned; - } - DeleteFromAEL(eMaxPair); - } -#endif - else throw clipperException("DoMaxima error"); -} -//------------------------------------------------------------------------------ - -void Clipper::ProcessEdgesAtTopOfScanbeam(const cInt topY) -{ - TEdge* e = m_ActiveEdges; - while( e ) - { - //1. process maxima, treating them as if they're 'bent' horizontal edges, - // but exclude maxima with horizontal edges. nb: e can't be a horizontal. - bool IsMaximaEdge = IsMaxima(e, topY); - - if(IsMaximaEdge) - { - TEdge* eMaxPair = GetMaximaPairEx(e); - IsMaximaEdge = (!eMaxPair || !IsHorizontal(*eMaxPair)); - } - - if(IsMaximaEdge) - { - if (m_StrictSimple) m_Maxima.push_back(e->Top.X); - TEdge* ePrev = e->PrevInAEL; - DoMaxima(e); - if( !ePrev ) e = m_ActiveEdges; - else e = ePrev->NextInAEL; - } - else - { - //2. promote horizontal edges, otherwise update Curr.X and Curr.Y ... - if (IsIntermediate(e, topY) && IsHorizontal(*e->NextInLML)) - { - UpdateEdgeIntoAEL(e); - if (e->OutIdx >= 0) - AddOutPt(e, e->Bot); - AddEdgeToSEL(e); - } - else - { - e->Curr.X = TopX( *e, topY ); - e->Curr.Y = topY; -#ifdef use_xyz - e->Curr.Z = topY == e->Top.Y ? e->Top.Z : (topY == e->Bot.Y ? e->Bot.Z : 0); -#endif - } - - //When StrictlySimple and 'e' is being touched by another edge, then - //make sure both edges have a vertex here ... - if (m_StrictSimple) - { - TEdge* ePrev = e->PrevInAEL; - if ((e->OutIdx >= 0) && (e->WindDelta != 0) && ePrev && (ePrev->OutIdx >= 0) && - (ePrev->Curr.X == e->Curr.X) && (ePrev->WindDelta != 0)) - { - IntPoint pt = e->Curr; -#ifdef use_xyz - SetZ(pt, *ePrev, *e); -#endif - OutPt* op = AddOutPt(ePrev, pt); - OutPt* op2 = AddOutPt(e, pt); - AddJoin(op, op2, pt); //StrictlySimple (type-3) join - } - } - - e = e->NextInAEL; - } - } - - //3. Process horizontals at the Top of the scanbeam ... - m_Maxima.sort(); - ProcessHorizontals(); - m_Maxima.clear(); - - //4. Promote intermediate vertices ... - e = m_ActiveEdges; - while(e) - { - if(IsIntermediate(e, topY)) - { - OutPt* op = 0; - if( e->OutIdx >= 0 ) - op = AddOutPt(e, e->Top); - UpdateEdgeIntoAEL(e); - - //if output polygons share an edge, they'll need joining later ... - TEdge* ePrev = e->PrevInAEL; - TEdge* eNext = e->NextInAEL; - if (ePrev && ePrev->Curr.X == e->Bot.X && - ePrev->Curr.Y == e->Bot.Y && op && - ePrev->OutIdx >= 0 && ePrev->Curr.Y > ePrev->Top.Y && - SlopesEqual(e->Curr, e->Top, ePrev->Curr, ePrev->Top, m_UseFullRange) && - (e->WindDelta != 0) && (ePrev->WindDelta != 0)) - { - OutPt* op2 = AddOutPt(ePrev, e->Bot); - AddJoin(op, op2, e->Top); - } - else if (eNext && eNext->Curr.X == e->Bot.X && - eNext->Curr.Y == e->Bot.Y && op && - eNext->OutIdx >= 0 && eNext->Curr.Y > eNext->Top.Y && - SlopesEqual(e->Curr, e->Top, eNext->Curr, eNext->Top, m_UseFullRange) && - (e->WindDelta != 0) && (eNext->WindDelta != 0)) - { - OutPt* op2 = AddOutPt(eNext, e->Bot); - AddJoin(op, op2, e->Top); - } - } - e = e->NextInAEL; - } -} -//------------------------------------------------------------------------------ - -void Clipper::FixupOutPolyline(OutRec &outrec) -{ - OutPt *pp = outrec.Pts; - OutPt *lastPP = pp->Prev; - while (pp != lastPP) - { - pp = pp->Next; - if (pp->Pt == pp->Prev->Pt) - { - if (pp == lastPP) lastPP = pp->Prev; - OutPt *tmpPP = pp->Prev; - tmpPP->Next = pp->Next; - pp->Next->Prev = tmpPP; - delete pp; - pp = tmpPP; - } - } - - if (pp == pp->Prev) - { - DisposeOutPts(pp); - outrec.Pts = 0; - return; - } -} -//------------------------------------------------------------------------------ - -void Clipper::FixupOutPolygon(OutRec &outrec) -{ - //FixupOutPolygon() - removes duplicate points and simplifies consecutive - //parallel edges by removing the middle vertex. - OutPt *lastOK = 0; - outrec.BottomPt = 0; - OutPt *pp = outrec.Pts; - bool preserveCol = m_PreserveCollinear || m_StrictSimple; - - for (;;) - { - if (pp->Prev == pp || pp->Prev == pp->Next) - { - DisposeOutPts(pp); - outrec.Pts = 0; - return; - } - - //test for duplicate points and collinear edges ... - if ((pp->Pt == pp->Next->Pt) || (pp->Pt == pp->Prev->Pt) || - (SlopesEqual(pp->Prev->Pt, pp->Pt, pp->Next->Pt, m_UseFullRange) && - (!preserveCol || !Pt2IsBetweenPt1AndPt3(pp->Prev->Pt, pp->Pt, pp->Next->Pt)))) - { - lastOK = 0; - OutPt *tmp = pp; - pp->Prev->Next = pp->Next; - pp->Next->Prev = pp->Prev; - pp = pp->Prev; - delete tmp; - } - else if (pp == lastOK) break; - else - { - if (!lastOK) lastOK = pp; - pp = pp->Next; - } - } - outrec.Pts = pp; -} -//------------------------------------------------------------------------------ - -int PointCount(OutPt *Pts) -{ - if (!Pts) return 0; - int result = 0; - OutPt* p = Pts; - do - { - result++; - p = p->Next; - } - while (p != Pts); - return result; -} -//------------------------------------------------------------------------------ - -void Clipper::BuildResult(Paths &polys) -{ - polys.reserve(m_PolyOuts.size()); - for (PolyOutList::size_type i = 0; i < m_PolyOuts.size(); ++i) - { - if (!m_PolyOuts[i]->Pts) continue; - Path pg; - OutPt* p = m_PolyOuts[i]->Pts->Prev; - int cnt = PointCount(p); - if (cnt < 2) continue; - pg.reserve(cnt); - for (int i = 0; i < cnt; ++i) - { - pg.push_back(p->Pt); - p = p->Prev; - } - polys.push_back(pg); - } -} -//------------------------------------------------------------------------------ - -void Clipper::BuildResult2(PolyTree& polytree) -{ - polytree.Clear(); - polytree.AllNodes.reserve(m_PolyOuts.size()); - //add each output polygon/contour to polytree ... - for (PolyOutList::size_type i = 0; i < m_PolyOuts.size(); i++) - { - OutRec* outRec = m_PolyOuts[i]; - int cnt = PointCount(outRec->Pts); - if ((outRec->IsOpen && cnt < 2) || (!outRec->IsOpen && cnt < 3)) continue; - FixHoleLinkage(*outRec); - PolyNode* pn = new PolyNode(); - //nb: polytree takes ownership of all the PolyNodes - polytree.AllNodes.push_back(pn); - outRec->PolyNd = pn; - pn->Parent = 0; - pn->Index = 0; - pn->Contour.reserve(cnt); - OutPt *op = outRec->Pts->Prev; - for (int j = 0; j < cnt; j++) - { - pn->Contour.push_back(op->Pt); - op = op->Prev; - } - } - - //fixup PolyNode links etc ... - polytree.Childs.reserve(m_PolyOuts.size()); - for (PolyOutList::size_type i = 0; i < m_PolyOuts.size(); i++) - { - OutRec* outRec = m_PolyOuts[i]; - if (!outRec->PolyNd) continue; - if (outRec->IsOpen) - { - outRec->PolyNd->m_IsOpen = true; - polytree.AddChild(*outRec->PolyNd); - } - else if (outRec->FirstLeft && outRec->FirstLeft->PolyNd) - outRec->FirstLeft->PolyNd->AddChild(*outRec->PolyNd); - else - polytree.AddChild(*outRec->PolyNd); - } -} -//------------------------------------------------------------------------------ - -void SwapIntersectNodes(IntersectNode &int1, IntersectNode &int2) -{ - //just swap the contents (because fIntersectNodes is a single-linked-list) - IntersectNode inode = int1; //gets a copy of Int1 - int1.Edge1 = int2.Edge1; - int1.Edge2 = int2.Edge2; - int1.Pt = int2.Pt; - int2.Edge1 = inode.Edge1; - int2.Edge2 = inode.Edge2; - int2.Pt = inode.Pt; -} -//------------------------------------------------------------------------------ - -inline bool E2InsertsBeforeE1(TEdge &e1, TEdge &e2) -{ - if (e2.Curr.X == e1.Curr.X) - { - if (e2.Top.Y > e1.Top.Y) - return e2.Top.X < TopX(e1, e2.Top.Y); - else return e1.Top.X > TopX(e2, e1.Top.Y); - } - else return e2.Curr.X < e1.Curr.X; -} -//------------------------------------------------------------------------------ - -bool GetOverlap(const cInt a1, const cInt a2, const cInt b1, const cInt b2, - cInt& Left, cInt& Right) -{ - if (a1 < a2) - { - if (b1 < b2) {Left = std::max(a1,b1); Right = std::min(a2,b2);} - else {Left = std::max(a1,b2); Right = std::min(a2,b1);} - } - else - { - if (b1 < b2) {Left = std::max(a2,b1); Right = std::min(a1,b2);} - else {Left = std::max(a2,b2); Right = std::min(a1,b1);} - } - return Left < Right; -} -//------------------------------------------------------------------------------ - -inline void UpdateOutPtIdxs(OutRec& outrec) -{ - OutPt* op = outrec.Pts; - do - { - op->Idx = outrec.Idx; - op = op->Prev; - } - while(op != outrec.Pts); -} -//------------------------------------------------------------------------------ - -void Clipper::InsertEdgeIntoAEL(TEdge *edge, TEdge* startEdge) -{ - if(!m_ActiveEdges) - { - edge->PrevInAEL = 0; - edge->NextInAEL = 0; - m_ActiveEdges = edge; - } - else if(!startEdge && E2InsertsBeforeE1(*m_ActiveEdges, *edge)) - { - edge->PrevInAEL = 0; - edge->NextInAEL = m_ActiveEdges; - m_ActiveEdges->PrevInAEL = edge; - m_ActiveEdges = edge; - } - else - { - if(!startEdge) startEdge = m_ActiveEdges; - while(startEdge->NextInAEL && - !E2InsertsBeforeE1(*startEdge->NextInAEL , *edge)) - startEdge = startEdge->NextInAEL; - edge->NextInAEL = startEdge->NextInAEL; - if(startEdge->NextInAEL) startEdge->NextInAEL->PrevInAEL = edge; - edge->PrevInAEL = startEdge; - startEdge->NextInAEL = edge; - } -} -//---------------------------------------------------------------------- - -OutPt* DupOutPt(OutPt* outPt, bool InsertAfter) -{ - OutPt* result = new OutPt; - result->Pt = outPt->Pt; - result->Idx = outPt->Idx; - if (InsertAfter) - { - result->Next = outPt->Next; - result->Prev = outPt; - outPt->Next->Prev = result; - outPt->Next = result; - } - else - { - result->Prev = outPt->Prev; - result->Next = outPt; - outPt->Prev->Next = result; - outPt->Prev = result; - } - return result; -} -//------------------------------------------------------------------------------ - -bool JoinHorz(OutPt* op1, OutPt* op1b, OutPt* op2, OutPt* op2b, - const IntPoint Pt, bool DiscardLeft) -{ - Direction Dir1 = (op1->Pt.X > op1b->Pt.X ? dRightToLeft : dLeftToRight); - Direction Dir2 = (op2->Pt.X > op2b->Pt.X ? dRightToLeft : dLeftToRight); - if (Dir1 == Dir2) return false; - - //When DiscardLeft, we want Op1b to be on the Left of Op1, otherwise we - //want Op1b to be on the Right. (And likewise with Op2 and Op2b.) - //So, to facilitate this while inserting Op1b and Op2b ... - //when DiscardLeft, make sure we're AT or RIGHT of Pt before adding Op1b, - //otherwise make sure we're AT or LEFT of Pt. (Likewise with Op2b.) - if (Dir1 == dLeftToRight) - { - while (op1->Next->Pt.X <= Pt.X && - op1->Next->Pt.X >= op1->Pt.X && op1->Next->Pt.Y == Pt.Y) - op1 = op1->Next; - if (DiscardLeft && (op1->Pt.X != Pt.X)) op1 = op1->Next; - op1b = DupOutPt(op1, !DiscardLeft); - if (op1b->Pt != Pt) - { - op1 = op1b; - op1->Pt = Pt; - op1b = DupOutPt(op1, !DiscardLeft); - } - } - else - { - while (op1->Next->Pt.X >= Pt.X && - op1->Next->Pt.X <= op1->Pt.X && op1->Next->Pt.Y == Pt.Y) - op1 = op1->Next; - if (!DiscardLeft && (op1->Pt.X != Pt.X)) op1 = op1->Next; - op1b = DupOutPt(op1, DiscardLeft); - if (op1b->Pt != Pt) - { - op1 = op1b; - op1->Pt = Pt; - op1b = DupOutPt(op1, DiscardLeft); - } - } - - if (Dir2 == dLeftToRight) - { - while (op2->Next->Pt.X <= Pt.X && - op2->Next->Pt.X >= op2->Pt.X && op2->Next->Pt.Y == Pt.Y) - op2 = op2->Next; - if (DiscardLeft && (op2->Pt.X != Pt.X)) op2 = op2->Next; - op2b = DupOutPt(op2, !DiscardLeft); - if (op2b->Pt != Pt) - { - op2 = op2b; - op2->Pt = Pt; - op2b = DupOutPt(op2, !DiscardLeft); - }; - } else - { - while (op2->Next->Pt.X >= Pt.X && - op2->Next->Pt.X <= op2->Pt.X && op2->Next->Pt.Y == Pt.Y) - op2 = op2->Next; - if (!DiscardLeft && (op2->Pt.X != Pt.X)) op2 = op2->Next; - op2b = DupOutPt(op2, DiscardLeft); - if (op2b->Pt != Pt) - { - op2 = op2b; - op2->Pt = Pt; - op2b = DupOutPt(op2, DiscardLeft); - }; - }; - - if ((Dir1 == dLeftToRight) == DiscardLeft) - { - op1->Prev = op2; - op2->Next = op1; - op1b->Next = op2b; - op2b->Prev = op1b; - } - else - { - op1->Next = op2; - op2->Prev = op1; - op1b->Prev = op2b; - op2b->Next = op1b; - } - return true; -} -//------------------------------------------------------------------------------ - -bool Clipper::JoinPoints(Join *j, OutRec* outRec1, OutRec* outRec2) -{ - OutPt *op1 = j->OutPt1, *op1b; - OutPt *op2 = j->OutPt2, *op2b; - - //There are 3 kinds of joins for output polygons ... - //1. Horizontal joins where Join.OutPt1 & Join.OutPt2 are vertices anywhere - //along (horizontal) collinear edges (& Join.OffPt is on the same horizontal). - //2. Non-horizontal joins where Join.OutPt1 & Join.OutPt2 are at the same - //location at the Bottom of the overlapping segment (& Join.OffPt is above). - //3. StrictSimple joins where edges touch but are not collinear and where - //Join.OutPt1, Join.OutPt2 & Join.OffPt all share the same point. - bool isHorizontal = (j->OutPt1->Pt.Y == j->OffPt.Y); - - if (isHorizontal && (j->OffPt == j->OutPt1->Pt) && - (j->OffPt == j->OutPt2->Pt)) - { - //Strictly Simple join ... - if (outRec1 != outRec2) return false; - op1b = j->OutPt1->Next; - while (op1b != op1 && (op1b->Pt == j->OffPt)) - op1b = op1b->Next; - bool reverse1 = (op1b->Pt.Y > j->OffPt.Y); - op2b = j->OutPt2->Next; - while (op2b != op2 && (op2b->Pt == j->OffPt)) - op2b = op2b->Next; - bool reverse2 = (op2b->Pt.Y > j->OffPt.Y); - if (reverse1 == reverse2) return false; - if (reverse1) - { - op1b = DupOutPt(op1, false); - op2b = DupOutPt(op2, true); - op1->Prev = op2; - op2->Next = op1; - op1b->Next = op2b; - op2b->Prev = op1b; - j->OutPt1 = op1; - j->OutPt2 = op1b; - return true; - } else - { - op1b = DupOutPt(op1, true); - op2b = DupOutPt(op2, false); - op1->Next = op2; - op2->Prev = op1; - op1b->Prev = op2b; - op2b->Next = op1b; - j->OutPt1 = op1; - j->OutPt2 = op1b; - return true; - } - } - else if (isHorizontal) - { - //treat horizontal joins differently to non-horizontal joins since with - //them we're not yet sure where the overlapping is. OutPt1.Pt & OutPt2.Pt - //may be anywhere along the horizontal edge. - op1b = op1; - while (op1->Prev->Pt.Y == op1->Pt.Y && op1->Prev != op1b && op1->Prev != op2) - op1 = op1->Prev; - while (op1b->Next->Pt.Y == op1b->Pt.Y && op1b->Next != op1 && op1b->Next != op2) - op1b = op1b->Next; - if (op1b->Next == op1 || op1b->Next == op2) return false; //a flat 'polygon' - - op2b = op2; - while (op2->Prev->Pt.Y == op2->Pt.Y && op2->Prev != op2b && op2->Prev != op1b) - op2 = op2->Prev; - while (op2b->Next->Pt.Y == op2b->Pt.Y && op2b->Next != op2 && op2b->Next != op1) - op2b = op2b->Next; - if (op2b->Next == op2 || op2b->Next == op1) return false; //a flat 'polygon' - - cInt Left, Right; - //Op1 --> Op1b & Op2 --> Op2b are the extremites of the horizontal edges - if (!GetOverlap(op1->Pt.X, op1b->Pt.X, op2->Pt.X, op2b->Pt.X, Left, Right)) - return false; - - //DiscardLeftSide: when overlapping edges are joined, a spike will created - //which needs to be cleaned up. However, we don't want Op1 or Op2 caught up - //on the discard Side as either may still be needed for other joins ... - IntPoint Pt; - bool DiscardLeftSide; - if (op1->Pt.X >= Left && op1->Pt.X <= Right) - { - Pt = op1->Pt; DiscardLeftSide = (op1->Pt.X > op1b->Pt.X); - } - else if (op2->Pt.X >= Left&& op2->Pt.X <= Right) - { - Pt = op2->Pt; DiscardLeftSide = (op2->Pt.X > op2b->Pt.X); - } - else if (op1b->Pt.X >= Left && op1b->Pt.X <= Right) - { - Pt = op1b->Pt; DiscardLeftSide = op1b->Pt.X > op1->Pt.X; - } - else - { - Pt = op2b->Pt; DiscardLeftSide = (op2b->Pt.X > op2->Pt.X); - } - j->OutPt1 = op1; j->OutPt2 = op2; - return JoinHorz(op1, op1b, op2, op2b, Pt, DiscardLeftSide); - } else - { - //nb: For non-horizontal joins ... - // 1. Jr.OutPt1.Pt.Y == Jr.OutPt2.Pt.Y - // 2. Jr.OutPt1.Pt > Jr.OffPt.Y - - //make sure the polygons are correctly oriented ... - op1b = op1->Next; - while ((op1b->Pt == op1->Pt) && (op1b != op1)) op1b = op1b->Next; - bool Reverse1 = ((op1b->Pt.Y > op1->Pt.Y) || - !SlopesEqual(op1->Pt, op1b->Pt, j->OffPt, m_UseFullRange)); - if (Reverse1) - { - op1b = op1->Prev; - while ((op1b->Pt == op1->Pt) && (op1b != op1)) op1b = op1b->Prev; - if ((op1b->Pt.Y > op1->Pt.Y) || - !SlopesEqual(op1->Pt, op1b->Pt, j->OffPt, m_UseFullRange)) return false; - }; - op2b = op2->Next; - while ((op2b->Pt == op2->Pt) && (op2b != op2))op2b = op2b->Next; - bool Reverse2 = ((op2b->Pt.Y > op2->Pt.Y) || - !SlopesEqual(op2->Pt, op2b->Pt, j->OffPt, m_UseFullRange)); - if (Reverse2) - { - op2b = op2->Prev; - while ((op2b->Pt == op2->Pt) && (op2b != op2)) op2b = op2b->Prev; - if ((op2b->Pt.Y > op2->Pt.Y) || - !SlopesEqual(op2->Pt, op2b->Pt, j->OffPt, m_UseFullRange)) return false; - } - - if ((op1b == op1) || (op2b == op2) || (op1b == op2b) || - ((outRec1 == outRec2) && (Reverse1 == Reverse2))) return false; - - if (Reverse1) - { - op1b = DupOutPt(op1, false); - op2b = DupOutPt(op2, true); - op1->Prev = op2; - op2->Next = op1; - op1b->Next = op2b; - op2b->Prev = op1b; - j->OutPt1 = op1; - j->OutPt2 = op1b; - return true; - } else - { - op1b = DupOutPt(op1, true); - op2b = DupOutPt(op2, false); - op1->Next = op2; - op2->Prev = op1; - op1b->Prev = op2b; - op2b->Next = op1b; - j->OutPt1 = op1; - j->OutPt2 = op1b; - return true; - } - } -} -//---------------------------------------------------------------------- - -static OutRec* ParseFirstLeft(OutRec* FirstLeft) -{ - while (FirstLeft && !FirstLeft->Pts) - FirstLeft = FirstLeft->FirstLeft; - return FirstLeft; -} -//------------------------------------------------------------------------------ - -void Clipper::FixupFirstLefts1(OutRec* OldOutRec, OutRec* NewOutRec) -{ - //tests if NewOutRec contains the polygon before reassigning FirstLeft - for (PolyOutList::size_type i = 0; i < m_PolyOuts.size(); ++i) - { - OutRec* outRec = m_PolyOuts[i]; - OutRec* firstLeft = ParseFirstLeft(outRec->FirstLeft); - if (outRec->Pts && firstLeft == OldOutRec) - { - if (Poly2ContainsPoly1(outRec->Pts, NewOutRec->Pts)) - outRec->FirstLeft = NewOutRec; - } - } -} -//---------------------------------------------------------------------- - -void Clipper::FixupFirstLefts2(OutRec* InnerOutRec, OutRec* OuterOutRec) -{ - //A polygon has split into two such that one is now the inner of the other. - //It's possible that these polygons now wrap around other polygons, so check - //every polygon that's also contained by OuterOutRec's FirstLeft container - //(including 0) to see if they've become inner to the new inner polygon ... - OutRec* orfl = OuterOutRec->FirstLeft; - for (PolyOutList::size_type i = 0; i < m_PolyOuts.size(); ++i) - { - OutRec* outRec = m_PolyOuts[i]; - - if (!outRec->Pts || outRec == OuterOutRec || outRec == InnerOutRec) - continue; - OutRec* firstLeft = ParseFirstLeft(outRec->FirstLeft); - if (firstLeft != orfl && firstLeft != InnerOutRec && firstLeft != OuterOutRec) - continue; - if (Poly2ContainsPoly1(outRec->Pts, InnerOutRec->Pts)) - outRec->FirstLeft = InnerOutRec; - else if (Poly2ContainsPoly1(outRec->Pts, OuterOutRec->Pts)) - outRec->FirstLeft = OuterOutRec; - else if (outRec->FirstLeft == InnerOutRec || outRec->FirstLeft == OuterOutRec) - outRec->FirstLeft = orfl; - } -} -//---------------------------------------------------------------------- -void Clipper::FixupFirstLefts3(OutRec* OldOutRec, OutRec* NewOutRec) -{ - //reassigns FirstLeft WITHOUT testing if NewOutRec contains the polygon - for (PolyOutList::size_type i = 0; i < m_PolyOuts.size(); ++i) - { - OutRec* outRec = m_PolyOuts[i]; - OutRec* firstLeft = ParseFirstLeft(outRec->FirstLeft); - if (outRec->Pts && firstLeft == OldOutRec) - outRec->FirstLeft = NewOutRec; - } -} -//---------------------------------------------------------------------- - -void Clipper::JoinCommonEdges() -{ - for (JoinList::size_type i = 0; i < m_Joins.size(); i++) - { - Join* join = m_Joins[i]; - - OutRec *outRec1 = GetOutRec(join->OutPt1->Idx); - OutRec *outRec2 = GetOutRec(join->OutPt2->Idx); - - if (!outRec1->Pts || !outRec2->Pts) continue; - if (outRec1->IsOpen || outRec2->IsOpen) continue; - - //get the polygon fragment with the correct hole state (FirstLeft) - //before calling JoinPoints() ... - OutRec *holeStateRec; - if (outRec1 == outRec2) holeStateRec = outRec1; - else if (OutRec1RightOfOutRec2(outRec1, outRec2)) holeStateRec = outRec2; - else if (OutRec1RightOfOutRec2(outRec2, outRec1)) holeStateRec = outRec1; - else holeStateRec = GetLowermostRec(outRec1, outRec2); - - if (!JoinPoints(join, outRec1, outRec2)) continue; - - if (outRec1 == outRec2) - { - //instead of joining two polygons, we've just created a new one by - //splitting one polygon into two. - outRec1->Pts = join->OutPt1; - outRec1->BottomPt = 0; - outRec2 = CreateOutRec(); - outRec2->Pts = join->OutPt2; - - //update all OutRec2.Pts Idx's ... - UpdateOutPtIdxs(*outRec2); - - if (Poly2ContainsPoly1(outRec2->Pts, outRec1->Pts)) - { - //outRec1 contains outRec2 ... - outRec2->IsHole = !outRec1->IsHole; - outRec2->FirstLeft = outRec1; - - if (m_UsingPolyTree) FixupFirstLefts2(outRec2, outRec1); - - if ((outRec2->IsHole ^ m_ReverseOutput) == (Area(*outRec2) > 0)) - ReversePolyPtLinks(outRec2->Pts); - - } else if (Poly2ContainsPoly1(outRec1->Pts, outRec2->Pts)) - { - //outRec2 contains outRec1 ... - outRec2->IsHole = outRec1->IsHole; - outRec1->IsHole = !outRec2->IsHole; - outRec2->FirstLeft = outRec1->FirstLeft; - outRec1->FirstLeft = outRec2; - - if (m_UsingPolyTree) FixupFirstLefts2(outRec1, outRec2); - - if ((outRec1->IsHole ^ m_ReverseOutput) == (Area(*outRec1) > 0)) - ReversePolyPtLinks(outRec1->Pts); - } - else - { - //the 2 polygons are completely separate ... - outRec2->IsHole = outRec1->IsHole; - outRec2->FirstLeft = outRec1->FirstLeft; - - //fixup FirstLeft pointers that may need reassigning to OutRec2 - if (m_UsingPolyTree) FixupFirstLefts1(outRec1, outRec2); - } - - } else - { - //joined 2 polygons together ... - - outRec2->Pts = 0; - outRec2->BottomPt = 0; - outRec2->Idx = outRec1->Idx; - - outRec1->IsHole = holeStateRec->IsHole; - if (holeStateRec == outRec2) - outRec1->FirstLeft = outRec2->FirstLeft; - outRec2->FirstLeft = outRec1; - - if (m_UsingPolyTree) FixupFirstLefts3(outRec2, outRec1); - } - } -} - -//------------------------------------------------------------------------------ -// ClipperOffset support functions ... -//------------------------------------------------------------------------------ - -DoublePoint GetUnitNormal(const IntPoint &pt1, const IntPoint &pt2) -{ - if(pt2.X == pt1.X && pt2.Y == pt1.Y) - return DoublePoint(0, 0); - - double Dx = (double)(pt2.X - pt1.X); - double dy = (double)(pt2.Y - pt1.Y); - double f = 1 *1.0/ std::sqrt( Dx*Dx + dy*dy ); - Dx *= f; - dy *= f; - return DoublePoint(dy, -Dx); -} - -//------------------------------------------------------------------------------ -// ClipperOffset class -//------------------------------------------------------------------------------ - -ClipperOffset::ClipperOffset(double miterLimit, double arcTolerance) -{ - this->MiterLimit = miterLimit; - this->ArcTolerance = arcTolerance; - m_lowest.X = -1; -} -//------------------------------------------------------------------------------ - -ClipperOffset::~ClipperOffset() -{ - Clear(); -} -//------------------------------------------------------------------------------ - -void ClipperOffset::Clear() -{ - for (int i = 0; i < m_polyNodes.ChildCount(); ++i) - delete m_polyNodes.Childs[i]; - m_polyNodes.Childs.clear(); - m_lowest.X = -1; -} -//------------------------------------------------------------------------------ - -void ClipperOffset::AddPath(const Path& path, JoinType joinType, EndType endType) -{ - int highI = (int)path.size() - 1; - if (highI < 0) return; - PolyNode* newNode = new PolyNode(); - newNode->m_jointype = joinType; - newNode->m_endtype = endType; - - //strip duplicate points from path and also get index to the lowest point ... - if (endType == etClosedLine || endType == etClosedPolygon) - while (highI > 0 && path[0] == path[highI]) highI--; - newNode->Contour.reserve(highI + 1); - newNode->Contour.push_back(path[0]); - int j = 0, k = 0; - for (int i = 1; i <= highI; i++) - if (newNode->Contour[j] != path[i]) - { - j++; - newNode->Contour.push_back(path[i]); - if (path[i].Y > newNode->Contour[k].Y || - (path[i].Y == newNode->Contour[k].Y && - path[i].X < newNode->Contour[k].X)) k = j; - } - if (endType == etClosedPolygon && j < 2) - { - delete newNode; - return; - } - m_polyNodes.AddChild(*newNode); - - //if this path's lowest pt is lower than all the others then update m_lowest - if (endType != etClosedPolygon) return; - if (m_lowest.X < 0) - m_lowest = IntPoint(m_polyNodes.ChildCount() - 1, k); - else - { - IntPoint ip = m_polyNodes.Childs[(int)m_lowest.X]->Contour[(int)m_lowest.Y]; - if (newNode->Contour[k].Y > ip.Y || - (newNode->Contour[k].Y == ip.Y && - newNode->Contour[k].X < ip.X)) - m_lowest = IntPoint(m_polyNodes.ChildCount() - 1, k); - } -} -//------------------------------------------------------------------------------ - -void ClipperOffset::AddPaths(const Paths& paths, JoinType joinType, EndType endType) -{ - for (Paths::size_type i = 0; i < paths.size(); ++i) - AddPath(paths[i], joinType, endType); -} -//------------------------------------------------------------------------------ - -void ClipperOffset::FixOrientations() -{ - //fixup orientations of all closed paths if the orientation of the - //closed path with the lowermost vertex is wrong ... - if (m_lowest.X >= 0 && - !Orientation(m_polyNodes.Childs[(int)m_lowest.X]->Contour)) - { - for (int i = 0; i < m_polyNodes.ChildCount(); ++i) - { - PolyNode& node = *m_polyNodes.Childs[i]; - if (node.m_endtype == etClosedPolygon || - (node.m_endtype == etClosedLine && Orientation(node.Contour))) - ReversePath(node.Contour); - } - } else - { - for (int i = 0; i < m_polyNodes.ChildCount(); ++i) - { - PolyNode& node = *m_polyNodes.Childs[i]; - if (node.m_endtype == etClosedLine && !Orientation(node.Contour)) - ReversePath(node.Contour); - } - } -} -//------------------------------------------------------------------------------ - -void ClipperOffset::Execute(Paths& solution, double delta) -{ - solution.clear(); - FixOrientations(); - DoOffset(delta); - - //now clean up 'corners' ... - Clipper clpr; - clpr.AddPaths(m_destPolys, ptSubject, true); - if (delta > 0) - { - clpr.Execute(ctUnion, solution, pftPositive, pftPositive); - } - else - { - IntRect r = clpr.GetBounds(); - Path outer(4); - outer[0] = IntPoint(r.left - 10, r.bottom + 10); - outer[1] = IntPoint(r.right + 10, r.bottom + 10); - outer[2] = IntPoint(r.right + 10, r.top - 10); - outer[3] = IntPoint(r.left - 10, r.top - 10); - - clpr.AddPath(outer, ptSubject, true); - clpr.ReverseSolution(true); - clpr.Execute(ctUnion, solution, pftNegative, pftNegative); - if (solution.size() > 0) solution.erase(solution.begin()); - } -} -//------------------------------------------------------------------------------ - -void ClipperOffset::Execute(PolyTree& solution, double delta) -{ - solution.Clear(); - FixOrientations(); - DoOffset(delta); - - //now clean up 'corners' ... - Clipper clpr; - clpr.AddPaths(m_destPolys, ptSubject, true); - if (delta > 0) - { - clpr.Execute(ctUnion, solution, pftPositive, pftPositive); - } - else - { - IntRect r = clpr.GetBounds(); - Path outer(4); - outer[0] = IntPoint(r.left - 10, r.bottom + 10); - outer[1] = IntPoint(r.right + 10, r.bottom + 10); - outer[2] = IntPoint(r.right + 10, r.top - 10); - outer[3] = IntPoint(r.left - 10, r.top - 10); - - clpr.AddPath(outer, ptSubject, true); - clpr.ReverseSolution(true); - clpr.Execute(ctUnion, solution, pftNegative, pftNegative); - //remove the outer PolyNode rectangle ... - if (solution.ChildCount() == 1 && solution.Childs[0]->ChildCount() > 0) - { - PolyNode* outerNode = solution.Childs[0]; - solution.Childs.reserve(outerNode->ChildCount()); - solution.Childs[0] = outerNode->Childs[0]; - solution.Childs[0]->Parent = outerNode->Parent; - for (int i = 1; i < outerNode->ChildCount(); ++i) - solution.AddChild(*outerNode->Childs[i]); - } - else - solution.Clear(); - } -} -//------------------------------------------------------------------------------ - -void ClipperOffset::DoOffset(double delta) -{ - m_destPolys.clear(); - m_delta = delta; - - //if Zero offset, just copy any CLOSED polygons to m_p and return ... - if (NEAR_ZERO(delta)) - { - m_destPolys.reserve(m_polyNodes.ChildCount()); - for (int i = 0; i < m_polyNodes.ChildCount(); i++) - { - PolyNode& node = *m_polyNodes.Childs[i]; - if (node.m_endtype == etClosedPolygon) - m_destPolys.push_back(node.Contour); - } - return; - } - - //see offset_triginometry3.svg in the documentation folder ... - if (MiterLimit > 2) m_miterLim = 2/(MiterLimit * MiterLimit); - else m_miterLim = 0.5; - - double y; - if (ArcTolerance <= 0.0) y = def_arc_tolerance; - else if (ArcTolerance > std::fabs(delta) * def_arc_tolerance) - y = std::fabs(delta) * def_arc_tolerance; - else y = ArcTolerance; - //see offset_triginometry2.svg in the documentation folder ... - double steps = pi / std::acos(1 - y / std::fabs(delta)); - if (steps > std::fabs(delta) * pi) - steps = std::fabs(delta) * pi; //ie excessive precision check - m_sin = std::sin(two_pi / steps); - m_cos = std::cos(two_pi / steps); - m_StepsPerRad = steps / two_pi; - if (delta < 0.0) m_sin = -m_sin; - - m_destPolys.reserve(m_polyNodes.ChildCount() * 2); - for (int i = 0; i < m_polyNodes.ChildCount(); i++) - { - PolyNode& node = *m_polyNodes.Childs[i]; - m_srcPoly = node.Contour; - - int len = (int)m_srcPoly.size(); - if (len == 0 || (delta <= 0 && (len < 3 || node.m_endtype != etClosedPolygon))) - continue; - - m_destPoly.clear(); - if (len == 1) - { - if (node.m_jointype == jtRound) - { - double X = 1.0, Y = 0.0; - for (cInt j = 1; j <= steps; j++) - { - m_destPoly.push_back(IntPoint( - Round(m_srcPoly[0].X + X * delta), - Round(m_srcPoly[0].Y + Y * delta))); - double X2 = X; - X = X * m_cos - m_sin * Y; - Y = X2 * m_sin + Y * m_cos; - } - } - else - { - double X = -1.0, Y = -1.0; - for (int j = 0; j < 4; ++j) - { - m_destPoly.push_back(IntPoint( - Round(m_srcPoly[0].X + X * delta), - Round(m_srcPoly[0].Y + Y * delta))); - if (X < 0) X = 1; - else if (Y < 0) Y = 1; - else X = -1; - } - } - m_destPolys.push_back(m_destPoly); - continue; - } - //build m_normals ... - m_normals.clear(); - m_normals.reserve(len); - for (int j = 0; j < len - 1; ++j) - m_normals.push_back(GetUnitNormal(m_srcPoly[j], m_srcPoly[j + 1])); - if (node.m_endtype == etClosedLine || node.m_endtype == etClosedPolygon) - m_normals.push_back(GetUnitNormal(m_srcPoly[len - 1], m_srcPoly[0])); - else - m_normals.push_back(DoublePoint(m_normals[len - 2])); - - if (node.m_endtype == etClosedPolygon) - { - int k = len - 1; - for (int j = 0; j < len; ++j) - OffsetPoint(j, k, node.m_jointype); - m_destPolys.push_back(m_destPoly); - } - else if (node.m_endtype == etClosedLine) - { - int k = len - 1; - for (int j = 0; j < len; ++j) - OffsetPoint(j, k, node.m_jointype); - m_destPolys.push_back(m_destPoly); - m_destPoly.clear(); - //re-build m_normals ... - DoublePoint n = m_normals[len -1]; - for (int j = len - 1; j > 0; j--) - m_normals[j] = DoublePoint(-m_normals[j - 1].X, -m_normals[j - 1].Y); - m_normals[0] = DoublePoint(-n.X, -n.Y); - k = 0; - for (int j = len - 1; j >= 0; j--) - OffsetPoint(j, k, node.m_jointype); - m_destPolys.push_back(m_destPoly); - } - else - { - int k = 0; - for (int j = 1; j < len - 1; ++j) - OffsetPoint(j, k, node.m_jointype); - - IntPoint pt1; - if (node.m_endtype == etOpenButt) - { - int j = len - 1; - pt1 = IntPoint((cInt)Round(m_srcPoly[j].X + m_normals[j].X * - delta), (cInt)Round(m_srcPoly[j].Y + m_normals[j].Y * delta)); - m_destPoly.push_back(pt1); - pt1 = IntPoint((cInt)Round(m_srcPoly[j].X - m_normals[j].X * - delta), (cInt)Round(m_srcPoly[j].Y - m_normals[j].Y * delta)); - m_destPoly.push_back(pt1); - } - else - { - int j = len - 1; - k = len - 2; - m_sinA = 0; - m_normals[j] = DoublePoint(-m_normals[j].X, -m_normals[j].Y); - if (node.m_endtype == etOpenSquare) - DoSquare(j, k); - else - DoRound(j, k); - } - - //re-build m_normals ... - for (int j = len - 1; j > 0; j--) - m_normals[j] = DoublePoint(-m_normals[j - 1].X, -m_normals[j - 1].Y); - m_normals[0] = DoublePoint(-m_normals[1].X, -m_normals[1].Y); - - k = len - 1; - for (int j = k - 1; j > 0; --j) OffsetPoint(j, k, node.m_jointype); - - if (node.m_endtype == etOpenButt) - { - pt1 = IntPoint((cInt)Round(m_srcPoly[0].X - m_normals[0].X * delta), - (cInt)Round(m_srcPoly[0].Y - m_normals[0].Y * delta)); - m_destPoly.push_back(pt1); - pt1 = IntPoint((cInt)Round(m_srcPoly[0].X + m_normals[0].X * delta), - (cInt)Round(m_srcPoly[0].Y + m_normals[0].Y * delta)); - m_destPoly.push_back(pt1); - } - else - { - k = 1; - m_sinA = 0; - if (node.m_endtype == etOpenSquare) - DoSquare(0, 1); - else - DoRound(0, 1); - } - m_destPolys.push_back(m_destPoly); - } - } -} -//------------------------------------------------------------------------------ - -void ClipperOffset::OffsetPoint(int j, int& k, JoinType jointype) -{ - //cross product ... - m_sinA = (m_normals[k].X * m_normals[j].Y - m_normals[j].X * m_normals[k].Y); - if (std::fabs(m_sinA * m_delta) < 1.0) - { - //dot product ... - double cosA = (m_normals[k].X * m_normals[j].X + m_normals[j].Y * m_normals[k].Y ); - if (cosA > 0) // angle => 0 degrees - { - m_destPoly.push_back(IntPoint(Round(m_srcPoly[j].X + m_normals[k].X * m_delta), - Round(m_srcPoly[j].Y + m_normals[k].Y * m_delta))); - return; - } - //else angle => 180 degrees - } - else if (m_sinA > 1.0) m_sinA = 1.0; - else if (m_sinA < -1.0) m_sinA = -1.0; - - if (m_sinA * m_delta < 0) - { - m_destPoly.push_back(IntPoint(Round(m_srcPoly[j].X + m_normals[k].X * m_delta), - Round(m_srcPoly[j].Y + m_normals[k].Y * m_delta))); - m_destPoly.push_back(m_srcPoly[j]); - m_destPoly.push_back(IntPoint(Round(m_srcPoly[j].X + m_normals[j].X * m_delta), - Round(m_srcPoly[j].Y + m_normals[j].Y * m_delta))); - } - else - switch (jointype) - { - case jtMiter: - { - double r = 1 + (m_normals[j].X * m_normals[k].X + - m_normals[j].Y * m_normals[k].Y); - if (r >= m_miterLim) DoMiter(j, k, r); else DoSquare(j, k); - break; - } - case jtSquare: DoSquare(j, k); break; - case jtRound: DoRound(j, k); break; - } - k = j; -} -//------------------------------------------------------------------------------ - -void ClipperOffset::DoSquare(int j, int k) -{ - double dx = std::tan(std::atan2(m_sinA, - m_normals[k].X * m_normals[j].X + m_normals[k].Y * m_normals[j].Y) / 4); - m_destPoly.push_back(IntPoint( - Round(m_srcPoly[j].X + m_delta * (m_normals[k].X - m_normals[k].Y * dx)), - Round(m_srcPoly[j].Y + m_delta * (m_normals[k].Y + m_normals[k].X * dx)))); - m_destPoly.push_back(IntPoint( - Round(m_srcPoly[j].X + m_delta * (m_normals[j].X + m_normals[j].Y * dx)), - Round(m_srcPoly[j].Y + m_delta * (m_normals[j].Y - m_normals[j].X * dx)))); -} -//------------------------------------------------------------------------------ - -void ClipperOffset::DoMiter(int j, int k, double r) -{ - double q = m_delta / r; - m_destPoly.push_back(IntPoint(Round(m_srcPoly[j].X + (m_normals[k].X + m_normals[j].X) * q), - Round(m_srcPoly[j].Y + (m_normals[k].Y + m_normals[j].Y) * q))); -} -//------------------------------------------------------------------------------ - -void ClipperOffset::DoRound(int j, int k) -{ - double a = std::atan2(m_sinA, - m_normals[k].X * m_normals[j].X + m_normals[k].Y * m_normals[j].Y); - int steps = std::max((int)Round(m_StepsPerRad * std::fabs(a)), 1); - - double X = m_normals[k].X, Y = m_normals[k].Y, X2; - for (int i = 0; i < steps; ++i) - { - m_destPoly.push_back(IntPoint( - Round(m_srcPoly[j].X + X * m_delta), - Round(m_srcPoly[j].Y + Y * m_delta))); - X2 = X; - X = X * m_cos - m_sin * Y; - Y = X2 * m_sin + Y * m_cos; - } - m_destPoly.push_back(IntPoint( - Round(m_srcPoly[j].X + m_normals[j].X * m_delta), - Round(m_srcPoly[j].Y + m_normals[j].Y * m_delta))); -} - -//------------------------------------------------------------------------------ -// Miscellaneous public functions -//------------------------------------------------------------------------------ - -void Clipper::DoSimplePolygons() -{ - PolyOutList::size_type i = 0; - while (i < m_PolyOuts.size()) - { - OutRec* outrec = m_PolyOuts[i++]; - OutPt* op = outrec->Pts; - if (!op || outrec->IsOpen) continue; - do //for each Pt in Polygon until duplicate found do ... - { - OutPt* op2 = op->Next; - while (op2 != outrec->Pts) - { - if ((op->Pt == op2->Pt) && op2->Next != op && op2->Prev != op) - { - //split the polygon into two ... - OutPt* op3 = op->Prev; - OutPt* op4 = op2->Prev; - op->Prev = op4; - op4->Next = op; - op2->Prev = op3; - op3->Next = op2; - - outrec->Pts = op; - OutRec* outrec2 = CreateOutRec(); - outrec2->Pts = op2; - UpdateOutPtIdxs(*outrec2); - if (Poly2ContainsPoly1(outrec2->Pts, outrec->Pts)) - { - //OutRec2 is contained by OutRec1 ... - outrec2->IsHole = !outrec->IsHole; - outrec2->FirstLeft = outrec; - if (m_UsingPolyTree) FixupFirstLefts2(outrec2, outrec); - } - else - if (Poly2ContainsPoly1(outrec->Pts, outrec2->Pts)) - { - //OutRec1 is contained by OutRec2 ... - outrec2->IsHole = outrec->IsHole; - outrec->IsHole = !outrec2->IsHole; - outrec2->FirstLeft = outrec->FirstLeft; - outrec->FirstLeft = outrec2; - if (m_UsingPolyTree) FixupFirstLefts2(outrec, outrec2); - } - else - { - //the 2 polygons are separate ... - outrec2->IsHole = outrec->IsHole; - outrec2->FirstLeft = outrec->FirstLeft; - if (m_UsingPolyTree) FixupFirstLefts1(outrec, outrec2); - } - op2 = op; //ie get ready for the Next iteration - } - op2 = op2->Next; - } - op = op->Next; - } - while (op != outrec->Pts); - } -} -//------------------------------------------------------------------------------ - -void ReversePath(Path& p) -{ - std::reverse(p.begin(), p.end()); -} -//------------------------------------------------------------------------------ - -void ReversePaths(Paths& p) -{ - for (Paths::size_type i = 0; i < p.size(); ++i) - ReversePath(p[i]); -} -//------------------------------------------------------------------------------ - -void SimplifyPolygon(const Path &in_poly, Paths &out_polys, PolyFillType fillType) -{ - Clipper c; - c.StrictlySimple(true); - c.AddPath(in_poly, ptSubject, true); - c.Execute(ctUnion, out_polys, fillType, fillType); -} -//------------------------------------------------------------------------------ - -void SimplifyPolygons(const Paths &in_polys, Paths &out_polys, PolyFillType fillType) -{ - Clipper c; - c.StrictlySimple(true); - c.AddPaths(in_polys, ptSubject, true); - c.Execute(ctUnion, out_polys, fillType, fillType); -} -//------------------------------------------------------------------------------ - -void SimplifyPolygons(Paths &polys, PolyFillType fillType) -{ - SimplifyPolygons(polys, polys, fillType); -} -//------------------------------------------------------------------------------ - -inline double DistanceSqrd(const IntPoint& pt1, const IntPoint& pt2) -{ - double Dx = ((double)pt1.X - pt2.X); - double dy = ((double)pt1.Y - pt2.Y); - return (Dx*Dx + dy*dy); -} -//------------------------------------------------------------------------------ - -double DistanceFromLineSqrd( - const IntPoint& pt, const IntPoint& ln1, const IntPoint& ln2) -{ - //The equation of a line in general form (Ax + By + C = 0) - //given 2 points (x�,y�) & (x�,y�) is ... - //(y� - y�)x + (x� - x�)y + (y� - y�)x� - (x� - x�)y� = 0 - //A = (y� - y�); B = (x� - x�); C = (y� - y�)x� - (x� - x�)y� - //perpendicular distance of point (x�,y�) = (Ax� + By� + C)/Sqrt(A� + B�) - //see http://en.wikipedia.org/wiki/Perpendicular_distance - double A = double(ln1.Y - ln2.Y); - double B = double(ln2.X - ln1.X); - double C = A * ln1.X + B * ln1.Y; - C = A * pt.X + B * pt.Y - C; - return (C * C) / (A * A + B * B); -} -//--------------------------------------------------------------------------- - -bool SlopesNearCollinear(const IntPoint& pt1, - const IntPoint& pt2, const IntPoint& pt3, double distSqrd) -{ - //this function is more accurate when the point that's geometrically - //between the other 2 points is the one that's tested for distance. - //ie makes it more likely to pick up 'spikes' ... - if (Abs(pt1.X - pt2.X) > Abs(pt1.Y - pt2.Y)) - { - if ((pt1.X > pt2.X) == (pt1.X < pt3.X)) - return DistanceFromLineSqrd(pt1, pt2, pt3) < distSqrd; - else if ((pt2.X > pt1.X) == (pt2.X < pt3.X)) - return DistanceFromLineSqrd(pt2, pt1, pt3) < distSqrd; - else - return DistanceFromLineSqrd(pt3, pt1, pt2) < distSqrd; - } - else - { - if ((pt1.Y > pt2.Y) == (pt1.Y < pt3.Y)) - return DistanceFromLineSqrd(pt1, pt2, pt3) < distSqrd; - else if ((pt2.Y > pt1.Y) == (pt2.Y < pt3.Y)) - return DistanceFromLineSqrd(pt2, pt1, pt3) < distSqrd; - else - return DistanceFromLineSqrd(pt3, pt1, pt2) < distSqrd; - } -} -//------------------------------------------------------------------------------ - -bool PointsAreClose(IntPoint pt1, IntPoint pt2, double distSqrd) -{ - double Dx = (double)pt1.X - pt2.X; - double dy = (double)pt1.Y - pt2.Y; - return ((Dx * Dx) + (dy * dy) <= distSqrd); -} -//------------------------------------------------------------------------------ - -OutPt* ExcludeOp(OutPt* op) -{ - OutPt* result = op->Prev; - result->Next = op->Next; - op->Next->Prev = result; - result->Idx = 0; - return result; -} -//------------------------------------------------------------------------------ - -void CleanPolygon(const Path& in_poly, Path& out_poly, double distance) -{ - //distance = proximity in units/pixels below which vertices - //will be stripped. Default ~= sqrt(2). - - size_t size = in_poly.size(); - - if (size == 0) - { - out_poly.clear(); - return; - } - - OutPt* outPts = new OutPt[size]; - for (size_t i = 0; i < size; ++i) - { - outPts[i].Pt = in_poly[i]; - outPts[i].Next = &outPts[(i + 1) % size]; - outPts[i].Next->Prev = &outPts[i]; - outPts[i].Idx = 0; - } - - double distSqrd = distance * distance; - OutPt* op = &outPts[0]; - while (op->Idx == 0 && op->Next != op->Prev) - { - if (PointsAreClose(op->Pt, op->Prev->Pt, distSqrd)) - { - op = ExcludeOp(op); - size--; - } - else if (PointsAreClose(op->Prev->Pt, op->Next->Pt, distSqrd)) - { - ExcludeOp(op->Next); - op = ExcludeOp(op); - size -= 2; - } - else if (SlopesNearCollinear(op->Prev->Pt, op->Pt, op->Next->Pt, distSqrd)) - { - op = ExcludeOp(op); - size--; - } - else - { - op->Idx = 1; - op = op->Next; - } - } - - if (size < 3) size = 0; - out_poly.resize(size); - for (size_t i = 0; i < size; ++i) - { - out_poly[i] = op->Pt; - op = op->Next; - } - delete [] outPts; -} -//------------------------------------------------------------------------------ - -void CleanPolygon(Path& poly, double distance) -{ - CleanPolygon(poly, poly, distance); -} -//------------------------------------------------------------------------------ - -void CleanPolygons(const Paths& in_polys, Paths& out_polys, double distance) -{ - out_polys.resize(in_polys.size()); - for (Paths::size_type i = 0; i < in_polys.size(); ++i) - CleanPolygon(in_polys[i], out_polys[i], distance); -} -//------------------------------------------------------------------------------ - -void CleanPolygons(Paths& polys, double distance) -{ - CleanPolygons(polys, polys, distance); -} -//------------------------------------------------------------------------------ - -void Minkowski(const Path& poly, const Path& path, - Paths& solution, bool isSum, bool isClosed) -{ - int delta = (isClosed ? 1 : 0); - size_t polyCnt = poly.size(); - size_t pathCnt = path.size(); - Paths pp; - pp.reserve(pathCnt); - if (isSum) - for (size_t i = 0; i < pathCnt; ++i) - { - Path p; - p.reserve(polyCnt); - for (size_t j = 0; j < poly.size(); ++j) - p.push_back(IntPoint(path[i].X + poly[j].X, path[i].Y + poly[j].Y)); - pp.push_back(p); - } - else - for (size_t i = 0; i < pathCnt; ++i) - { - Path p; - p.reserve(polyCnt); - for (size_t j = 0; j < poly.size(); ++j) - p.push_back(IntPoint(path[i].X - poly[j].X, path[i].Y - poly[j].Y)); - pp.push_back(p); - } - - solution.clear(); - solution.reserve((pathCnt + delta) * (polyCnt + 1)); - for (size_t i = 0; i < pathCnt - 1 + delta; ++i) - for (size_t j = 0; j < polyCnt; ++j) - { - Path quad; - quad.reserve(4); - quad.push_back(pp[i % pathCnt][j % polyCnt]); - quad.push_back(pp[(i + 1) % pathCnt][j % polyCnt]); - quad.push_back(pp[(i + 1) % pathCnt][(j + 1) % polyCnt]); - quad.push_back(pp[i % pathCnt][(j + 1) % polyCnt]); - if (!Orientation(quad)) ReversePath(quad); - solution.push_back(quad); - } -} -//------------------------------------------------------------------------------ - -void MinkowskiSum(const Path& pattern, const Path& path, Paths& solution, bool pathIsClosed) -{ - Minkowski(pattern, path, solution, true, pathIsClosed); - Clipper c; - c.AddPaths(solution, ptSubject, true); - c.Execute(ctUnion, solution, pftNonZero, pftNonZero); -} -//------------------------------------------------------------------------------ - -void TranslatePath(const Path& input, Path& output, const IntPoint delta) -{ - //precondition: input != output - output.resize(input.size()); - for (size_t i = 0; i < input.size(); ++i) - output[i] = IntPoint(input[i].X + delta.X, input[i].Y + delta.Y); -} -//------------------------------------------------------------------------------ - -void MinkowskiSum(const Path& pattern, const Paths& paths, Paths& solution, bool pathIsClosed) -{ - Clipper c; - for (size_t i = 0; i < paths.size(); ++i) - { - Paths tmp; - Minkowski(pattern, paths[i], tmp, true, pathIsClosed); - c.AddPaths(tmp, ptSubject, true); - if (pathIsClosed) - { - Path tmp2; - TranslatePath(paths[i], tmp2, pattern[0]); - c.AddPath(tmp2, ptClip, true); - } - } - c.Execute(ctUnion, solution, pftNonZero, pftNonZero); -} -//------------------------------------------------------------------------------ - -void MinkowskiDiff(const Path& poly1, const Path& poly2, Paths& solution) -{ - Minkowski(poly1, poly2, solution, false, true); - Clipper c; - c.AddPaths(solution, ptSubject, true); - c.Execute(ctUnion, solution, pftNonZero, pftNonZero); -} -//------------------------------------------------------------------------------ - -enum NodeType {ntAny, ntOpen, ntClosed}; - -void AddPolyNodeToPaths(const PolyNode& polynode, NodeType nodetype, Paths& paths) -{ - bool match = true; - if (nodetype == ntClosed) match = !polynode.IsOpen(); - else if (nodetype == ntOpen) return; - - if (!polynode.Contour.empty() && match) - paths.push_back(polynode.Contour); - for (int i = 0; i < polynode.ChildCount(); ++i) - AddPolyNodeToPaths(*polynode.Childs[i], nodetype, paths); -} -//------------------------------------------------------------------------------ - -void PolyTreeToPaths(const PolyTree& polytree, Paths& paths) -{ - paths.resize(0); - paths.reserve(polytree.Total()); - AddPolyNodeToPaths(polytree, ntAny, paths); -} -//------------------------------------------------------------------------------ - -void ClosedPathsFromPolyTree(const PolyTree& polytree, Paths& paths) -{ - paths.resize(0); - paths.reserve(polytree.Total()); - AddPolyNodeToPaths(polytree, ntClosed, paths); -} -//------------------------------------------------------------------------------ - -void OpenPathsFromPolyTree(PolyTree& polytree, Paths& paths) -{ - paths.resize(0); - paths.reserve(polytree.Total()); - //Open paths are top level only, so ... - for (int i = 0; i < polytree.ChildCount(); ++i) - if (polytree.Childs[i]->IsOpen()) - paths.push_back(polytree.Childs[i]->Contour); -} -//------------------------------------------------------------------------------ - -std::ostream& operator <<(std::ostream &s, const IntPoint &p) -{ - s << "(" << p.X << "," << p.Y << ")"; - return s; -} -//------------------------------------------------------------------------------ - -std::ostream& operator <<(std::ostream &s, const Path &p) -{ - if (p.empty()) return s; - Path::size_type last = p.size() -1; - for (Path::size_type i = 0; i < last; i++) - s << "(" << p[i].X << "," << p[i].Y << "), "; - s << "(" << p[last].X << "," << p[last].Y << ")\n"; - return s; -} -//------------------------------------------------------------------------------ - -std::ostream& operator <<(std::ostream &s, const Paths &p) -{ - for (Paths::size_type i = 0; i < p.size(); i++) - s << p[i]; - s << "\n"; - return s; -} -//------------------------------------------------------------------------------ - -} //ClipperLib namespace diff --git a/deploy/android_demo/app/src/main/cpp/ocr_clipper.hpp b/deploy/android_demo/app/src/main/cpp/ocr_clipper.hpp deleted file mode 100644 index 7129b535c3..0000000000 --- a/deploy/android_demo/app/src/main/cpp/ocr_clipper.hpp +++ /dev/null @@ -1,547 +0,0 @@ -/******************************************************************************* -* * -* Author : Angus Johnson * -* Version : 6.4.2 * -* Date : 27 February 2017 * -* Website : http://www.angusj.com * -* Copyright : Angus Johnson 2010-2017 * -* * -* License: * -* Use, modification & distribution is subject to Boost Software License Ver 1. * -* http://www.boost.org/LICENSE_1_0.txt * -* * -* Attributions: * -* The code in this library is an extension of Bala Vatti's clipping algorithm: * -* "A generic solution to polygon clipping" * -* Communications of the ACM, Vol 35, Issue 7 (July 1992) pp 56-63. * -* http://portal.acm.org/citation.cfm?id=129906 * -* * -* Computer graphics and geometric modeling: implementation and algorithms * -* By Max K. Agoston * -* Springer; 1 edition (January 4, 2005) * -* http://books.google.com/books?q=vatti+clipping+agoston * -* * -* See also: * -* "Polygon Offsetting by Computing Winding Numbers" * -* Paper no. DETC2005-85513 pp. 565-575 * -* ASME 2005 International Design Engineering Technical Conferences * -* and Computers and Information in Engineering Conference (IDETC/CIE2005) * -* September 24-28, 2005 , Long Beach, California, USA * -* http://www.me.berkeley.edu/~mcmains/pubs/DAC05OffsetPolygon.pdf * -* * -*******************************************************************************/ - -#ifndef clipper_hpp -#define clipper_hpp - -#define CLIPPER_VERSION "6.4.2" - -//use_int32: When enabled 32bit ints are used instead of 64bit ints. This -//improve performance but coordinate values are limited to the range +/- 46340 -//#define use_int32 - -//use_xyz: adds a Z member to IntPoint. Adds a minor cost to perfomance. -//#define use_xyz - -//use_lines: Enables line clipping. Adds a very minor cost to performance. -#define use_lines - -//use_deprecated: Enables temporary support for the obsolete functions -//#define use_deprecated - -#include -#include -#include -#include -#include -#include -#include -#include -#include - -namespace ClipperLib { - -enum ClipType { - ctIntersection, ctUnion, ctDifference, ctXor -}; -enum PolyType { - ptSubject, ptClip -}; -//By far the most widely used winding rules for polygon filling are -//EvenOdd & NonZero (GDI, GDI+, XLib, OpenGL, Cairo, AGG, Quartz, SVG, Gr32) -//Others rules include Positive, Negative and ABS_GTR_EQ_TWO (only in OpenGL) -//see http://glprogramming.com/red/chapter11.html -enum PolyFillType { - pftEvenOdd, pftNonZero, pftPositive, pftNegative -}; - -#ifdef use_int32 -typedef int cInt; -static cInt const loRange = 0x7FFF; -static cInt const hiRange = 0x7FFF; -#else -typedef signed long long cInt; -static cInt const loRange = 0x3FFFFFFF; -static cInt const hiRange = 0x3FFFFFFFFFFFFFFFLL; -typedef signed long long long64; //used by Int128 class -typedef unsigned long long ulong64; - -#endif - -struct IntPoint { - cInt X; - cInt Y; -#ifdef use_xyz - cInt Z; - IntPoint(cInt x = 0, cInt y = 0, cInt z = 0): X(x), Y(y), Z(z) {}; -#else - - IntPoint(cInt x = 0, cInt y = 0) : X(x), Y(y) {}; -#endif - - friend inline bool operator==(const IntPoint &a, const IntPoint &b) { - return a.X == b.X && a.Y == b.Y; - } - - friend inline bool operator!=(const IntPoint &a, const IntPoint &b) { - return a.X != b.X || a.Y != b.Y; - } -}; -//------------------------------------------------------------------------------ - -typedef std::vector Path; -typedef std::vector Paths; - -inline Path &operator<<(Path &poly, const IntPoint &p) { - poly.push_back(p); - return poly; -} - -inline Paths &operator<<(Paths &polys, const Path &p) { - polys.push_back(p); - return polys; -} - -std::ostream &operator<<(std::ostream &s, const IntPoint &p); - -std::ostream &operator<<(std::ostream &s, const Path &p); - -std::ostream &operator<<(std::ostream &s, const Paths &p); - -struct DoublePoint { - double X; - double Y; - - DoublePoint(double x = 0, double y = 0) : X(x), Y(y) {} - - DoublePoint(IntPoint ip) : X((double) ip.X), Y((double) ip.Y) {} -}; -//------------------------------------------------------------------------------ - -#ifdef use_xyz -typedef void (*ZFillCallback)(IntPoint& e1bot, IntPoint& e1top, IntPoint& e2bot, IntPoint& e2top, IntPoint& pt); -#endif - -enum InitOptions { - ioReverseSolution = 1, ioStrictlySimple = 2, ioPreserveCollinear = 4 -}; -enum JoinType { - jtSquare, jtRound, jtMiter -}; -enum EndType { - etClosedPolygon, etClosedLine, etOpenButt, etOpenSquare, etOpenRound -}; - -class PolyNode; - -typedef std::vector PolyNodes; - -class PolyNode { -public: - PolyNode(); - - virtual ~PolyNode() {}; - Path Contour; - PolyNodes Childs; - PolyNode *Parent; - - PolyNode *GetNext() const; - - bool IsHole() const; - - bool IsOpen() const; - - int ChildCount() const; - -private: - //PolyNode& operator =(PolyNode& other); - unsigned Index; //node index in Parent.Childs - bool m_IsOpen; - JoinType m_jointype; - EndType m_endtype; - - PolyNode *GetNextSiblingUp() const; - - void AddChild(PolyNode &child); - - friend class Clipper; //to access Index - friend class ClipperOffset; -}; - -class PolyTree : public PolyNode { -public: - ~PolyTree() { Clear(); }; - - PolyNode *GetFirst() const; - - void Clear(); - - int Total() const; - -private: - //PolyTree& operator =(PolyTree& other); - PolyNodes AllNodes; - - friend class Clipper; //to access AllNodes -}; - -bool Orientation(const Path &poly); - -double Area(const Path &poly); - -int PointInPolygon(const IntPoint &pt, const Path &path); - -void SimplifyPolygon(const Path &in_poly, Paths &out_polys, PolyFillType fillType = pftEvenOdd); - -void SimplifyPolygons(const Paths &in_polys, Paths &out_polys, PolyFillType fillType = pftEvenOdd); - -void SimplifyPolygons(Paths &polys, PolyFillType fillType = pftEvenOdd); - -void CleanPolygon(const Path &in_poly, Path &out_poly, double distance = 1.415); - -void CleanPolygon(Path &poly, double distance = 1.415); - -void CleanPolygons(const Paths &in_polys, Paths &out_polys, double distance = 1.415); - -void CleanPolygons(Paths &polys, double distance = 1.415); - -void MinkowskiSum(const Path &pattern, const Path &path, Paths &solution, bool pathIsClosed); - -void MinkowskiSum(const Path &pattern, const Paths &paths, Paths &solution, bool pathIsClosed); - -void MinkowskiDiff(const Path &poly1, const Path &poly2, Paths &solution); - -void PolyTreeToPaths(const PolyTree &polytree, Paths &paths); - -void ClosedPathsFromPolyTree(const PolyTree &polytree, Paths &paths); - -void OpenPathsFromPolyTree(PolyTree &polytree, Paths &paths); - -void ReversePath(Path &p); - -void ReversePaths(Paths &p); - -struct IntRect { - cInt left; - cInt top; - cInt right; - cInt bottom; -}; - -//enums that are used internally ... -enum EdgeSide { - esLeft = 1, esRight = 2 -}; - -//forward declarations (for stuff used internally) ... -struct TEdge; -struct IntersectNode; -struct LocalMinimum; -struct OutPt; -struct OutRec; -struct Join; - -typedef std::vector PolyOutList; -typedef std::vector EdgeList; -typedef std::vector JoinList; -typedef std::vector IntersectList; - -//------------------------------------------------------------------------------ - -//ClipperBase is the ancestor to the Clipper class. It should not be -//instantiated directly. This class simply abstracts the conversion of sets of -//polygon coordinates into edge objects that are stored in a LocalMinima list. -class ClipperBase { -public: - ClipperBase(); - - virtual ~ClipperBase(); - - virtual bool AddPath(const Path &pg, PolyType PolyTyp, bool Closed); - - bool AddPaths(const Paths &ppg, PolyType PolyTyp, bool Closed); - - virtual void Clear(); - - IntRect GetBounds(); - - bool PreserveCollinear() { return m_PreserveCollinear; }; - - void PreserveCollinear(bool value) { m_PreserveCollinear = value; }; -protected: - void DisposeLocalMinimaList(); - - TEdge *AddBoundsToLML(TEdge *e, bool IsClosed); - - virtual void Reset(); - - TEdge *ProcessBound(TEdge *E, bool IsClockwise); - - void InsertScanbeam(const cInt Y); - - bool PopScanbeam(cInt &Y); - - bool LocalMinimaPending(); - - bool PopLocalMinima(cInt Y, const LocalMinimum *&locMin); - - OutRec *CreateOutRec(); - - void DisposeAllOutRecs(); - - void DisposeOutRec(PolyOutList::size_type index); - - void SwapPositionsInAEL(TEdge *edge1, TEdge *edge2); - - void DeleteFromAEL(TEdge *e); - - void UpdateEdgeIntoAEL(TEdge *&e); - - typedef std::vector MinimaList; - MinimaList::iterator m_CurrentLM; - MinimaList m_MinimaList; - - bool m_UseFullRange; - EdgeList m_edges; - bool m_PreserveCollinear; - bool m_HasOpenPaths; - PolyOutList m_PolyOuts; - TEdge *m_ActiveEdges; - - typedef std::priority_queue ScanbeamList; - ScanbeamList m_Scanbeam; -}; -//------------------------------------------------------------------------------ - -class Clipper : public virtual ClipperBase { -public: - Clipper(int initOptions = 0); - - bool Execute(ClipType clipType, - Paths &solution, - PolyFillType fillType = pftEvenOdd); - - bool Execute(ClipType clipType, - Paths &solution, - PolyFillType subjFillType, - PolyFillType clipFillType); - - bool Execute(ClipType clipType, - PolyTree &polytree, - PolyFillType fillType = pftEvenOdd); - - bool Execute(ClipType clipType, - PolyTree &polytree, - PolyFillType subjFillType, - PolyFillType clipFillType); - - bool ReverseSolution() { return m_ReverseOutput; }; - - void ReverseSolution(bool value) { m_ReverseOutput = value; }; - - bool StrictlySimple() { return m_StrictSimple; }; - - void StrictlySimple(bool value) { m_StrictSimple = value; }; - //set the callback function for z value filling on intersections (otherwise Z is 0) -#ifdef use_xyz - void ZFillFunction(ZFillCallback zFillFunc); -#endif -protected: - virtual bool ExecuteInternal(); - -private: - JoinList m_Joins; - JoinList m_GhostJoins; - IntersectList m_IntersectList; - ClipType m_ClipType; - typedef std::list MaximaList; - MaximaList m_Maxima; - TEdge *m_SortedEdges; - bool m_ExecuteLocked; - PolyFillType m_ClipFillType; - PolyFillType m_SubjFillType; - bool m_ReverseOutput; - bool m_UsingPolyTree; - bool m_StrictSimple; -#ifdef use_xyz - ZFillCallback m_ZFill; //custom callback -#endif - - void SetWindingCount(TEdge &edge); - - bool IsEvenOddFillType(const TEdge &edge) const; - - bool IsEvenOddAltFillType(const TEdge &edge) const; - - void InsertLocalMinimaIntoAEL(const cInt botY); - - void InsertEdgeIntoAEL(TEdge *edge, TEdge *startEdge); - - void AddEdgeToSEL(TEdge *edge); - - bool PopEdgeFromSEL(TEdge *&edge); - - void CopyAELToSEL(); - - void DeleteFromSEL(TEdge *e); - - void SwapPositionsInSEL(TEdge *edge1, TEdge *edge2); - - bool IsContributing(const TEdge &edge) const; - - bool IsTopHorz(const cInt XPos); - - void DoMaxima(TEdge *e); - - void ProcessHorizontals(); - - void ProcessHorizontal(TEdge *horzEdge); - - void AddLocalMaxPoly(TEdge *e1, TEdge *e2, const IntPoint &pt); - - OutPt *AddLocalMinPoly(TEdge *e1, TEdge *e2, const IntPoint &pt); - - OutRec *GetOutRec(int idx); - - void AppendPolygon(TEdge *e1, TEdge *e2); - - void IntersectEdges(TEdge *e1, TEdge *e2, IntPoint &pt); - - OutPt *AddOutPt(TEdge *e, const IntPoint &pt); - - OutPt *GetLastOutPt(TEdge *e); - - bool ProcessIntersections(const cInt topY); - - void BuildIntersectList(const cInt topY); - - void ProcessIntersectList(); - - void ProcessEdgesAtTopOfScanbeam(const cInt topY); - - void BuildResult(Paths &polys); - - void BuildResult2(PolyTree &polytree); - - void SetHoleState(TEdge *e, OutRec *outrec); - - void DisposeIntersectNodes(); - - bool FixupIntersectionOrder(); - - void FixupOutPolygon(OutRec &outrec); - - void FixupOutPolyline(OutRec &outrec); - - bool IsHole(TEdge *e); - - bool FindOwnerFromSplitRecs(OutRec &outRec, OutRec *&currOrfl); - - void FixHoleLinkage(OutRec &outrec); - - void AddJoin(OutPt *op1, OutPt *op2, const IntPoint offPt); - - void ClearJoins(); - - void ClearGhostJoins(); - - void AddGhostJoin(OutPt *op, const IntPoint offPt); - - bool JoinPoints(Join *j, OutRec *outRec1, OutRec *outRec2); - - void JoinCommonEdges(); - - void DoSimplePolygons(); - - void FixupFirstLefts1(OutRec *OldOutRec, OutRec *NewOutRec); - - void FixupFirstLefts2(OutRec *InnerOutRec, OutRec *OuterOutRec); - - void FixupFirstLefts3(OutRec *OldOutRec, OutRec *NewOutRec); - -#ifdef use_xyz - void SetZ(IntPoint& pt, TEdge& e1, TEdge& e2); -#endif -}; -//------------------------------------------------------------------------------ - -class ClipperOffset { -public: - ClipperOffset(double miterLimit = 2.0, double roundPrecision = 0.25); - - ~ClipperOffset(); - - void AddPath(const Path &path, JoinType joinType, EndType endType); - - void AddPaths(const Paths &paths, JoinType joinType, EndType endType); - - void Execute(Paths &solution, double delta); - - void Execute(PolyTree &solution, double delta); - - void Clear(); - - double MiterLimit; - double ArcTolerance; -private: - Paths m_destPolys; - Path m_srcPoly; - Path m_destPoly; - std::vector m_normals; - double m_delta, m_sinA, m_sin, m_cos; - double m_miterLim, m_StepsPerRad; - IntPoint m_lowest; - PolyNode m_polyNodes; - - void FixOrientations(); - - void DoOffset(double delta); - - void OffsetPoint(int j, int &k, JoinType jointype); - - void DoSquare(int j, int k); - - void DoMiter(int j, int k, double r); - - void DoRound(int j, int k); -}; -//------------------------------------------------------------------------------ - -class clipperException : public std::exception { -public: - clipperException(const char *description) : m_descr(description) {} - - virtual ~clipperException() throw() {} - - virtual const char *what() const throw() { return m_descr.c_str(); } - -private: - std::string m_descr; -}; -//------------------------------------------------------------------------------ - -} //ClipperLib namespace - -#endif //clipper_hpp - - diff --git a/deploy/android_demo/app/src/main/cpp/ocr_crnn_process.cpp b/deploy/android_demo/app/src/main/cpp/ocr_crnn_process.cpp deleted file mode 100644 index 96f37b9b42..0000000000 --- a/deploy/android_demo/app/src/main/cpp/ocr_crnn_process.cpp +++ /dev/null @@ -1,140 +0,0 @@ -// Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. -// -// Licensed under the Apache License, Version 2.0 (the "License"); -// you may not use this file except in compliance with the License. -// You may obtain a copy of the License at -// -// http://www.apache.org/licenses/LICENSE-2.0 -// -// Unless required by applicable law or agreed to in writing, software -// distributed under the License is distributed on an "AS IS" BASIS, -// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -// See the License for the specific language governing permissions and -// limitations under the License. - -#include "ocr_crnn_process.h" -#include -#include -#include -#include -#include -#include - -const std::string CHARACTER_TYPE = "ch"; -const int MAX_DICT_LENGTH = 6624; -const std::vector REC_IMAGE_SHAPE = {3, 32, 320}; - -static cv::Mat crnn_resize_norm_img(cv::Mat img, float wh_ratio) { - int imgC = REC_IMAGE_SHAPE[0]; - int imgW = REC_IMAGE_SHAPE[2]; - int imgH = REC_IMAGE_SHAPE[1]; - - if (CHARACTER_TYPE == "ch") - imgW = int(32 * wh_ratio); - - float ratio = float(img.cols) / float(img.rows); - int resize_w = 0; - if (ceilf(imgH * ratio) > imgW) - resize_w = imgW; - else - resize_w = int(ceilf(imgH * ratio)); - cv::Mat resize_img; - cv::resize(img, resize_img, cv::Size(resize_w, imgH), 0.f, 0.f, cv::INTER_CUBIC); - - resize_img.convertTo(resize_img, CV_32FC3, 1 / 255.f); - - for (int h = 0; h < resize_img.rows; h++) { - for (int w = 0; w < resize_img.cols; w++) { - resize_img.at(h, w)[0] = (resize_img.at(h, w)[0] - 0.5) * 2; - resize_img.at(h, w)[1] = (resize_img.at(h, w)[1] - 0.5) * 2; - resize_img.at(h, w)[2] = (resize_img.at(h, w)[2] - 0.5) * 2; - } - } - - cv::Mat dist; - cv::copyMakeBorder(resize_img, dist, 0, 0, 0, int(imgW - resize_w), cv::BORDER_CONSTANT, - {0, 0, 0}); - - return dist; - -} - -cv::Mat crnn_resize_img(const cv::Mat &img, float wh_ratio) { - int imgC = REC_IMAGE_SHAPE[0]; - int imgW = REC_IMAGE_SHAPE[2]; - int imgH = REC_IMAGE_SHAPE[1]; - - if (CHARACTER_TYPE == "ch") { - imgW = int(32 * wh_ratio); - } - - float ratio = float(img.cols) / float(img.rows); - int resize_w = 0; - if (ceilf(imgH * ratio) > imgW) - resize_w = imgW; - else - resize_w = int(ceilf(imgH * ratio)); - cv::Mat resize_img; - cv::resize(img, resize_img, cv::Size(resize_w, imgH)); - return resize_img; -} - - -cv::Mat get_rotate_crop_image(const cv::Mat &srcimage, const std::vector> &box) { - - std::vector> points = box; - - int x_collect[4] = {box[0][0], box[1][0], box[2][0], box[3][0]}; - int y_collect[4] = {box[0][1], box[1][1], box[2][1], box[3][1]}; - int left = int(*std::min_element(x_collect, x_collect + 4)); - int right = int(*std::max_element(x_collect, x_collect + 4)); - int top = int(*std::min_element(y_collect, y_collect + 4)); - int bottom = int(*std::max_element(y_collect, y_collect + 4)); - - cv::Mat img_crop; - srcimage(cv::Rect(left, top, right - left, bottom - top)).copyTo(img_crop); - - for (int i = 0; i < points.size(); i++) { - points[i][0] -= left; - points[i][1] -= top; - } - - int img_crop_width = int(sqrt(pow(points[0][0] - points[1][0], 2) + - pow(points[0][1] - points[1][1], 2))); - int img_crop_height = int(sqrt(pow(points[0][0] - points[3][0], 2) + - pow(points[0][1] - points[3][1], 2))); - - cv::Point2f pts_std[4]; - pts_std[0] = cv::Point2f(0., 0.); - pts_std[1] = cv::Point2f(img_crop_width, 0.); - pts_std[2] = cv::Point2f(img_crop_width, img_crop_height); - pts_std[3] = cv::Point2f(0.f, img_crop_height); - - cv::Point2f pointsf[4]; - pointsf[0] = cv::Point2f(points[0][0], points[0][1]); - pointsf[1] = cv::Point2f(points[1][0], points[1][1]); - pointsf[2] = cv::Point2f(points[2][0], points[2][1]); - pointsf[3] = cv::Point2f(points[3][0], points[3][1]); - - cv::Mat M = cv::getPerspectiveTransform(pointsf, pts_std); - - cv::Mat dst_img; - cv::warpPerspective(img_crop, dst_img, M, cv::Size(img_crop_width, img_crop_height), - cv::BORDER_REPLICATE); - - if (float(dst_img.rows) >= float(dst_img.cols) * 1.5) { - /* - cv::Mat srcCopy = cv::Mat(dst_img.rows, dst_img.cols, dst_img.depth()); - cv::transpose(dst_img, srcCopy); - cv::flip(srcCopy, srcCopy, 0); - return srcCopy; - */ - cv::transpose(dst_img, dst_img); - cv::flip(dst_img, dst_img, 0); - return dst_img; - } else { - return dst_img; - } - -} - diff --git a/deploy/android_demo/app/src/main/cpp/ocr_crnn_process.h b/deploy/android_demo/app/src/main/cpp/ocr_crnn_process.h deleted file mode 100644 index 99d0124afc..0000000000 --- a/deploy/android_demo/app/src/main/cpp/ocr_crnn_process.h +++ /dev/null @@ -1,19 +0,0 @@ -// -// Created by fujiayi on 2020/7/3. -// -#pragma once - -#include -#include -#include "common.h" - -extern const std::vector REC_IMAGE_SHAPE; - -cv::Mat get_rotate_crop_image(const cv::Mat &srcimage, const std::vector> &box); - -cv::Mat crnn_resize_img(const cv::Mat &img, float wh_ratio); - -template -inline size_t argmax(ForwardIterator first, ForwardIterator last) { - return std::distance(first, std::max_element(first, last)); -} \ No newline at end of file diff --git a/deploy/android_demo/app/src/main/cpp/ocr_db_post_process.cpp b/deploy/android_demo/app/src/main/cpp/ocr_db_post_process.cpp deleted file mode 100644 index 7c3c60db1f..0000000000 --- a/deploy/android_demo/app/src/main/cpp/ocr_db_post_process.cpp +++ /dev/null @@ -1,336 +0,0 @@ -// Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. -// -// Licensed under the Apache License, Version 2.0 (the "License"); -// you may not use this file except in compliance with the License. -// You may obtain a copy of the License at -// -// http://www.apache.org/licenses/LICENSE-2.0 -// -// Unless required by applicable law or agreed to in writing, software -// distributed under the License is distributed on an "AS IS" BASIS, -// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -// See the License for the specific language governing permissions and -// limitations under the License. - -#include -#include -#include -#include "opencv2/core.hpp" -#include "opencv2/imgcodecs.hpp" -#include "opencv2/imgproc.hpp" -#include "ocr_clipper.hpp" - -static void getcontourarea(float **box, float unclip_ratio, float &distance) { - int pts_num = 4; - float area = 0.0f; - float dist = 0.0f; - for (int i = 0; i < pts_num; i++) { - area += box[i][0] * box[(i + 1) % pts_num][1] - box[i][1] * box[(i + 1) % pts_num][0]; - dist += sqrtf( - (box[i][0] - box[(i + 1) % pts_num][0]) * (box[i][0] - box[(i + 1) % pts_num][0]) + - (box[i][1] - box[(i + 1) % pts_num][1]) * (box[i][1] - box[(i + 1) % pts_num][1])); - } - area = fabs(float(area / 2.0)); - - distance = area * unclip_ratio / dist; - -} - -static cv::RotatedRect unclip(float **box) { - float unclip_ratio = 2.0; - float distance = 1.0; - - getcontourarea(box, unclip_ratio, distance); - - ClipperLib::ClipperOffset offset; - ClipperLib::Path p; - p << ClipperLib::IntPoint(int(box[0][0]), int(box[0][1])) - << ClipperLib::IntPoint(int(box[1][0]), int(box[1][1])) << - ClipperLib::IntPoint(int(box[2][0]), int(box[2][1])) - << ClipperLib::IntPoint(int(box[3][0]), int(box[3][1])); - offset.AddPath(p, ClipperLib::jtRound, ClipperLib::etClosedPolygon); - - ClipperLib::Paths soln; - offset.Execute(soln, distance); - std::vector points; - - for (int j = 0; j < soln.size(); j++) { - for (int i = 0; i < soln[soln.size() - 1].size(); i++) { - points.emplace_back(soln[j][i].X, soln[j][i].Y); - } - } - cv::RotatedRect res = cv::minAreaRect(points); - - return res; -} - -static float **Mat2Vec(cv::Mat mat) { - auto **array = new float *[mat.rows]; - for (int i = 0; i < mat.rows; ++i){ - array[i] = new float[mat.cols]; - } - for (int i = 0; i < mat.rows; ++i) { - for (int j = 0; j < mat.cols; ++j) { - array[i][j] = mat.at(i, j); - } - } - - return array; -} - -static void quickSort(float **s, int l, int r) { - if (l < r) { - int i = l, j = r; - float x = s[l][0]; - float *xp = s[l]; - while (i < j) { - while (i < j && s[j][0] >= x){ - j--; - } - if (i < j){ - std::swap(s[i++], s[j]); - } - while (i < j && s[i][0] < x){ - i++; - } - if (i < j){ - std::swap(s[j--], s[i]); - } - } - s[i] = xp; - quickSort(s, l, i - 1); - quickSort(s, i + 1, r); - } -} - -static void quickSort_vector(std::vector> &box, int l, int r, int axis) { - if (l < r) { - int i = l, j = r; - int x = box[l][axis]; - std::vector xp(box[l]); - while (i < j) { - while (i < j && box[j][axis] >= x){ - j--; - } - if (i < j){ - std::swap(box[i++], box[j]); - } - while (i < j && box[i][axis] < x){ - i++; - } - if (i < j){ - std::swap(box[j--], box[i]); - } - } - box[i] = xp; - quickSort_vector(box, l, i - 1, axis); - quickSort_vector(box, i + 1, r, axis); - } -} - -static std::vector> order_points_clockwise(std::vector> pts) { - std::vector> box = pts; - quickSort_vector(box, 0, int(box.size() - 1), 0); - std::vector> leftmost = {box[0], box[1]}; - std::vector> rightmost = {box[2], box[3]}; - - if (leftmost[0][1] > leftmost[1][1]){ - std::swap(leftmost[0], leftmost[1]); - } - - if (rightmost[0][1] > rightmost[1][1]){ - std::swap(rightmost[0], rightmost[1]); - } - - std::vector> rect = {leftmost[0], rightmost[0], rightmost[1], leftmost[1]}; - return rect; -} - -static float **get_mini_boxes(cv::RotatedRect box, float &ssid) { - ssid = box.size.width >= box.size.height ? box.size.height : box.size.width; - - cv::Mat points; - cv::boxPoints(box, points); - // sorted box points - auto array = Mat2Vec(points); - quickSort(array, 0, 3); - - float *idx1 = array[0], *idx2 = array[1], *idx3 = array[2], *idx4 = array[3]; - if (array[3][1] <= array[2][1]) { - idx2 = array[3]; - idx3 = array[2]; - } else { - idx2 = array[2]; - idx3 = array[3]; - } - if (array[1][1] <= array[0][1]) { - idx1 = array[1]; - idx4 = array[0]; - } else { - idx1 = array[0]; - idx4 = array[1]; - } - - array[0] = idx1; - array[1] = idx2; - array[2] = idx3; - array[3] = idx4; - - return array; -} - -template T clamp(T x, T min, T max) { - if (x > max){ - return max; - } - if (x < min){ - return min; - } - return x; -} - -static float clampf(float x, float min, float max) { - if (x > max) - return max; - if (x < min) - return min; - return x; -} - - -float box_score_fast(float **box_array, cv::Mat pred) { - auto array = box_array; - int width = pred.cols; - int height = pred.rows; - - float box_x[4] = {array[0][0], array[1][0], array[2][0], array[3][0]}; - float box_y[4] = {array[0][1], array[1][1], array[2][1], array[3][1]}; - - int xmin = clamp(int(std::floorf(*(std::min_element(box_x, box_x + 4)))), 0, width - 1); - int xmax = clamp(int(std::ceilf(*(std::max_element(box_x, box_x + 4)))), 0, width - 1); - int ymin = clamp(int(std::floorf(*(std::min_element(box_y, box_y + 4)))), 0, height - 1); - int ymax = clamp(int(std::ceilf(*(std::max_element(box_y, box_y + 4)))), 0, height - 1); - - cv::Mat mask; - mask = cv::Mat::zeros(ymax - ymin + 1, xmax - xmin + 1, CV_8UC1); - - cv::Point root_point[4]; - root_point[0] = cv::Point(int(array[0][0]) - xmin, int(array[0][1]) - ymin); - root_point[1] = cv::Point(int(array[1][0]) - xmin, int(array[1][1]) - ymin); - root_point[2] = cv::Point(int(array[2][0]) - xmin, int(array[2][1]) - ymin); - root_point[3] = cv::Point(int(array[3][0]) - xmin, int(array[3][1]) - ymin); - const cv::Point *ppt[1] = {root_point}; - int npt[] = {4}; - cv::fillPoly(mask, ppt, npt, 1, cv::Scalar(1)); - - cv::Mat croppedImg; - pred(cv::Rect(xmin, ymin, xmax - xmin + 1, ymax - ymin + 1)).copyTo(croppedImg); - - auto score = cv::mean(croppedImg, mask)[0]; - return score; -} - - -std::vector>> -boxes_from_bitmap(const cv::Mat& pred, const cv::Mat& bitmap) { - const int min_size = 3; - const int max_candidates = 1000; - const float box_thresh = 0.5; - - int width = bitmap.cols; - int height = bitmap.rows; - - std::vector> contours; - std::vector hierarchy; - - cv::findContours(bitmap, contours, hierarchy, cv::RETR_LIST, cv::CHAIN_APPROX_SIMPLE); - - int num_contours = contours.size() >= max_candidates ? max_candidates : contours.size(); - - std::vector>> boxes; - - for (int _i = 0; _i < num_contours; _i++) { - float ssid; - cv::RotatedRect box = cv::minAreaRect(contours[_i]); - auto array = get_mini_boxes(box, ssid); - - auto box_for_unclip = array; - //end get_mini_box - - if (ssid < min_size) { - continue; - } - - float score; - score = box_score_fast(array, pred); - //end box_score_fast - if (score < box_thresh){ - continue; - } - - - // start for unclip - cv::RotatedRect points = unclip(box_for_unclip); - // end for unclip - - cv::RotatedRect clipbox = points; - auto cliparray = get_mini_boxes(clipbox, ssid); - - if (ssid < min_size + 2) continue; - - int dest_width = pred.cols; - int dest_height = pred.rows; - std::vector> intcliparray; - - for (int num_pt = 0; num_pt < 4; num_pt++) { - std::vector a{ - int(clampf(roundf(cliparray[num_pt][0] / float(width) * float(dest_width)), 0, - float(dest_width))), - int(clampf(roundf(cliparray[num_pt][1] / float(height) * float(dest_height)), 0, - float(dest_height)))}; - intcliparray.emplace_back(std::move(a)); - } - boxes.emplace_back(std::move(intcliparray)); - - }//end for - return boxes; -} - -int _max(int a, int b) { - return a >= b ? a : b; -} - -int _min(int a, int b) { - return a >= b ? b : a; -} - -std::vector>> -filter_tag_det_res(const std::vector>>& o_boxes, - float ratio_h, float ratio_w,const cv::Mat& srcimg) { - int oriimg_h = srcimg.rows; - int oriimg_w = srcimg.cols; - std::vector>> boxes{o_boxes}; - std::vector>> root_points; - for (int n = 0; n < boxes.size(); n++) { - boxes[n] = order_points_clockwise(boxes[n]); - for (int m = 0; m < boxes[0].size(); m++) { - boxes[n][m][0] /= ratio_w; - boxes[n][m][1] /= ratio_h; - - boxes[n][m][0] = int(_min(_max(boxes[n][m][0], 0), oriimg_w - 1)); - boxes[n][m][1] = int(_min(_max(boxes[n][m][1], 0), oriimg_h - 1)); - } - } - - for (int n = 0; n < boxes.size(); n++) { - int rect_width, rect_height; - rect_width = int(sqrt( - pow(boxes[n][0][0] - boxes[n][1][0], 2) + pow(boxes[n][0][1] - boxes[n][1][1], 2))); - rect_height = int(sqrt( - pow(boxes[n][0][0] - boxes[n][3][0], 2) + pow(boxes[n][0][1] - boxes[n][3][1], 2))); - if (rect_width <= 10 || rect_height <= 10) - continue; - root_points.push_back(boxes[n]); - } - return root_points; -} \ No newline at end of file diff --git a/deploy/android_demo/app/src/main/cpp/ocr_db_post_process.h b/deploy/android_demo/app/src/main/cpp/ocr_db_post_process.h deleted file mode 100644 index 86117512e3..0000000000 --- a/deploy/android_demo/app/src/main/cpp/ocr_db_post_process.h +++ /dev/null @@ -1,17 +0,0 @@ -// -// Created by fujiayi on 2020/7/2. -// -#pragma once -#include -#include - -std::vector>> -boxes_from_bitmap(const cv::Mat &pred, const cv::Mat &bitmap); - -std::vector>> -filter_tag_det_res( - const std::vector>> &o_boxes, - float ratio_h, - float ratio_w, - const cv::Mat &srcimg -); \ No newline at end of file diff --git a/deploy/android_demo/app/src/main/cpp/ocr_ppredictor.cpp b/deploy/android_demo/app/src/main/cpp/ocr_ppredictor.cpp deleted file mode 100644 index 3d01477155..0000000000 --- a/deploy/android_demo/app/src/main/cpp/ocr_ppredictor.cpp +++ /dev/null @@ -1,186 +0,0 @@ -// -// Created by fujiayi on 2020/7/1. -// - -#include "ocr_ppredictor.h" -#include "preprocess.h" -#include "common.h" -#include "ocr_db_post_process.h" -#include "ocr_crnn_process.h" - -namespace ppredictor { - -OCR_PPredictor::OCR_PPredictor(const OCR_Config &config) : _config(config) { - -} - -int -OCR_PPredictor::init(const std::string &det_model_content, const std::string &rec_model_content) { - _det_predictor = std::unique_ptr( - new PPredictor{_config.thread_num, NET_OCR, _config.mode}); - _det_predictor->init_nb(det_model_content); - - _rec_predictor = std::unique_ptr( - new PPredictor{_config.thread_num, NET_OCR_INTERNAL, _config.mode}); - _rec_predictor->init_nb(rec_model_content); - return RETURN_OK; -} - -int OCR_PPredictor::init_from_file(const std::string &det_model_path, const std::string &rec_model_path){ - _det_predictor = std::unique_ptr( - new PPredictor{_config.thread_num, NET_OCR, _config.mode}); - _det_predictor->init_from_file(det_model_path); - - _rec_predictor = std::unique_ptr( - new PPredictor{_config.thread_num, NET_OCR_INTERNAL, _config.mode}); - _rec_predictor->init_from_file(rec_model_path); - return RETURN_OK; -} -/** - * for debug use, show result of First Step - * @param filter_boxes - * @param boxes - * @param srcimg - */ -static void visual_img(const std::vector>> &filter_boxes, - const std::vector>> &boxes, - const cv::Mat &srcimg) { - // visualization - cv::Point rook_points[filter_boxes.size()][4]; - for (int n = 0; n < filter_boxes.size(); n++) { - for (int m = 0; m < filter_boxes[0].size(); m++) { - rook_points[n][m] = cv::Point(int(filter_boxes[n][m][0]), int(filter_boxes[n][m][1])); - } - } - - cv::Mat img_vis; - srcimg.copyTo(img_vis); - for (int n = 0; n < boxes.size(); n++) { - const cv::Point *ppt[1] = {rook_points[n]}; - int npt[] = {4}; - cv::polylines(img_vis, ppt, npt, 1, 1, CV_RGB(0, 255, 0), 2, 8, 0); - } - // 调试用,自行替换需要修改的路径 - cv::imwrite("/sdcard/1/vis.png", img_vis); -} - -std::vector -OCR_PPredictor::infer_ocr(const std::vector &dims, const float *input_data, int input_len, - int net_flag, cv::Mat &origin) { - - PredictorInput input = _det_predictor->get_first_input(); - input.set_dims(dims); - input.set_data(input_data, input_len); - std::vector results = _det_predictor->infer(); - PredictorOutput &res = results.at(0); - std::vector>> filtered_box - = calc_filtered_boxes(res.get_float_data(), res.get_size(), (int) dims[2], (int) dims[3], - origin); - LOGI("Filter_box size %ld", filtered_box.size()); - return infer_rec(filtered_box, origin); -} - -std::vector -OCR_PPredictor::infer_rec(const std::vector>> &boxes, - const cv::Mat &origin_img) { - std::vector mean = {0.5f, 0.5f, 0.5f}; - std::vector scale = {1 / 0.5f, 1 / 0.5f, 1 / 0.5f}; - std::vector dims = {1, 3, 0, 0}; - std::vector ocr_results; - - PredictorInput input = _rec_predictor->get_first_input(); - for (auto bp = boxes.crbegin(); bp != boxes.crend(); ++bp) { - const std::vector> &box = *bp; - cv::Mat crop_img = get_rotate_crop_image(origin_img, box); - float wh_ratio = float(crop_img.cols) / float(crop_img.rows); - cv::Mat input_image = crnn_resize_img(crop_img, wh_ratio); - input_image.convertTo(input_image, CV_32FC3, 1 / 255.0f); - const float *dimg = reinterpret_cast(input_image.data); - int input_size = input_image.rows * input_image.cols; - - dims[2] = input_image.rows; - dims[3] = input_image.cols; - input.set_dims(dims); - - neon_mean_scale(dimg, input.get_mutable_float_data(), input_size, mean, scale); - - std::vector results = _rec_predictor->infer(); - - OCRPredictResult res; - res.word_index = postprocess_rec_word_index(results.at(0)); - if (res.word_index.empty()) { - continue; - } - res.score = postprocess_rec_score(results.at(1)); - res.points = box; - ocr_results.emplace_back(std::move(res)); - } - LOGI("ocr_results finished %lu", ocr_results.size()); - return ocr_results; -} - -std::vector>> -OCR_PPredictor::calc_filtered_boxes(const float *pred, int pred_size, int output_height, - int output_width, const cv::Mat &origin) { - const double threshold = 0.3; - const double maxvalue = 1; - - cv::Mat pred_map = cv::Mat::zeros(output_height, output_width, CV_32F); - memcpy(pred_map.data, pred, pred_size * sizeof(float)); - cv::Mat cbuf_map; - pred_map.convertTo(cbuf_map, CV_8UC1); - - cv::Mat bit_map; - cv::threshold(cbuf_map, bit_map, threshold, maxvalue, cv::THRESH_BINARY); - - std::vector>> boxes = boxes_from_bitmap(pred_map, bit_map); - float ratio_h = output_height * 1.0f / origin.rows; - float ratio_w = output_width * 1.0f / origin.cols; - std::vector>> filter_boxes = filter_tag_det_res(boxes, ratio_h, - ratio_w, origin); - return filter_boxes; -} - -std::vector OCR_PPredictor::postprocess_rec_word_index(const PredictorOutput &res) { - const int *rec_idx = res.get_int_data(); - const std::vector> rec_idx_lod = res.get_lod(); - - std::vector pred_idx; - for (int n = int(rec_idx_lod[0][0]); n < int(rec_idx_lod[0][1] * 2); n += 2) { - pred_idx.emplace_back(rec_idx[n]); - } - return pred_idx; -} - -float OCR_PPredictor::postprocess_rec_score(const PredictorOutput &res) { - const float *predict_batch = res.get_float_data(); - const std::vector predict_shape = res.get_shape(); - const std::vector> predict_lod = res.get_lod(); - int blank = predict_shape[1]; - float score = 0.f; - int count = 0; - for (int n = predict_lod[0][0]; n < predict_lod[0][1] - 1; n++) { - int argmax_idx = argmax(predict_batch + n * predict_shape[1], - predict_batch + (n + 1) * predict_shape[1]); - float max_value = predict_batch[n * predict_shape[1] + argmax_idx]; - if (blank - 1 - argmax_idx > 1e-5) { - score += max_value; - count += 1; - } - - } - if (count == 0) { - LOGE("calc score count 0"); - } else { - score /= count; - } - LOGI("calc score: %f", score); - return score; - -} - - -NET_TYPE OCR_PPredictor::get_net_flag() const { - return NET_OCR; -} -} \ No newline at end of file diff --git a/deploy/android_demo/app/src/main/cpp/ocr_ppredictor.h b/deploy/android_demo/app/src/main/cpp/ocr_ppredictor.h deleted file mode 100644 index eb2bc3bc98..0000000000 --- a/deploy/android_demo/app/src/main/cpp/ocr_ppredictor.h +++ /dev/null @@ -1,112 +0,0 @@ -// -// Created by fujiayi on 2020/7/1. -// - -#pragma once - -#include -#include -#include -#include "ppredictor.h" - -namespace ppredictor { - -/** - * Config - */ -struct OCR_Config { - int thread_num = 4; // Thread num - paddle::lite_api::PowerMode mode = paddle::lite_api::LITE_POWER_HIGH; // PaddleLite Mode -}; - -/** - * PolyGone Result - */ -struct OCRPredictResult { - std::vector word_index; - std::vector> points; - float score; -}; - -/** - * OCR there are 2 models - * 1. First model(det),select polygones to show where are the texts - * 2. crop from the origin images, use these polygones to infer - */ -class OCR_PPredictor : public PPredictor_Interface { -public: - OCR_PPredictor(const OCR_Config &config); - - virtual ~OCR_PPredictor() { - - } - - /** - * 初始化二个模型的Predictor - * @param det_model_content - * @param rec_model_content - * @return - */ - int init(const std::string &det_model_content, const std::string &rec_model_content); - int init_from_file(const std::string &det_model_path, const std::string &rec_model_path); - /** - * Return OCR result - * @param dims - * @param input_data - * @param input_len - * @param net_flag - * @param origin - * @return - */ - virtual std::vector - infer_ocr(const std::vector &dims, const float *input_data, int input_len, - int net_flag, cv::Mat &origin); - - - virtual NET_TYPE get_net_flag() const; - - -private: - - /** - * calcul Polygone from the result image of first model - * @param pred - * @param output_height - * @param output_width - * @param origin - * @return - */ - std::vector>> - calc_filtered_boxes(const float *pred, int pred_size, int output_height, int output_width, - const cv::Mat &origin); - - /** - * infer for second model - * - * @param boxes - * @param origin - * @return - */ - std::vector - infer_rec(const std::vector>> &boxes, const cv::Mat &origin); - - /** - * Postprocess or sencod model to extract text - * @param res - * @return - */ - std::vector postprocess_rec_word_index(const PredictorOutput &res); - - /** - * calculate confidence of second model text result - * @param res - * @return - */ - float postprocess_rec_score(const PredictorOutput &res); - - std::unique_ptr _det_predictor; - std::unique_ptr _rec_predictor; - OCR_Config _config; - -}; -} diff --git a/deploy/android_demo/app/src/main/cpp/ppredictor.cpp b/deploy/android_demo/app/src/main/cpp/ppredictor.cpp deleted file mode 100644 index a9086bc6c0..0000000000 --- a/deploy/android_demo/app/src/main/cpp/ppredictor.cpp +++ /dev/null @@ -1,70 +0,0 @@ -#include "ppredictor.h" -#include "common.h" - -namespace ppredictor { -PPredictor::PPredictor(int thread_num, int net_flag, paddle::lite_api::PowerMode mode) : - _thread_num(thread_num), _net_flag(net_flag), _mode(mode) { -} - -int PPredictor::init_nb(const std::string &model_content) { - paddle::lite_api::MobileConfig config; - config.set_model_from_buffer(model_content); - return _init(config); -} - -int PPredictor::init_from_file(const std::string &model_content){ - paddle::lite_api::MobileConfig config; - config.set_model_from_file(model_content); - return _init(config); -} - -template -int PPredictor::_init(ConfigT &config) { - config.set_threads(_thread_num); - config.set_power_mode(_mode); - _predictor = paddle::lite_api::CreatePaddlePredictor(config); - LOGI("paddle instance created"); - return RETURN_OK; -} - -PredictorInput PPredictor::get_input(int index) { - PredictorInput input{_predictor->GetInput(index), index, _net_flag}; - _is_input_get = true; - return input; -} - -std::vector PPredictor::get_inputs(int num) { - std::vector results; - for (int i = 0; i < num; i++) { - results.emplace_back(get_input(i)); - } - return results; -} - -PredictorInput PPredictor::get_first_input() { - return get_input(0); -} - -std::vector PPredictor::infer() { - LOGI("infer Run start %d", _net_flag); - std::vector results; - if (!_is_input_get) { - return results; - } - _predictor->Run(); - LOGI("infer Run end"); - - for (int i = 0; i < _predictor->GetOutputNames().size(); i++) { - std::unique_ptr output_tensor = _predictor->GetOutput(i); - LOGI("output tensor[%d] size %ld", i, product(output_tensor->shape())); - PredictorOutput result{std::move(output_tensor), i, _net_flag}; - results.emplace_back(std::move(result)); - } - return results; -} - -NET_TYPE PPredictor::get_net_flag() const { - return (NET_TYPE) _net_flag; -} - -} \ No newline at end of file diff --git a/deploy/android_demo/app/src/main/cpp/ppredictor.h b/deploy/android_demo/app/src/main/cpp/ppredictor.h deleted file mode 100644 index 1391109f91..0000000000 --- a/deploy/android_demo/app/src/main/cpp/ppredictor.h +++ /dev/null @@ -1,74 +0,0 @@ -#pragma once - -#include "paddle_api.h" -#include "predictor_input.h" -#include "predictor_output.h" - -namespace ppredictor { - -/** - * PaddleLite Preditor Common Interface - */ -class PPredictor_Interface { -public: - virtual ~PPredictor_Interface() { - - } - - - virtual NET_TYPE get_net_flag() const = 0; - -}; - -/** - * Common Predictor - */ -class PPredictor : public PPredictor_Interface { -public: - PPredictor(int thread_num, int net_flag = 0, - paddle::lite_api::PowerMode mode = paddle::lite_api::LITE_POWER_HIGH); - - virtual ~PPredictor() { - - } - - /** - * init paddlitelite opt model,nb format ,or use ini_paddle - * @param model_content - * @return 0 - */ - virtual int init_nb(const std::string &model_content); - - virtual int init_from_file(const std::string &model_content); - - std::vector infer(); - - std::shared_ptr get_predictor() { - return _predictor; - } - - virtual std::vector get_inputs(int num); - - virtual PredictorInput get_input(int index); - - virtual PredictorInput get_first_input(); - - virtual NET_TYPE get_net_flag() const; - -protected: - template - int _init(ConfigT &config); - -private: - int _thread_num; - paddle::lite_api::PowerMode _mode; - std::shared_ptr _predictor; - bool _is_input_get = false; - int _net_flag; - -}; - - -} - - diff --git a/deploy/android_demo/app/src/main/cpp/predictor_input.cpp b/deploy/android_demo/app/src/main/cpp/predictor_input.cpp deleted file mode 100644 index 9a1dd223fd..0000000000 --- a/deploy/android_demo/app/src/main/cpp/predictor_input.cpp +++ /dev/null @@ -1,29 +0,0 @@ -#include "predictor_input.h" - -namespace ppredictor { - - -void PredictorInput::set_dims(std::vector dims) { - // yolov3 - if (_net_flag == 101 && _index == 1) { - _tensor->Resize({1, 2}); - _tensor->mutable_data()[0] = (int) dims.at(2); - _tensor->mutable_data()[1] = (int) dims.at(3); - } else { - _tensor->Resize(dims); - } - _is_dims_set = true; -} - -float *PredictorInput::get_mutable_float_data() { - if (!_is_dims_set) { - LOGE("PredictorInput::set_dims is not called"); - } - return _tensor->mutable_data(); -} - -void PredictorInput::set_data(const float *input_data, int input_float_len) { - float *input_raw_data = get_mutable_float_data(); - memcpy(input_raw_data, input_data, input_float_len * sizeof(float)); -} -} \ No newline at end of file diff --git a/deploy/android_demo/app/src/main/cpp/predictor_input.h b/deploy/android_demo/app/src/main/cpp/predictor_input.h deleted file mode 100644 index b48db18952..0000000000 --- a/deploy/android_demo/app/src/main/cpp/predictor_input.h +++ /dev/null @@ -1,28 +0,0 @@ -#pragma once - -#include -#include -#include "common.h" - -namespace ppredictor { -class PredictorInput { -public: - PredictorInput(std::unique_ptr &&tensor, int index, int net_flag) : - _tensor(std::move(tensor)), _index(index),_net_flag(net_flag) { - - } - - - void set_dims(std::vector dims); - - float *get_mutable_float_data(); - - void set_data(const float *input_data, int input_float_len); - -private: - std::unique_ptr _tensor; - bool _is_dims_set = false; - int _index; - int _net_flag; -}; -} diff --git a/deploy/android_demo/app/src/main/cpp/predictor_output.cpp b/deploy/android_demo/app/src/main/cpp/predictor_output.cpp deleted file mode 100644 index 081556333d..0000000000 --- a/deploy/android_demo/app/src/main/cpp/predictor_output.cpp +++ /dev/null @@ -1,27 +0,0 @@ -#include "predictor_output.h" -namespace ppredictor { -const float* PredictorOutput::get_float_data() const{ - return _tensor->data(); -} - -const int* PredictorOutput::get_int_data() const{ - return _tensor->data(); -} - -const std::vector> PredictorOutput::get_lod() const{ - return _tensor->lod(); -} - -int64_t PredictorOutput::get_size() const{ - if (_net_flag == NET_OCR) { - return _tensor->shape().at(2) * _tensor->shape().at(3); - } else { - return product(_tensor->shape()); - } -} - -const std::vector PredictorOutput::get_shape() const{ - return _tensor->shape(); - -} -} \ No newline at end of file diff --git a/deploy/android_demo/app/src/main/cpp/predictor_output.h b/deploy/android_demo/app/src/main/cpp/predictor_output.h deleted file mode 100644 index ec7086c62f..0000000000 --- a/deploy/android_demo/app/src/main/cpp/predictor_output.h +++ /dev/null @@ -1,35 +0,0 @@ -#pragma once - -#include -#include -#include "common.h" - -namespace ppredictor { -class PredictorOutput { -public: - PredictorOutput(){ - - } - PredictorOutput(std::unique_ptr &&tensor, int index, int net_flag) : - _tensor(std::move(tensor)), _index(index), _net_flag(net_flag) { - - } - - const float* get_float_data() const; - const int* get_int_data() const; - int64_t get_size() const; - const std::vector> get_lod() const; - const std::vector get_shape() const; - - std::vector data; // return float, or use data_int - std::vector data_int; // several layers return int ,or use data - std::vector shape; // PaddleLite output shape - std::vector> lod; // PaddleLite output lod - -private: - std::unique_ptr _tensor; - int _index; - int _net_flag; -}; -} - diff --git a/deploy/android_demo/app/src/main/cpp/preprocess.cpp b/deploy/android_demo/app/src/main/cpp/preprocess.cpp deleted file mode 100644 index 5543cdd1d6..0000000000 --- a/deploy/android_demo/app/src/main/cpp/preprocess.cpp +++ /dev/null @@ -1,84 +0,0 @@ -#include "preprocess.h" -#include - -cv::Mat bitmap_to_cv_mat(JNIEnv *env, jobject bitmap) { - AndroidBitmapInfo info; - int result = AndroidBitmap_getInfo(env, bitmap, &info); - if (result != ANDROID_BITMAP_RESULT_SUCCESS) { - LOGE("AndroidBitmap_getInfo failed, result: %d", result); - return cv::Mat{}; - } - if (info.format != ANDROID_BITMAP_FORMAT_RGBA_8888) { - LOGE("Bitmap format is not RGBA_8888 !"); - return cv::Mat{}; - } - unsigned char *srcData = NULL; - AndroidBitmap_lockPixels(env, bitmap, (void **) &srcData); - cv::Mat mat = cv::Mat::zeros(info.height, info.width, CV_8UC4); - memcpy(mat.data, srcData, info.height * info.width * 4); - AndroidBitmap_unlockPixels(env, bitmap); - cv::cvtColor(mat, mat, cv::COLOR_RGBA2BGR); - /** - if (!cv::imwrite("/sdcard/1/copy.jpg", mat)){ - LOGE("Write image failed " ); - } - */ - - return mat; -} - -cv::Mat resize_img(const cv::Mat& img, int height, int width){ - if (img.rows == height && img.cols == width){ - return img; - } - cv::Mat new_img; - cv::resize(img, new_img, cv::Size(height, width)); - return new_img; -} - -// fill tensor with mean and scale and trans layout: nhwc -> nchw, neon speed up -void neon_mean_scale(const float* din, - float* dout, - int size, - const std::vector& mean, - const std::vector& scale) { - if (mean.size() != 3 || scale.size() != 3) { - LOGE("[ERROR] mean or scale size must equal to 3"); - return; - } - - float32x4_t vmean0 = vdupq_n_f32(mean[0]); - float32x4_t vmean1 = vdupq_n_f32(mean[1]); - float32x4_t vmean2 = vdupq_n_f32(mean[2]); - float32x4_t vscale0 = vdupq_n_f32(scale[0]); - float32x4_t vscale1 = vdupq_n_f32(scale[1]); - float32x4_t vscale2 = vdupq_n_f32(scale[2]); - - float* dout_c0 = dout; - float* dout_c1 = dout + size; - float* dout_c2 = dout + size * 2; - - int i = 0; - for (; i < size - 3; i += 4) { - float32x4x3_t vin3 = vld3q_f32(din); - float32x4_t vsub0 = vsubq_f32(vin3.val[0], vmean0); - float32x4_t vsub1 = vsubq_f32(vin3.val[1], vmean1); - float32x4_t vsub2 = vsubq_f32(vin3.val[2], vmean2); - float32x4_t vs0 = vmulq_f32(vsub0, vscale0); - float32x4_t vs1 = vmulq_f32(vsub1, vscale1); - float32x4_t vs2 = vmulq_f32(vsub2, vscale2); - vst1q_f32(dout_c0, vs0); - vst1q_f32(dout_c1, vs1); - vst1q_f32(dout_c2, vs2); - - din += 12; - dout_c0 += 4; - dout_c1 += 4; - dout_c2 += 4; - } - for (; i < size; i++) { - *(dout_c0++) = (*(din++) - mean[0]) * scale[0]; - *(dout_c1++) = (*(din++) - mean[1]) * scale[1]; - *(dout_c2++) = (*(din++) - mean[2]) * scale[2]; - } -} \ No newline at end of file diff --git a/deploy/android_demo/app/src/main/cpp/preprocess.h b/deploy/android_demo/app/src/main/cpp/preprocess.h deleted file mode 100644 index c256c44011..0000000000 --- a/deploy/android_demo/app/src/main/cpp/preprocess.h +++ /dev/null @@ -1,14 +0,0 @@ -#pragma once - -#include -#include -#include "common.h" -cv::Mat bitmap_to_cv_mat(JNIEnv *env, jobject bitmap); - -cv::Mat resize_img(const cv::Mat& img, int height, int width); - -void neon_mean_scale(const float* din, - float* dout, - int size, - const std::vector& mean, - const std::vector& scale); diff --git a/deploy/android_demo/app/src/main/java/com/baidu/paddle/lite/demo/ocr/AppCompatPreferenceActivity.java b/deploy/android_demo/app/src/main/java/com/baidu/paddle/lite/demo/ocr/AppCompatPreferenceActivity.java deleted file mode 100644 index 49af0afea4..0000000000 --- a/deploy/android_demo/app/src/main/java/com/baidu/paddle/lite/demo/ocr/AppCompatPreferenceActivity.java +++ /dev/null @@ -1,128 +0,0 @@ -/* - * Copyright (C) 2014 The Android Open Source Project - * - * Licensed under the Apache License, Version 2.0 (the "License"); - * you may not use this file except in compliance with the License. - * You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -package com.baidu.paddle.lite.demo.ocr; - -import android.content.res.Configuration; -import android.os.Bundle; -import android.preference.PreferenceActivity; -import android.view.MenuInflater; -import android.view.View; -import android.view.ViewGroup; - -import androidx.annotation.LayoutRes; -import androidx.annotation.Nullable; -import androidx.appcompat.app.ActionBar; -import androidx.appcompat.app.AppCompatDelegate; -import androidx.appcompat.widget.Toolbar; - -/** - * A {@link PreferenceActivity} which implements and proxies the necessary calls - * to be used with AppCompat. - *

- * This technique can be used with an {@link android.app.Activity} class, not just - * {@link PreferenceActivity}. - */ -public abstract class AppCompatPreferenceActivity extends PreferenceActivity { - private AppCompatDelegate mDelegate; - - @Override - protected void onCreate(Bundle savedInstanceState) { - getDelegate().installViewFactory(); - getDelegate().onCreate(savedInstanceState); - super.onCreate(savedInstanceState); - } - - @Override - protected void onPostCreate(Bundle savedInstanceState) { - super.onPostCreate(savedInstanceState); - getDelegate().onPostCreate(savedInstanceState); - } - - public ActionBar getSupportActionBar() { - return getDelegate().getSupportActionBar(); - } - - public void setSupportActionBar(@Nullable Toolbar toolbar) { - getDelegate().setSupportActionBar(toolbar); - } - - @Override - public MenuInflater getMenuInflater() { - return getDelegate().getMenuInflater(); - } - - @Override - public void setContentView(@LayoutRes int layoutResID) { - getDelegate().setContentView(layoutResID); - } - - @Override - public void setContentView(View view) { - getDelegate().setContentView(view); - } - - @Override - public void setContentView(View view, ViewGroup.LayoutParams params) { - getDelegate().setContentView(view, params); - } - - @Override - public void addContentView(View view, ViewGroup.LayoutParams params) { - getDelegate().addContentView(view, params); - } - - @Override - protected void onPostResume() { - super.onPostResume(); - getDelegate().onPostResume(); - } - - @Override - protected void onTitleChanged(CharSequence title, int color) { - super.onTitleChanged(title, color); - getDelegate().setTitle(title); - } - - @Override - public void onConfigurationChanged(Configuration newConfig) { - super.onConfigurationChanged(newConfig); - getDelegate().onConfigurationChanged(newConfig); - } - - @Override - protected void onStop() { - super.onStop(); - getDelegate().onStop(); - } - - @Override - protected void onDestroy() { - super.onDestroy(); - getDelegate().onDestroy(); - } - - public void invalidateOptionsMenu() { - getDelegate().invalidateOptionsMenu(); - } - - private AppCompatDelegate getDelegate() { - if (mDelegate == null) { - mDelegate = AppCompatDelegate.create(this, null); - } - return mDelegate; - } -} diff --git a/deploy/android_demo/app/src/main/java/com/baidu/paddle/lite/demo/ocr/MainActivity.java b/deploy/android_demo/app/src/main/java/com/baidu/paddle/lite/demo/ocr/MainActivity.java deleted file mode 100644 index afb261dcf2..0000000000 --- a/deploy/android_demo/app/src/main/java/com/baidu/paddle/lite/demo/ocr/MainActivity.java +++ /dev/null @@ -1,473 +0,0 @@ -package com.baidu.paddle.lite.demo.ocr; - -import android.Manifest; -import android.app.ProgressDialog; -import android.content.ContentResolver; -import android.content.Context; -import android.content.Intent; -import android.content.SharedPreferences; -import android.content.pm.PackageManager; -import android.database.Cursor; -import android.graphics.Bitmap; -import android.graphics.BitmapFactory; -import android.media.ExifInterface; -import android.net.Uri; -import android.os.Bundle; -import android.os.Environment; -import android.os.Handler; -import android.os.HandlerThread; -import android.os.Message; -import android.preference.PreferenceManager; -import android.provider.MediaStore; -import android.text.method.ScrollingMovementMethod; -import android.util.Log; -import android.view.Menu; -import android.view.MenuInflater; -import android.view.MenuItem; -import android.widget.ImageView; -import android.widget.TextView; -import android.widget.Toast; - -import androidx.annotation.NonNull; -import androidx.appcompat.app.AppCompatActivity; -import androidx.core.app.ActivityCompat; -import androidx.core.content.ContextCompat; -import androidx.core.content.FileProvider; - -import java.io.File; -import java.io.IOException; -import java.io.InputStream; -import java.text.SimpleDateFormat; -import java.util.Date; - -public class MainActivity extends AppCompatActivity { - private static final String TAG = MainActivity.class.getSimpleName(); - public static final int OPEN_GALLERY_REQUEST_CODE = 0; - public static final int TAKE_PHOTO_REQUEST_CODE = 1; - - public static final int REQUEST_LOAD_MODEL = 0; - public static final int REQUEST_RUN_MODEL = 1; - public static final int RESPONSE_LOAD_MODEL_SUCCESSED = 0; - public static final int RESPONSE_LOAD_MODEL_FAILED = 1; - public static final int RESPONSE_RUN_MODEL_SUCCESSED = 2; - public static final int RESPONSE_RUN_MODEL_FAILED = 3; - - protected ProgressDialog pbLoadModel = null; - protected ProgressDialog pbRunModel = null; - - protected Handler receiver = null; // Receive messages from worker thread - protected Handler sender = null; // Send command to worker thread - protected HandlerThread worker = null; // Worker thread to load&run model - - // UI components of object detection - protected TextView tvInputSetting; - protected ImageView ivInputImage; - protected TextView tvOutputResult; - protected TextView tvInferenceTime; - - // Model settings of object detection - protected String modelPath = ""; - protected String labelPath = ""; - protected String imagePath = ""; - protected int cpuThreadNum = 1; - protected String cpuPowerMode = ""; - protected String inputColorFormat = ""; - protected long[] inputShape = new long[]{}; - protected float[] inputMean = new float[]{}; - protected float[] inputStd = new float[]{}; - protected float scoreThreshold = 0.1f; - private String currentPhotoPath; - - protected Predictor predictor = new Predictor(); - - @Override - protected void onCreate(Bundle savedInstanceState) { - super.onCreate(savedInstanceState); - setContentView(R.layout.activity_main); - - // Clear all setting items to avoid app crashing due to the incorrect settings - SharedPreferences sharedPreferences = PreferenceManager.getDefaultSharedPreferences(this); - SharedPreferences.Editor editor = sharedPreferences.edit(); - editor.clear(); - editor.commit(); - - // Prepare the worker thread for mode loading and inference - receiver = new Handler() { - @Override - public void handleMessage(Message msg) { - switch (msg.what) { - case RESPONSE_LOAD_MODEL_SUCCESSED: - pbLoadModel.dismiss(); - onLoadModelSuccessed(); - break; - case RESPONSE_LOAD_MODEL_FAILED: - pbLoadModel.dismiss(); - Toast.makeText(MainActivity.this, "Load model failed!", Toast.LENGTH_SHORT).show(); - onLoadModelFailed(); - break; - case RESPONSE_RUN_MODEL_SUCCESSED: - pbRunModel.dismiss(); - onRunModelSuccessed(); - break; - case RESPONSE_RUN_MODEL_FAILED: - pbRunModel.dismiss(); - Toast.makeText(MainActivity.this, "Run model failed!", Toast.LENGTH_SHORT).show(); - onRunModelFailed(); - break; - default: - break; - } - } - }; - - worker = new HandlerThread("Predictor Worker"); - worker.start(); - sender = new Handler(worker.getLooper()) { - public void handleMessage(Message msg) { - switch (msg.what) { - case REQUEST_LOAD_MODEL: - // Load model and reload test image - if (onLoadModel()) { - receiver.sendEmptyMessage(RESPONSE_LOAD_MODEL_SUCCESSED); - } else { - receiver.sendEmptyMessage(RESPONSE_LOAD_MODEL_FAILED); - } - break; - case REQUEST_RUN_MODEL: - // Run model if model is loaded - if (onRunModel()) { - receiver.sendEmptyMessage(RESPONSE_RUN_MODEL_SUCCESSED); - } else { - receiver.sendEmptyMessage(RESPONSE_RUN_MODEL_FAILED); - } - break; - default: - break; - } - } - }; - - // Setup the UI components - tvInputSetting = findViewById(R.id.tv_input_setting); - ivInputImage = findViewById(R.id.iv_input_image); - tvInferenceTime = findViewById(R.id.tv_inference_time); - tvOutputResult = findViewById(R.id.tv_output_result); - tvInputSetting.setMovementMethod(ScrollingMovementMethod.getInstance()); - tvOutputResult.setMovementMethod(ScrollingMovementMethod.getInstance()); - } - - @Override - protected void onResume() { - super.onResume(); - SharedPreferences sharedPreferences = PreferenceManager.getDefaultSharedPreferences(this); - boolean settingsChanged = false; - String model_path = sharedPreferences.getString(getString(R.string.MODEL_PATH_KEY), - getString(R.string.MODEL_PATH_DEFAULT)); - String label_path = sharedPreferences.getString(getString(R.string.LABEL_PATH_KEY), - getString(R.string.LABEL_PATH_DEFAULT)); - String image_path = sharedPreferences.getString(getString(R.string.IMAGE_PATH_KEY), - getString(R.string.IMAGE_PATH_DEFAULT)); - settingsChanged |= !model_path.equalsIgnoreCase(modelPath); - settingsChanged |= !label_path.equalsIgnoreCase(labelPath); - settingsChanged |= !image_path.equalsIgnoreCase(imagePath); - int cpu_thread_num = Integer.parseInt(sharedPreferences.getString(getString(R.string.CPU_THREAD_NUM_KEY), - getString(R.string.CPU_THREAD_NUM_DEFAULT))); - settingsChanged |= cpu_thread_num != cpuThreadNum; - String cpu_power_mode = - sharedPreferences.getString(getString(R.string.CPU_POWER_MODE_KEY), - getString(R.string.CPU_POWER_MODE_DEFAULT)); - settingsChanged |= !cpu_power_mode.equalsIgnoreCase(cpuPowerMode); - String input_color_format = - sharedPreferences.getString(getString(R.string.INPUT_COLOR_FORMAT_KEY), - getString(R.string.INPUT_COLOR_FORMAT_DEFAULT)); - settingsChanged |= !input_color_format.equalsIgnoreCase(inputColorFormat); - long[] input_shape = - Utils.parseLongsFromString(sharedPreferences.getString(getString(R.string.INPUT_SHAPE_KEY), - getString(R.string.INPUT_SHAPE_DEFAULT)), ","); - float[] input_mean = - Utils.parseFloatsFromString(sharedPreferences.getString(getString(R.string.INPUT_MEAN_KEY), - getString(R.string.INPUT_MEAN_DEFAULT)), ","); - float[] input_std = - Utils.parseFloatsFromString(sharedPreferences.getString(getString(R.string.INPUT_STD_KEY) - , getString(R.string.INPUT_STD_DEFAULT)), ","); - settingsChanged |= input_shape.length != inputShape.length; - settingsChanged |= input_mean.length != inputMean.length; - settingsChanged |= input_std.length != inputStd.length; - if (!settingsChanged) { - for (int i = 0; i < input_shape.length; i++) { - settingsChanged |= input_shape[i] != inputShape[i]; - } - for (int i = 0; i < input_mean.length; i++) { - settingsChanged |= input_mean[i] != inputMean[i]; - } - for (int i = 0; i < input_std.length; i++) { - settingsChanged |= input_std[i] != inputStd[i]; - } - } - float score_threshold = - Float.parseFloat(sharedPreferences.getString(getString(R.string.SCORE_THRESHOLD_KEY), - getString(R.string.SCORE_THRESHOLD_DEFAULT))); - settingsChanged |= scoreThreshold != score_threshold; - if (settingsChanged) { - modelPath = model_path; - labelPath = label_path; - imagePath = image_path; - cpuThreadNum = cpu_thread_num; - cpuPowerMode = cpu_power_mode; - inputColorFormat = input_color_format; - inputShape = input_shape; - inputMean = input_mean; - inputStd = input_std; - scoreThreshold = score_threshold; - // Update UI - tvInputSetting.setText("Model: " + modelPath.substring(modelPath.lastIndexOf("/") + 1) + "\n" + "CPU" + - " Thread Num: " + Integer.toString(cpuThreadNum) + "\n" + "CPU Power Mode: " + cpuPowerMode); - tvInputSetting.scrollTo(0, 0); - // Reload model if configure has been changed - loadModel(); - } - } - - public void loadModel() { - pbLoadModel = ProgressDialog.show(this, "", "Loading model...", false, false); - sender.sendEmptyMessage(REQUEST_LOAD_MODEL); - } - - public void runModel() { - pbRunModel = ProgressDialog.show(this, "", "Running model...", false, false); - sender.sendEmptyMessage(REQUEST_RUN_MODEL); - } - - public boolean onLoadModel() { - return predictor.init(MainActivity.this, modelPath, labelPath, cpuThreadNum, - cpuPowerMode, - inputColorFormat, - inputShape, inputMean, - inputStd, scoreThreshold); - } - - public boolean onRunModel() { - return predictor.isLoaded() && predictor.runModel(); - } - - public void onLoadModelSuccessed() { - // Load test image from path and run model - try { - if (imagePath.isEmpty()) { - return; - } - Bitmap image = null; - // Read test image file from custom path if the first character of mode path is '/', otherwise read test - // image file from assets - if (!imagePath.substring(0, 1).equals("/")) { - InputStream imageStream = getAssets().open(imagePath); - image = BitmapFactory.decodeStream(imageStream); - } else { - if (!new File(imagePath).exists()) { - return; - } - image = BitmapFactory.decodeFile(imagePath); - } - if (image != null && predictor.isLoaded()) { - predictor.setInputImage(image); - runModel(); - } - } catch (IOException e) { - Toast.makeText(MainActivity.this, "Load image failed!", Toast.LENGTH_SHORT).show(); - e.printStackTrace(); - } - } - - public void onLoadModelFailed() { - } - - public void onRunModelSuccessed() { - // Obtain results and update UI - tvInferenceTime.setText("Inference time: " + predictor.inferenceTime() + " ms"); - Bitmap outputImage = predictor.outputImage(); - if (outputImage != null) { - ivInputImage.setImageBitmap(outputImage); - } - tvOutputResult.setText(predictor.outputResult()); - tvOutputResult.scrollTo(0, 0); - } - - public void onRunModelFailed() { - } - - public void onImageChanged(Bitmap image) { - // Rerun model if users pick test image from gallery or camera - if (image != null && predictor.isLoaded()) { - predictor.setInputImage(image); - runModel(); - } - } - - public void onSettingsClicked() { - startActivity(new Intent(MainActivity.this, SettingsActivity.class)); - } - - @Override - public boolean onCreateOptionsMenu(Menu menu) { - MenuInflater inflater = getMenuInflater(); - inflater.inflate(R.menu.menu_action_options, menu); - return true; - } - - public boolean onPrepareOptionsMenu(Menu menu) { - boolean isLoaded = predictor.isLoaded(); - menu.findItem(R.id.open_gallery).setEnabled(isLoaded); - menu.findItem(R.id.take_photo).setEnabled(isLoaded); - return super.onPrepareOptionsMenu(menu); - } - - @Override - public boolean onOptionsItemSelected(MenuItem item) { - switch (item.getItemId()) { - case android.R.id.home: - finish(); - break; - case R.id.open_gallery: - if (requestAllPermissions()) { - openGallery(); - } - break; - case R.id.take_photo: - if (requestAllPermissions()) { - takePhoto(); - } - break; - case R.id.settings: - if (requestAllPermissions()) { - // Make sure we have SDCard r&w permissions to load model from SDCard - onSettingsClicked(); - } - break; - } - return super.onOptionsItemSelected(item); - } - - @Override - public void onRequestPermissionsResult(int requestCode, @NonNull String[] permissions, - @NonNull int[] grantResults) { - super.onRequestPermissionsResult(requestCode, permissions, grantResults); - if (grantResults[0] != PackageManager.PERMISSION_GRANTED || grantResults[1] != PackageManager.PERMISSION_GRANTED) { - Toast.makeText(this, "Permission Denied", Toast.LENGTH_SHORT).show(); - } - } - - private boolean requestAllPermissions() { - if (ContextCompat.checkSelfPermission(this, Manifest.permission.WRITE_EXTERNAL_STORAGE) - != PackageManager.PERMISSION_GRANTED || ContextCompat.checkSelfPermission(this, - Manifest.permission.CAMERA) - != PackageManager.PERMISSION_GRANTED) { - ActivityCompat.requestPermissions(this, new String[]{Manifest.permission.WRITE_EXTERNAL_STORAGE, - Manifest.permission.CAMERA}, - 0); - return false; - } - return true; - } - - private void openGallery() { - Intent intent = new Intent(Intent.ACTION_PICK, null); - intent.setDataAndType(MediaStore.Images.Media.EXTERNAL_CONTENT_URI, "image/*"); - startActivityForResult(intent, OPEN_GALLERY_REQUEST_CODE); - } - - private void takePhoto() { - Intent takePictureIntent = new Intent(MediaStore.ACTION_IMAGE_CAPTURE); - // Ensure that there's a camera activity to handle the intent - if (takePictureIntent.resolveActivity(getPackageManager()) != null) { - // Create the File where the photo should go - File photoFile = null; - try { - photoFile = createImageFile(); - } catch (IOException ex) { - Log.e("MainActitity", ex.getMessage(), ex); - Toast.makeText(MainActivity.this, - "Create Camera temp file failed: " + ex.getMessage(), Toast.LENGTH_SHORT).show(); - } - // Continue only if the File was successfully created - if (photoFile != null) { - Log.i(TAG, "FILEPATH " + getExternalFilesDir("Pictures").getAbsolutePath()); - Uri photoURI = FileProvider.getUriForFile(this, - "com.baidu.paddle.lite.demo.ocr.fileprovider", - photoFile); - currentPhotoPath = photoFile.getAbsolutePath(); - takePictureIntent.putExtra(MediaStore.EXTRA_OUTPUT, photoURI); - startActivityForResult(takePictureIntent, TAKE_PHOTO_REQUEST_CODE); - Log.i(TAG, "startActivityForResult finished"); - } - } - - } - - private File createImageFile() throws IOException { - // Create an image file name - String timeStamp = new SimpleDateFormat("yyyyMMdd_HHmmss").format(new Date()); - String imageFileName = "JPEG_" + timeStamp + "_"; - File storageDir = getExternalFilesDir(Environment.DIRECTORY_PICTURES); - File image = File.createTempFile( - imageFileName, /* prefix */ - ".bmp", /* suffix */ - storageDir /* directory */ - ); - - return image; - } - - @Override - protected void onActivityResult(int requestCode, int resultCode, Intent data) { - super.onActivityResult(requestCode, resultCode, data); - if (resultCode == RESULT_OK) { - switch (requestCode) { - case OPEN_GALLERY_REQUEST_CODE: - if (data == null) { - break; - } - try { - ContentResolver resolver = getContentResolver(); - Uri uri = data.getData(); - Bitmap image = MediaStore.Images.Media.getBitmap(resolver, uri); - String[] proj = {MediaStore.Images.Media.DATA}; - Cursor cursor = managedQuery(uri, proj, null, null, null); - cursor.moveToFirst(); - onImageChanged(image); - } catch (IOException e) { - Log.e(TAG, e.toString()); - } - break; - case TAKE_PHOTO_REQUEST_CODE: - if (currentPhotoPath != null) { - ExifInterface exif = null; - try { - exif = new ExifInterface(currentPhotoPath); - } catch (IOException e) { - e.printStackTrace(); - } - int orientation = exif.getAttributeInt(ExifInterface.TAG_ORIENTATION, - ExifInterface.ORIENTATION_UNDEFINED); - Log.i(TAG, "rotation " + orientation); - Bitmap image = BitmapFactory.decodeFile(currentPhotoPath); - image = Utils.rotateBitmap(image, orientation); - onImageChanged(image); - } else { - Log.e(TAG, "currentPhotoPath is null"); - } - break; - default: - break; - } - } - } - - @Override - protected void onDestroy() { - if (predictor != null) { - predictor.releaseModel(); - } - worker.quit(); - super.onDestroy(); - } -} diff --git a/deploy/android_demo/app/src/main/java/com/baidu/paddle/lite/demo/ocr/MiniActivity.java b/deploy/android_demo/app/src/main/java/com/baidu/paddle/lite/demo/ocr/MiniActivity.java deleted file mode 100644 index d5608911db..0000000000 --- a/deploy/android_demo/app/src/main/java/com/baidu/paddle/lite/demo/ocr/MiniActivity.java +++ /dev/null @@ -1,157 +0,0 @@ -package com.baidu.paddle.lite.demo.ocr; - -import android.graphics.Bitmap; -import android.graphics.BitmapFactory; -import android.os.Build; -import android.os.Bundle; -import android.os.Handler; -import android.os.HandlerThread; -import android.os.Message; -import android.util.Log; -import android.view.View; -import android.widget.Button; -import android.widget.ImageView; -import android.widget.TextView; -import android.widget.Toast; - -import androidx.appcompat.app.AppCompatActivity; - -import java.io.IOException; -import java.io.InputStream; - -public class MiniActivity extends AppCompatActivity { - - - public static final int REQUEST_LOAD_MODEL = 0; - public static final int REQUEST_RUN_MODEL = 1; - public static final int REQUEST_UNLOAD_MODEL = 2; - public static final int RESPONSE_LOAD_MODEL_SUCCESSED = 0; - public static final int RESPONSE_LOAD_MODEL_FAILED = 1; - public static final int RESPONSE_RUN_MODEL_SUCCESSED = 2; - public static final int RESPONSE_RUN_MODEL_FAILED = 3; - - private static final String TAG = "MiniActivity"; - - protected Handler receiver = null; // Receive messages from worker thread - protected Handler sender = null; // Send command to worker thread - protected HandlerThread worker = null; // Worker thread to load&run model - protected volatile Predictor predictor = null; - - private String assetModelDirPath = "models/ocr_v1_for_cpu"; - private String assetlabelFilePath = "labels/ppocr_keys_v1.txt"; - - private Button button; - private ImageView imageView; // image result - private TextView textView; // text result - - @Override - protected void onCreate(Bundle savedInstanceState) { - super.onCreate(savedInstanceState); - setContentView(R.layout.activity_mini); - - Log.i(TAG, "SHOW in Logcat"); - - // Prepare the worker thread for mode loading and inference - worker = new HandlerThread("Predictor Worker"); - worker.start(); - sender = new Handler(worker.getLooper()) { - public void handleMessage(Message msg) { - switch (msg.what) { - case REQUEST_LOAD_MODEL: - // Load model and reload test image - if (!onLoadModel()) { - runOnUiThread(new Runnable() { - @Override - public void run() { - Toast.makeText(MiniActivity.this, "Load model failed!", Toast.LENGTH_SHORT).show(); - } - }); - } - break; - case REQUEST_RUN_MODEL: - // Run model if model is loaded - final boolean isSuccessed = onRunModel(); - runOnUiThread(new Runnable() { - @Override - public void run() { - if (isSuccessed){ - onRunModelSuccessed(); - }else{ - Toast.makeText(MiniActivity.this, "Run model failed!", Toast.LENGTH_SHORT).show(); - } - } - }); - break; - } - } - }; - sender.sendEmptyMessage(REQUEST_LOAD_MODEL); // corresponding to REQUEST_LOAD_MODEL, to call onLoadModel() - - imageView = findViewById(R.id.imageView); - textView = findViewById(R.id.sample_text); - button = findViewById(R.id.button); - button.setOnClickListener(new View.OnClickListener() { - @Override - public void onClick(View v) { - sender.sendEmptyMessage(REQUEST_RUN_MODEL); - } - }); - - - } - - @Override - protected void onDestroy() { - onUnloadModel(); - if (Build.VERSION.SDK_INT >= Build.VERSION_CODES.JELLY_BEAN_MR2) { - worker.quitSafely(); - } else { - worker.quit(); - } - super.onDestroy(); - } - - /** - * call in onCreate, model init - * - * @return - */ - private boolean onLoadModel() { - if (predictor == null) { - predictor = new Predictor(); - } - return predictor.init(this, assetModelDirPath, assetlabelFilePath); - } - - /** - * init engine - * call in onCreate - * - * @return - */ - private boolean onRunModel() { - try { - String assetImagePath = "images/5.jpg"; - InputStream imageStream = getAssets().open(assetImagePath); - Bitmap image = BitmapFactory.decodeStream(imageStream); - // Input is Bitmap - predictor.setInputImage(image); - return predictor.isLoaded() && predictor.runModel(); - } catch (IOException e) { - e.printStackTrace(); - return false; - } - } - - private void onRunModelSuccessed() { - Log.i(TAG, "onRunModelSuccessed"); - textView.setText(predictor.outputResult); - imageView.setImageBitmap(predictor.outputImage); - } - - private void onUnloadModel() { - if (predictor != null) { - predictor.releaseModel(); - } - } -} diff --git a/deploy/android_demo/app/src/main/java/com/baidu/paddle/lite/demo/ocr/OCRPredictorNative.java b/deploy/android_demo/app/src/main/java/com/baidu/paddle/lite/demo/ocr/OCRPredictorNative.java deleted file mode 100644 index 2e78a3ece9..0000000000 --- a/deploy/android_demo/app/src/main/java/com/baidu/paddle/lite/demo/ocr/OCRPredictorNative.java +++ /dev/null @@ -1,100 +0,0 @@ -package com.baidu.paddle.lite.demo.ocr; - -import android.graphics.Bitmap; -import android.util.Log; - -import java.util.ArrayList; -import java.util.concurrent.atomic.AtomicBoolean; - -public class OCRPredictorNative { - - private static final AtomicBoolean isSOLoaded = new AtomicBoolean(); - - public static void loadLibrary() throws RuntimeException { - if (!isSOLoaded.get() && isSOLoaded.compareAndSet(false, true)) { - try { - System.loadLibrary("Native"); - } catch (Throwable e) { - RuntimeException exception = new RuntimeException( - "Load libNative.so failed, please check it exists in apk file.", e); - throw exception; - } - } - } - - private Config config; - - private long nativePointer = 0; - - public OCRPredictorNative(Config config) { - this.config = config; - loadLibrary(); - nativePointer = init(config.detModelFilename, config.recModelFilename, - config.cpuThreadNum, config.cpuPower); - Log.i("OCRPredictorNative", "load success " + nativePointer); - - } - - public void release() { - if (nativePointer != 0) { - nativePointer = 0; - destory(nativePointer); - } - } - - public ArrayList runImage(float[] inputData, int width, int height, int channels, Bitmap originalImage) { - Log.i("OCRPredictorNative", "begin to run image " + inputData.length + " " + width + " " + height); - float[] dims = new float[]{1, channels, height, width}; - float[] rawResults = forward(nativePointer, inputData, dims, originalImage); - ArrayList results = postprocess(rawResults); - return results; - } - - public static class Config { - public int cpuThreadNum; - public String cpuPower; - public String detModelFilename; - public String recModelFilename; - - } - - protected native long init(String detModelPath, String recModelPath, int threadNum, String cpuMode); - - protected native float[] forward(long pointer, float[] buf, float[] ddims, Bitmap originalImage); - - protected native void destory(long pointer); - - private ArrayList postprocess(float[] raw) { - ArrayList results = new ArrayList(); - int begin = 0; - - while (begin < raw.length) { - int point_num = Math.round(raw[begin]); - int word_num = Math.round(raw[begin + 1]); - OcrResultModel model = parse(raw, begin + 2, point_num, word_num); - begin += 2 + 1 + point_num * 2 + word_num; - results.add(model); - } - - return results; - } - - private OcrResultModel parse(float[] raw, int begin, int pointNum, int wordNum) { - int current = begin; - OcrResultModel model = new OcrResultModel(); - model.setConfidence(raw[current]); - current++; - for (int i = 0; i < pointNum; i++) { - model.addPoints(Math.round(raw[current + i * 2]), Math.round(raw[current + i * 2 + 1])); - } - current += (pointNum * 2); - for (int i = 0; i < wordNum; i++) { - int index = Math.round(raw[current + i]); - model.addWordIndex(index); - } - Log.i("OCRPredictorNative", "word finished " + wordNum); - return model; - } - - -} diff --git a/deploy/android_demo/app/src/main/java/com/baidu/paddle/lite/demo/ocr/OcrResultModel.java b/deploy/android_demo/app/src/main/java/com/baidu/paddle/lite/demo/ocr/OcrResultModel.java deleted file mode 100644 index 9494574e0d..0000000000 --- a/deploy/android_demo/app/src/main/java/com/baidu/paddle/lite/demo/ocr/OcrResultModel.java +++ /dev/null @@ -1,52 +0,0 @@ -package com.baidu.paddle.lite.demo.ocr; - -import android.graphics.Point; - -import java.util.ArrayList; -import java.util.List; - -public class OcrResultModel { - private List points; - private List wordIndex; - private String label; - private float confidence; - - public OcrResultModel() { - super(); - points = new ArrayList<>(); - wordIndex = new ArrayList<>(); - } - - public void addPoints(int x, int y) { - Point point = new Point(x, y); - points.add(point); - } - - public void addWordIndex(int index) { - wordIndex.add(index); - } - - public List getPoints() { - return points; - } - - public List getWordIndex() { - return wordIndex; - } - - public String getLabel() { - return label; - } - - public void setLabel(String label) { - this.label = label; - } - - public float getConfidence() { - return confidence; - } - - public void setConfidence(float confidence) { - this.confidence = confidence; - } -} diff --git a/deploy/android_demo/app/src/main/java/com/baidu/paddle/lite/demo/ocr/Predictor.java b/deploy/android_demo/app/src/main/java/com/baidu/paddle/lite/demo/ocr/Predictor.java deleted file mode 100644 index 078bba286c..0000000000 --- a/deploy/android_demo/app/src/main/java/com/baidu/paddle/lite/demo/ocr/Predictor.java +++ /dev/null @@ -1,355 +0,0 @@ -package com.baidu.paddle.lite.demo.ocr; - -import android.content.Context; -import android.graphics.Bitmap; -import android.graphics.Canvas; -import android.graphics.Color; -import android.graphics.Paint; -import android.graphics.Path; -import android.graphics.Point; -import android.util.Log; - -import java.io.File; -import java.io.InputStream; -import java.util.ArrayList; -import java.util.Date; -import java.util.List; -import java.util.Vector; - -import static android.graphics.Color.*; - -public class Predictor { - private static final String TAG = Predictor.class.getSimpleName(); - public boolean isLoaded = false; - public int warmupIterNum = 1; - public int inferIterNum = 1; - public int cpuThreadNum = 4; - public String cpuPowerMode = "LITE_POWER_HIGH"; - public String modelPath = ""; - public String modelName = ""; - protected OCRPredictorNative paddlePredictor = null; - protected float inferenceTime = 0; - // Only for object detection - protected Vector wordLabels = new Vector(); - protected String inputColorFormat = "BGR"; - protected long[] inputShape = new long[]{1, 3, 960}; - protected float[] inputMean = new float[]{0.485f, 0.456f, 0.406f}; - protected float[] inputStd = new float[]{1.0f / 0.229f, 1.0f / 0.224f, 1.0f / 0.225f}; - protected float scoreThreshold = 0.1f; - protected Bitmap inputImage = null; - protected Bitmap outputImage = null; - protected volatile String outputResult = ""; - protected float preprocessTime = 0; - protected float postprocessTime = 0; - - - public Predictor() { - } - - public boolean init(Context appCtx, String modelPath, String labelPath) { - isLoaded = loadModel(appCtx, modelPath, cpuThreadNum, cpuPowerMode); - if (!isLoaded) { - return false; - } - isLoaded = loadLabel(appCtx, labelPath); - return isLoaded; - } - - - public boolean init(Context appCtx, String modelPath, String labelPath, int cpuThreadNum, String cpuPowerMode, - String inputColorFormat, - long[] inputShape, float[] inputMean, - float[] inputStd, float scoreThreshold) { - if (inputShape.length != 3) { - Log.e(TAG, "Size of input shape should be: 3"); - return false; - } - if (inputMean.length != inputShape[1]) { - Log.e(TAG, "Size of input mean should be: " + Long.toString(inputShape[1])); - return false; - } - if (inputStd.length != inputShape[1]) { - Log.e(TAG, "Size of input std should be: " + Long.toString(inputShape[1])); - return false; - } - if (inputShape[0] != 1) { - Log.e(TAG, "Only one batch is supported in the image classification demo, you can use any batch size in " + - "your Apps!"); - return false; - } - if (inputShape[1] != 1 && inputShape[1] != 3) { - Log.e(TAG, "Only one/three channels are supported in the image classification demo, you can use any " + - "channel size in your Apps!"); - return false; - } - if (!inputColorFormat.equalsIgnoreCase("BGR")) { - Log.e(TAG, "Only BGR color format is supported."); - return false; - } - boolean isLoaded = init(appCtx, modelPath, labelPath); - if (!isLoaded) { - return false; - } - this.inputColorFormat = inputColorFormat; - this.inputShape = inputShape; - this.inputMean = inputMean; - this.inputStd = inputStd; - this.scoreThreshold = scoreThreshold; - return true; - } - - protected boolean loadModel(Context appCtx, String modelPath, int cpuThreadNum, String cpuPowerMode) { - // Release model if exists - releaseModel(); - - // Load model - if (modelPath.isEmpty()) { - return false; - } - String realPath = modelPath; - if (!modelPath.substring(0, 1).equals("/")) { - // Read model files from custom path if the first character of mode path is '/' - // otherwise copy model to cache from assets - realPath = appCtx.getCacheDir() + "/" + modelPath; - Utils.copyDirectoryFromAssets(appCtx, modelPath, realPath); - } - if (realPath.isEmpty()) { - return false; - } - - OCRPredictorNative.Config config = new OCRPredictorNative.Config(); - config.cpuThreadNum = cpuThreadNum; - config.detModelFilename = realPath + File.separator + "ch_det_mv3_db_opt.nb"; - config.recModelFilename = realPath + File.separator + "ch_rec_mv3_crnn_opt.nb"; - Log.e("Predictor", "model path" + config.detModelFilename + " ; " + config.recModelFilename); - config.cpuPower = cpuPowerMode; - paddlePredictor = new OCRPredictorNative(config); - - this.cpuThreadNum = cpuThreadNum; - this.cpuPowerMode = cpuPowerMode; - this.modelPath = realPath; - this.modelName = realPath.substring(realPath.lastIndexOf("/") + 1); - return true; - } - - public void releaseModel() { - if (paddlePredictor != null) { - paddlePredictor.release(); - paddlePredictor = null; - } - isLoaded = false; - cpuThreadNum = 1; - cpuPowerMode = "LITE_POWER_HIGH"; - modelPath = ""; - modelName = ""; - } - - protected boolean loadLabel(Context appCtx, String labelPath) { - wordLabels.clear(); - // Load word labels from file - try { - InputStream assetsInputStream = appCtx.getAssets().open(labelPath); - int available = assetsInputStream.available(); - byte[] lines = new byte[available]; - assetsInputStream.read(lines); - assetsInputStream.close(); - String words = new String(lines); - String[] contents = words.split("\n"); - for (String content : contents) { - wordLabels.add(content); - } - Log.i(TAG, "Word label size: " + wordLabels.size()); - } catch (Exception e) { - Log.e(TAG, e.getMessage()); - return false; - } - return true; - } - - - public boolean runModel() { - if (inputImage == null || !isLoaded()) { - return false; - } - - // Pre-process image, and feed input tensor with pre-processed data - - Bitmap scaleImage = Utils.resizeWithStep(inputImage, Long.valueOf(inputShape[2]).intValue(), 32); - - Date start = new Date(); - int channels = (int) inputShape[1]; - int width = scaleImage.getWidth(); - int height = scaleImage.getHeight(); - float[] inputData = new float[channels * width * height]; - if (channels == 3) { - int[] channelIdx = null; - if (inputColorFormat.equalsIgnoreCase("RGB")) { - channelIdx = new int[]{0, 1, 2}; - } else if (inputColorFormat.equalsIgnoreCase("BGR")) { - channelIdx = new int[]{2, 1, 0}; - } else { - Log.i(TAG, "Unknown color format " + inputColorFormat + ", only RGB and BGR color format is " + - "supported!"); - return false; - } - int[] channelStride = new int[]{width * height, width * height * 2}; - int p = scaleImage.getPixel(scaleImage.getWidth() - 1, scaleImage.getHeight() - 1); - for (int y = 0; y < height; y++) { - for (int x = 0; x < width; x++) { - int color = scaleImage.getPixel(x, y); - float[] rgb = new float[]{(float) red(color) / 255.0f, (float) green(color) / 255.0f, - (float) blue(color) / 255.0f}; - inputData[y * width + x] = (rgb[channelIdx[0]] - inputMean[0]) / inputStd[0]; - inputData[y * width + x + channelStride[0]] = (rgb[channelIdx[1]] - inputMean[1]) / inputStd[1]; - inputData[y * width + x + channelStride[1]] = (rgb[channelIdx[2]] - inputMean[2]) / inputStd[2]; - - } - } - } else if (channels == 1) { - for (int y = 0; y < height; y++) { - for (int x = 0; x < width; x++) { - int color = inputImage.getPixel(x, y); - float gray = (float) (red(color) + green(color) + blue(color)) / 3.0f / 255.0f; - inputData[y * width + x] = (gray - inputMean[0]) / inputStd[0]; - } - } - } else { - Log.i(TAG, "Unsupported channel size " + Integer.toString(channels) + ", only channel 1 and 3 is " + - "supported!"); - return false; - } - float[] pixels = inputData; - Log.i(TAG, "pixels " + pixels[0] + " " + pixels[1] + " " + pixels[2] + " " + pixels[3] - + " " + pixels[pixels.length / 2] + " " + pixels[pixels.length / 2 + 1] + " " + pixels[pixels.length - 2] + " " + pixels[pixels.length - 1]); - Date end = new Date(); - preprocessTime = (float) (end.getTime() - start.getTime()); - - // Warm up - for (int i = 0; i < warmupIterNum; i++) { - paddlePredictor.runImage(inputData, width, height, channels, inputImage); - } - warmupIterNum = 0; // do not need warm - // Run inference - start = new Date(); - ArrayList results = paddlePredictor.runImage(inputData, width, height, channels, inputImage); - end = new Date(); - inferenceTime = (end.getTime() - start.getTime()) / (float) inferIterNum; - - results = postprocess(results); - Log.i(TAG, "[stat] Preprocess Time: " + preprocessTime - + " ; Inference Time: " + inferenceTime + " ;Box Size " + results.size()); - drawResults(results); - - return true; - } - - - public boolean isLoaded() { - return paddlePredictor != null && isLoaded; - } - - public String modelPath() { - return modelPath; - } - - public String modelName() { - return modelName; - } - - public int cpuThreadNum() { - return cpuThreadNum; - } - - public String cpuPowerMode() { - return cpuPowerMode; - } - - public float inferenceTime() { - return inferenceTime; - } - - public Bitmap inputImage() { - return inputImage; - } - - public Bitmap outputImage() { - return outputImage; - } - - public String outputResult() { - return outputResult; - } - - public float preprocessTime() { - return preprocessTime; - } - - public float postprocessTime() { - return postprocessTime; - } - - - public void setInputImage(Bitmap image) { - if (image == null) { - return; - } - this.inputImage = image.copy(Bitmap.Config.ARGB_8888, true); - } - - private ArrayList postprocess(ArrayList results) { - for (OcrResultModel r : results) { - StringBuffer word = new StringBuffer(); - for (int index : r.getWordIndex()) { - if (index >= 0 && index < wordLabels.size()) { - word.append(wordLabels.get(index)); - } else { - Log.e(TAG, "Word index is not in label list:" + index); - word.append("×"); - } - } - r.setLabel(word.toString()); - } - return results; - } - - private void drawResults(ArrayList results) { - StringBuffer outputResultSb = new StringBuffer(""); - for (int i = 0; i < results.size(); i++) { - OcrResultModel result = results.get(i); - StringBuilder sb = new StringBuilder(""); - sb.append(result.getLabel()); - sb.append(" ").append(result.getConfidence()); - sb.append("; Points: "); - for (Point p : result.getPoints()) { - sb.append("(").append(p.x).append(",").append(p.y).append(") "); - } - Log.i(TAG, sb.toString()); // show LOG in Logcat panel - outputResultSb.append(i + 1).append(": ").append(result.getLabel()).append("\n"); - } - outputResult = outputResultSb.toString(); - outputImage = inputImage; - Canvas canvas = new Canvas(outputImage); - Paint paintFillAlpha = new Paint(); - paintFillAlpha.setStyle(Paint.Style.FILL); - paintFillAlpha.setColor(Color.parseColor("#3B85F5")); - paintFillAlpha.setAlpha(50); - - Paint paint = new Paint(); - paint.setColor(Color.parseColor("#3B85F5")); - paint.setStrokeWidth(5); - paint.setStyle(Paint.Style.STROKE); - - for (OcrResultModel result : results) { - Path path = new Path(); - List points = result.getPoints(); - path.moveTo(points.get(0).x, points.get(0).y); - for (int i = points.size() - 1; i >= 0; i--) { - Point p = points.get(i); - path.lineTo(p.x, p.y); - } - canvas.drawPath(path, paint); - canvas.drawPath(path, paintFillAlpha); - } - } - -} diff --git a/deploy/android_demo/app/src/main/java/com/baidu/paddle/lite/demo/ocr/SettingsActivity.java b/deploy/android_demo/app/src/main/java/com/baidu/paddle/lite/demo/ocr/SettingsActivity.java deleted file mode 100644 index b3653ccc2e..0000000000 --- a/deploy/android_demo/app/src/main/java/com/baidu/paddle/lite/demo/ocr/SettingsActivity.java +++ /dev/null @@ -1,201 +0,0 @@ -package com.baidu.paddle.lite.demo.ocr; - -import android.content.SharedPreferences; -import android.os.Bundle; -import android.preference.CheckBoxPreference; -import android.preference.EditTextPreference; -import android.preference.ListPreference; - -import androidx.appcompat.app.ActionBar; - -import java.util.ArrayList; -import java.util.List; - - -public class SettingsActivity extends AppCompatPreferenceActivity implements SharedPreferences.OnSharedPreferenceChangeListener { - ListPreference lpChoosePreInstalledModel = null; - CheckBoxPreference cbEnableCustomSettings = null; - EditTextPreference etModelPath = null; - EditTextPreference etLabelPath = null; - EditTextPreference etImagePath = null; - ListPreference lpCPUThreadNum = null; - ListPreference lpCPUPowerMode = null; - ListPreference lpInputColorFormat = null; - EditTextPreference etInputShape = null; - EditTextPreference etInputMean = null; - EditTextPreference etInputStd = null; - EditTextPreference etScoreThreshold = null; - - List preInstalledModelPaths = null; - List preInstalledLabelPaths = null; - List preInstalledImagePaths = null; - List preInstalledInputShapes = null; - List preInstalledCPUThreadNums = null; - List preInstalledCPUPowerModes = null; - List preInstalledInputColorFormats = null; - List preInstalledInputMeans = null; - List preInstalledInputStds = null; - List preInstalledScoreThresholds = null; - - @Override - public void onCreate(Bundle savedInstanceState) { - super.onCreate(savedInstanceState); - addPreferencesFromResource(R.xml.settings); - ActionBar supportActionBar = getSupportActionBar(); - if (supportActionBar != null) { - supportActionBar.setDisplayHomeAsUpEnabled(true); - } - - // Initialized pre-installed models - preInstalledModelPaths = new ArrayList(); - preInstalledLabelPaths = new ArrayList(); - preInstalledImagePaths = new ArrayList(); - preInstalledInputShapes = new ArrayList(); - preInstalledCPUThreadNums = new ArrayList(); - preInstalledCPUPowerModes = new ArrayList(); - preInstalledInputColorFormats = new ArrayList(); - preInstalledInputMeans = new ArrayList(); - preInstalledInputStds = new ArrayList(); - preInstalledScoreThresholds = new ArrayList(); - // Add ssd_mobilenet_v1_pascalvoc_for_cpu - preInstalledModelPaths.add(getString(R.string.MODEL_PATH_DEFAULT)); - preInstalledLabelPaths.add(getString(R.string.LABEL_PATH_DEFAULT)); - preInstalledImagePaths.add(getString(R.string.IMAGE_PATH_DEFAULT)); - preInstalledCPUThreadNums.add(getString(R.string.CPU_THREAD_NUM_DEFAULT)); - preInstalledCPUPowerModes.add(getString(R.string.CPU_POWER_MODE_DEFAULT)); - preInstalledInputColorFormats.add(getString(R.string.INPUT_COLOR_FORMAT_DEFAULT)); - preInstalledInputShapes.add(getString(R.string.INPUT_SHAPE_DEFAULT)); - preInstalledInputMeans.add(getString(R.string.INPUT_MEAN_DEFAULT)); - preInstalledInputStds.add(getString(R.string.INPUT_STD_DEFAULT)); - preInstalledScoreThresholds.add(getString(R.string.SCORE_THRESHOLD_DEFAULT)); - - // Setup UI components - lpChoosePreInstalledModel = - (ListPreference) findPreference(getString(R.string.CHOOSE_PRE_INSTALLED_MODEL_KEY)); - String[] preInstalledModelNames = new String[preInstalledModelPaths.size()]; - for (int i = 0; i < preInstalledModelPaths.size(); i++) { - preInstalledModelNames[i] = - preInstalledModelPaths.get(i).substring(preInstalledModelPaths.get(i).lastIndexOf("/") + 1); - } - lpChoosePreInstalledModel.setEntries(preInstalledModelNames); - lpChoosePreInstalledModel.setEntryValues(preInstalledModelPaths.toArray(new String[preInstalledModelPaths.size()])); - cbEnableCustomSettings = - (CheckBoxPreference) findPreference(getString(R.string.ENABLE_CUSTOM_SETTINGS_KEY)); - etModelPath = (EditTextPreference) findPreference(getString(R.string.MODEL_PATH_KEY)); - etModelPath.setTitle("Model Path (SDCard: " + Utils.getSDCardDirectory() + ")"); - etLabelPath = (EditTextPreference) findPreference(getString(R.string.LABEL_PATH_KEY)); - etImagePath = (EditTextPreference) findPreference(getString(R.string.IMAGE_PATH_KEY)); - lpCPUThreadNum = - (ListPreference) findPreference(getString(R.string.CPU_THREAD_NUM_KEY)); - lpCPUPowerMode = - (ListPreference) findPreference(getString(R.string.CPU_POWER_MODE_KEY)); - lpInputColorFormat = - (ListPreference) findPreference(getString(R.string.INPUT_COLOR_FORMAT_KEY)); - etInputShape = (EditTextPreference) findPreference(getString(R.string.INPUT_SHAPE_KEY)); - etInputMean = (EditTextPreference) findPreference(getString(R.string.INPUT_MEAN_KEY)); - etInputStd = (EditTextPreference) findPreference(getString(R.string.INPUT_STD_KEY)); - etScoreThreshold = (EditTextPreference) findPreference(getString(R.string.SCORE_THRESHOLD_KEY)); - } - - private void reloadPreferenceAndUpdateUI() { - SharedPreferences sharedPreferences = getPreferenceScreen().getSharedPreferences(); - boolean enableCustomSettings = - sharedPreferences.getBoolean(getString(R.string.ENABLE_CUSTOM_SETTINGS_KEY), false); - String modelPath = sharedPreferences.getString(getString(R.string.CHOOSE_PRE_INSTALLED_MODEL_KEY), - getString(R.string.MODEL_PATH_DEFAULT)); - int modelIdx = lpChoosePreInstalledModel.findIndexOfValue(modelPath); - if (modelIdx >= 0 && modelIdx < preInstalledModelPaths.size()) { - if (!enableCustomSettings) { - SharedPreferences.Editor editor = sharedPreferences.edit(); - editor.putString(getString(R.string.MODEL_PATH_KEY), preInstalledModelPaths.get(modelIdx)); - editor.putString(getString(R.string.LABEL_PATH_KEY), preInstalledLabelPaths.get(modelIdx)); - editor.putString(getString(R.string.IMAGE_PATH_KEY), preInstalledImagePaths.get(modelIdx)); - editor.putString(getString(R.string.CPU_THREAD_NUM_KEY), preInstalledCPUThreadNums.get(modelIdx)); - editor.putString(getString(R.string.CPU_POWER_MODE_KEY), preInstalledCPUPowerModes.get(modelIdx)); - editor.putString(getString(R.string.INPUT_COLOR_FORMAT_KEY), - preInstalledInputColorFormats.get(modelIdx)); - editor.putString(getString(R.string.INPUT_SHAPE_KEY), preInstalledInputShapes.get(modelIdx)); - editor.putString(getString(R.string.INPUT_MEAN_KEY), preInstalledInputMeans.get(modelIdx)); - editor.putString(getString(R.string.INPUT_STD_KEY), preInstalledInputStds.get(modelIdx)); - editor.putString(getString(R.string.SCORE_THRESHOLD_KEY), - preInstalledScoreThresholds.get(modelIdx)); - editor.commit(); - } - lpChoosePreInstalledModel.setSummary(modelPath); - } - cbEnableCustomSettings.setChecked(enableCustomSettings); - etModelPath.setEnabled(enableCustomSettings); - etLabelPath.setEnabled(enableCustomSettings); - etImagePath.setEnabled(enableCustomSettings); - lpCPUThreadNum.setEnabled(enableCustomSettings); - lpCPUPowerMode.setEnabled(enableCustomSettings); - lpInputColorFormat.setEnabled(enableCustomSettings); - etInputShape.setEnabled(enableCustomSettings); - etInputMean.setEnabled(enableCustomSettings); - etInputStd.setEnabled(enableCustomSettings); - etScoreThreshold.setEnabled(enableCustomSettings); - modelPath = sharedPreferences.getString(getString(R.string.MODEL_PATH_KEY), - getString(R.string.MODEL_PATH_DEFAULT)); - String labelPath = sharedPreferences.getString(getString(R.string.LABEL_PATH_KEY), - getString(R.string.LABEL_PATH_DEFAULT)); - String imagePath = sharedPreferences.getString(getString(R.string.IMAGE_PATH_KEY), - getString(R.string.IMAGE_PATH_DEFAULT)); - String cpuThreadNum = sharedPreferences.getString(getString(R.string.CPU_THREAD_NUM_KEY), - getString(R.string.CPU_THREAD_NUM_DEFAULT)); - String cpuPowerMode = sharedPreferences.getString(getString(R.string.CPU_POWER_MODE_KEY), - getString(R.string.CPU_POWER_MODE_DEFAULT)); - String inputColorFormat = sharedPreferences.getString(getString(R.string.INPUT_COLOR_FORMAT_KEY), - getString(R.string.INPUT_COLOR_FORMAT_DEFAULT)); - String inputShape = sharedPreferences.getString(getString(R.string.INPUT_SHAPE_KEY), - getString(R.string.INPUT_SHAPE_DEFAULT)); - String inputMean = sharedPreferences.getString(getString(R.string.INPUT_MEAN_KEY), - getString(R.string.INPUT_MEAN_DEFAULT)); - String inputStd = sharedPreferences.getString(getString(R.string.INPUT_STD_KEY), - getString(R.string.INPUT_STD_DEFAULT)); - String scoreThreshold = sharedPreferences.getString(getString(R.string.SCORE_THRESHOLD_KEY), - getString(R.string.SCORE_THRESHOLD_DEFAULT)); - etModelPath.setSummary(modelPath); - etModelPath.setText(modelPath); - etLabelPath.setSummary(labelPath); - etLabelPath.setText(labelPath); - etImagePath.setSummary(imagePath); - etImagePath.setText(imagePath); - lpCPUThreadNum.setValue(cpuThreadNum); - lpCPUThreadNum.setSummary(cpuThreadNum); - lpCPUPowerMode.setValue(cpuPowerMode); - lpCPUPowerMode.setSummary(cpuPowerMode); - lpInputColorFormat.setValue(inputColorFormat); - lpInputColorFormat.setSummary(inputColorFormat); - etInputShape.setSummary(inputShape); - etInputShape.setText(inputShape); - etInputMean.setSummary(inputMean); - etInputMean.setText(inputMean); - etInputStd.setSummary(inputStd); - etInputStd.setText(inputStd); - etScoreThreshold.setText(scoreThreshold); - etScoreThreshold.setSummary(scoreThreshold); - } - - @Override - protected void onResume() { - super.onResume(); - getPreferenceScreen().getSharedPreferences().registerOnSharedPreferenceChangeListener(this); - reloadPreferenceAndUpdateUI(); - } - - @Override - protected void onPause() { - super.onPause(); - getPreferenceScreen().getSharedPreferences().unregisterOnSharedPreferenceChangeListener(this); - } - - @Override - public void onSharedPreferenceChanged(SharedPreferences sharedPreferences, String key) { - if (key.equals(getString(R.string.CHOOSE_PRE_INSTALLED_MODEL_KEY))) { - SharedPreferences.Editor editor = sharedPreferences.edit(); - editor.putBoolean(getString(R.string.ENABLE_CUSTOM_SETTINGS_KEY), false); - editor.commit(); - } - reloadPreferenceAndUpdateUI(); - } -} diff --git a/deploy/android_demo/app/src/main/java/com/baidu/paddle/lite/demo/ocr/Utils.java b/deploy/android_demo/app/src/main/java/com/baidu/paddle/lite/demo/ocr/Utils.java deleted file mode 100644 index ef46805760..0000000000 --- a/deploy/android_demo/app/src/main/java/com/baidu/paddle/lite/demo/ocr/Utils.java +++ /dev/null @@ -1,159 +0,0 @@ -package com.baidu.paddle.lite.demo.ocr; - -import android.content.Context; -import android.graphics.Bitmap; -import android.graphics.Matrix; -import android.media.ExifInterface; -import android.os.Environment; - -import java.io.*; - -public class Utils { - private static final String TAG = Utils.class.getSimpleName(); - - public static void copyFileFromAssets(Context appCtx, String srcPath, String dstPath) { - if (srcPath.isEmpty() || dstPath.isEmpty()) { - return; - } - InputStream is = null; - OutputStream os = null; - try { - is = new BufferedInputStream(appCtx.getAssets().open(srcPath)); - os = new BufferedOutputStream(new FileOutputStream(new File(dstPath))); - byte[] buffer = new byte[1024]; - int length = 0; - while ((length = is.read(buffer)) != -1) { - os.write(buffer, 0, length); - } - } catch (FileNotFoundException e) { - e.printStackTrace(); - } catch (IOException e) { - e.printStackTrace(); - } finally { - try { - os.close(); - is.close(); - } catch (IOException e) { - e.printStackTrace(); - } - } - } - - public static void copyDirectoryFromAssets(Context appCtx, String srcDir, String dstDir) { - if (srcDir.isEmpty() || dstDir.isEmpty()) { - return; - } - try { - if (!new File(dstDir).exists()) { - new File(dstDir).mkdirs(); - } - for (String fileName : appCtx.getAssets().list(srcDir)) { - String srcSubPath = srcDir + File.separator + fileName; - String dstSubPath = dstDir + File.separator + fileName; - if (new File(srcSubPath).isDirectory()) { - copyDirectoryFromAssets(appCtx, srcSubPath, dstSubPath); - } else { - copyFileFromAssets(appCtx, srcSubPath, dstSubPath); - } - } - } catch (Exception e) { - e.printStackTrace(); - } - } - - public static float[] parseFloatsFromString(String string, String delimiter) { - String[] pieces = string.trim().toLowerCase().split(delimiter); - float[] floats = new float[pieces.length]; - for (int i = 0; i < pieces.length; i++) { - floats[i] = Float.parseFloat(pieces[i].trim()); - } - return floats; - } - - public static long[] parseLongsFromString(String string, String delimiter) { - String[] pieces = string.trim().toLowerCase().split(delimiter); - long[] longs = new long[pieces.length]; - for (int i = 0; i < pieces.length; i++) { - longs[i] = Long.parseLong(pieces[i].trim()); - } - return longs; - } - - public static String getSDCardDirectory() { - return Environment.getExternalStorageDirectory().getAbsolutePath(); - } - - public static boolean isSupportedNPU() { - return false; - // String hardware = android.os.Build.HARDWARE; - // return hardware.equalsIgnoreCase("kirin810") || hardware.equalsIgnoreCase("kirin990"); - } - - public static Bitmap resizeWithStep(Bitmap bitmap, int maxLength, int step) { - int width = bitmap.getWidth(); - int height = bitmap.getHeight(); - int maxWH = Math.max(width, height); - float ratio = 1; - int newWidth = width; - int newHeight = height; - if (maxWH > maxLength) { - ratio = maxLength * 1.0f / maxWH; - newWidth = (int) Math.floor(ratio * width); - newHeight = (int) Math.floor(ratio * height); - } - - newWidth = newWidth - newWidth % step; - if (newWidth == 0) { - newWidth = step; - } - newHeight = newHeight - newHeight % step; - if (newHeight == 0) { - newHeight = step; - } - return Bitmap.createScaledBitmap(bitmap, newWidth, newHeight, true); - } - - public static Bitmap rotateBitmap(Bitmap bitmap, int orientation) { - - Matrix matrix = new Matrix(); - switch (orientation) { - case ExifInterface.ORIENTATION_NORMAL: - return bitmap; - case ExifInterface.ORIENTATION_FLIP_HORIZONTAL: - matrix.setScale(-1, 1); - break; - case ExifInterface.ORIENTATION_ROTATE_180: - matrix.setRotate(180); - break; - case ExifInterface.ORIENTATION_FLIP_VERTICAL: - matrix.setRotate(180); - matrix.postScale(-1, 1); - break; - case ExifInterface.ORIENTATION_TRANSPOSE: - matrix.setRotate(90); - matrix.postScale(-1, 1); - break; - case ExifInterface.ORIENTATION_ROTATE_90: - matrix.setRotate(90); - break; - case ExifInterface.ORIENTATION_TRANSVERSE: - matrix.setRotate(-90); - matrix.postScale(-1, 1); - break; - case ExifInterface.ORIENTATION_ROTATE_270: - matrix.setRotate(-90); - break; - default: - return bitmap; - } - try { - Bitmap bmRotated = Bitmap.createBitmap(bitmap, 0, 0, bitmap.getWidth(), bitmap.getHeight(), matrix, true); - bitmap.recycle(); - return bmRotated; - } - catch (OutOfMemoryError e) { - e.printStackTrace(); - return null; - } - } -} diff --git a/deploy/android_demo/app/src/main/res/drawable-v24/ic_launcher_foreground.xml b/deploy/android_demo/app/src/main/res/drawable-v24/ic_launcher_foreground.xml deleted file mode 100644 index 1f6bb29060..0000000000 --- a/deploy/android_demo/app/src/main/res/drawable-v24/ic_launcher_foreground.xml +++ /dev/null @@ -1,34 +0,0 @@ - - - - - - - - - - - diff --git a/deploy/android_demo/app/src/main/res/drawable/ic_launcher_background.xml b/deploy/android_demo/app/src/main/res/drawable/ic_launcher_background.xml deleted file mode 100644 index 0d025f9bf6..0000000000 --- a/deploy/android_demo/app/src/main/res/drawable/ic_launcher_background.xml +++ /dev/null @@ -1,170 +0,0 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - diff --git a/deploy/android_demo/app/src/main/res/layout/activity_main.xml b/deploy/android_demo/app/src/main/res/layout/activity_main.xml deleted file mode 100644 index adc70e200f..0000000000 --- a/deploy/android_demo/app/src/main/res/layout/activity_main.xml +++ /dev/null @@ -1,99 +0,0 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - \ No newline at end of file diff --git a/deploy/android_demo/app/src/main/res/layout/activity_mini.xml b/deploy/android_demo/app/src/main/res/layout/activity_mini.xml deleted file mode 100644 index ec4622ae5c..0000000000 --- a/deploy/android_demo/app/src/main/res/layout/activity_mini.xml +++ /dev/null @@ -1,46 +0,0 @@ - - - - - - - - -