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fish_manager.py
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fish_manager.py
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"""
This file is part of Fish Tracker.
Copyright 2021, VTT Technical research centre of Finland Ltd.
Developed by: Mikael Uimonen.
Fish Tracker is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
Fish Tracker is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with Fish Tracker. If not, see <https://www.gnu.org/licenses/>.
"""
from PyQt5 import QtGui, QtCore, QtWidgets
from PyQt5.QtCore import Qt
import numpy as np
import cv2
import seaborn as sns
from bisect import insort
from enum import IntEnum
import file_handler as fh
from tracker import Tracker
from tracker_parameters import TrackerParameters
from log_object import LogObject
from filter_parameters import FilterParameters
fish_headers = ["", "ID", "Length", "Direction", "Frame in", "Frame out", "Duration", "Detections", "MAD",
"Tortuosity", "Speed"]
fish_sort_keys = [lambda f: f.color_ind, lambda f: f.id, lambda f: -f.length, lambda f: f.dirSortValue(),
lambda f: f.frame_in, lambda f: f.frame_out, lambda f: f.duration, lambda f: f.detection_count,
lambda f: f.mad, lambda f: f.tortuosity, lambda f: f.speed]
data_lambda_list = [lambda f: f.color_ind, lambda f: f.id, lambda f: f.length, lambda f: f.direction.name,
lambda f: f.frame_in, lambda f: f.frame_out, lambda f: f.duration, lambda f: f.detection_count,
lambda f: f.mad, lambda f: f.tortuosity, lambda f: f.speed]
COLUMN_COUNT = 11
N_COLORS = 16
#color_palette = sns.color_palette('bright', N_COLORS)
color_palette = [[c[2], c[1], c[0]] for c in sns.color_palette('bright', N_COLORS)]
pyqt_palette = [QtGui.QColor.fromRgbF(c[2], c[1], c[0]) for c in color_palette]
#color_palette_deep = sns.color_palette('deep', N_COLORS)
color_palette_deep = [[c[2], c[1], c[0]] for c in sns.color_palette('deep', N_COLORS)]
pyqt_palette_deep = [QtGui.QColor.fromRgbF(c[2], c[1], c[0]) for c in color_palette_deep]
# Stores and manages tracked fish items.
# Items can be edited with the functions defined here through e.g. fish_list.py.
class FishManager(QtCore.QAbstractTableModel):
updateContentsSignal = QtCore.pyqtSignal()
updateSelectionSignal = QtCore.pyqtSignal(QtCore.QItemSelection, QtCore.QItemSelectionModel.SelectionFlags)
def __init__(self, playback_manager, tracker):
super().__init__()
self.playback_manager = playback_manager
if self.playback_manager is not None:
self.playback_manager.file_opened.connect(self.onFileOpened)
self.playback_manager.file_closed.connect(self.onFileClosed)
self.tracker = tracker
if tracker is not None:
self.tracker.init_signal.connect(self.onTrackingInitialized)
self.tracker.all_computed_signal.connect(self.updateDataFromTracker)
# All fish items currently stored.
self.all_fish = {}
# Fish items that are currently displayed.
self.fish_list = []
self.selected_rows = set()
# Index for fish_sort_keys array, that contains lambda functions to sort the currently shown array.
# Default: ID
self.sort_ind = 1
# Sort direction, ascending or descending
self.sort_order = QtCore.Qt.DescendingOrder
# Min number of detections required for a fish to be included in fish_list
self.min_detections = 2
# Major axis distance, i.e. delta angle (degrees) between the first and the last associated detection
self.mad_limit = 0
# Percentile with which the shown length is determined
self.length_percentile = 50
# Clear previous fish entries when new data is acquired.
self.clear_old_data = True
# If fish (tracks) are shown.
self.show_fish = True
# If fish (tracks) are shown in Echogram.
self.show_echogram_fish = True
self.frame_rate = None
self.frame_time = None
self.update_fish_colors = False
# Inverted upstream / downstream.
self.up_down_inverted = False
def testPopulate(self, frame_count):
"""
Simple test function.
"""
self.all_fish = {}
self.fish_list.clear()
for i in range(10):
f = FishEntry(i + 1)
f.length = round(np.random.normal(1.2, 0.1), 3)
f.direction = SwimDirection(np.random.randint(low=0, high=2))
f.frame_in = np.random.randint(frame_count)
f.frame_out = min(f.frame_in + np.random.randint(100), frame_count)
f.duration = f.frame_out - f.frame_in + 1
f.mad = np.random.randint(30)
f.tortuosity = np.random.uniform(1,2)
self.all_fish[f.id] = f
self.trimFishList()
def refreshAllFishData(self):
for f in self.all_fish.values():
self.refreshData(f)
def trimFishList(self, force_color_update=False):
"""
Updates shown table (fish_list) from all instances containing dictionary (all_fish).
fish_list is trimmed based on the minimum duration.
"""
fl = [fish for fish in self.all_fish.values() if fish.checkConditions(self.min_detections, self.mad_limit)]
reverse = self.sort_order != QtCore.Qt.AscendingOrder
fl.sort(key=fish_sort_keys[self.sort_ind], reverse=reverse)
len_new = len(fl)
len_old = len(self.fish_list)
if len_new > len_old:
self.beginInsertRows(QtCore.QModelIndex(), len_old, max(0, len_new-1))
self.fish_list = fl
self.endInsertRows()
elif len_new < len_old:
self.beginRemoveRows(QtCore.QModelIndex(), max(0, len_new-1), max(0, len_old-1))
self.fish_list = fl
self.endRemoveRows()
else:
self.fish_list = fl
if self.update_fish_colors or force_color_update:
self.updateFishColors()
self.refreshLayout()
def onFileOpened(self):
self.clear()
self.frame_rate = self.playback_manager.getRecordFrameRate()
self.frame_time = (1.0 / self.frame_rate) if self.frame_rate is not None else None
def onFileClosed(self):
self.clear()
self.frame_rate = None
self.frame_time = None
def onTrackingInitialized(self, clearData):
if clearData:
self.clear()
def clear(self):
self.all_fish = {}
self.trimFishList()
def refreshLayout(self):
self.layoutChanged.emit()
self.dataChanged.emit(QtCore.QModelIndex(), QtCore.QModelIndex())
self.updateContentsSignal.emit()
def data(self, index, role):
"""
Return data for TableView based on row and column.
Row: Fish
Column: Some parameter of the fish
"""
if role == Qt.DisplayRole:
row = index.row()
col = index.column()
try:
return data_lambda_list[col](self.fish_list[row])
except IndexError:
if row >= len(self.fish_list):
LogObject().print("Bad index {}/{}".format(row, len(self.fish_list) - 1))
return QtCore.QVariant()
else:
return QtCore.QVariant()
def rowCount(self, index=None):
return len(self.fish_list)
def columnCount(self, index=None):
return COLUMN_COUNT;
def allDirectionCounts(self):
"""
Returns direction counts (Total, Up, Down, None) of all fish.
"""
return self.directionCountsHelp(self.all_fish.values())
def directionCounts(self):
"""
Returns direction counts (Total, Up, Down, None) of currently displayed fish.
"""
return self.directionCountsHelp(self.fish_list)
def directionCountsHelp(self, f_list):
total_count = 0
up_count = 0
down_count = 0
none_count = 0
for f in f_list:
total_count += 1
if f.direction == SwimDirection.UP:
up_count += 1
elif f.direction == SwimDirection.DOWN:
down_count += 1
else:
none_count += 1
return total_count, up_count, down_count, none_count
def headerData(self, section, orientation, role=Qt.DisplayRole):
if role == Qt.DisplayRole and orientation == Qt.Horizontal:
return fish_headers[section]
def sort(self, col, order=QtCore.Qt.AscendingOrder):
#self.layoutAboutToBeChanged.emit()
self.sort_ind = col
self.sort_order = order
reverse = order != QtCore.Qt.AscendingOrder
self.fish_list.sort(key = fish_sort_keys[col], reverse = reverse)
#self.layoutChanged.emit()
self.dataChanged.emit(QtCore.QModelIndex(), QtCore.QModelIndex())
def getShownFish(self, row):
if row < len(self.fish_list):
return self.fish_list[row]
else:
return None
def addFish(self):
"""
Manual addition of fish.
Currently not supported. Manual fish detection from frames is required,
i.e. user should be able to select fish location from SonarView for each frame.
"""
f = FishEntry(self.getNewID())
self.all_fish[f.id] = f
self.trimFishList()
def getNewID(self, ind=1):
keys = self.all_fish.keys()
while ind in keys:
ind += 1
return ind
def removeFish(self, rows, update=True):
if(len(rows) > 0):
for row in sorted(rows, reverse=True):
if row >= len(self.fish_list):
continue
fish_id = self.fish_list[row].id
try:
del_f = self.all_fish.pop(fish_id)
del del_f
except KeyError:
LogObject().print("KeyError occured when removing entry with id:", fish_id)
if update:
self.trimFishList()
def mergeFish(self, rows):
if rows == None or len(rows) == 0:
return
sorted_rows = sorted(rows)
new_fish = self.fish_list[sorted_rows[0]].copy()
for i in range(1, len(sorted_rows)):
row = sorted_rows[i]
fish = self.fish_list[row]
new_fish.merge(fish)
self.refreshData(new_fish)
self.removeFish(rows, False)
self.all_fish[new_fish.id] = new_fish
self.trimFishList()
def splitFish(self, rows, frame):
if rows == None or len(rows) == 0:
return
for row in sorted(rows):
fish = self.fish_list[row]
frame_inds = fish.tracks.keys()
if fish.frame_in < frame and fish.frame_out > frame:
id = self.getNewID(fish.id)
new_fish = fish.split(frame, id)
fish.forceLengthByPercentile(self.length_percentile)
new_fish.forceLengthByPercentile(self.length_percentile)
self.all_fish[id] = new_fish
self.refreshData(fish)
self.refreshData(new_fish)
self.trimFishList()
def clearMeasurements(self, rows):
if rows == None or len(rows) == 0:
return
for row in rows:
if row >= len(self.fish_list):
continue
self.fish_list[row].forceLengthByPercentile(self.length_percentile)
self.dataChanged.emit(QtCore.QModelIndex(), QtCore.QModelIndex())
def selectFromEchogram(self, frame_min, frame_max, height_min, height_max):
"""
Finds fish that are within given frame and height limits and sends a signal
to select the corresponding rows in table view.
"""
new_selection = set()
polar_transform = self.playback_manager.playback_thread.polar_transform
min_d, max_d = self.playback_manager.getRadiusLimits()
for ind, fish in enumerate(self.fish_list):
# Skip fish outside the given range of frames
if fish.frame_out < frame_min or fish.frame_in > frame_max:
continue
for frame, track in fish.tracks.items():
if frame >= frame_min and frame <= frame_max:
track, det = fish.tracks[frame]
center = FishEntry.trackCenter(track)
distance, angle = polar_transform.cart2polMetric(center[0], center[1], True)
if distance >= height_min and distance <= height_max:
new_selection.add(ind)
break
self.setSelection(new_selection)
def setSelection(self, rows):
"""
Creates a QItemSelection based on given rows (shown fish items)
and emits updateSelectionSignal with the selection.
"""
selection = QtCore.QItemSelection()
for row in rows:
ind_1 = self.index(row, 0)
ind_2 = self.index(row, self.columnCount() - 1)
range = QtCore.QItemSelectionRange(ind_1, ind_2)
selection.append(range)
self.updateSelectionSignal.emit(selection, QtCore.QItemSelectionModel.ClearAndSelect)
def onSelectionChanged(self, selected):
self.selected_rows = selected
self.updateContentsSignal.emit()
def flags(self, index):
if not index.isValid():
return Qt.ItemIsEnabled
return Qt.ItemIsSelectable | Qt.ItemIsEditable | Qt.ItemIsEnabled
def setData(self, index, value, role):
if index.isValid() and role == Qt.EditRole:
col = index.column()
row = index.row()
fish = self.fish_list[row]
if col == 1:
id, success = intTryParse(value)
if success:
if id not in self.all_fish:
self.all_fish[id] = self.all_fish.pop(fish.id)
fish.id = id
self.trimFishList()
return True
elif col == 2:
length, success = floatTryParse(value)
if success:
fish.length = length
self.dataChanged.emit(index, index)
return True
elif col == 3:
try:
fish.direction = SwimDirection[value]
self.dataChanged.emit(index, index)
return True
except KeyError:
pass
return False
def secondaryTrack(self, filter_parameters):
"""
Applies filters to fish data and starts tracker's secondaryTrack process with used detections.
Used detections are excluded from tracking.
"""
self.clear_old_data = False
min_dets = filter_parameters.getParameter(FilterParameters.ParametersEnum.min_duration)
mad_limit = filter_parameters.getParameter(FilterParameters.ParametersEnum.mad_limit)
LogObject().print1(f"Filter Parameters: {min_dets} {mad_limit}")
used_dets = self.applyFiltersAndGetUsedDetections(min_dets, mad_limit)
self.playback_manager.runInThread(lambda: self.tracker.secondaryTrack(used_dets, self.tracker.secondary_parameters))
def updateDataFromTracker(self):
"""
Iterates through the results of the tracker and updates the data in FishManager.
If clear_old_data is set, the old data is first removed.
"""
if self.clear_old_data:
self.clear()
self.clear_old_data = True
# Iterate through all frames.
for frame, tracks in self.tracker.tracks_by_frame.items():
try:
# Iterate through all tracks in a frame.
for tr, det in tracks:
id = tr[4]
if id in self.all_fish:
f = self.all_fish[id]
f.addTrack(tr, det, frame)
else:
f = FishEntryFromTrack(tr, det, frame)
self.all_fish[id] = f
except ValueError as e:
print(tracks)
raise e
# Trim tails, i.e. remove last tracks with no corresponding detection.
if self.tracker.parameters.getParameter(TrackerParameters.ParametersEnum.trim_tails):
for id, fish in self.all_fish.items():
fish.trimTail()
# Refresh values
for fish in self.all_fish.values():
self.refreshData(fish)
fish.setLengthByPercentile(self.length_percentile)
self.printDirectionCounts()
self.trimFishList(force_color_update=True)
def applyFilters(self):
"""
Applies the current filters by replacing the contents of all_fish
with the contents of fish_list. fish_list is the "filtered version"
of all_fish.
"""
self.trimFishList()
self.all_fish = {}
for fish in self.fish_list:
self.all_fish[fish.id] = fish
def getDetectionsInFish(self):
"""
Returns detections that have been associated with the current fish.
"""
detections = {}
for fish in self.all_fish.values():
for frame, (_, det) in fish.tracks.items():
if det is None:
continue
if frame not in detections:
detections[frame] = [det]
else:
detections[frame].append(det)
return detections
def applyFiltersAndGetUsedDetections(self, min_detections=None, mad_limit=None):
"""
Applies filters and returns the detections associated to the remaining fish.
If optional parameters are not given, the current values in FishManager are used.
"""
temp_min_detections = self.min_detections
temp_mad_limit = self.mad_limit
if min_detections is not None:
self.min_detections = min_detections
if mad_limit is not None:
self.mad_limit = mad_limit
LogObject().print1(f"Fish before applying filters: {len(self.all_fish)}")
self.applyFilters()
LogObject().print1(f"Fish after applying filters: {len(self.all_fish)}")
used_dets = self.getDetectionsInFish()
count = 0
for frame, dets in used_dets.items():
count += len(dets)
LogObject().print1(f"Total detections used in filtered results: {count}")
self.min_detections = temp_min_detections
self.mad_limit = temp_mad_limit
return used_dets
def refreshData(self, fish):
"""
Refresh calculated variables of the given fish.
"""
fish.setFrames()
fish.setPathVariables(self.up_down_inverted, self.frame_time, 1.0/self.playback_manager.getPixelsPerMeter())
fish.setLengths()
def updateFishColors(self):
color_ind = 0
for id, fish in self.all_fish.items():
fish.color_ind = color_ind
color_ind = (color_ind + 1) % N_COLORS
def isColor(self, index):
return index.column() == 0
def isDropdown(self, index):
return index.column() == 3
def dropdown_options(self):
return [sd.name for sd in list(SwimDirection)]
def getDropdownIndex(self, index):
try:
return self.fish_list[index.row()].direction
except IndexError:
return SwimDirection.NONE
def setMinDetections(self, value):
self.min_detections = value
self.trimFishList()
def setMAD(self, value):
self.mad_limit = value
self.trimFishList()
def setLengthPercentile(self, value):
self.length_percentile = value
for fish in self.all_fish.values():
fish.setLengthByPercentile(self.length_percentile)
self.dataChanged.emit(QtCore.QModelIndex(), QtCore.QModelIndex())
def toggleUpDownInversion(self):
self.setUpDownInversion(not self.up_down_inverted)
def setUpDownInversion(self, value):
self.up_down_inverted = value
pixels_per_meter = self.playback_manager.getPixelsPerMeter()
if pixels_per_meter is not None:
meters_per_pixel = 1.0 / pixels_per_meter
for fish in self.all_fish.values():
fish.setPathVariables(self.up_down_inverted, self.frame_time, meters_per_pixel)
self.dataChanged.emit(QtCore.QModelIndex(), QtCore.QModelIndex())
def setShowEchogramFish(self, value):
self.show_echogram_fish = value
def visualize(self, image, frame_ind, show_size=True, show_id=True, show_bounding_box=True):
"""
Draws the tracked fish to the full sized image using opencv.
Returns the modified image.
"""
fish_by_frame = self.getFishInFrame(frame_ind)
if len(fish_by_frame) == 0:
return image
colors = sns.color_palette('deep', max(0, len(fish_by_frame)))
for fish in fish_by_frame:
tr, det = fish.tracks[frame_ind]
if show_id:
center = FishEntry.trackCenter(tr)
image = cv2.putText(image, f"ID: {fish.id}", (int(center[1])-20, int(center[0])+25), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255,255,255), 1, cv2.LINE_AA)
if show_size and det is not None:
det.visualize(image, colors, True, False)
if show_bounding_box:
corners = np.array([[tr[0], tr[1]], [tr[2], tr[1]], [tr[2], tr[3]], [tr[0], tr[3]]]) #, [tr[0], tr[1]]
for i in range(0,3):
cv2.line(image, (int(corners[i,1]),int(corners[i,0])), (int(corners[i+1,1]),int(corners[i+1,0])), (255,255,255), 1)
cv2.line(image, (int(corners[3,1]),int(corners[3,0])), (int(corners[0,1]),int(corners[0,0])), (255,255,255), 1)
return image
def getFishInFrame(self, ind):
return [f for f in self.fish_list if ind in f.tracks.keys()]
def getSavedList(self):
return self.fish_list if fh.getConfValue(fh.ConfKeys.filter_tracks_on_save) else self.all_fish.values()
def saveToFile(self, path):
"""
Tries to save all fish information (from all_fish dictionary) to a file.
"""
if(self.playback_manager.playback_thread is None):
LogObject().print("No file open, cannot save.")
return
try:
with open(path, "w") as file:
file.write("id;frame;length;distance;angle;direction;corner1 x;corner1 y;corner2 x;corner2 y;corner3 x;corner3 y;corner4 x;corner4 y; detection\n")
lines = self.getSaveLines()
lines.sort(key = lambda l: (l[0].id, l[1]))
for _, _, line in lines:
file.write(line)
LogObject().print("Tracks saved to path:", path)
except PermissionError as e:
LogObject().print("Cannot open file {}. Permission denied.".format(path))
def getSaveLines(self):
"""
Iterates through all the fish and returns a list containing the fish objects, frames the fish appear in, and the following information:
ID, Frame, Length, Angle, Direction, Corner coordinates and wether the values are from a detection or a track.
Detection information are preferred over tracks.
"""
lines = []
polar_transform = self.playback_manager.playback_thread.polar_transform
f1 = "{:.5f}"
lineBase1 = "{};{};" + "{};{};{};".format(f1,f1,f1) + "{};"
lineBase2 = "{};{};" + "{};{};{};".format(f1,f1,f1) + "{};"
for fish in self.getSavedList():
for frame, td in fish.tracks.items():
track, detection = td
# Values calculated from detection
if detection is not None:
length = fish.length if fish.length_overwritten else detection.length
line = lineBase1.format(fish.id, frame, length, detection.distance, detection.angle, fish.direction.name)
if detection.corners is not None:
line += self.cornersToString(detection.corners, ";")
else:
line += ";".join(8 * [" "])
line += ";1"
# Values calculated from track
else:
if fish.length_overwritten:
length = fish.length
else:
length, _ = polar_transform.getMetricDistance(*track[:4])
#center = [(track[2]+track[0])/2, (track[3]+track[1])/2]
center = FishEntry.trackCenter(track)
distance, angle = polar_transform.cart2polMetric(center[0], center[1], True)
angle = float(angle / np.pi * 180 + 90)
line = lineBase1.format(fish.id, frame, length, distance, angle, fish.direction.name)
line += self.cornersToString([[track[0], track[1]], [track[2], track[1]], [track[2], track[3]], [track[0], track[3]]], ";")
line += ";0"
lines.append((fish, frame, line + "\n"))
return lines
def cornersToString(self, corners, delim):
"""
Formats the corner information in a saveable format.
"""
base = "{:.2f}" + delim + "{:.2f}"
return delim.join(base.format(cx,cy) for cy, cx in corners[0:4])
def loadFromFile(self, path):
try:
with open(path, 'r') as file:
self.clear()
header = file.readline()
for line in file:
split_line = line.split(';')
id = int(split_line[0])
frame = int(split_line[1])
length = float(split_line[2])
direction = SwimDirection[split_line[5]]
track = [float(split_line[7]), float(split_line[6]), float(split_line[11]), float(split_line[10]), id]
if id in self.all_fish:
f = self.all_fish[id]
f.addTrack(track, None, frame)
else:
f = FishEntryFromTrack(track, None, frame)
f.length = length
f.direction = direction
self.all_fish[id] = f
self.refreshAllFishData()
self.trimFishList(force_color_update=True)
except PermissionError as e:
LogObject().print(f"Cannot open file {path}. Permission denied.")
except ValueError as e:
LogObject().print(f"Invalid values encountered in {path}, when trying to import tracks. {e}")
def convertToWritable(self, frame, label, track):
return [frame, label, list(map(float, track))]
def getSaveDictionary(self):
"""
Returns a dictionary of fish to be saved in SaveManager.
"""
fish = {}
for f in self.getSavedList():
fish_tracks = [self.convertToWritable(frame, int(det.label), track[0:4]) if det is not None else
self.convertToWritable(frame, None, track[0:4])
for frame, (track, det) in f.tracks.items()]
fish[str(f.id)] = fish_tracks
return fish
def applySaveDictionary(self, data, dets):
"""
Load fish entries from data provided by SaveManager.
"""
self.clear()
for _id, f_data in data.items():
id = int(_id)
f = None
for frame, det_label, track in f_data:
if f is None:
f = FishEntry(id, frame, frame)
if det_label is not None:
# Goes through detections in the same frame and tries to assign the
# corresponding detection based on the label.
frame_dets = dets[frame]
match_found = False
for fd in frame_dets:
if fd.label == det_label:
# Adds track with a matching detection to the FishEntry
f.addTrack(track, fd, frame)
match_found = True
break
if not match_found:
LogObject().print("Warning: Match not found in frame {} for label {}".format(frame, det_label))
else:
f.addTrack(track, None, frame)
if f is not None:
self.all_fish[id] = f
self.refreshAllFishData()
self.printDirectionCounts()
self.trimFishList(force_color_update=True)
def printDirectionCounts(self):
tc, uc, dc, nc = self.allDirectionCounts()
LogObject().print1(f"Direction counts: Total {tc}, Up {uc}, Down {dc}, None {nc}")
class SwimDirection(IntEnum):
UP = 0
DOWN = 1
NONE = 2
def FishEntryFromTrack(track, detection, frame):
fish = FishEntry(track[4], frame, frame)
fish.addTrack(track, detection, frame)
return fish
class FishEntry():
def __init__(self, id, frame_in=0, frame_out=0):
self.id = int(id)
self.length = 0
self.direction = SwimDirection.NONE
self.frame_in = frame_in
self.frame_out = frame_out
self.duration = frame_out - frame_in + 1
self.mad = 0
self.tortuosity = 1
self.speed = 0
# tracks: Dictionary {frame index : (track, detection)}
self.tracks = {}
self.detection_count = 0
# lengths: Sorted list [lengths of detections]
self.lengths = []
self.length_overwritten = False
self.color_ind = 0
def __repr__(self):
return "FishEntry {}: {:.1f} {}".format(self.id, self.length, self.direction.name)
def dirSortValue(self):
return self.direction.value * 10**8 + self.id
def setLength(self, value):
self.length = value
self.length_overwritten = True
def setLengthByPercentile(self, percentile):
if not self.length_overwritten:
if len(self.lengths) > 0:
self.length = round(float(np.percentile(self.lengths, percentile)),3)
def forceLengthByPercentile(self, percentile):
self.length_overwritten = False
self.setLengthByPercentile(percentile)
def checkConditions(self, duration, mad):
return self.duration >= duration and self.mad >= mad
def addTrack(self, track, detection, frame):
self.tracks[frame] = (track[0:4], detection)
if detection is not None:
insort(self.lengths, detection.length)
#self.setFrames()
def copy(self):
f = FishEntry(self.id, self.frame_in, self.frame_out)
f.length = self.length
f.direction = self.direction
f.tracks = self.tracks.copy()
f.lengths = self.lengths.copy()
f.length_overwritten = self.length_overwritten
f.color_ind = self.color_ind
f.mad = self.mad
f.tortuosity = self.tortuosity
f.speed = self.speed
return f
def merge(self, other):
self.frame_in = min(self.frame_in, other.frame_in)
self.frame_out = max(self.frame_out, other.frame_out)
self.duration = self.frame_out - self.frame_in + 1
for l in other.lengths:
insort(self.lengths, l)
for frame, track in other.tracks.items():
if frame not in self.tracks:
self.tracks[frame] = track
else:
# TODO: Overlapping tracks.
# Currently only self.tracks are kept when tracks overlap each other.
pass
def split(self, frame, new_id):
"""
Splits the fish in two at the argument "frame".
frame: the first included frame of the second fish
new_id: the new id of the second fish
"""
f = FishEntry(new_id, frame, self.frame_out)
for tr_frame in list(self.tracks.keys()):
if tr_frame >= frame:
tr, det = self.tracks.pop(tr_frame)
f.addTrack(tr, det, tr_frame)
#self.setLengths()
#self.setFrames()
return f
def trimTail(self):
"""
Removes the tail of the tracks, i.e. the last tracks with no corresponding detections (det == None).
"""
for frame in self.getTail():
self.tracks.pop(frame)
#self.setLengths()
#self.setFrames()
def getTail(self):
tail = []
for frame, (tr, det) in self.tracks.items():
if det is None:
tail.append(frame)
else:
tail = []
return tail
def setFrames(self):
inds = self.tracks.keys()
if len(inds) > 0:
self.frame_in = min(inds)
self.frame_out = max(inds)
self.duration = self.frame_out - self.frame_in + 1
self.detection_count = len([det for _, det in self.tracks.values() if det is not None])
def setPathVariables(self, inverted, frame_time, meters_per_pixel):
"""
Calculates variables from the path of the fish,
i.e. swim direction, mad, tortuosity and speed.
"""
valid_dets = [d for _, d in self.tracks.values() if d is not None]
if len(valid_dets) <= 1:
self.direction = SwimDirection.NONE
self.mad = 0
self.tortuosity = 1
self.speed = 0
else:
end_point_distance = valid_dets[-1].center - valid_dets[0].center
if inverted:
self.direction = SwimDirection.UP if end_point_distance[1] <= 0 else SwimDirection.DOWN
else:
self.direction = SwimDirection.UP if end_point_distance[1] > 0 else SwimDirection.DOWN
self.mad = abs(valid_dets[-1].angle - valid_dets[0].angle)
path_length = self.calculatePathLength(valid_dets)
norm_dist = np.linalg.norm(end_point_distance)
self.tortuosity = float(path_length / norm_dist) if norm_dist > 0 else 1
if frame_time is not None:
self.speed = float(path_length * meters_per_pixel / ((self.frame_out - self.frame_in) * frame_time))
else:
self.speed = 0
def calculatePathLength(self, dets):
dist_sum = 0
prev_point = dets[0].center
for i in range(1, len(dets)):
new_point = dets[i].center
dist_sum += np.linalg.norm(new_point - prev_point)
prev_point = new_point
return float(dist_sum)
def setLengths(self):
self.lengths = sorted([det.length for _, det in self.tracks.values() if det is not None])
@staticmethod
def trackCenter(track):
return [(track[2]+track[0])/2, (track[3]+track[1])/2]
def floatTryParse(value):
try:
return float(value), True
except ValueError:
return value, False
def intTryParse(value):
try:
return int(value), True
except ValueError:
return value, False
if __name__ == "__main__":
fish_manager = FishManager(None, None)
fish_manager.testPopulate(500)
for fish in fish_manager.fish_list:
print(fish)