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montagem dos graficos
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‎grafico_metricas.ipynb‎

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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"%load_ext autoreload\n",
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"%autoreload 2"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"import os\n",
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"import sys\n",
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"module_path = os.path.abspath(os.path.join('..'))\n",
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"if module_path not in sys.path:\n",
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" sys.path.append(module_path)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"import cv2\n",
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"import sys\n",
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"import math\n",
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"import time\n",
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"import random\n",
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"import os\n",
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"from datetime import datetime\n",
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"from copy import deepcopy\n",
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"import numpy as np\n",
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"import matplotlib.pyplot as plt\n",
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"from skimage.metrics import structural_similarity as ssim\n",
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"from sewar.full_ref import vifp"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"from iEBMO import bmoIE"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"pSize = [1]\n",
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"maxIter = 1\n",
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"# imageNameList = ['./data/kodim/kodim04.png']\n",
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"# imageNameList = ['a0027.tiff', 'a0037.tiff', 'a0050.tiff']\n",
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"# imageNameList = ['a0027.png', 'a0037.png', 'a0050.png']\n",
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"\n",
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"# print(imageNameList)\n",
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"\n",
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"imageNameList = ['./data/kodim/kodim01.png', './data/kodim/kodim02.png', './data/kodim/kodim03.png', './data/kodim/kodim04.png',\n",
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" './data/kodim/kodim05.png', './data/kodim/kodim06.png', './data/kodim/kodim07.png', './data/kodim/kodim08.png', \n",
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" './data/kodim/kodim09.png', './data/kodim/kodim10.png','./data/kodim/kodim11.png', './data/kodim/kodim12.png', \n",
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" './data/kodim/kodim13.png', './data/kodim/kodim14.png', './data/kodim/kodim15.png', './data/kodim/kodim16.png', \n",
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" './data/kodim/kodim17.png', './data/kodim/kodim18.png', './data/kodim/kodim19.png', './data/kodim/kodim20.png', \n",
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" './data/kodim/kodim21.png', './data/kodim/kodim22.png', './data/kodim/kodim23.png', './data/kodim/kodim24.png', ]"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"import datetime\n",
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"for i in range(len(imageNameList)):\n",
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" averagePsnr = 0\n",
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" averageSsim = 0\n",
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" averageVif = 0\n",
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" print(imageNameList[i])\n",
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" for popSize in pSize:\n",
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" print(popSize)\n",
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"\n",
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" inputName = \"GroundTruth/kodakDataset/\"+imageNameList[i]\n",
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" truthName = imageNameList[i]\n",
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"\n",
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" trImg = cv2.imread(truthName, 0)\n",
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" # cv2.imshow('input', trImg)\n",
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" histr = cv2.calcHist([trImg], [0], None, [256], [0, 256])\n",
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" plt.plot(histr)\n",
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" # histogram of ground truth\n",
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" name_image_list = imageNameList[i].split('/')\n",
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" time = datetime.datetime.now()\n",
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" print(time)\n",
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" plt.savefig(f\"./histogramsDIBCO/ht_{str(time).split('.')[1]}{name_image_list[-1]}\")\n",
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" plt.clf()\n",
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" cv2.imwrite(f\"./truthDIBCO/t_{str(time).split('.')[1]}{name_image_list[-1]}\", trImg)\n",
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"\n",
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" bestImage = deepcopy(trImg)\n",
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"\n",
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" maxPsnr = 0\n",
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" maxSsim = 0\n",
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" maxVif = 0\n",
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" maxfit = -1000\n",
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" for iteration in range(10):\n",
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" outputImage, fitval = bmoIE(truthName, popSize, maxIter)\n",
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"\n",
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" truthImage = cv2.imread(truthName, 0)\n",
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" psnrval = cv2.PSNR(outputImage, truthImage)\n",
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" ssimval = ssim(outputImage, truthImage)\n",
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" vifval = vifp(outputImage, truthImage)\n",
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" print(iteration,psnrval,ssimval,vifval,int((psnrval+ssimval+vifval)*100))\n",
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" print(psnrval, ssimval, vifval)\n",
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" \n",
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" # salvar metricas em arquivo\n",
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" with open('./metrics/metrics.txt', 'a') as f:\n",
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" f.write(f'{psnrval} {ssimval} {vifval} - {name_image_list[-1]}\\n')\n",
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" \n",
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" if (psnrval+ssimval+vifval) > maxfit:\n",
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" maxfit = psnrval+ssimval+vifval\n",
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" maxPsnr = psnrval\n",
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" maxSsim = ssimval\n",
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" maxVif = vifval\n",
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" bestImage = deepcopy(outputImage)\n",
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" # cv2.imshow(str(iteration+1),bestImage)\n",
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"\n",
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" print(maxPsnr, maxSsim, maxVif)\n",
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"\n",
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" averagePsnr += maxPsnr\n",
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" averageSsim += maxSsim\n",
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" averageVif += maxVif\n",
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" print(i+1,averagePsnr,averageSsim,averageVif)\n",
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"\n",
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" histr = cv2.calcHist([bestImage],[0],None,[256],[0,256])\n",
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" plt.plot(histr)\n",
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" time = datetime.datetime.now()\n",
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" plt.savefig(f\"./histogramsDIBCO/ho_{str(time).split('.')[1]}{name_image_list[-1]}\") #histogram of output image\n",
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" plt.clf()\n",
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" transImageName = \"o_\"+name_image_list[-1]\n",
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" cv2.imwrite(f\"./outputDIBCO/{str(time).split('.')[1]}{transImageName}\", bestImage)\n",
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"\n",
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"\n",
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" averagePsnr /= len(imageNameList)\n",
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" averageSsim /= len(imageNameList)\n",
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" averageVif /= len(imageNameList)\n",
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" print(\"final\")\n",
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" print(averagePsnr)\n",
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" print(averageSsim)\n",
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" print(averageVif)"
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]
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}
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],
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"metadata": {
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"language_info": {
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"name": "python"
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},
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"orig_nbformat": 4
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}

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