Benjamin_Loison/Robust_image_source_identification_on_modern_smartphones
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Add and use getImageCrop

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Benjamin Loison 2024-05-03 03:13:38 +02:00
parent fd6a9868fe
commit 0c429aa4d6
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2 changed files with 10 additions and 5 deletions
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7
datasets/raise/attribute_source_camera.py
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@ -3,7 +3,7 @@
import numpy as np
import matplotlib.pyplot as plt
from tqdm import tqdm
from utils import denoise, iterativeMean, getColorChannel, escapeFilePath, Color, mergeSingleColorChannelImagesAccordingToBayerFilter, rescaleRawImageForDenoiser, updateExtremes, saveNpArray, getColorMeans
from utils import denoise, iterativeMean, getColorChannel, escapeFilePath, Color, mergeSingleColorChannelImagesAccordingToBayerFilter, rescaleRawImageForDenoiser, updateExtremes, saveNpArray, getColorMeans, getImageCrop
import sys
import os
import random
@ -60,7 +60,7 @@ def getImageFilePath(camera, cameraImageIndex):
def getSingleColorChannelImages(camera, cameraImageIndex):
imageFilePath = getImageFilePath(camera, cameraImageIndex)
singleColorChannelImages = {color: rescaleIfNeeded(getColorChannel(imageFilePath, color)[:minimalColorChannelCameraResolution[0],:minimalColorChannelCameraResolution[1]], minColor, maxColor) for color in Color}
singleColorChannelImages = {color: rescaleIfNeeded(getImageCrop(getColorChannel(imageFilePath, color), minimalColorChannelCameraResolution), minColor, maxColor) for color in Color}
return singleColorChannelImages
def getMultipleColorsImage(singleColorChannelImages):
@ -74,8 +74,7 @@ def getImagePrnuEstimateNpArray(singleColorChannelImages, multipleColorsImage, c
return imagePrnuEstimateNpArray
imagesCamerasFilePaths = {camera: [f'{IMAGES_CAMERAS_FOLDER[camera]}/{imagesCamerasFileName}' for imagesCamerasFileName in imagesCamerasFileNames[camera]] for camera in imagesCamerasFileNames}
#print(imagesCamerasFilePaths)
cameraColorMeans = {camera: getColorMeans(imagesCamerasFilePaths[camera], Color, DENOISER) for camera in imagesCamerasFilePaths}
cameraColorMeans = {camera: getColorMeans(imagesCamerasFilePaths[camera], Color, DENOISER, minimalColorChannelCameraResolution) for camera in imagesCamerasFilePaths}
from utils import silentTqdm
#tqdm = silentTqdm

8
datasets/raise/utils.py
View File

@ -132,12 +132,14 @@ def updateExtremes(imageNpArray, minColor, maxColor):
def print(*toPrint):
__builtin__.print(datetime.now(), *toPrint)
def getColorMeans(imagesFileNames, colors, denoiser):
def getColorMeans(imagesFileNames, colors, denoiser, singleColorChannelCropResolution = None):
colorMeans = {}
for color in colors:
colorIterativeMean = iterativeMean()
for imageFileName in tqdm(imagesFileNames, f'Computing mean of {color} colored images'):
imageNpArray = getImageNpArray(imageFileName, False, color, denoiser)
if singleColorChannelCropResolution is not None:
imageNpArray = getImageCrop(imageNpArray, singleColorChannelCropResolution)
imageNpArray = gaussian_filter(imageNpArray, sigma = 5)
colorIterativeMean.add(imageNpArray)
colorMeans[color] = colorIterativeMean.mean
@ -156,3 +158,7 @@ def getImageNpArray(imageFilePath, computeExtremes, color, denoiser):
# Pay attention to range of values expected by the denoiser.
# Indeed if provide the thousands valued raw image, then the denoiser only returns values between 0 and 1 and making the difference between both look pointless.
return imageNpArray
def getImageCrop(image, cropResolution):
imageCrop = image[:cropResolution[0], :cropResolution[1]]
return imageCrop