Benjamin_Loison/Robust_image_source_identification_on_modern_smartphones
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Update forgotten to commit scripts

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Benjamin Loison 2024-05-15 20:00:44 +02:00
parent 6e7e06b85c
commit 60a9dfe89c
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2 changed files with 2 additions and 2 deletions
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2
datasets/raise/attribute_source_camera.py
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@ -159,7 +159,7 @@ for computeExtremes in tqdm(([True] if minColor is None or maxColor is None else
minColor, maxColor = updateExtremes(multipleColorsImage, minColor, maxColor)
continue
if DENOISER == Denoiser.MEAN:
if DENOISER == Denoiser.MEAN and not PREDICT_ONLY_ON_WHOLE_TRAINING_SET:
for color in Color:
cameraColorMeans[camera][color].add(singleColorChannelImages[color])
imagePrnuEstimateNpArray = getImagePrnuEstimateNpArray(singleColorChannelImages, multipleColorsImage, camera)

2
datasets/raise/utils.py
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@ -205,7 +205,7 @@ def getColorMeans(imagesFileNames, colors, singleColorChannelCropResolution = No
for color in colors:
colorIterativeMean = iterativeMean()
for imageFileName in tqdm(imagesFileNames, f'Computing mean of {str(color).replace("_", " ")} colored images'):
imageNpArray = getImageNpArray(imageFileName, False, color, Denoiser.MEAN)
imageNpArray, minColor_, maxColor_ = getImageNpArray(imageFileName, False, color, Denoiser.MEAN, None, None)
if singleColorChannelCropResolution is not None:
imageNpArray = getImageCrop(imageNpArray, singleColorChannelCropResolution)
imageNpArray = gaussian_filter(imageNpArray, sigma = 5)