Benjamin_Loison/Robust_image_source_identification_on_modern_smartphones
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Ease providing {min,max}Color

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Benjamin Loison 2024-04-25 15:30:23 +02:00
parent c642fa430e
commit 60a4f78fa6
Signed by: Benjamin_Loison
SSH Key Fingerprint: SHA256:BtnEgYTlHdOg1u+RmYcDE0mnfz1rhv5dSbQ2gyxW8B8
1 changed files with 9 additions and 8 deletions
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17
datasets/raise/extract_noise.py
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@ -125,15 +125,16 @@ def treatImage(imageFileName, computeExtremes = False, color = None):
mean = ((mean * numberOfImagesInMean) + imageNoiseNpArray) / (numberOfImagesInMean + 1)
numberOfImagesInMean += 1
# Assuming same intensity scale across color channels.
for imageFileName in tqdm(imagesFileNames, 'Computing extremes of images'):
for color in colors:
treatImage(imageFileName, computeExtremes = True, color = color)
if minColor is None or maxColor is None:
# Assuming same intensity scale across color channels.
for imageFileName in tqdm(imagesFileNames, 'Computing extremes of images'):
for color in colors:
treatImage(imageFileName, computeExtremes = True, color = color)
# To skip this step next time.
# Maybe thanks to `rawpy.RawPy` fields, possibly stating device maximal value, can avoid doing so to some extent.
print(f'{minColor=}')
print(f'{maxColor=}')
# To skip this step next time.
# Maybe thanks to `rawpy.RawPy` fields, possibly stating device maximal value, can avoid doing so to some extent.
print(f'{minColor=}')
print(f'{maxColor=}')
if denoiser == 'mean':
means = {}