Benjamin_Loison/Robust_image_source_identification_on_modern_smartphones
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Precise purpose of a part of code

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Benjamin Loison 2024-05-13 03:13:58 +02:00
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datasets/raise/attribute_source_camera.py
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@ -96,8 +96,7 @@ returnSingleColorChannelImage = lambda singleColorChannelImage, _minColor, _maxC
# - the second one is about estimating better and better the PRNU of each camera, as consider more and more training images and measuring the resulting attribution of cameras
for computeExtremes in tqdm(([True] if minColor is None or maxColor is None else []) + [False], 'Compute extremes'):
rescaleIfNeeded = returnSingleColorChannelImage if computeExtremes else rescaleRawImageForDenoiser
# As the second loop firstly compute noises of testing images.
# What about `MEAN` denoiser condition?
# As the second loop firstly if the denoiser is not `MEAN` or if `MEAN` predicts only on the whole training set, then compute noises of testing images.
if not computeExtremes:
print(f'{minColor=} {maxColor=}')
if DENOISER != Denoiser.MEAN or PREDICT_ONLY_ON_WHOLE_TRAINING_SET: