Precise purpose of a part of code
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@ -96,8 +96,7 @@ returnSingleColorChannelImage = lambda singleColorChannelImage, _minColor, _maxC
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# - 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
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for computeExtremes in tqdm(([True] if minColor is None or maxColor is None else []) + [False], 'Compute extremes'):
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rescaleIfNeeded = returnSingleColorChannelImage if computeExtremes else rescaleRawImageForDenoiser
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# As the second loop firstly compute noises of testing images.
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# What about `MEAN` denoiser condition?
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# 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.
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if not computeExtremes:
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print(f'{minColor=} {maxColor=}')
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if DENOISER != Denoiser.MEAN or PREDICT_ONLY_ON_WHOLE_TRAINING_SET:
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