Benjamin_Loison/Robust_image_source_identification_on_modern_smartphones
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Simplify loops

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The idea was initially in the context of #62 to optimize execution
speed.
This commit is contained in:
Benjamin Loison
2024-04-30 03:36:04 +02:00
parent ad5aa22ae6
commit 20fcb247c6
1 changed files with 3 additions and 2 deletions
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5
datasets/raise/split_and_compare_prnus_of_subgroups.py
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@@ -30,14 +30,15 @@ rmss = []
minColor = None
maxColor = None
returnSingleColorChannelImage = lambda singleColorChannelImage, _minColor, _maxColor: singleColorChannelImage
for computeExtremes in tqdm(([True] if minColor is None or maxColor is None else []) + [False], 'Compute extremes'):
rescaleIfNeeded = returnSingleColorChannelImage if computeExtremes else rescaleRawImageForDenoiser
for subgroupImageIndex in tqdm(range(numberOfImagesPerSubgroup), 'Subgroup image index'):
for subgroupIndex in tqdm(range(NUMBER_OF_SUBGROUPS), 'Subgroup'):
imageIndex = (subgroupIndex * NUMBER_OF_SUBGROUPS) + subgroupImageIndex
imageFileName = imagesFileNames[imageIndex]
imageFilePath = f'{IMAGES_FOLDER}/{imageFileName}'
returnSingleColorChannelImage = lambda singleColorChannelImage, _minColor, _maxColor: singleColorChannelImage
rescaleIfNeeded = returnSingleColorChannelImage if computeExtremes else rescaleRawImageForDenoiser
singleColorChannelImages = {color: rescaleIfNeeded(getColorChannel(imageFilePath, color), minColor, maxColor) for color in Color}
multipleColorsImage = mergeSingleColorChannelImagesAccordingToBayerFilter(singleColorChannelImages)