diff --git a/datasets/raise/attribute_source_camera.py b/datasets/raise/attribute_source_camera.py
index 934a813..e7f5f7e 100755
--- a/datasets/raise/attribute_source_camera.py
+++ b/datasets/raise/attribute_source_camera.py
@@ -58,11 +58,14 @@ def getImageFilePath(camera, cameraImageIndex):
     imageFilePath = f'{IMAGES_CAMERAS_FOLDER[camera]}/{imageFileName}'
     return imageFilePath
 
-def getSingleColorChannelAndMultipleColorsImage(camera, cameraImageIndex):
+def getSingleColorChannelImages(camera, cameraImageIndex):
     imageFilePath = getImageFilePath(camera, cameraImageIndex)
     singleColorChannelImages = {color: rescaleIfNeeded(getColorChannel(imageFilePath, color)[:minimalColorChannelCameraResolution[0],:minimalColorChannelCameraResolution[1]], minColor, maxColor) for color in Color}
+    return singleColorChannelImages
+
+def getMultipleColorsImage(singleColorChannelImages):
     multipleColorsImage = mergeSingleColorChannelImagesAccordingToBayerFilter(singleColorChannelImages)
-    return singleColorChannelImages, multipleColorsImage
+    return multipleColorsImage
 
 from utils import silentTqdm
 #tqdm = silentTqdm
@@ -78,7 +81,8 @@ for computeExtremes in tqdm(([True] if minColor is None or maxColor is None else
             for cameraTestingImageIndex in tqdm(range(numberOfTestingImages), 'Camera testing image index'):
                 print(f'{camera=} {numberOfTrainingImages + cameraTestingImageIndex=}')
 
-                singleColorChannelImages, multipleColorsImage = getSingleColorChannelAndMultipleColorsImage(camera, numberOfTrainingImages + cameraTestingImageIndex)
+                singleColorChannelImages = getSingleColorChannelImages(camera, numberOfTrainingImages + cameraTestingImageIndex)
+                multipleColorsImage = getMultipleColorsImage(singleColorChannelImages)
 
                 # Should make a function
                 singleColorChannelDenoisedImages = {color: denoise(singleColorChannelImages[color], DENOISER) for color in Color}
@@ -88,7 +92,8 @@ for computeExtremes in tqdm(([True] if minColor is None or maxColor is None else
                 cameraTestingImagesNoise[camera] = cameraTestingImagesNoise.get(camera, []) + [imagePrnuEstimateNpArray]
     for cameraTrainingImageIndex in tqdm(range(minimumNumberOfImagesCameras if computeExtremes else numberOfTrainingImages), 'Camera training image index'):
         for cameraIndex, camera in enumerate(tqdm(IMAGES_CAMERAS_FOLDER, 'Camera')):
-            singleColorChannelImages, multipleColorsImage = getSingleColorChannelAndMultipleColorsImage(camera, cameraTrainingImageIndex)
+            singleColorChannelImages = getSingleColorChannelImages(camera, cameraTrainingImageIndex)
+            multipleColorsImage = getMultipleColorsImage(singleColorChannelImages)
 
             if computeExtremes:
                 minColor, maxColor = updateExtremes(multipleColorsImage, minColor, maxColor)