diff --git a/datasets/raise/attribute_source_camera.py b/datasets/raise/attribute_source_camera.py
index 4e348c2..a319024 100755
--- a/datasets/raise/attribute_source_camera.py
+++ b/datasets/raise/attribute_source_camera.py
@@ -58,7 +58,8 @@ def getImageFilePath(camera, cameraImageIndex):
     imageFilePath = f'{IMAGES_CAMERAS_FOLDER[camera]}/{imageFileName}'
     return imageFilePath
 
-def getMultipleColorsImage(imageFilePath):
+def getMultipleColorsImage(camera, cameraImageIndex):
+    imageFilePath = getImageFilePath(camera, cameraImageIndex)
     singleColorChannelImages = {color: rescaleIfNeeded(getColorChannel(imageFilePath, color)[:minimalColorChannelCameraResolution[0],:minimalColorChannelCameraResolution[1]], minColor, maxColor) for color in Color}
     multipleColorsImage = mergeSingleColorChannelImagesAccordingToBayerFilter(singleColorChannelImages)
     return multipleColorsImage
@@ -75,10 +76,9 @@ for computeExtremes in tqdm(([True] if minColor is None or maxColor is None else
         print('Extracting noise of testing images')
         for camera in tqdm(IMAGES_CAMERAS_FOLDER, 'Camera'):
             for cameraTestingImageIndex in tqdm(range(numberOfTestingImages), 'Camera testing image index'):
-                imageFilePath = getImageFilePath(camera, numberOfTrainingImages + cameraTestingImageIndex)
-                print(f'{imageFilePath=}')
+                print(f'{camera=} {numberOfTrainingImages + cameraTestingImageIndex=}')
 
-                multipleColorsImage = getMultipleColorsImage(imageFilePath)
+                multipleColorsImage = getMultipleColorsImage(camera, numberOfTrainingImages + cameraTestingImageIndex)
 
                 # Should make a function
                 singleColorChannelDenoisedImages = {color: denoise(singleColorChannelImages[color], DENOISER) for color in Color}
@@ -88,8 +88,7 @@ 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')):
-            imageFilePath = getImageFilePath(camera, cameraTrainingImageIndex)
-            multipleColorsImage = getMultipleColorsImage(imageFilePath)
+            multipleColorsImage = getMultipleColorsImage(camera, cameraTrainingImageIndex)
 
             if computeExtremes:
                 minColor, maxColor = updateExtremes(multipleColorsImage, minColor, maxColor)