diff --git a/datasets/raise/fft/verify_dots.py b/datasets/raise/fft/verify_dots.py
index 99760fb..af744ac 100644
--- a/datasets/raise/fft/verify_dots.py
+++ b/datasets/raise/fft/verify_dots.py
@@ -12,19 +12,26 @@ folder = '../rafael/230424'
 meanImages = iterativeMean()
 filePaths = [f'{folder}/{file}' for file in os.listdir(folder) if isARawImage(file)]
 
-for filePath in tqdm(filePaths):
+for filePath in tqdm(filePaths, 'Compute mean image'):
     imageColorChannels = {color: getColorChannel(filePath, color) for color in Color}
     imageMergedColorChannels = mergeSingleColorChannelImagesAccordingToBayerFilter(imageColorChannels)
     meanImages.add(imageMergedColorChannels)
+    #plt.imshow(imageMergedColorChannels)
+    #plt.show()
+    #break
 
-#print(meanImages.mean.shape)
+#plt.imshow(meanImages.mean)
+#plt.show()
 
 # Is not there anything clever than this to do? See [Robust_image_source_identification_on_modern_smartphones/issues/72](https://gitea.lemnoslife.com/Benjamin_Loison/Robust_image_source_identification_on_modern_smartphones/issues/72).
 estimatedPrnu = iterativeMean()
-for filePath in tqdm(filePaths):
+for filePath in tqdm(filePaths, 'Compute estimated PRNU'):
     imageColorChannels = {color: getColorChannel(filePath, color) for color in Color}
     imageMergedColorChannels = mergeSingleColorChannelImagesAccordingToBayerFilter(imageColorChannels)
     estimatedPrnu.add(imageMergedColorChannels - meanImages.mean)
+    #plt.imshow(estimatedPrnu.mean)
+    #plt.show()
+    #break
 
 plt.imshow(estimatedPrnu.mean)
 plt.show()
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