Add easy support for single or multiple colors

datasets/raise/extract_noise.py

@@ -10,11 +10,14 @@ import csv
 import rawpy
 from utils import Color
 
-imagesFolderPath = '/mnt/HDD0/raise'
+imagesFolderPath = 'rafael/arw'
 imagesFolderPathFileName = imagesFolderPath.replace('/', '_')
-denoiser = 'wavelet'
+denoiser = 'bilateral'
 
 raiseNotFlatFields = False
+singleColorChannel = Color.GREEN_RIGHT
+
+colors = Color if singleColorChannel is None else [singleColorChannel]
 
 denoise = getattr(skimage.restoration, f'denoise_{denoiser}')
 
@@ -33,7 +36,7 @@ if raiseNotFlatFields:
 
 SKY = range(2_699, 2_807)
 WALL = range(2_807, 2_912)
-#imagesFileNames = [f'DSC0{imageIndex}.ARW' for imageIndex in SKY]
+imagesFileNames = [f'DSC0{imageIndex}.ARW' for imageIndex in SKY]
 
 minColor = None
 maxColor = None
@@ -102,7 +105,7 @@ def treatImage(imageFileName, computeExtremes = False, color = None):
 
 # Assuming same intensity scale across color channels.
 for imageFileName in tqdm(imagesFileNames, 'Computing extremes of images'):
-    for color in Color:
+    for color in colors:
         treatImage(imageFileName, computeExtremes = True, color = color)
 
 # To skip this step next time.
@@ -110,7 +113,7 @@ for imageFileName in tqdm(imagesFileNames, 'Computing extremes of images'):
 print(f'{minColor=}')
 print(f'{maxColor=}')
 
-for color in Color:
+for color in colors:
     mean = None
     numberOfImagesInMean = 0