datasets/raise/merge_with_same_color_scale_single_color_channel_images_according_to_bayer_filter.py

@@ -6,8 +6,8 @@ import numpy as np
 
 PREFIX = 'means/mean_rafael_230424_'
 
-def getImageByColor(color, denoiser):
-    filePath = PREFIX + f'{denoiser}_{color}.npy'
+def getImageByColor(color):
+    filePath = PREFIX + f'{color}.npy'
     image = np.load(filePath)
     return image
 
@@ -20,16 +20,13 @@ DENOISERS = [
 ]
 
 for denoiser in DENOISERS:
-    singleColorChannelImages = {color: getImageByColor(color, denoiser) for color in Color}
+    singleColorChannelImages = {color: getImageByColor(color) for color in Color}
     multipleColorsImage = mergeSingleColorChannelImagesAccordingToBayerFilter(singleColorChannelImages)
     multipleColorsImageDenoisers[denoiser] = multipleColorsImage
 
-plt.boxplot(list(map(np.ravel, multipleColorsImageDenoisers.values())), labels = DENOISERS)
-plt.grid(True)
-plt.show()
-
 def getExtreme(extreme):
     vExtreme = extreme(list(multipleColorsImageDenoisers.values()))
+    #print(vExtreme)
     return vExtreme
 
 vMin, vMax = [getExtreme(extreme) for extreme in [np.min, np.max]]