Save mean of each color channel to merge them into a single image being

the mean of images

Otherwise for each color channel could use:

```py
plt.imsave(f'{fileName}.png', colorMean)
```

datasets/raise/extract_noise.py

@@ -9,6 +9,7 @@ from tqdm import tqdm
 import csv
 import rawpy
 from utils import Color
+import matplotlib.pyplot as plt
 
 imagesFolderPath = 'rafael/arw'
 imagesFolderPathFileName = imagesFolderPath.replace('/', '_')
@@ -153,6 +154,9 @@ if denoiser == 'mean':
                 colorMean = ((colorMean * numberOfImagesInColorMean) + imageNpArray) / (numberOfImagesInColorMean + 1)
             numberOfImagesInColorMean += 1
         means[color] = colorMean
+        fileName = f'mean_{imagesFolderPathFileName}_{color}'
+        # Then use `merge_single_color_channel_images_according_to_bayer_filter.py` to consider all color channels, instead of saving this single color channel as an image.
+        saveNpArray(fileName, colorMean)
 
 for color in colors:
     mean = None