#49: Remove intermediary bias by not working on images but numpy arrays instead

datasets/raise/merge_single_color_channel_images_according_to_bayer_filter.py

@@ -1,15 +1,18 @@
 from PIL import Image
 from utils import Color
 from tqdm import tqdm
+import matplotlib.pyplot as plt
 
 def getImageByColor(color):
-    return Image.open(f'means/mean_flat-field_nef_wavelet_{color}.png')
+    filePath = f'means/mean_rafael_arw_bilateral_{color}.npy'
+    image = np.load(filePath)
+    return image
 
 color = Color.BLUE
 image = getImageByColor(color)
-width, height = image.size
+width, height = image.shape
 
-multipleColorsImage = Image.new('RGB', [dimension * 2 for dimension in image.size])
+multipleColorsImage = np.empty([dimension * 2 for dimension in image.shape], dtype = np.float64)
 
 def getNewIndex(index, offset):
     newIndex = (index - offset) * 2 + offset
@@ -19,7 +22,7 @@ for color in tqdm(Color, 'Color'):
     colorImage = getImageByColor(color)
     for y in tqdm(range(height), 'Height'):
         for x in range(width):
-            pixel = colorImage.getpixel((x, y))
+            pixel = colorImage[x, y]
             '''
             Assume Bayer Filter:
             RG
@@ -33,6 +36,6 @@ for color in tqdm(Color, 'Color'):
             }[color]
             newX, newY = [getNewIndex(index, offset) for index, offset in [(x, offsetX), (y, offsetY)]]
 
-            multipleColorsImage.putpixel((newX, newY), pixel)
+            multipleColorsImage[newX, newY] = pixel
 
-multipleColorsImage.save('multipleColors.png')
+plt.imsave('multiple_colors.png', multipleColorsImage)