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pre_processing/contrast_normalization/contrast_normalization.py

+import os
+import cv2
+import numpy as np
+from skimage import exposure
+
+
+# contrast = 1 for clahe
+# contrast = 2 for contrast stretching
+
+contrast = 1
+
+# optinal image cropping
+
+crop_image = False
+size_y = 1521
+size_x = 1931
+
+input_folder = "input"
+output_folder = "output"
+
+for filename in os.listdir(input_folder):
+    image = cv2.imread(os.path.join(input_folder, filename))
+    image_height, image_width, _ = image.shape
+    # center crop image to given size
+    if crop_image: 
+        crop_y = (image_height-size_y)//2
+        crop_x = (image_width-size_x)//2
+        image = image[crop_y:crop_y+size_y, crop_x:crop_x+size_x]
+    original = image.copy()
+
+    if contrast != 0:
+        image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+    if contrast == 1:
+        # adaptive Equalization
+        image = exposure.equalize_adapthist(image)
+        image = image.astype('float32') * 255
+    elif contrast == 2:
+        # contrast stretching
+        p2, p98 = np.percentile(image, (2, 98))
+        image = exposure.rescale_intensity(image, in_range=(p2, p98))
+    if contrast != 0:
+        image = cv2.cvtColor(image, cv2.COLOR_GRAY2BGR)
+
+    cv2.imwrite(os.path.join(output_folder, filename), image)