Update Final_Black_White_Patch_inversion.py

Final_Black_White_Patch_inversion.py

@@ -1,7 +1,7 @@
 import cv2
 import numpy as np
 
-def scan_image(image_original, image, filter_patch):
+def scan_image_inversion(image_original, image, filter_patch):
     W, H = image.shape[:2]
     filter_size = filter_patch.shape
     t = filter_size[0]
@@ -9,7 +9,7 @@ def scan_image(image_original, image, filter_patch):
     for y in range((H-t)//t + 1):
         roi = image[y*t:(y*t)+t, :]
         if (roi.shape[0]<filter_patch.shape[0]):
-            print(">>>>")
+            print(f">>>>{roi.shape[0]<filter_patch.shape[0]}")
             break
         result = cv2.bitwise_or(roi, filter_patch)
 
@@ -22,16 +22,15 @@ def scan_image(image_original, image, filter_patch):
             cnt+=1
             # new_roi = cv2.bitwise_not(roi)
             new_roi = 255-roi
-            cv2.imwrite(f"black_patches/{cnt}.png", roi)
             image_original[y*t:(y*t)+t, :] = new_roi
 
     return image_original
 
-
-# Example usage
-image = cv2.imread('fin.png', cv2.IMREAD_GRAYSCALE)
-image_original = cv2.imread('fin.png', cv2.IMREAD_GRAYSCALE)
-_, black_white_image = cv2.threshold(image, 127, 255, cv2.THRESH_BINARY)
-filter_size = 100
-filter = np.zeros((filter_size, black_white_image.shape[1]), dtype=np.uint8)
-inverted_image = scan_image(image_original, black_white_image, filter)
+def black_patch_inversion(input_image_path, out_image_path):
+    image = cv2.imread(input_image_path, cv2.IMREAD_GRAYSCALE)
+    image_original = cv2.imread(input_image_path, cv2.IMREAD_GRAYSCALE)
+    _, black_white_image = cv2.threshold(image, 127, 255, cv2.THRESH_BINARY)
+    filter_size = 5
+    filter_patch = np.zeros((filter_size, black_white_image.shape[1]), dtype=np.uint8)
+    inverted_image = scan_image_inversion(image_original, black_white_image, filter_patch)
+    cv2.imwrite(out_image_path, inverted_image)