Update cv.py

cv.py

@@ -1,8 +1,9 @@
 import cv2
 import numpy as np
 from sklearn.neighbors import NearestNeighbors
+import os
 
-def detect_back_patches(image_path, threshold_distance):
+def detect_back_patches(image_path, threshold_distance, save_path):
     # Read the image
     image = cv2.imread(image_path)
     
@@ -24,6 +25,14 @@ def detect_back_patches(image_path, threshold_distance):
     # Get the ROIs corresponding to the filtered patches
     ROIs = [patches[idx] for idx in filtered_patches_indices]
     
+    # Save the black patches as images
+    if not os.path.exists(save_path):
+        os.makedirs(save_path)
+    
+    for i, roi in enumerate(ROIs):
+        patch_image = roi.reshape(gray_image.shape[0] // 32, gray_image.shape[1] // 32)
+        cv2.imwrite(os.path.join(save_path, f"black_patch_{i}.jpg"), patch_image)
+    
     return ROIs
 
 def extract_patches(image, patch_size=(32, 32)):
@@ -42,4 +51,6 @@ def extract_patches(image, patch_size=(32, 32)):
 # Example usage
 image_path = 'document_image.jpg'
 threshold_distance = 100  # Adjust this threshold based on your requirements
-back_patches_ROIs = detect_back_patches(image_path, threshold_distance)
+save_path = 'black_patches'
+back_patches_ROIs = detect_back_patches(image_path, threshold_distance, save_path)
+