Update pixelateTG.py

pixelateTG.py

@@ -34,29 +34,32 @@ def overlay(photo_path, user_id, overlay_type, resize_factor, bot):
         random_overlay = random.choice(overlay_files)
         overlay_image = cv2.imread(random_overlay, cv2.IMREAD_UNCHANGED)
         original_aspect_ratio = overlay_image.shape[1] / overlay_image.shape[0]
-        center_x = x + w // 2
-        center_y = y + h // 2
+
+        # Calculate the new dimensions
         new_width = int(resize_factor * w)
         new_height = int(new_width / original_aspect_ratio)
-        overlay_image_resized = cv2.resize(overlay_image, (new_width, new_height), interpolation=cv2.INTER_AREA)
 
-        # Ensure ROI dimensions match
-        roi_start_x = max(0, center_x - new_width // 2)
-        roi_start_y = max(0, center_y - new_height // 2)
-        roi_end_x = min(image.shape[1], roi_start_x + new_width)
-        roi_end_y = min(image.shape[0], roi_start_y + new_height)
+        # Ensure the overlay is centered on the face
+        center_x = x + w // 2
+        center_y = y + h // 2
+        start_x = max(center_x - new_width // 2, 0)
+        start_y = max(center_y - new_height // 2, 0)
+        end_x = min(start_x + new_width, image.shape[1])
+        end_y = min(start_y + new_height, image.shape[0])
+
+        # Adjust the new dimensions to fit within the image boundaries
+        overlay_width = end_x - start_x
+        overlay_height = end_y - start_y
 
-        overlay_resized_width = roi_end_x - roi_start_x
-        overlay_resized_height = roi_end_y - roi_start_y
-
-        overlay_image_resized = cv2.resize(overlay_image_resized, (overlay_resized_width, overlay_resized_height), interpolation=cv2.INTER_AREA)
-
-        # Blending
+        # Resize the overlay image to match the adjusted dimensions
+        overlay_image_resized = cv2.resize(overlay_image, (overlay_width, overlay_height), interpolation=cv2.INTER_AREA)
+
+        # Blend the overlay onto the image
         try:
             alpha_mask = overlay_image_resized[:, :, 3] / 255.0
             for c in range(3):
-                image[roi_start_y:roi_end_y, roi_start_x:roi_end_x, c] = (alpha_mask * overlay_image_resized[:, :, c] +
-                                                                          (1 - alpha_mask) * image[roi_start_y:roi_end_y, roi_start_x:roi_end_x, c])
+                image[start_y:end_y, start_x:end_x, c] = (alpha_mask * overlay_image_resized[:, :, c] +
+                                                          (1 - alpha_mask) * image[start_y:end_y, start_x:end_x, c])
         except ValueError as e:
             print(f"Error blending overlay: {e}")
             continue
@@ -84,21 +87,6 @@ def cats_overlay(photo_path, user_id, bot):
 def clowns_overlay(photo_path, user_id, bot):
     return overlay(photo_path, user_id, 'clown', RESIZE_FACTOR, bot)
 
-def process_image(photo_path, user_id, file_id, bot):
-    image = cv2.imread(photo_path)
-    faces = detect_heads(image)
-
-    def process_face(x, y, w, h):
-        face = image[y:y+h, x:x+w]
-        pixelated_face = cv2.resize(face, (0, 0), fx=PIXELATION_FACTOR, fy=PIXELATION_FACTOR, interpolation=cv2.INTER_NEAREST)
-        image[y:y+h, x:x+w] = cv2.resize(pixelated_face, (w, h), interpolation=cv2.INTER_NEAREST)
-
-    futures = [executor.submit(process_face, x, y, w, h) for (x, y, w, h) in faces]
-    wait(futures)
-
-    processed_path = f"processed/{user_id}_{file_id}.jpg"
-    cv2.imwrite(processed_path, image, [int(cv2.IMWRITE_JPEG_QUALITY), 95])
-    return processed_path
 
 def process_gif(gif_path, session_id, user_id, bot):
     frames = imageio.mimread(gif_path)