Update pixelateTG.py

pixelateTG.py

@@ -34,44 +34,34 @@ 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
+        overlay_x = int(center_x - 0.5 * resize_factor * w) - int(0.1 * resize_factor * w)
+        overlay_y = int(center_y - 0.5 * resize_factor * h) - int(0.1 * resize_factor * w)
         new_width = int(resize_factor * w)
         new_height = int(new_width / original_aspect_ratio)
-
-        # Ensure new dimensions are within the image bounds
-        new_width = min(new_width, image.shape[1] - x)
-        new_height = min(new_height, image.shape[0] - y)
-
         overlay_image_resized = cv2.resize(overlay_image, (new_width, new_height), interpolation=cv2.INTER_AREA)
-
-        # Compute overlay position
-        center_x = x + w // 2
-        center_y = y + h // 2
-        overlay_x = max(0, int(center_x - new_width / 2))
-        overlay_y = max(0, int(center_y - new_height / 2))
-
-        # Determine the region of interest (ROI)
-        roi_start_x = overlay_x
-        roi_start_y = overlay_y
+        overlay_x = max(0, overlay_x)
+        overlay_y = max(0, overlay_y)
+        roi_start_x = max(0, overlay_x)
+        roi_start_y = max(0, overlay_y)
         roi_end_x = min(image.shape[1], overlay_x + new_width)
         roi_end_y = min(image.shape[0], overlay_y + new_height)
-
-        # Adjust the overlay region to fit within the image
-        overlay_image_resized = overlay_image_resized[:roi_end_y - roi_start_y, :roi_end_x - roi_start_x]
-
-        # Handle the alpha channel for transparency
-        alpha_mask = overlay_image_resized[:, :, 3] / 255.0
-        for c in range(0, 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[roi_start_y:roi_end_y, roi_start_x:roi_end_x, :3] = (
+            overlay_image_resized[
+                roi_start_y - overlay_y : roi_end_y - overlay_y,
+                roi_start_x - overlay_x : roi_end_x - overlay_x,
+                :3
+            ] * (overlay_image_resized[:, :, 3:] / 255.0) +
+            image[roi_start_y:roi_end_y, roi_start_x:roi_end_x, :3] *
+            (1.0 - overlay_image_resized[:, :, 3:] / 255.0)
+        )
 
     processed_path = f"processed/{user_id}_{overlay_type}.jpg"
     cv2.imwrite(processed_path, image, [int(cv2.IMWRITE_JPEG_QUALITY), 95])
 
     return processed_path
 
-
 # Overlay functions
 def liotta_overlay(photo_path, user_id, bot):
     return overlay(photo_path, user_id, 'liotta', RESIZE_FACTOR, bot)