Update pixelateTG.py

pixelateTG.py

@@ -35,44 +35,39 @@ def overlay(photo_path, user_id, overlay_type, resize_factor, bot):
         overlay_image = cv2.imread(random_overlay, cv2.IMREAD_UNCHANGED)
         original_aspect_ratio = overlay_image.shape[1] / overlay_image.shape[0]
 
-        # Calculate the new dimensions
+        # Calculate new dimensions for the overlay
         new_width = int(resize_factor * w)
         new_height = int(new_width / original_aspect_ratio)
 
         # 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
-
-        # Resize the overlay image to match the adjusted dimensions
-        overlay_image_resized = cv2.resize(overlay_image, (overlay_width, overlay_height), interpolation=cv2.INTER_AREA)
-
-        # Calculate the regions of interest
-        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 + overlay_width)
-        roi_end_y = min(image.shape[0], roi_start_y + overlay_height)
-
-        # Adjust resized overlay if it goes out of bounds
-        resized_overlay_start_x = 0 if start_x >= 0 else abs(start_x)
-        resized_overlay_start_y = 0 if start_y >= 0 else abs(start_y)
-        resized_overlay_width = overlay_width if end_x <= image.shape[1] else overlay_image_resized.shape[1] - resized_overlay_start_x
-        resized_overlay_height = overlay_height if end_y <= image.shape[0] else overlay_image_resized.shape[0] - resized_overlay_start_y
+
+        # Overlay position adjusted for better centering
+        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)
+
+        # Clamp values to ensure they are within the image boundaries
+        overlay_x = max(0, overlay_x)
+        overlay_y = max(0, overlay_y)
+
+        # Resize the overlay image
+        overlay_image_resized = cv2.resize(overlay_image, (new_width, new_height), interpolation=cv2.INTER_AREA)
+
+        # Calculate the regions of interest (ROI)
+        roi_start_x = overlay_x
+        roi_start_y = overlay_y
+        roi_end_x = min(image.shape[1], overlay_x + new_width)
+        roi_end_y = min(image.shape[0], overlay_y + new_height)
 
         # Blend the overlay onto the image
         try:
-            alpha_mask = overlay_image_resized[resized_overlay_start_y:resized_overlay_start_y + resized_overlay_height, resized_overlay_start_x:resized_overlay_start_x + resized_overlay_width, 3] / 255.0
+            overlay_part = overlay_image_resized[:roi_end_y - roi_start_y, :roi_end_x - roi_start_x]
+            alpha_mask = overlay_part[:, :, 3] / 255.0
             for c in range(3):
-                image[roi_start_y:roi_start_y + resized_overlay_height, roi_start_x:roi_start_x + resized_overlay_width, c] = (
-                    alpha_mask * overlay_image_resized[resized_overlay_start_y:resized_overlay_start_y + resized_overlay_height, resized_overlay_start_x:resized_overlay_start_x + resized_overlay_width, c] +
-                    (1 - alpha_mask) * image[roi_start_y:roi_start_y + resized_overlay_height, roi_start_x:roi_start_x + resized_overlay_width, c]
+                image[roi_start_y:roi_end_y, roi_start_x:roi_end_x, c] = (
+                    alpha_mask * overlay_part[:, :, c] +
+                    (1 - alpha_mask) * image[roi_start_y:roi_end_y, roi_start_x:roi_end_x, c]
                 )
         except ValueError as e:
             print(f"Error blending overlay: {e}")
@@ -83,6 +78,7 @@ def overlay(photo_path, user_id, overlay_type, resize_factor, bot):
     return processed_path
 
 
+
 # Overlay functions
 def liotta_overlay(photo_path, user_id, bot):
     return overlay(photo_path, user_id, 'liotta', RESIZE_FACTOR, bot)