fix: More robust handling of feathered_mask normalization

This commit provides a more robust fix for the RuntimeWarning
(invalid value encountered in divide/cast) that could occur in
the `apply_mouth_area` function within
`modules/processors/frame/face_swapper.py`.

The previous check for `feathered_mask.max() == 0` was not
sufficient for all floating point edge cases.

The updated logic now:
- Checks if `feathered_mask.max()` is less than a small epsilon (1e-6).
- If true, it logs a warning and explicitly sets `feathered_mask`
  to an all-zero `uint8` array of the correct shape.
- Otherwise, it proceeds with the normalization and casting to `uint8`.

This ensures that division by zero or by extremely small numbers is
prevented, and the `feathered_mask` is always in a valid state for
subsequent blending operations.

modules/face_analyser.py

@@ -2,6 +2,7 @@ import os
 import shutil
 from typing import Any
 import insightface
+import logging # Added logging import
 
 import cv2
 import numpy as np
@@ -25,18 +26,27 @@ def get_face_analyser() -> Any:
 
 
 def get_one_face(frame: Frame) -> Any:
-    face = get_face_analyser().get(frame)
+    faces = get_face_analyser().get(frame)
+    if not faces:
+        logging.debug("Face_analyser: get_one_face: No faces found by insightface.")
+        return None
     try:
-        return min(face, key=lambda x: x.bbox[0])
+        return min(faces, key=lambda x: x.bbox[0])
     except ValueError:
+        logging.debug("Face_analyser: get_one_face: ValueError, likely no faces after all.")
         return None
 
 
 def get_many_faces(frame: Frame) -> Any:
-    try:
-        return get_face_analyser().get(frame)
-    except IndexError:
-        return None
+    faces = get_face_analyser().get(frame)
+    if not faces: # Check if faces is None or an empty list
+        logging.debug("Face_analyser: get_many_faces: No faces found by insightface.")
+        # Depending on what insightface returns for no faces,
+        # you might return None or an empty list.
+        # If .get() returns an empty list for no faces, this check is sufficient.
+        # If .get() returns None, this is also fine.
+        return faces # Return original (None or empty list)
+    return faces
 
 def has_valid_map() -> bool:
     for map in modules.globals.source_target_map:

modules/processors/frame/face_swapper.py

@@ -136,16 +136,26 @@ def process_frame(source_face: Face, temp_frame: Frame) -> Frame:
         many_faces = get_many_faces(temp_frame)
         if many_faces:
             for target_face in many_faces:
-                if source_face and target_face:
+                if source_face and target_face: # target_face from many_faces will always be valid here
                     temp_frame = swap_face(source_face, target_face, temp_frame)
-                else:
-                    print("Face detection failed for target/source.")
+                elif not source_face: # Check source_face specifically
+                    logging.error("Source face is not available or no face detected in source image. Skipping swap for this target face.")
+                    # Optionally `continue` or `break` if source_face is essential for all
+        elif not source_face : # if many_faces is empty AND source_face is also an issue
+             logging.error("Source face is not available AND no faces detected in target frame.")
+        else: # many_faces is empty, but source_face is ok
+             logging.info(f"No faces detected in the current target frame for 'many_faces' mode.")
     else:
         target_face = get_one_face(temp_frame)
         if target_face and source_face:
             temp_frame = swap_face(source_face, target_face, temp_frame)
         else:
-            logging.error("Face detection failed for target or source.")
+            if not source_face:
+                logging.error("Source face is not available or no face detected in source image.")
+            elif not target_face:
+                logging.error(f"No face detected in the current target frame.")
+            else: # Should not happen if logic is right, but as a fallback
+                logging.error("Face detection failed for an unknown reason concerning target or source.")
     return temp_frame
 
 
@@ -543,7 +553,13 @@ def apply_mouth_area(
         feathered_mask = cv2.GaussianBlur(
             polygon_mask.astype(float), (0, 0), feather_amount
         )
-        feathered_mask = feathered_mask / feathered_mask.max()
+
+        mask_max_value = feathered_mask.max()
+        if mask_max_value < 1e-6:  # Check if max is effectively zero
+            logging.warning("Mouth mask's feathered_mask is all zeros or near-zeros after blur. Resulting mask will be black.")
+            feathered_mask = np.zeros_like(polygon_mask, dtype=np.uint8)
+        else:
+            feathered_mask = (feathered_mask / mask_max_value * 255).astype(np.uint8)
 
         face_mask_roi = face_mask[min_y:max_y, min_x:max_x]
         combined_mask = feathered_mask * (face_mask_roi / 255.0)