update algo

app.py

@@ -52,32 +52,38 @@ def create_face_mask(pil_image):
     """
     Create a binary mask (PIL Image) from a PIL image by detecting the face region.
     The mask will be white (255) on the detected face area and black (0) elsewhere.
+    An ellipse is used to better match the shape of a face.
     """
     try:
-        # Convert PIL image to a numpy array in RGB format
+        # Convert the PIL image to a numpy array in RGB format
         image_np = np.array(pil_image.convert("RGB"))
         # Convert to grayscale for face detection
         gray = cv2.cvtColor(image_np, cv2.COLOR_RGB2GRAY)
 
-        # Load the Haar cascade for face detection (make sure opencv data is installed)
+        # Load the Haar cascade for face detection
         cascade_path = cv2.data.haarcascades + "haarcascade_frontalface_default.xml"
         face_cascade = cv2.CascadeClassifier(cascade_path)
 
         # Detect faces in the image
         faces = face_cascade.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=5)
 
-        # Create an empty mask with the same dimensions as the image
+        # Create an empty mask with the same dimensions as the grayscale image
         mask = np.zeros_like(gray, dtype=np.uint8)
 
-        # For each detected face, draw a white rectangle (or a more refined shape)
+        # For each detected face, draw an ellipse instead of a rectangle
         for (x, y, w, h) in faces:
-            # Optionally expand the bounding box slightly
+            # Optionally expand the bounding box slightly for a better fit
             padding = 0.2
             x1 = max(0, int(x - w * padding))
             y1 = max(0, int(y - h * padding))
             x2 = min(gray.shape[1], int(x + w * (1 + padding)))
             y2 = min(gray.shape[0], int(y + h * (1 + padding)))
-            mask[y1:y2, x1:x2] = 255
+
+            # Calculate the center and axes for the ellipse
+            center = (int((x1 + x2) / 2), int((y1 + y2) / 2))
+            axes = (int((x2 - x1) / 2), int((y2 - y1) / 2))
+            # Draw a filled ellipse (white) on the mask
+            cv2.ellipse(mask, center, axes, 0, 0, 360, 255, -1)
 
         return Image.fromarray(mask)
     except Exception as e:
@@ -98,7 +104,7 @@ def face_swap_app(target_img, face_img):
         reference_image=target_img,
         edit_image=face_img,
         edit_mask=edit_mask,
-        prompt="Face swap",
+        prompt="retain face",
         output_height=1024,
         output_width=1024,
         sampler='flow_euler',