Update app.py

app.py

@@ -20,22 +20,10 @@ def preprocess_image(img):
     adjusted = cv2.convertScaleAbs(img, alpha=alpha, beta=beta)
     return adjusted
 
-def smooth_blend(img, swapped_img, face_mask):
-    # Dilate the mask for better blending
-    kernel = np.ones((5, 5), np.uint8)
-    mask = cv2.dilate(face_mask, kernel, iterations=2)
-    mask = cv2.GaussianBlur(mask, (15, 15), 0)
-    mask = mask / 255.0
-    mask = np.repeat(mask[:, :, np.newaxis], 3, axis=2)
-    result = (swapped_img * mask + img * (1 - mask)).astype(np.uint8)
-    return result
-
-def create_face_mask(img, keypoints):
-    # Create a convex hull mask around the face using keypoints
-    hull = cv2.convexHull(keypoints.astype(np.int32))
-    mask = np.zeros(img.shape[:2], dtype=np.uint8)
-    cv2.fillConvexPoly(mask, hull, 255)
-    return mask
+def sharpen_image(img):
+    kernel = np.array([[0, -1, 0], [-1, 5, -1], [0, -1, 0]])
+    sharpened = cv2.filter2D(img, -1, kernel)
+    return np.clip(sharpened, 0, 255).astype(np.uint8)
 
 def swap_faces(src_img, dst_img, blur_strength=5, sharpen=False):
     try:
@@ -54,26 +42,15 @@ def swap_faces(src_img, dst_img, blur_strength=5, sharpen=False):
         src_face = src_faces[0]
         dst_face = dst_faces[0]
 
-        # Create a mask for smoother blending
-        dst_kps = dst_face.kps
-        face_mask = create_face_mask(dst_rgb, dst_kps)
+        swapped_img = swapper.get(dst_rgb, dst_face, src_face, paste_back=True)
 
-        # Perform face swap
-        swapped_img = swapper.get(dst_rgb, dst_face, src_face, paste_back=False)
-
-        # Blend the swapped face with the original image
-        blended_img = smooth_blend(dst_rgb, swapped_img, face_mask)
-
-        # Post-processing
         if blur_strength > 0:
-            blended_img = cv2.GaussianBlur(blended_img, (blur_strength, blur_strength), 0)
+            swapped_img = cv2.GaussianBlur(swapped_img, (blur_strength, blur_strength), 0)
 
         if sharpen:
-            kernel = np.array([[0, -1, 0], [-1, 5, -1], [0, -1, 0]])
-            blended_img = cv2.filter2D(blended_img, -1, kernel)
-            blended_img = np.clip(blended_img, 0, 255).astype(np.uint8)
+            swapped_img = sharpen_image(swapped_img)
 
-        result = cv2.cvtColor(blended_img, cv2.COLOR_RGB2BGR)
+        result = cv2.cvtColor(swapped_img, cv2.COLOR_RGB2BGR)
         return result
     except Exception as e:
         print(f"Error: {str(e)}")