Update app.py

app.py

@@ -5,8 +5,6 @@ import insightface
 from insightface.app import FaceAnalysis
 from PIL import Image
 from nudenet import NudeDetector
-from skimage import io
-from skimage.draw import polygon
 
 # Initialize the FaceAnalysis model
 app = FaceAnalysis(name='buffalo_l')
@@ -41,7 +39,19 @@ def check_for_adult_content(image):
 
     return False  # No explicit content detected
 
-# Face swapping function with added sharpening
+# Validate ROI to prevent out-of-bound errors
+def validate_roi(roi, image_shape):
+    x, y, w, h = roi
+    img_h, img_w = image_shape[:2]
+
+    x = max(0, x)
+    y = max(0, y)
+    w = min(w, img_w - x)
+    h = min(h, img_h - y)
+
+    return x, y, w, h
+
+# Face swapping function with sharpening
 def swap_faces(destination_image, source_image):
     # Load the destination and source images from Streamlit inputs
     img = cv2.cvtColor(np.array(destination_image), cv2.COLOR_RGB2BGR)
@@ -60,36 +70,27 @@ def swap_faces(destination_image, source_image):
     res = img.copy()
     try:
         for face in faces:
-            res = swapper.get(res, face, test_face, paste_back=True)
-    except MemoryError:
-        return "Memory error: Face swapping operation failed due to memory overload."
+            bbox = face['bbox'].astype(int)
+            x, y, w, h = validate_roi(bbox, img.shape)  # Validate ROI
 
-    # Apply texture blending for smoother integration (Poisson editing)
-    mask = np.zeros_like(res, dtype=np.uint8)
-    points = face['bbox'].astype(np.int32)  # Bounding box points
-    rr, cc = polygon([points[1], points[3], points[3], points[1]],
-                     [points[0], points[0], points[2], points[2]])
-    mask[rr, cc] = 255  # Create mask
+            # Resize source face to match destination face size
+            test_face_resized = cv2.resize(test, (w, h))
 
-    # Use seamlessClone to blend the swapped face
-    center = (points[0] + points[2]) // 2, (points[1] + points[3]) // 2
-    blended_res = cv2.seamlessClone(res, img, mask, center, cv2.NORMAL_CLONE)
+            res = swapper.get(res, face, test_face_resized, paste_back=True)
+    except MemoryError:
+        return "Memory error: Face swapping operation failed due to memory overload."
 
-    # Apply sharpening for clearer image
+    # Apply sharpening for a clearer image
     kernel = np.array([[0, -1, 0],
                        [-1, 5, -1],
                        [0, -1, 0]])
-    sharpened_res = cv2.filter2D(blended_res, -1, kernel)
-
-
-    # Commented smoothing (blurring) for testing purposes
-    smoothed_res = cv2.GaussianBlur(res, (5, 5), 0)
+    sharpened_res = cv2.filter2D(res, -1, kernel)
 
     # Convert the result to RGB for display in Streamlit
     sharpened_res_rgb = cv2.cvtColor(sharpened_res, cv2.COLOR_BGR2RGB)
 
     return sharpened_res_rgb
-    
+
 # Streamlit app layout
 def main():
     st.set_page_config(page_title="SnapSwap", page_icon=":camera:")