Update app.py

app.py

@@ -19,32 +19,27 @@ swapper = insightface.model_zoo.get_model('inswapper_128.onnx')
 
 
 def swapi(imagen):
-    # Check if the input is a file path (str) or an image array (numpy.ndarray)
-    if isinstance(imagen, str):
-        img = cv2.imread(imagen)
-    else:
-        img = np.array(imagen)
+    # Use the uploaded image to extract features
+    img_user = cv2.imread(imagen)
+    faces_user = app.get(img_user)
 
-    if img is None:
-        raise ValueError("Failed to read the image.")
+    # Use another image "background1" for modifications
+    img_background = cv2.imread('background1.jpg')
+    faces_background = app.get(img_background)
 
-    if img.shape[-1] == 3:  # Check if the image is RGB or grayscale
-        img = cv2.cvtColor(img, cv2.COLOR_RGB2BGR)
+    # Assuming the user image has a face and we are using its features
+    source_face = faces_user[0]
 
-    faces = app.get(img)
-
-    if not faces:
-        return img  # If no faces are detected, return the original image
+    # Apply modifications to the "background1" image
+    res = img_background.copy()
+    for face in faces_background:
+        res = swapper.get(res, face, source_face, paste_back=True)
 
-    source_face = faces[0]
-    bbox = source_face['bbox']
-    bbox = [int(b) for b in bbox]
+    # Convert from BGR to RGB
+    res_rgb = cv2.cvtColor(res, cv2.COLOR_BGR2RGB)
 
-    res = img.copy()
-    for face in faces:
-        res = swapper.get(res, face, source_face, paste_back=True)
+    return res_rgb
 
-    return res  
 
 
 with gr.Blocks() as blocks: