Update app.py

app.py

@@ -108,11 +108,9 @@ def enhance_face(img, face_helper, has_aligned, num_flow_steps, scale=2):
         face_helper.get_face_landmarks_5(only_center_face=False, eye_dist_threshold=5)
         face_helper.align_warp_face()
     if len(face_helper.cropped_faces) == 0:
-        raise gr.Error("Could not identify any face in the image.")
+        raise Exception("Could not identify any face in the image.")
     if has_aligned and len(face_helper.cropped_faces) > 1:
-        raise gr.Error(
-            "You marked that the input image is aligned, but multiple faces were detected."
-        )
+        raise Exception("You marked that the input image is aligned, but multiple faces were detected.")
 
     # face restoration
     for i, cropped_face in tqdm(enumerate(face_helper.cropped_faces)):
@@ -157,14 +155,14 @@ def inference(
     progress=gr.Progress(track_tqdm=True),
 ):
     if img is None:
-        raise gr.Error("Please upload an image before submitting.")
+        raise Exception("Please upload an image before submitting.")
     if randomize_seed:
         seed = random.randint(0, MAX_SEED)
     torch.manual_seed(seed)
     img = cv2.imread(img, cv2.IMREAD_COLOR)
     h, w = img.shape[0:2]
     if h > 4500 or w > 4500:
-        raise gr.Error("Image size too large.")
+        raise Exception("Image size too large.")
 
     face_helper = FaceRestoreHelper(
         scale,