Update app.py

app.py

@@ -194,11 +194,17 @@ def load_scheduler(scheduler_dir):
     scheduler_config = RectifiedFlowScheduler.load_config(scheduler_config_path)
     return RectifiedFlowScheduler.from_config(scheduler_config)
 
-# Helper function for image processing
 def center_crop_and_resize(frame, target_height, target_width):
+    # State 객체인 경우 value 값을 가져옴
+    if isinstance(target_height, gr.State):
+        target_height = target_height.value
+    if isinstance(target_width, gr.State):
+        target_width = target_width.value
+        
     h, w, _ = frame.shape
     aspect_ratio_target = target_width / target_height
     aspect_ratio_frame = w / h
+    
     if aspect_ratio_frame > aspect_ratio_target:
         new_width = int(h * aspect_ratio_target)
         x_start = (w - new_width) // 2
@@ -207,8 +213,11 @@ def center_crop_and_resize(frame, target_height, target_width):
         new_height = int(w / aspect_ratio_target)
         y_start = (h - new_height) // 2
         frame_cropped = frame[y_start : y_start + new_height, :]
+    
     frame_resized = cv2.resize(frame_cropped, (target_width, target_height))
     return frame_resized
+    
+
 
 def load_image_to_tensor_with_resize(image_path, target_height=512, target_width=768):
     image = Image.open(image_path).convert("RGB")
@@ -381,6 +390,11 @@ def generate_video_from_image(
     num_frames,
     progress=gr.Progress(),
 ):
+    # State 객체의 value 값을 가져옴
+    height = height.value if isinstance(height, gr.State) else height
+    width = width.value if isinstance(width, gr.State) else width
+    num_frames = num_frames.value if isinstance(num_frames, gr.State) else num_frames
+    
     if not image_path:
         raise gr.Error("입력 이미지를 제공해주세요.", duration=5)