thay thế gr.Box() bằng gr.Row() và gr.Column()

app.py

@@ -20,7 +20,6 @@ from transforms import (
 import gradio as gr
 from huggingface_hub import hf_hub_download
 
-
 # Device on which to run the model
 # Set to cuda to load on GPU
 device = "cpu"
@@ -47,9 +46,7 @@ for k, v in imagenet_classnames.items():
 def get_index(num_frames, num_segments=8):
     seg_size = float(num_frames - 1) / num_segments
     start = int(seg_size / 2)
-    offsets = np.array([
-        start + int(np.round(seg_size * idx)) for idx in range(num_segments)
-    ])
+    offsets = np.array([start + int(np.round(seg_size * idx)) for idx in range(num_segments)])
     return offsets
 
 
@@ -134,28 +131,26 @@ with demo:
     )
 
     with gr.Tab("Video"):
-        with gr.Box():
-            with gr.Row():
-                with gr.Column():
-                    with gr.Row():
-                        input_video = gr.Video(label='Input Video').style(height=360)
-                    with gr.Row():
-                        submit_video_button = gr.Button('Submit')
-                with gr.Column():
-                        label_video = gr.Label(num_top_classes=5)
+        with gr.Row():  # Replace gr.Box() with gr.Row()
+            with gr.Column():  # Inside a column layout
+                with gr.Row():  # For individual row layout within a column
+                    input_video = gr.Video(label='Input Video').style(height=360)
+                with gr.Row():
+                    submit_video_button = gr.Button('Submit')
+            with gr.Column():
+                    label_video = gr.Label(num_top_classes=5)
             with gr.Row():
                 example_videos = gr.Dataset(components=[input_video], samples=[['./videos/hitting_baseball.mp4'], ['./videos/hoverboarding.mp4'], ['./videos/yoga.mp4']])
         
     with gr.Tab("Image"):
-        with gr.Box():
-            with gr.Row():
-                with gr.Column():
-                    with gr.Row():
-                        input_image = gr.Image(label='Input Image', type='pil').style(height=360)
-                    with gr.Row():
-                        submit_image_button = gr.Button('Submit')
-                with gr.Column():
-                    label_image = gr.Label(num_top_classes=5)
+        with gr.Row():  # Replace gr.Box() with gr.Row()
+            with gr.Column():  # Inside a column layout
+                with gr.Row():
+                    input_image = gr.Image(label='Input Image', type='pil').style(height=360)
+                with gr.Row():
+                    submit_image_button = gr.Button('Submit')
+            with gr.Column():
+                label_image = gr.Label(num_top_classes=5)
             with gr.Row():
                 example_images = gr.Dataset(components=[input_image], samples=[['./images/cat.png'], ['./images/dog.png'], ['./images/panda.png']])
 
@@ -170,4 +165,4 @@ with demo:
     submit_image_button.click(fn=inference_image, inputs=input_image, outputs=label_image)
     example_images.click(fn=set_example_image, inputs=example_images, outputs=example_images.components)
 
-demo.launch(enable_queue=True)
+demo.launch(enable_queue=True)