1. changed app design from interface to blocks API based

app.py

@@ -13,51 +13,50 @@ example_list = list(map(lambda el:[el], example_list))
 
 demo = gr.Blocks()
 
-#input_video = gr.Video(label="Input Video", show_label=True)
-#output_label = gr.Label(label="Model Output", show_label=True)
-#output_gif = gr.Image(label="Video Gif", show_label=True)
-#title = "Video Classification with Transformers"
-#description = "This space demonstrates the use of a hybrid (CNN-Transformer based) model for video classification. \n The model can classify videos belonging to the following action categories: CricketShot, Punch, ShavingBeard, TennisSwing, PlayingCello. \n Upload a video and try out 🤗 "
+# input_video = gr.Video(label="Input Video", show_label=True)
+# output_label = gr.Label(label="Model Output", show_label=True)
+# output_gif = gr.Image(label="Video Gif", show_label=True)
+# title = "Video Classification with Transformers"
+# description = "This space demonstrates the use of a hybrid (CNN-Transformer based) model for video classification. \n The model can classify videos belonging to the following action categories: CricketShot, Punch, ShavingBeard, TennisSwing, PlayingCello. \n Upload a video and try out 🤗 "
 
-#article = '\n Demo created by: <a href=\"https://www.linkedin.com/in/shivalika-singh/\">Shivalika Singh</a> <br> Based on this <a href=\"https://keras.io/examples/vision/video_transformers/\">Keras example</a> by <a href=\"https://twitter.com/RisingSayak\">Sayak Paul</a> <br> Demo Powered by this <a href=\"https://huggingface.co/shivi/video-transformers/\"> Video Classification</a> model'
+# article = '\n Demo created by: <a href=\"https://www.linkedin.com/in/shivalika-singh/\">Shivalika Singh</a> <br> Based on this <a href=\"https://keras.io/examples/vision/video_transformers/\">Keras example</a> by <a href=\"https://twitter.com/RisingSayak\">Sayak Paul</a> <br> Demo Powered by this <a href=\"https://huggingface.co/shivi/video-transformers/\"> Video Classification</a> model'
 
-#gr.Interface(predict_action, input_video, [output_label, output_gif], examples=example_list, allow_flagging=False, analytics_enabled=False,
-#  title=title, description=description, cache_examples=True, article=article).launch(enable_queue=True,share=True)
+# gr.Interface(predict_action, input_video, [output_label, output_gif], examples=example_list, allow_flagging=False, analytics_enabled=False,
+#   title=title, description=description, cache_examples=True, article=article).launch(enable_queue=True,share=True)
 
 
 with demo:
     
-     gr.Markdown("# **<p align='center'>Video Classification with Transformers</p>**")
-     gr.Markdown("This space demonstrates the use of hybrid Transformer-based models for video classification that operate on CNN feature maps.")
+    gr.Markdown("# **<p align='center'>Video Classification with Transformers</p>**")
+    gr.Markdown("This space demonstrates the use of hybrid Transformer-based models for video classification that operate on CNN feature maps.")
     
-     with gr.Tabs():
+    with gr.Tabs():
                 
-         with gr.TabItem("Upload & Predict"):
-             with gr.Box():
+        with gr.TabItem("Upload & Predict"):
+            with gr.Box():
                 
-                 with gr.Row():
-                     input_video = gr.Video(label="Input Video", show_label=True)
-                     output_label = gr.Label(label="Model Output", show_label=True)
-                     output_gif = gr.Image(label="Video Gif", show_label=True)
+                with gr.Row():
+                    input_video = gr.Video(label="Input Video", show_label=True)
+                    output_label = gr.Label(label="Model Output", show_label=True)
+                    output_gif = gr.Image(label="Video Gif", show_label=True)
             
-             gr.Markdown("**Predict**")
+            gr.Markdown("**Predict**")
             
-             with gr.Box():
-                 with gr.Row():
-                     submit_button = gr.Button("Submit")
+            with gr.Box():
+                with gr.Row():
+                    submit_button = gr.Button("Submit")
             
-             gr.Markdown("**Examples:**")
-             gr.Markdown("The model is trained to classify videos belonging to the following classes:")
-             gr.Markdown("CricketShot, PlayingCello, Punch, ShavingBeard, TennisSwing")
-
-             with gr.Column():
-                  gr.Examples(example_list, [input_video], [output_label,output_gif], predict_action, cache_examples=True)
-                 #examples = gr.components.Dataset(components=[input_video], samples=example_list, type='values')
-                 #examples.click(load_example, examples, input_video)
+            gr.Markdown("**Examples:**")
+            gr.Markdown("The model is trained to classify videos belonging to the following classes:")
+            gr.Markdown("CricketShot, PlayingCello, Punch, ShavingBeard, TennisSwing")
+
+            with gr.Column():
+                gr.Examples(example_list, [input_video], [output_label,output_gif], predict_action, cache_examples=True)
+                # examples = gr.components.Dataset(components=[input_video], samples=example_list, type='values')
+                # examples.click(load_example, examples, input_video)
         
-     submit_button.click(predict_action, inputs=input_video, outputs=[output_label,output_gif])
+    submit_button.click(predict_action, inputs=input_video, outputs=[output_label,output_gif])
     
-     gr.Markdown('\n Author: <a href=\"https://www.linkedin.com/in/shivalika-singh/\">Shivalika Singh</a> <br> Based on this <a href=\"https://keras.io/examples/vision/video_transformers/\">Keras example</a> by <a href=\"https://twitter.com/RisingSayak\">Sayak Paul</a> <br> Demo Powered by this <a href=\"https://huggingface.co/shivi/video-transformers/\"> Video Classification</a> model')
+    gr.Markdown('\n Author: <a href=\"https://www.linkedin.com/in/shivalika-singh/\">Shivalika Singh</a> <br> Based on this <a href=\"https://keras.io/examples/vision/video_transformers/\">Keras example</a> by <a href=\"https://twitter.com/RisingSayak\">Sayak Paul</a> <br> Demo Powered by this <a href=\"https://huggingface.co/shivi/video-transformers/\"> Video Classification</a> model')
     
- demo.launch()
-
+demo.launch()