update inference

app.py

@@ -129,15 +129,6 @@ if __name__ == "__main__":
     inject_motion_embeddings_combinations = ['down 1280','up 1280','down 640','up 640']
     default_motion_embeddings_combinations = ['down 1280','up 1280']
 
-    examples_train = [
-        'assets/train/car_turn.mp4',
-        'assets/train/pan_up.mp4',
-        'assets/train/run_up.mp4',
-        'assets/train/train_ride.mp4',
-        'assets/train/orbit_shot.mp4',
-        'assets/train/dolly_zoom_out.mp4',
-        'assets/train/santa_dance.mp4',
-    ]
 
     examples_inference = [
         ['results/pan_up/source.mp4', 'A flora garden.', 'camera', 'pan_up/checkpoint'],
@@ -210,59 +201,29 @@ if __name__ == "__main__":
             </a>
         """
         )
-        with gr.Tab("Train"):
-            with gr.Row():
-                with gr.Column():
-                    video_input = gr.Video(label="Upload Video")
-                    train_button = gr.Button("Train")
-                with gr.Column():
-                    checkpoint_output = gr.Textbox(label="Checkpoint Directory")
-            
-            with gr.Accordion("Advanced Settings", open=False):
-                with gr.Row():
-                    motion_embeddings_combinations = gr.Dropdown(label="Motion Embeddings Combinations", choices=inject_motion_embeddings_combinations, multiselect=True,value=default_motion_embeddings_combinations)
-                    unet_dropdown = gr.Dropdown(label="Unet", choices=["videoCrafter2", "zeroscope_v2_576w"], value="videoCrafter2")
-                    checkpointing_steps = gr.Dropdown(label="Checkpointing Steps",choices=[100,50],value=100)
-                    max_train_steps = gr.Slider(label="Max Train Steps", minimum=200,maximum=500,value=200,step=50)
+        
+        with gr.Row():
+            with gr.Column():
+                preview_video = gr.Video(label="Preview Video")
+                text_input = gr.Textbox(label="Input Text")
+                checkpoint_dropdown = gr.Dropdown(label="Select Checkpoint", choices=get_checkpoints('results'))
+                seed = gr.Number(label="Seed", value=0)
+                inference_button = gr.Button("Generate Video")
             
-            # examples
-            gr.Examples(examples=examples_train,inputs=[video_input])
-
-
-            train_button.click(
-                lambda video, mec, u, cs, mts: train_model(video, generate_config_train(mec, u, cs, mts)),
-                inputs=[video_input, motion_embeddings_combinations, unet_dropdown, checkpointing_steps, max_train_steps],
-                outputs=checkpoint_output
-            )
-
-        with gr.Tab("Inference"):
-            with gr.Row():
-                with gr.Column():
-                    preview_video = gr.Video(label="Preview Video")
-                    text_input = gr.Textbox(label="Input Text")
-                    checkpoint_dropdown = gr.Dropdown(label="Select Checkpoint", choices=get_checkpoints('results'))
-                    seed = gr.Number(label="Seed", value=0)
-                    inference_button = gr.Button("Generate Video")
+            with gr.Column():
                 
-                with gr.Column():
-                    
-                    output_video = gr.Video(label="Output Video")
-                    generated_prompt = gr.Textbox(label="Generated Prompt")
-
-            with gr.Accordion("Advanced Settings", open=False):
-                with gr.Row():
-                    inference_steps = gr.Number(label="Inference Steps", value=30)
-                    motion_type = gr.Dropdown(label="Motion Type", choices=["camera", "object"], value="object")
-
-            gr.Examples(examples=examples_inference,inputs=[preview_video,text_input,motion_type,checkpoint_dropdown])
+                output_video = gr.Video(label="Output Video")
+                generated_prompt = gr.Textbox(label="Generated Prompt")
 
+        with gr.Accordion("Advanced Settings", open=False):
+            with gr.Row():
+                inference_steps = gr.Number(label="Inference Steps", value=30)
+                motion_type = gr.Dropdown(label="Motion Type", choices=["camera", "object"], value="object")
 
-            def update_checkpoints(checkpoint_dir):
-                return gr.update(choices=get_checkpoints('results'))
+        gr.Examples(examples=examples_inference,inputs=[preview_video,text_input,motion_type,checkpoint_dropdown])
 
-            checkpoint_dropdown.change(fn=update_preview_video, inputs=checkpoint_dropdown, outputs=preview_video)
-            checkpoint_output.change(update_checkpoints, inputs=checkpoint_output, outputs=checkpoint_dropdown)
-            inference_button.click(inference_model, inputs=[text_input, checkpoint_dropdown,inference_steps,motion_type, seed], outputs=output_video)
-            output_video.change(fn=update_generated_prompt, inputs=[text_input], outputs=generated_prompt)
+        checkpoint_dropdown.change(fn=update_preview_video, inputs=checkpoint_dropdown, outputs=preview_video)
+        inference_button.click(inference_model, inputs=[text_input, checkpoint_dropdown,inference_steps,motion_type, seed], outputs=output_video)
+        output_video.change(fn=update_generated_prompt, inputs=[text_input], outputs=generated_prompt)
 
     demo.launch()