Adapt UI

gradio_server.py

@@ -5,6 +5,7 @@ from loguru import logger
 from datetime import datetime
 import gradio as gr
 import random
+import spaces
 
 from hyvideo.utils.file_utils import save_videos_grid
 from hyvideo.config import parse_args
@@ -20,6 +21,7 @@ def initialize_model(model_path):
     hunyuan_video_sampler = HunyuanVideoSampler.from_pretrained(models_root_path, args=args)
     return hunyuan_video_sampler
 
+@spaces.GPU(duration=120)
 def generate_video(
     model,
     prompt,
@@ -89,7 +91,7 @@ def create_demo(model_path, save_path):
                             ("624x832 (3:4, 540p)", "624x832"),
                             ("720x720 (1:1, 540p)", "720x720"),
                         ],
-                        value="1280x720",
+                        value="832x624",
                         label="Resolution"
                     )
                     video_length = gr.Dropdown(
@@ -98,9 +100,9 @@ def create_demo(model_path, save_path):
                             ("2s(65f)", 65),
                             ("5s(129f)", 129),
                         ],
-                        value=129,
+                        value=65,
                     )
-                num_inference_steps = gr.Slider(1, 100, value=50, step=1, label="Number of Inference Steps")
+                num_inference_steps = gr.Slider(1, 100, value=5, step=1, label="Number of Inference Steps")
                 show_advanced = gr.Checkbox(label="Show Advanced Options", value=False)
                 with gr.Row(visible=False) as advanced_row:
                     with gr.Column():
@@ -109,10 +111,10 @@ def create_demo(model_path, save_path):
                         flow_shift = gr.Slider(0.0, 10.0, value=7.0, step=0.1, label="Flow Shift") 
                         embedded_guidance_scale = gr.Slider(1.0, 20.0, value=6.0, step=0.5, label="Embedded Guidance Scale")
                 show_advanced.change(fn=lambda x: gr.Row(visible=x), inputs=[show_advanced], outputs=[advanced_row])
-                generate_btn = gr.Button("Generate")
+                generate_btn = gr.Button(value = "🚀 Generate Video", variant = "primary")
             
             with gr.Column():
-                output = gr.Video(label="Generated Video")
+                output = gr.Video(label = "Generated Video", autoplay = True)
         
         generate_btn.click(
             fn=lambda *inputs: generate_video(model, *inputs),
@@ -133,9 +135,5 @@ def create_demo(model_path, save_path):
 
 if __name__ == "__main__":
     os.environ["GRADIO_ANALYTICS_ENABLED"] = "False"
-    server_name = os.getenv("SERVER_NAME", "0.0.0.0")
-    server_port = int(os.getenv("SERVER_PORT", "8081"))
-    args = parse_args()
-    print(args)
     demo = create_demo(args.model_base, args.save_path)
-    demo.launch(server_name=server_name, server_port=server_port)
+    demo.queue(10).launch()