Upload app.py

app.py

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+import spaces
+import logging
+from datetime import datetime
+from pathlib import Path
+
+import gradio as gr
+import torch
+import torchaudio
+import os
+
+import tempfile
+
+log = logging.getLogger()
+
+
+#@spaces.GPU(duration=120)
+@torch.inference_mode()
+def video_to_audio(video: gr.Video, prompt: str, negative_prompt: str, seed: int, num_steps: int,
+                   cfg_strength: float, duration: float):
+
+    os.system("bash v2a.sh")
+    
+    return "v2a"
+
+
+video_to_audio_tab = gr.Interface(
+    fn=video_to_audio,
+    description="""
+    Project page: <a href="https://hkchengrex.com/MMAudio/">https://hkchengrex.com/MMAudio/</a><br>
+    Code: <a href="https://github.com/hkchengrex/MMAudio">https://github.com/hkchengrex/MMAudio</a><br>
+    NOTE: It takes longer to process high-resolution videos (>384 px on the shorter side). 
+    Doing so does not improve results.
+    The model has been trained on 8-second videos. Using much longer or shorter videos will degrade performance. Around 5s~12s should be fine.
+    """,
+    inputs=[
+        gr.Video(),
+        gr.Text(label='Prompt'),
+        gr.Text(label='Negative prompt', value='music'),
+        gr.Number(label='Seed (-1: random)', value=-1, precision=0, minimum=-1),
+        gr.Number(label='Num steps', value=25, precision=0, minimum=1),
+        gr.Number(label='Guidance Strength', value=4.5, minimum=1),
+        gr.Number(label='Duration (sec)', value=8, minimum=1),
+    ],
+    outputs='playable_video',
+    cache_examples=False,
+    title='MMAudio — Video-to-Audio Synthesis',
+    examples=[
+        [
+            'https://huggingface.co/hkchengrex/MMAudio/resolve/main/examples/sora_beach.mp4',
+            'waves, seagulls',
+            '',
+            0,
+            25,
+            4.5,
+            10,
+        ],
+    ])
+
+
+if __name__ == "__main__":
+    gr.TabbedInterface([video_to_audio_tab],
+                       ['Video-to-Audio']).launch()
+