Spaces:
Runtime error
Runtime error
| import argparse | |
| import gradio as gr | |
| from audiodiffusion import AudioDiffusion | |
| def generate_spectrogram_audio_and_loop(model_id): | |
| audio_diffusion = AudioDiffusion(model_id=model_id) | |
| image, (sample_rate, | |
| audio) = audio_diffusion.generate_spectrogram_and_audio() | |
| loop = AudioDiffusion.loop_it(audio, sample_rate) | |
| if loop is None: | |
| loop = audio | |
| return image, (sample_rate, audio), (sample_rate, loop) | |
| demo = gr.Interface( | |
| fn=generate_spectrogram_audio_and_loop, | |
| title="Audio Diffusion", | |
| description="Generate audio using Huggingface diffusers.\ | |
| The models without 'latent' or 'ddim' give better results but take about \ | |
| 20 minutes without a GPU. For GPU, you can use \ | |
| [colab](https://colab.research.google.com/github/teticio/audio-diffusion/blob/master/notebooks/gradio_app.ipynb) \ | |
| to run this app.", | |
| inputs=[ | |
| gr.Dropdown(label="Model", | |
| choices=[ | |
| "teticio/audio-diffusion-256", | |
| "teticio/ZUN-diffusion-256", | |
| "teticio/audio-diffusion-breaks-256", | |
| "teticio/audio-diffusion-instrumental-hiphop-256", | |
| "teticio/audio-diffusion-ddim-256", | |
| "teticio/latent-audio-diffusion-256", | |
| "teticio/latent-audio-diffusion-ddim-256" | |
| ], | |
| value="teticio/latent-audio-diffusion-ddim-256") | |
| ], | |
| outputs=[ | |
| gr.Image(label="Mel spectrogram", image_mode="L"), | |
| gr.Audio(label="Audio"), | |
| gr.Audio(label="Loop"), | |
| ], | |
| allow_flagging="never") | |
| if __name__ == "__main__": | |
| parser = argparse.ArgumentParser() | |
| parser.add_argument("--port", type=int) | |
| parser.add_argument("--server", type=int) | |
| args = parser.parse_args() | |
| demo.launch(server_name=args.server or "0.0.0.0", server_port=args.port) | |