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.\ This takes about 20 minutes without a GPU, so why not make yourself a \ cup of tea in the meantime?", inputs=[ gr.Dropdown(label="Model", choices=[ "teticio/audio-diffusion-256", "teticio/audio-diffusion-breaks-256", "teticio/audio-diffusion-instrumental-hiphop-256" ], value="teticio/audio-diffusion-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)