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# Riffusion
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2022-11-25 14:20:30 -07:00
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2022-11-25 17:32:38 -07:00
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Python backend for the Riffusion app that does the model inference and audio processing.
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2022-11-25 17:30:11 -07:00
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* a diffusers pipeline that performs prompt interpolation combined with image conditioning
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* a module for (approximately) converting between spectrograms and waveforms
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* a flask server to provide model inference via API to the next.js app
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2022-12-12 19:55:40 -07:00
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2022-11-25 17:48:10 -07:00
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The web app lives at https://github.com/hmartiro/riffusion-app
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For details read https://www.riffusion.com/about
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2022-11-25 17:30:11 -07:00
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## Install
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Tested with Python 3.9 and diffusers 0.9.0
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```
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conda create --name riffusion-inference python=3.9
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conda activate riffusion-inference
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python -m pip install -r requirements.txt
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```
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## Run
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Start the Flask server:
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```
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python -m riffusion.server --port 3013 --host 127.0.0.1 --checkpoint /path/to/diffusers_checkpoint
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```
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The model endpoint is now available at `http://127.0.0.1:3013/run_inference` via POST request.
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Example input (see [InferenceInput](https://github.com/hmartiro/riffusion-inference/blob/main/riffusion/datatypes.py#L28) for the API):
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```
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{
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alpha: 0.75,
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num_inference_steps: 50,
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seed_image_id: "og_beat",
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start: {
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prompt: "church bells on sunday",
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seed: 42,
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denoising: 0.75,
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guidance: 7.0,
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},
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end: {
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prompt: "jazz with piano",
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seed: 123,
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denoising: 0.75,
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guidance: 7.0,
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},
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}
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```
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Example output (see [InferenceOutput](https://github.com/hmartiro/riffusion-inference/blob/main/riffusion/datatypes.py#L54) for the API):
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```
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{
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image: "< base64 encoded JPEG image >",
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audio: "< base64 encoded MP3 clip >",,
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}
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```
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