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| import gradio as gr | |
| from musicautobot.utils.setup_musescore import play_wav | |
| from music21.midi.translate import midiFileToStream | |
| from pathlib import Path | |
| from midi2audio import FluidSynth | |
| # from musicautobot.numpy_encode import * | |
| from musicautobot.config import default_config | |
| from musicautobot.music_transformer import * | |
| from musicautobot.utils.midifile import * | |
| # from musicautobot.utils.file_processing import process_all | |
| import pickle | |
| import subprocess | |
| import os | |
| print(os.getcwd()) | |
| # Load the stored data. This is needed to generate the vocab. | |
| print('Loading data to build vocabulary.') | |
| data_dir = Path('.') | |
| data = load_data(data_dir, 'data.pkl') | |
| from huggingface_hub import hf_hub_download | |
| print('Downloading model.') | |
| model_cache_path = hf_hub_download(repo_id="psistolar/musicautobot-fine1", filename="model.pth") | |
| # Default config options | |
| config = default_config() | |
| config['encode_position'] = True | |
| print("Building model.") | |
| # Load our fine-tuned model | |
| learner = music_model_learner( | |
| data, | |
| config=config.copy(), | |
| pretrained_path=model_cache_path | |
| ) | |
| print("Ready to use.") | |
| def process_midi(midi_file): | |
| name = Path(midi_file.name) | |
| # create the model input object | |
| item = MusicItem.from_file(name, data.vocab); | |
| # full is the prediction appended to the input | |
| pred, full = learner.predict(item, n_words=100) | |
| # convert to stream and then MIDI file | |
| stream = full.to_stream() | |
| out = music21.midi.translate.streamToMidiFile(stream) | |
| # save MIDI file | |
| out.open('result.midi', 'wb') | |
| out.write() | |
| out.close() | |
| # use fluidsynth to convert MIDI to WAV so the user can hear the output | |
| sound_font = "/usr/share/sounds/sf2/FluidR3_GM.sf2" | |
| FluidSynth(sound_font).midi_to_audio('result.midi', 'result.wav') | |
| return 'result.wav' | |
| iface = gr.Interface( | |
| fn=process_midi, | |
| inputs="file", | |
| outputs="audio" | |
| ) | |
| iface.launch() |