ChatMusician / app.py
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import gradio as gr
import os
import re
import subprocess
import time
from symusic import Score, Synthesizer, BuiltInSF3, dump_wav
import torchaudio
import torch
import music21
def convert_midi_to_svg(midi_file_path, output_svg_path):
# Load MIDI file
midi_stream = music21.converter.parse(midi_file_path)
# Convert MIDI to MusicXML
musicxml_string = midi_stream.write('musicxml')
# Load MusicXML string
score = music21.converter.parseData(musicxml_string)
# Convert MusicXML to SVG
svg_string = score.write('musicxml.png', fmt='musicxml', subformats=['svg'])
# Write SVG to file
with open(output_svg_path, 'wb') as f:
f.write(svg_string)
return output_svg_path
def parse_abc_notation(text="", conversation_id='1'):
os.makedirs(f"tmp/{conversation_id}", exist_ok=True)
ts = time.time()
abc_pattern = r'(X:\d+\n(?:[^\n]*\n)+)'
abc_notation = re.findall(abc_pattern, text+'\n')
print(f'extract abc block: {abc_notation}')
if abc_notation:
# Convert ABC to midi
s = Score.from_abc(abc_notation[0])
wav_file = f'tmp/{conversation_id}/{ts}.mp3'
audio = Synthesizer().render(s, stereo=True)
torchaudio.save(wav_file, torch.FloatTensor(audio), 44100)
# Convert abc notation to SVG
tmp_midi = f'tmp/{conversation_id}/{ts}.mid'
midi_file = s.dump_midi(tmp_midi)
svg_file = f'tmp/{conversation_id}/{ts}.svg'
convert_midi_to_svg(tmp_midi, svg_file)
return svg_file, wav_file
else:
return None, None
gradio_app = gr.Interface(
parse_abc_notation,
inputs=["text"],
outputs=[gr.Image(label="Processed Image"), gr.Audio(label="Result")],
title="Hot Dog? Or Not?",
)
def greet(name, intensity):
return "Hello, " + name + "!" * int(intensity)
demo = gr.Interface(
fn=greet,
inputs=["text", "slider"],
outputs=["text"],
)
demo.launch()
if __name__ == "__main__":
gradio_app.launch()