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import streamlit as st |
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import numpy as np |
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import pretty_midi |
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from accompaniment_generator.generator.base import Generator |
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import os |
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import uuid |
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import time |
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from midi2audio import FluidSynth |
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from scipy.io import wavfile |
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ABOUT_TEXT = "🤗 Accompaniment Generator - generate accompaniment part with chord using Evolutionary algorithm." |
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CONTACT_TEXT = """ |
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_Built by Aleksey Korshuk with love_ ❤️ |
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[](https://github.com/AlekseyKorshuk) |
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[](https://twitter.com/intent/follow?screen_name=alekseykorshuk) |
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Star project repository: |
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[](https://github.com/AlekseyKorshuk/accompaniment-generator) |
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""" |
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st.sidebar.markdown( |
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""" |
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<style> |
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.aligncenter { |
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text-align: center; |
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} |
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</style> |
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<p class="aligncenter"> |
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<img src="https://seeklogo.com/images/A/apple-music-logo-4FBA5FADCC-seeklogo.com.png" width="220" /> |
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</p> |
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""", |
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unsafe_allow_html=True, |
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) |
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st.sidebar.markdown(ABOUT_TEXT) |
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st.sidebar.markdown(CONTACT_TEXT) |
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def inference(audio, num_epoch, tonic_name, chord_duration): |
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generator = Generator() |
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if chord_duration == 0.0: |
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chord_duration = None |
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output_midi_data = generator(audio, num_epoch=int(num_epoch), tonic=tonic_name, chord_duration=chord_duration)[0] |
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name = uuid.uuid4() |
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output_midi_data.write(f'{name}.mid') |
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fs = FluidSynth("font.sf2") |
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fs.midi_to_audio(f'{name}.mid', f'{name}.wav') |
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fs.midi_to_audio(audio, f'{name}-init.wav') |
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print([f'{name}-init.wav', f'{name}.wav']) |
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return f'{name}-init.wav', f'{name}.wav' |
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st.title("Accompaniment Generator") |
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st.markdown( |
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"App to generate accompaniment for MIDI music file with Evolutionary algorithm. Check out [project repository](https://github.com/AlekseyKorshuk/accompaniment-generator) and project limitations.") |
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article = "<p style='text-align: center'>" \ |
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"<a href='https://github.com/AlekseyKorshuk/accompaniment-generator' target='_blank'>Github Repo</a>" \ |
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"</p>" |
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from os import listdir |
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from os.path import isfile, join |
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onlyfiles = [f for f in listdir("./examples") if isfile(join("./examples", f))] |
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model_name = st.selectbox( |
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'Select example MIDI file (will be used only for empty file field):', |
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onlyfiles |
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) |
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uploaded_file = st.file_uploader( |
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'Upload MIDI file:' |
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) |
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num_epoch = st.number_input("Number of epochs:", |
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min_value=1, |
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max_value=1000, |
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step=1, |
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value=1, |
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) |
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chord_duration = st.number_input("Custom chord duration is seconds (leave zero for auto-calculation):", |
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min_value=0.0, |
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max_value=1000.0, |
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step=0.0001, |
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value=0.0, |
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format="%.4f" |
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) |
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tonic_name = st.selectbox( |
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'Select tonic:', |
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["minor", "major"] |
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) |
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generate_image_button = st.button("Generate") |
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if generate_image_button: |
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input_file = f"./examples/{model_name}" |
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if uploaded_file is not None: |
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input_file = uploaded_file.name |
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with open(input_file, 'wb') as f: |
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f.write(uploaded_file.getvalue()) |
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with st.spinner(text=f"Generating, this may take some time..."): |
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before, after = inference(input_file, num_epoch, tonic_name, chord_duration) |
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st.markdown("Before:") |
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st.audio(before) |
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st.markdown("After:") |
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st.audio(after) |
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if uploaded_file is not None: |
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os.remove(input_file) |
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