Learn Generative Adversarial Network (GAN) to generate music.
Some parts can be in Czech, because it was semestral work at Faculty of information technology at Czech technical university in Prague
clone this repository:
git clone git@github.com:Hanyman8/Music_keras.git
make a virtual environment and install requirements
python -m pip install -r requirements.txt
in main directory create directories results, static, static/classical_midi_piano
Download data clean = clean_midi, aligned = lmd_aligned a LMD-matched metadata lmd_matched_h5 from website
https://colinraffel.com/projects/lmd/
and extract them in the folder static
Data source: Colin Raffel. "Learning-Based Methods for Comparing Sequences, with Applications to Audio-to-MIDI Alignment and Matching". PhD Thesis, 2016.
open jupyter notebook data_datapreparation.ipynb and run it
Then run ntoebook music_gan.ipynb
everythink should work
Results of generated midi files can be found in the file results
Final model cal be saved (showed at the end of the notebook)
https://towardsdatascience.com/generating-pokemon-inspired-music-from-neural-networks-bc240014132 https://github.com/corynguyen19/midi-lstm-gan https://colinraffel.com/projects/lmd/ https://towardsdatascience.com/how-to-generate-music-using-a-lstm-neural-network-in-keras-68786834d4c5