/DrumTranscriber

Primary LanguagePython

Drum Transcriber - Transcribe Drum Audio Clips

This package helps users transcribes drum audio hits into 6 classes - Hihat, Crash, Kick Drum, Snare, Ride, and Toms.

demo

Dependencies

Run the following to install the python dependencies:

pip install librosa tensorflow numpy pandas scikit-learn streamlit streamlit-player

Usage

Basic Usage

from DrumTranscriber import DrumTranscriber
import librosa

samples, sr = librosa.load(PATH/TO/AUDIO/CLIP)

transcriber = DrumTranscriber()

# pandas dataframe containing probabilities of classes
predictions = transcriber.predict(samples, sr)

For Streamlit

cd to the parent directory and run the following command:

streamlit run frontend.py

A localhost website will appear with the demo app.

Getting Started

  1. Clone/Zip the directory
  2. Redownload the model .h5 file from /model/drum_transcriber.h5 (https://drive.google.com/file/d/1w2fIHeyr-st3sbk1PYrtGOYW6YAD1fsi/view?usp=sharing)

Note: There is an issue with Github zipping the .h5 model file. To properly get the model to work, I suggest downloading the model file from the Google Drive above and directly to replace the model from the clone/zipped folder.