Metadata-Version: 2.1
Name: omnizart
Version: 0.3.0
Summary: Omniscient Mozart, being able to transcribe everything in the music.
Home-page: https://sites.google.com/view/mctl/home
License: MIT
Keywords: automatic music transcription,drum transcription,vocal transcription,beat tracking
Author: BreezeWhite
Author-email: freedombluewater@gmail.com
Requires-Python: >=3.6.1,<3.9
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Topic :: Documentation :: Sphinx
Classifier: Topic :: Multimedia :: Sound/Audio :: MIDI
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Software Development :: Version Control :: Git
Requires-Dist: click (>=7.1.2,<8.0.0)
Requires-Dist: jsonschema (>=3.2.0,<4.0.0)
Requires-Dist: librosa (>=0.8.0,<0.9.0)
Requires-Dist: madmom (>=0.16.1,<0.17.0)
Requires-Dist: mir_eval (>=0.6,<0.7)
Requires-Dist: numba (==0.48)
Requires-Dist: opencv-python (>=4.4.0,<5.0.0)
Requires-Dist: pretty_midi (>=0.2.9,<0.3.0)
Requires-Dist: pyfluidsynth (>=1.2.5,<2.0.0)
Requires-Dist: pyyaml (>=5.3.1,<6.0.0)
Requires-Dist: spleeter (>=2.0.1,<3.0.0)
Requires-Dist: tensorflow (>=2.3.0,<3.0.0)
Requires-Dist: tqdm (>=4.49.0,<5.0.0)
Requires-Dist: urllib3 (>=1.25.11,<2.0.0)
Requires-Dist: vamp (>=1.1.0,<2.0.0)
Project-URL: Documentation, https://music-and-culture-technology-lab.github.io/omnizart-doc/
Project-URL: Repository, https://github.com/Music-and-Culture-Technology-Lab/omnizart
Description-Content-Type: text/markdown

# OMNIZART

[![build](https://github.com/Music-and-Culture-Technology-Lab/omnizart/workflows/general-check/badge.svg)](https://github.com/Music-and-Culture-Technology-Lab/omnizart/actions?query=workflow%3Ageneral-check)
[![docs](https://github.com/Music-and-Culture-Technology-Lab/omnizart/workflows/docs/badge.svg?branch=build_doc)](https://music-and-culture-technology-lab.github.io/omnizart-doc/)
[![PyPI version](https://badge.fury.io/py/omnizart.svg)](https://badge.fury.io/py/omnizart)
![PyPI - License](https://img.shields.io/pypi/l/omnizart)
[![PyPI - Downloads](https://img.shields.io/pypi/dm/omnizart)](https://pypistats.org/packages/omnizart)
[![Docker Pulls](https://img.shields.io/docker/pulls/mctlab/omnizart)](https://hub.docker.com/r/mctlab/omnizart)

Omnizart is a Python library that aims for democratizing automatic music transcription.
Given polyphonic music, it is able to transcribe pitched instruments, vocal melody, chords, drum events, and beat.
This is powered by the research outcomes from [Music and Culture Technology (MCT) Lab](https://sites.google.com/view/mctl/home).

### Transcribe your favorite songs now in Colab! [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://bit.ly/OmnizartColab)

# Quick start

Visit the [complete document](https://music-and-culture-technology-lab.github.io/omnizart-doc/) for detailed guidance.

## Pip
``` bash
# Install omnizart
pip install omnizart

# Download the checkpoints
omnizart download-checkpoints

# Transcribe your songs
omnizart drum transcribe <path/to/audio.wav>
omnizart chord transcribe <path/to/audio.wav>
omnizart music transcribe <path/to/audio.wav>
```

## Docker
```
docker pull mctlab/omnizart:latest
docker run -it mctlab/omnizart:latest bash
```

# Supported applications
| Application      | Transcription      | Training           | Evaluation | Description                                      |
|------------------|--------------------|--------------------|------------|--------------------------------------------------|
| music            | :heavy_check_mark: | :heavy_check_mark: |            | Transcribe musical notes of pitched instruments. |
| drum             | :heavy_check_mark: | :interrobang:      |            | Transcribe events of percussive instruments.     |
| vocal            | :heavy_check_mark: | :heavy_check_mark: |            | Transcribe note-level vocal melody.              |
| vocal-contour    | :heavy_check_mark: | :heavy_check_mark: |            | Transcribe frame-level vocal melody (F0).        |
| chord            | :heavy_check_mark: | :heavy_check_mark: |            | Transcribe chord progressions.                   |
| beat             | :heavy_check_mark: | :heavy_check_mark: |            | Transcribe beat position.                        |

**NOTES**
The current implementation for the drum model has unknown bugs, preventing loss convergence when training from scratch.
Fortunately, you can still enjoy drum transcription with the provided checkpoints.


