https://github.com/bmcfee/crema
convolutional and recurrent estimators for music analysis
https://github.com/bmcfee/crema
Last synced: about 1 year ago
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convolutional and recurrent estimators for music analysis
- Host: GitHub
- URL: https://github.com/bmcfee/crema
- Owner: bmcfee
- License: bsd-2-clause
- Created: 2017-04-25T15:52:28.000Z (about 9 years ago)
- Default Branch: main
- Last Pushed: 2024-05-05T20:54:42.000Z (about 2 years ago)
- Last Synced: 2025-05-07T04:06:40.235Z (about 1 year ago)
- Language: Python
- Size: 68.7 MB
- Stars: 90
- Watchers: 3
- Forks: 23
- Open Issues: 5
-
Metadata Files:
- Readme: README.md
- License: LICENSE.md
Awesome Lists containing this project
README
# crema
convolutional and recurrent estimators for music analysis
[](https://github.com/bmcfee/crema/actions/workflows/ci.yml)
[](https://codecov.io/gh/bmcfee/crema)
[](https://raw.githubusercontent.com/bmcfee/crema/master/LICENSE)
[](http://crema.readthedocs.io/en/latest/?badge=latest)
[](https://doi.org/10.5281/zenodo.1010486)
Usage options
-------------
From the command-line, print to the screen in [JAMS](https://github.com/marl/jams) format:
```
python -m crema.analyze file.mp3
```
or save to a file:
```
python -m crema.analyze file.mp3 -o file.jams
```
From within python:
```python
from crema.analyze import analyze
jam = analyze(filename='/path/to/file.mp3')
```
or if you have an audio buffer in memory, librosa-style:
```python
jam = analyze(y=y, sr=sr)
```