crema
convolutional and recurrent estimators for music analysis
Usage options
From the command-line, print to the screen in 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:
from crema.analyze import analyze
jam = analyze(filename='/path/to/file.mp3')
or if you have an audio buffer in memory, librosa-style:
jam = analyze(y=y, sr=sr)
1 maintainer
Metadata
1 maintainer
Release files for crema 0.2.0
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| crema-0.2.0.tar.gz | 5.9 MB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| crema-0.2.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 11.8 MB
Release files / crema-0.2.0.tar.gz
| Download URL | crema-0.2.0.tar.gz |
|---|---|
| Size | 5.9 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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No |
| Uploaded via |
twine/4.0.0 CPython/3.9.12
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Release files / crema-0.2.0-py3-none-any.whl
| Download URL | crema-0.2.0-py3-none-any.whl |
|---|---|
| Size | 5.9 MB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.0 CPython/3.9.12
|
Security for crema 0.2.0
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