# Nendo Plugin Classify Core
<br>
<p align="left">
<img src="https://okio.ai/docs/assets/nendo_core_logo.png" width="350" alt="nendo core">
</p>
<br>
---
[](https://twitter.com/okio_ai) [](https://discord.gg/XpkUsjwXTp)
Automatic music information retrieval (based on [essentia](https://essentia.upf.edu/)).
## Features
- Extract musical features from a `NendoTrack` or a `NendoCollection`
- Use descriptive features to filter, search and sort your library
- Extract rich features to annotate datasets for training custom models
## Installation
1. [Install nendo](https://github.com/okio-ai/nendo#installation)
2. `pip install nendo-plugin-classify-core`
## Usage
Take a look at a basic usage example below.
For more detailed information, please refer to the [documentation](https://okio.ai/docs/classify-core/advanced).
For more advanced examples, check out the examples folder.
or try it in colab:
<a target="_blank" href="https://colab.research.google.com/drive/1mmbjf0NfsF596p2zDWBDryuxvFYMGAzO?usp=sharing">
<img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/>
</a>
```python
from nendo import Nendo, NendoConfig
nd = Nendo(config=NendoConfig(plugins=["nendo_plugin_classify_core"]))
track = nd.library.add_track(file_path='/path/to/track.mp3')
track = nd.plugins.classify_core(track=track)
data = track.get_plugin_data(plugin_name="nendo_plugin_classify_core")
print(data)
tracks_with_filtered_tempo = nd.library.filter_tracks(
filters={"tempo": (170, 180)},
plugin_names=["nendo_plugin_classify_core"],
)
assert len(tracks_with_filtered_tempo) == 1
```
## Contributing
Visit our docs to learn all about how to contribute to Nendo: [Contributing](https://okio.ai/docs/contributing/)
## License
Nendo: MIT License
Essentia: Affero GPLv3 license
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"description": "# Nendo Plugin Classify Core\n\n<br>\n<p align=\"left\">\n <img src=\"https://okio.ai/docs/assets/nendo_core_logo.png\" width=\"350\" alt=\"nendo core\">\n</p>\n<br>\n\n---\n\n\n[](https://twitter.com/okio_ai) [](https://discord.gg/XpkUsjwXTp)\n\nAutomatic music information retrieval (based on [essentia](https://essentia.upf.edu/)).\n\n## Features\n\n- Extract musical features from a `NendoTrack` or a `NendoCollection`\n- Use descriptive features to filter, search and sort your library\n- Extract rich features to annotate datasets for training custom models\n\n## Installation\n\n1. [Install nendo](https://github.com/okio-ai/nendo#installation)\n2. `pip install nendo-plugin-classify-core`\n\n## Usage\n\nTake a look at a basic usage example below.\nFor more detailed information, please refer to the [documentation](https://okio.ai/docs/classify-core/advanced).\n\nFor more advanced examples, check out the examples folder.\nor try it in colab:\n\n<a target=\"_blank\" href=\"https://colab.research.google.com/drive/1mmbjf0NfsF596p2zDWBDryuxvFYMGAzO?usp=sharing\">\n <img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/>\n</a>\n\n\n```python\nfrom nendo import Nendo, NendoConfig\n\nnd = Nendo(config=NendoConfig(plugins=[\"nendo_plugin_classify_core\"]))\n\ntrack = nd.library.add_track(file_path='/path/to/track.mp3')\n\ntrack = nd.plugins.classify_core(track=track)\n\ndata = track.get_plugin_data(plugin_name=\"nendo_plugin_classify_core\")\nprint(data)\n\ntracks_with_filtered_tempo = nd.library.filter_tracks(\n filters={\"tempo\": (170, 180)},\n plugin_names=[\"nendo_plugin_classify_core\"],\n)\n\nassert len(tracks_with_filtered_tempo) == 1\n```\n\n## Contributing\n\nVisit our docs to learn all about how to contribute to Nendo: [Contributing](https://okio.ai/docs/contributing/)\n\n## License\n\nNendo: MIT License\n\nEssentia: Affero GPLv3 license",
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