nendo-plugin-classify-core


Namenendo-plugin-classify-core JSON
Version 0.2.11 PyPI version JSON
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home_pagehttps://okio.ai
SummaryNendo plugin for automatic music information retrieval.
upload_time2024-03-07 20:22:38
maintainer
docs_urlNone
authorFelix Lorenz
requires_python>=3.8,<3.11
licenseMIT
keywords nendo plugin audio generative music audio production audio analysis
VCS
bugtrack_url
requirements No requirements were recorded.
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coveralls test coverage No coveralls.
            # 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>

<p align="left">
<a href="https://okio.ai" target="_blank">
    <img src="https://img.shields.io/website/https/okio.ai" alt="Website">
</a>
<a href="https://twitter.com/okio_ai" target="_blank">
    <img src="https://img.shields.io/twitter/url/https/twitter.com/okio_ai.svg?style=social&label=Follow%20%40okio_ai" alt="Twitter">
</a>
<a href="https://discord.gg/gaZMZKzScj" target="_blank">
    <img src="https://dcbadge.vercel.app/api/server/XpkUsjwXTp?compact=true&style=flat" alt="Discord">
</a>
</p>

---

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`

    > **Note**: Installing this plugin together with another nendo plugin that uses `essentia`, you are likely to run into the runtime error `Error: module 'essentia.standard' has no attribute 'TensorflowPredictEffnetDiscogs'`. See the corresponding entry in the [troubleshooting guide](#essentia-cant-find-the-embedding-model) below for instructions on how to fix this issue.

## 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
```

## Troubleshooting

### Essentia can't find the embedding model

When I try to run the plugin, I get the following error:

```bash
Failed to import plugin 'nendo_plugin_classify_core'. Error: module 'essentia.standard' has no attribute 'TensorflowPredictEffnetDiscogs'
```

This is due to the fact that you have `essentia` and `essentia-tensorflow` installed at the same time, possibly because you installed another nendo plugin that uses `essentia`, like e.g. [nendo_plugin_quantize_core](https://github.com/okio-ai/nendo_plugin_quantize_core/). The fix in this case is to reinstall essentia, this time only installing the `essentia-tensorflow` package:

```bash
pip uninstall -y essentia essentia-tensorflow
pip install essentia-tensorflow
```

## 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<p align=\"left\">\n<a href=\"https://okio.ai\" target=\"_blank\">\n    <img src=\"https://img.shields.io/website/https/okio.ai\" alt=\"Website\">\n</a>\n<a href=\"https://twitter.com/okio_ai\" target=\"_blank\">\n    <img src=\"https://img.shields.io/twitter/url/https/twitter.com/okio_ai.svg?style=social&label=Follow%20%40okio_ai\" alt=\"Twitter\">\n</a>\n<a href=\"https://discord.gg/gaZMZKzScj\" target=\"_blank\">\n    <img src=\"https://dcbadge.vercel.app/api/server/XpkUsjwXTp?compact=true&style=flat\" alt=\"Discord\">\n</a>\n</p>\n\n---\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    > **Note**: Installing this plugin together with another nendo plugin that uses `essentia`, you are likely to run into the runtime error `Error: module 'essentia.standard' has no attribute 'TensorflowPredictEffnetDiscogs'`. See the corresponding entry in the [troubleshooting guide](#essentia-cant-find-the-embedding-model) below for instructions on how to fix this issue.\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## Troubleshooting\n\n### Essentia can't find the embedding model\n\nWhen I try to run the plugin, I get the following error:\n\n```bash\nFailed to import plugin 'nendo_plugin_classify_core'. Error: module 'essentia.standard' has no attribute 'TensorflowPredictEffnetDiscogs'\n```\n\nThis is due to the fact that you have `essentia` and `essentia-tensorflow` installed at the same time, possibly because you installed another nendo plugin that uses `essentia`, like e.g. [nendo_plugin_quantize_core](https://github.com/okio-ai/nendo_plugin_quantize_core/). The fix in this case is to reinstall essentia, this time only installing the `essentia-tensorflow` package:\n\n```bash\npip uninstall -y essentia essentia-tensorflow\npip install essentia-tensorflow\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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