semvec/pypi-packages huggingface dataset:
nendo-plugin-caption-lpmusiccaps 0.1.2
An audio captioning plugin based on LP-MusicCaps.
License: MIT
Requires Python: >=3.8,<3.11
Keywords: AI,generative,music,okio,nendo,music production,music generation,music information retrieval,audio captioning,MIR,music analysis,song analysis

# Nendo Plugin Caption LP-MusicCaps

<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>

---

An audio captioning plugin based on LP-MusicCaps.

## Features 

- Generate captions for all types of audio
- Caption your audio library and make it searchable by using the other nendo search plugins

## Requirements

This plugin requires the manual installation of the `LP-MusicCaps` repository from git, run:

```bash
git clone https://github.com/seungheondoh/lp-music-caps.git
cd lp-music-caps
pip install -e .
```

For more information, please refer to the [LP-MusicCaps repository](https://github.com/seungheondoh/lp-music-caps.git).

## Installation

1. [Install Nendo](https://github.com/okio-ai/nendo#installation)
2. `pip install nendo-plugin-caption-lpmusiccaps`

## Usage

Take a look at a basic usage example below.
For more detailed information, please refer to the [documentation](https://okio.ai/docs/plugins).

```pycon
>>> from nendo import Nendo
>>> nd = Nendo(plugins=["nendo_plugin_caption_lpmusiccaps"])
>>> track = nd.library.add_track(file_path="path/to/file.mp3")

>>> nd.plugins.caption_lpmusiccaps(track=track)
>>> track.get_plugin_value("caption")
```


## Contributing
Visit our docs to learn all about how to contribute to Nendo: [Contributing](https://okio.ai/docs/contributing/)


## License
Nendo: MIT License

LP-MusicCaps: CC-BY-NC 4.0 license.

Pretrained models: The weights are released under the CC-BY-NC 4.0 license
nendo-plugin-stemify-demucs 0.1.3
Nendo Plugin for Music Source Separation.
License: MIT
Requires Python: >=3.8,<3.11
Keywords: Nendo,AI,Machine Learning,Audio,Generative,Music,Audio Production,Audio Generation,Audio Analysis,Stemification,Souce Separation

# Nendo Plugin Stemify Demucs

<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>

---

Nendo Plugin for Music Source Separation (based on Meta [demucs](https://github.com/facebookresearch/demucs))

## Features

- Extract up to six different audio stems

## Installation

1. [Install Nendo](https://github.com/okio-ai/nendo#installation)
2. `pip install nendo-plugin-stemify-demucs`

## Usage

Take a look at a basic usage example below.
For more detailed information, please refer to the [documentation](https://okio.ai/docs/plugins).

For more advanced examples, check out the examples folder.
or try it in colab:

<a target="_blank" href="https://colab.research.google.com/drive/1rYBw5N0xzDf-NQJC1cQXqRBneBE8q4_z?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_stemify_demucs"]))

# load track
track = nd.library.add_track(file_path='/path/to/track.mp3')

# run stemification to get 6 stems
stems = nd.plugins.stemify_demucs(
    track=track,
    stem_types=["vocals", "drums", "bass", "other", "piano", "guitar"],
    model="htdemucs_6s"
)
vocals, drums = stems[0], stems[1]
drums.play()

# run stemification to get vocals and background
stems = nd.plugins.stemify_demucs(
    track=track,
    stem_types=["vocals", "no_vocals"],
    model="mdx_extra"
)

background = stems[1]
background.play()
```

## Contributing

Visit our docs to learn all about how to contribute to Nendo: [Contributing](https://okio.ai/docs/contributing/)


## License

Nendo: MIT License

Demucs: MIT License
rkale 1.0.3
Rclone wrapper to manage multiple datasets in a project
License: MIT
Requires Python: >=3.7,<4.0

# rkale

## Install

Install rkale in your project using poetry:

```bash
poetry add rkale
```

Use pip if you want a global installation:

```bash
pip install rkale
```

## Configuration

### Global

`~/.config/rkale/rkale.conf`:
```toml
[data]
root = "path to data folder where datasets are stored"

[aliases]
wasabi = "optional alias for remote in rclone.conf"

[rclone] # global flags for rclone
flags = ["--transfers 32", "--checkers 32"]
```

If aliases are empty the remote name from the project config is used in the
rclone lookup.

### Project
Configure project datasets in the pyproject.toml file:

`<project path>/pyproject.toml`:
```toml
[[tool.rkale.dataset]]
name = "dataset_1"
remote = "remote_1"

[[tool.rkale.dataset]]
name = "dataset_2"
remote = "remote_2"
```

The remote specified for the dataset must match a remote in the `rclone.conf`
or an alias in the global rkale configuration.

## Usage

### Python interface

```python
from rkale.config import dataset_paths


def dataset_path():
    return dataset_paths()["dataset_1"]
```

### Syncing datasets

Syncs the local datasets to be identical to the remote

```bash
rkale psync
```

Syncs the remote datasets to be identical to the local

```bash
rkale psync --upstream
```

Same as rclone sync but checks differences first and asks for confirmation

```bash
rkale sync <source> <destination>
```