semvec/pypi-packages huggingface dataset:
nnsvs 0.1.1
DNN-based singing voice synthesis library

# NNSVS

[![][docs-latest-img]][docs-latest-url]
[![PyPI](https://img.shields.io/pypi/v/nnsvs.svg)](https://pypi.python.org/pypi/nnsvs)
[![License](http://img.shields.io/badge/license-MIT-brightgreen.svg?style=flat)](LICENSE)
[![arXiv](https://img.shields.io/badge/arXiv-2210.15987-b31b1b.svg)](https://arxiv.org/abs/2210.15987)
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[![codecov](https://codecov.io/gh/nnsvs/nnsvs/branch/master/graph/badge.svg?token=Z66FDOQGH7)](https://codecov.io/gh/nnsvs/nnsvs)

[docs-latest-img]: https://img.shields.io/badge/docs-latest-blue.svg
[docs-latest-url]: https://nnsvs.github.io/nnsvs/

Neural network-based singing voice synthesis library for research

Documentation can be found at https://nnsvs.github.io.

## Citation

```
@article{yamamoto2022nnsvs,
  title={NNSVS: A Neural Network-Based Singing Voice Synthesis Toolkit},
  author={Yamamoto, Ryuichi and Yoneyama, Reo and Toda, Tomoki},
  journal={arXiv preprint arXiv:2210.15987},
  year={2022}
}
```

## Acknowledgements

- The inference implementation of uSFGAN was adapted from [chomeyama/HN-UnifiedSourceFilterGAN](https://github.com/chomeyama/HN-UnifiedSourceFilterGAN).
- The code for diffusion models was adapted from [DiffSinger](https://github.com/MoonInTheRiver/DiffSinger).
django-categories-api 0.2.2
Django-rest-framework API for django-categories

# Django Categories

[![codecov](https://codecov.io/gh/petrdlouhy/django-categories-api/branch/master/graph/badge.svg?token=rW8mpdZqWQ)](https://codecov.io/gh/petrdlouhy/django-categories-api)
[![Run Tox tests](https://github.com/PetrDlouhy/django-categories-api/actions/workflows/run-tests.yaml/badge.svg)](https://github.com/PetrDlouhy/django-categories-api/actions/workflows/run-tests.yaml)
[![Run Tox tests](https://img.shields.io/pypi/v/django-categories-api.svg)](https://pypi.python.org/pypi/django-categories-api/)

This application provides basic ``django-rest-framework`` API for Django Categories.


## Features of the project

The output contains category tree with counts of category items in each node (cummulative as well as direct counts).


## Countable fields

The API can contain number of related objects associatet with category.
This can be achieved by setting ``COUNTABLE_FIELD_RELATED_NAMES`` property in ``CATEGORIES_SETTINGS``:

```python
  CATEGORIES_SETTINGS = {
      "COUNTABLE_FIELD_RELATED_NAMES": ('field_name'),
  }
```

## Settings

The cache timeout and staggering can be changed by:

```python
  CATEGORIES_SETTINGS = {
      "CACHE_TIMEOUT": 60 * 60,
      "CACHE_STAGGERING": 60 * 10,
  }
```
tubelearn 1.0.0
Python script for extracting and cleaning YouTube video transcripts for Pre-Processing in machine learning.
Keywords: python,video,transcript,raw data,cleaning,machine learning,pre-processing



## Tube-Data: YouTube Video Transcript Extractor

Tube-Data is a Python script designed for extracting and cleaning YouTube video transcripts for preprocessing in machine learning. This versatile tool streamlines the process of acquiring high-quality text data from YouTube videos, making it ideal for various natural language processing tasks, sentiment analysis, speech recognition, and more.

## Features

- Extracts video transcripts from YouTube videos.
- Cleans transcripts by removing unwanted elements like music and applause.
- Saves cleaned transcripts into separate text files.
- Supports individual video URLs, batch processing from a list of URLs, and entire playlists.
- Streamlines the dataset collection process for machine learning applications.

## Installation

You can install the required dependencies using `pip`:

```bash
pip install youtube-transcript-api requests pytube regex
```

## Usage

### Extract Transcripts from a List of Video URLs

```python
from tube_data import text_link

# Provide a path to a text file containing YouTube video URLs.
text_link('path_to_file.txt', name='output_folder_name')
```

### Extract Transcript from a Single Video URL

```python
from tube_data import url_grab

# Provide a single YouTube video URL.
url_grab('video_url', name='output_folder_name')
```

### Extract Transcripts from a YouTube Playlist

```python
from tube_data import playlist_grab

# Provide the URL of a YouTube playlist.
playlist_grab('playlist_url', name='output_folder_name')
```

### Convert Playlist Video Links to Text File

```python
from tube_data import play2text

# Provide the URL of a YouTube playlist.
play2text('playlist_url')
```

## Development Status

This project is currently in the planning stage.

## License

This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.

## Contributions

Contributions are welcome! Please feel free to open issues or submit pull requests.

## Contact

For any inquiries or feedback, please contact [KabilPreethamK](mailto:kabilpreethamk@gmail.com).
tomtom-map-scraper 1.0.0
Search and extract Points of Interest from TomTom, for free.
Requires Python: >=3.6
Keywords: tomtom,poi,points of interest,api

# TomTom Map Scraper

A simple Python client to interact with the TomTom Points of Interest (POI) Search API, for **free**

## Features

- Ability to search for Points of Interest (POIs) with various filters.
- Retrieve API key automatically.
- Cached API key retrieval for faster subsequent requests.
- Ability to use proxies.

## Installation

```bash
pip install tomtom_map_scraper
```

## Usage

```python
from tomtom import TomTomClient

api = TomTomClient(limit=50)
result = api.search(query="Coffee", lat=37.7749, lon=-122.4194)
print(result)
```

## Available Parameters
### Parameters for `search` Method

The `search` method in `TomTomClient` class supports various parameters:

- **query**: The search string. For example, "Coffee".
- **lat**: Latitude value.
- **lon**: Longitude value.
- **brand_set**: Brands filter.
- **country_set**: Country filter.
- **radius**: Search radius (in meters).
- **limit**: Number of results to return (max: 100).
- **category_set**: Categories filter.
- **related_pois**: Relation of the POI. Can be one of the values from the `RelatedPois` enum (`ALL`, `OFF`, `PARENT`, `CHILDREN`).


For a more in depth documentation please visit: https://developer.tomtom.com/search-api/documentation/search-service/points-of-interest-search

_Note:_ Parameters that are not provided or set to `None` will not be included in the API request.