semvec/pypi-packages huggingface dataset:
vot-toolkit 0.7.4
Perform visual object tracking experiments and analyze results
Requires Python: >=3.7


The VOT evaluation toolkit
==========================

[![Documentation Status](https://readthedocs.org/projects/vot-toolkit/badge/?version=latest)](https://vot-toolkit.readthedocs.io/en/latest/?badge=latest)
[![PyPI package version](https://badge.fury.io/py/vot-toolkit.svg)](https://badge.fury.io/py/vot-toolkit)

This repository contains the official evaluation toolkit for the [Visual Object Tracking (VOT) challenge](http://votchallenge.net/). This is the official version of the toolkit, implemented in Python 3 language. If you are looking for the old Matlab version, you can find an archived repository [here](https://github.com/votchallenge/toolkit-legacy).

For more detailed informations consult the documentation available [here](http://vot-toolkit.readthedocs.io/). You can also subscribe to the VOT [mailing list](https://liste.arnes.si/mailman3/lists/votchallenge.lists.arnes.si/) to receive news about challenges and important software updates or join our [support form](https://groups.google.com/forum/?hl=en#!forum/votchallenge-help) to ask questions.

Developers
----------

The VOT toolkit is developed and maintained by  [Luka Čehovin Zajc](https://vicos.si/lukacu) with the help of the VOT innitiative members and the VOT community.

Contributors:

* [Luka Čehovin Zajc](https://vicos.si/lukacu), University of Ljubljana
* [Alan Lukežič](https://vicos.si/people/alan_lukezic/), University of Ljubljana
* Yan Song, Tampere University

Acknowledgements
----------------

The development of this package was supported by Slovenian research agency (ARRS) projects Z2-1866 and J2-316.

License
-------

Copyright (C) 2024 Luka Čehovin Zajc and the [VOT Challenge innitiative](http://votchallenge.net/).

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this program.  If not, see <http://www.gnu.org/licenses/>.

Enquiries, Question and Comments
--------------------------------

If you have any further enquiries, question, or comments, please refer to the contact information link on the [VOT homepage](http://votchallenge.net/). If you would like to file a bug report or a feature request, use the  [Github issue tracker](https://github.com/votchallenge/toolkit/issues). **The issue tracker is for toolkit issues only**, if you have a problem with tracker integration or any other questions, please use our [support forum](https://groups.google.com/forum/?hl=en#!forum/votchallenge-help).
raspberrypi-control 2.0.6
Control Raspberrypi board with ssh and python
Requires Python: >=3.10

# **Raspberry Pi controller**
## help
 [Raspberrypi controller Wiki](https://github.com/Geoloup/raspberry_control/wiki/)
## Feature
 1. Connect in ssh to the Raspberry Pi or any linux (Feature may be not presents)
 2. Can connect using IP or DOMAIN (.local included)
 3. Module and Global call are supported
 4. The function can be run on the Raspberry Pi  by adding `@raspberry_control.raspberry_command()` on top of a function and get the result
 5. Get Output of a function that was run on the raspberry
 6. Real-time output
 7. Run command on the Raspberry Pi with `raspberry_control.run_command("command here")`
 8. You can do `@raspberrypi.timeout(time,default)` will change the timeout for a functions
 9. Get file from the server and read it ? / write it localy and update after on the server
## Example

    import raspberrypi_control # import package for raspberrypi controlling over ssh  
    import os # raspberryPi control can automacly install package.
    import time  
      
    rp = raspberrypi_control # rp is for RaspberryPi  
      
    i = 1234567890  
      
      
    @rp.raspberry_command() # When function is called its automatcly run on the raspberrypi fallback : local
    def test():  
        print("Hello RaspBerryPi")  
        return "finished"  
      
      
    @rp.raspberry_command() # When function is called its automatcly run on the raspberrypi fallback : local
    def other():  
        global i  
        print("Hello RaspberryPi h")  
        th = 0  
        print(i)  
        os.system("echo Hello World")  
        while True:  
            th = th + 1  
            if th == 30:  
                time.sleep(0.1)  
                break  
        return th  
      
      
    if __name__ == "__main__": # put all you're code to run at start here. Because if not the code will be run 2 time  
        rp.raspberrypi().set_raspberry_info("username here", "password here") # set login info here
        rp.raspberrypi().set_preparation("raspberrypi.local", 8, 1) # config locator for the raspberrypi  
        rp.raspberrypi().local() # set the start ip set in the line in the top  
        rp.config("main") # file name if this file (no .py)  
        rp.run_command("Hello World",True) # true is for if console ouput is print or no
        print(test())  
        print(other()) # you can get the output after

## How to install the package
Do `pip install raspberry-control`
Supported for python 3.10 and higher*
*note not tested for lower version
<br>
Was tested to work on linux and window. Mac support may be limited
<br>
dependencies = [
    "requests",
    "paramiko",
    "psutil"
]

## Bug report
[Github - Issues](https://github.com/Geoloup/raspberry_control/issues/new?assignees=franck403&labels=bug&projects=&template=bug-report.yml&title=%5BBUG%5D+Untitled+Bug+Report)
audiovisually 0.1.4
A package for audiovisual AI processing
Requires Python: >=3.10

# Audiovisually

A Python package for leveraging audiovisual data for advanced AI applications.

[**Full Documentation**](https://bredauniversityadsai.github.io/2024-25d-fai2-adsai-group-nlp-3/)

## Table of Contents
- [Audiovisually](#audiovisually)
  - [Table of Contents](#table-of-contents)
  - [Introduction](#introduction)
  - [Features](#features)
  - [Installation](#installation)
  - [Package Structure](#package-structure)
  - [Usage](#usage)
  - [Contributing](#contributing)
  - [License](#license)

## Introduction
This package provides tools and utilities for processing and analyzing audiovisual data, enabling the development of intelligent systems that integrate audio and visual inputs.

## Features
- Audio and video data preprocessing
- Feature extraction for audiovisual datasets
- Pre-trained models for audiovisual tasks
- Customizable pipelines for specific use cases

## Installation
You can install the package directly from PyPI:

```bash
pip install audiovisually
```

## Package Structure
The package is organized as follows:

```
audiovisually
├── __init__.py
├── utils.py
├── preprocess.py
├── predict.py
├── evaluate.py
└── train.py
```

## Usage
Here’s an example of how to use the package:

```python
from audiovisually.preprocess import convert_video_to_mp3

# Convert a video file to MP3
convert_video_to_mp3("input_video.mp4", "output_audio.mp3")
```

## Contributing
Contributions are welcome! Please follow these steps:
1. Fork the repository.
2. Create a new branch (`git checkout -b feature-name`).
3. Commit your changes (`git commit -m 'Add feature'`).
4. Push to the branch (`git push origin feature-name`).
5. Open a pull request.

## License
This package is licensed under the [MIT License](LICENSE).