semvec/pypi-packages huggingface dataset:
imgcode 0.1
A simple package for Image & Video Analytics Practical
Requires Python: >=3.6

# imgcode Package

Welcome to the imgcode package! This package provides a variety of image and video processing methods that allow users to manipulate, analyze, and enhance images easily. Whether you're looking to convert image formats, detect faces, or apply filters, ImgPro has you covered.

## Available Methods

Here are the available methods in the netimg package:

1. **basic()**: Read, display, get size and type of an image.
2. **convert()**: Convert images to grayscale or binary, print size, resize, and copy images.
3. **geometry()**: Draw shapes on images.
4. **enhancement()**: Adjust brightness and contrast, create digital negatives.
5. **edge()**: Perform Canny edge detection on images.
6. **dct()**: Apply discrete cosine transformation for image compression.
7. **face()** or **eye()**: Detect faces or eyes in images.
8. **compression()**: Perform lossy and lossless image compression.
9. **video_face()**: Process pre-recorded video for face detection.
10. **face_live()**: Perform face detection in live video streams.

### Example Usage

```python
import imgcode as m
m.edge()
```
sanderthedragon-sphinxext 1.1.0
SanderTheDragon's Sphinx Extensions
Requires Python: >=3.10

.. SPDX-FileCopyrightText: 2021-2024 SanderTheDragon <sanderthedragon@zoho.com>
..
.. SPDX-License-Identifier: CC-BY-SA-4.0

###################################
SanderTheDragon's Sphinx Extensions
###################################
These are some `Sphinx <https://www.sphinx-doc.org>`_ extensions I wrote, feel free to use them.

- `Code Block Buttons <https://sanderthedragon.gitlab.io/sphinx-extensions/codeblockbuttons.html>`_ adds copy and view buttons to code blocks.
- `Extra Lexers <https://sanderthedragon.gitlab.io/sphinx-extensions/extralexers.html>`_ adds extra lexers to pygments currently only LLVM JSON.
- `Inline Code Highlight <https://sanderthedragon.gitlab.io/sphinx-extensions/inlinecodehighlight.html>`_ adds custom roles to be able to highlight inline code.
- `Mapped Link Role <https://sanderthedragon.gitlab.io/sphinx-extensions/mappedlinkrole.html>`_ adds custom roles which can be mapped to links.

************
Installation
************
The extensions can be installed with **pip**.

.. code-block:: sh

   pip install sanderthedragon-sphinxext

***********
Source Code
***********
The source code is hosted on `GitLab <https://gitlab.com/SanderTheDragon/sphinx-extensions>`_.

*********
Changelog
*********
Changelog is available `here <https://sanderthedragon.gitlab.io/sphinx-extensions/changelog.html>`_.

*******
License
*******
These documents are licensed under `CC-BY-SA-4.0 <https://spdx.org/licenses/CC-BY-SA-4.0.html>`_.
Code and examples are licensed under `MIT <https://spdx.org/licenses/MIT.html>`_.
Other files, like configuration files are licensed under `CC0-1.0 <https://spdx.org/licenses/CC0-1.0.html>`_.
netimg 0.1
A simple package for Image & Video Analytics Practical
Requires Python: >=3.6

# ImgPro Package

Welcome to the netimg package! This package provides a variety of image and video processing methods that allow users to manipulate, analyze, and enhance images easily. Whether you're looking to convert image formats, detect faces, or apply filters, ImgPro has you covered.

## Available Methods

Here are the available methods in the netimg package:

1. **basic()**: Read, display, get size and type of an image.
2. **convert()**: Convert images to grayscale or binary, print size, resize, and copy images.
3. **geometry()**: Draw shapes on images.
4. **enhancement()**: Adjust brightness and contrast, create digital negatives.
5. **edge()**: Perform Canny edge detection on images.
6. **dct()**: Apply discrete cosine transformation for image compression.
7. **face()** or **eye()**: Detect faces or eyes in images.
8. **compression()**: Perform lossy and lossless image compression.
9. **video_face()**: Process pre-recorded video for face detection.
10. **face_live()**: Perform face detection in live video streams.

### Example Usage

```python
import netimg as m
m.edge()
```
task-6-rakitin-sergey 0.0.26
A package for processing Formula 1 racing logs
Requires Python: >=3.11
Keywords: Formula 1, logs, racing

# F1 Racing Report Package

This Python package generates and prints a report for Formula 1 racing, based on logs of start and end times of racers. The package also provides a command-line interface (CLI) to interact with the report generation and allows flexible configuration options.

## Features

- **Report Generation**: Generate a sorted list of F1 racers by lap times.
- **CLI Interface**: Process files from a specified folder and print reports or errors.
- **Error Handling**: Provides detailed error messages for problematic records (e.g., invalid times).
- **Custom Report Options**: Includes optional sorting and underline settings.

## Installation

Install the package using PIP:

```bash
    pip install task_6_rakitin_sergey
```
# Usage

Enter the following commands via CMD.

## Below are some examples of how to use the CLI.

Basic Report generation (with ascending order by default):

```bash
    python -m task_6_rakitin_sergey.f1_report
```

Generate report with sorting order descending:

```bash
  python -m task_6_rakitin_sergey.f1_report --order desc
```

Print report with custom underline after a specific line (for example, 3):

```bash
    python -m task_6_rakitin_sergey.f1_report --underline_after 3
```

Show only errors:

```bash
    python -m task_6_rakitin_sergey.f1_report --errors_only
```

Show report for a specific driver:

```bash
    python -m task_6_rakitin_sergey.f1_report --driver "Sebastian Vettel"
```

Use an own path to .log and .txt files:

```bash
    python -m task_6_rakitin_sergey.f1_report --files <folder_path>
```

List of commands:

```bash
    python -m task_6_rakitin_sergey.f1_report --help
```

Import package to your project and call:

```bash
  from task_6_rakitin_sergey import f1_report

  if __name__ == "__main__":
      f1_report.command_line_input()
```

## Link to package page 

```Bash
    https://pypi.org/project/task-6-rakitin-sergey/
```
ai-voice-bot 1.0.1
An AI-powered voice bot using OpenAI Realtime API
Requires Python: >=3.8


# AI Voice Bot

This project is an AI-powered voice bot built using OpenAI's Realtime API. It allows for real-time voice interaction through a command-line interface (CLI) and can be modified to handle text output, as well as include a mocked version for cost-effective testing.

## Project Structure

- `ai_voice_bot/`: Contains the main implementation of the voice bot.
```
├───ai_voice_bot
│   ├───client
│   │   └───__pycache__
│   ├───handlers
│   │   └───__pycache__
│   ├───mock
│   │   └───__pycache__
│   └───__pycache__
```
- `misc/`: Directory for miscellaneous files.
- `.gitignore`: Specifies which files should be ignored by Git.
- `LICENSE`: The project's license file.
- `README.md`: The README file that you're reading right now.
- `install.bat`: A batch script for setting up the environment.
- `mock_bot.py`: A mock version of the bot for testing without using the API.
- `push.bat`: A batch script for pushing changes to GitHub.
- `setup.py`: The setup script for packaging and distributing the project.
- `text_bot.py`: The script for handling text-based output from the bot.
- `voice_bot.py`: The script for handling voice-based interaction.

## Features

- **Voice Interaction**: The bot supports real-time voice input and can generate real-time responses using OpenAI's Realtime API.
- **Text-Based Interaction**: You can modify the bot to handle text input and output instead of voice, allowing for more versatile use cases.
- **Mock Bot**: The mock bot allows for testing and development without incurring costs from the API.

## Installation

To install this project, clone the repository and run the following commands:

```bash
git clone https://github.com/myaichat/ai_voice_bot.git
cd ai_voice_bot
pip install -e .
```

## Usage

### Voice Interaction

To start the voice interaction bot, run the following command:

```bash
python voice_bot.py
```

### Text-Based Interaction

To start the text-based interaction bot, run the following command:

```bash
python text_bot.py
```

### Mock Bot

To run the mock bot for testing, use the following command:

```bash
python mock_bot.py
```

## Building the Project

To build the project and create a wheel distribution:

```bash
pip install wheel
python setup.py sdist bdist_wheel
```

You can find the built wheel file in the `dist/` folder.

## Contributing

Contributions are welcome! Feel free to open issues or submit pull requests.

## License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.

## References
https://github.com/run-llama/openai_realtime_client
Ciola 1.0.6
A personal library
Requires Python: >=3.10

# Ciola
Ciola is a library created FOR PERSONAL USE, but it can also be used by you. Honestly, I don't really care, but remember that if you use it, you won't find any documentation or support from me.

# Functions
1) Mail Generator
2) Password Generator
3) User Agent Generator
4) Human Behavior Functions for web automation (playwright)
Other utils will be added!