Metadata-Version: 2.1
Name: acid-chess
Version: 0.1.0rc1
Summary: The Chess Computer for nerds, by nerds.
Author-email: Bernhard Janetzki <boerni@gmail.com>
Project-URL: Homepage, https://github.com/ierror/acid-chess
Project-URL: Bug Tracker, https://github.com/ierror/acid-chess/issues
Keywords: feed,reader,tutorial
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE



<p align="center">
    <img src="docs/_static/images/logo/dark.png#gh-dark-mode-only" class="only-dark" align="center" width="25%" alt="Logo">
</p>

<p align="center">
    <img src="docs/_static/images/logo/light.png#gh-light-mode-only" class="only-light" align="center" width="25%" alt="Logo">
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&nbsp;

*The Chess Computer for nerds, by nerds.*

[![RTFM badge](https://img.shields.io/readthedocs/acid-chess/latest?style=flat-square)](https://acid-chess.readthedocs.io/)
[![Discord badge](https://img.shields.io/discord/1083067212803354624?style=flat-square&logo=discord)](https://discord.com/invite/wdMdBr6jxs)
[![License badge](https://img.shields.io/github/license/ierror/acid-chess?style=flat-square&color=blue)](https://github.com/ierror/acid-chess/blob/main/LICENSE)

&nbsp;

# Picture by Picture

ACID Chess is a chess computer written in Python, which can be used with any? board. By filming the board, the
contour of the board is recognized, and the positions of the individual pieces can be determined. Two [Neural Networks](/dev/neural_networks.html)
were trained for the board and squares recognition.

<img src="docs/_static/images/over-the-board.jpg" alt="How it works - over the board">

# Features

You can play against an engine, Stockfish or Maia are available, or play a game against another human. In both variants,
a PGN is generated, which you can load later in the analysis board at Lichess, or so, for analysis.

- Engine play against Stockfish or Maia
- Use polyglot opening books
- PGN exports

<img src="docs/_static/images/gui.jpg" alt="How it works - GUI">

# Planned Features

- Clock
- Play on Lichess
- ... see [issues](https://github.com/ierror/acid-chess/issues/) for details

# Technology

- Python as a programming language
- Qt (PySide6) as toolkit for the GUI (with own extension for reactive bindings)
- PyTorch (Lightning ) for the development of AI models

# I want to play against ACID!

We have tested ACID Chess with four different boards and were able to complete games without significant flaws. There
will be problems on unknown boards, but every tester makes ACID Chess better!

Regardless of the chosen installation method: ACID Chess saves images of data that cannot be classified sufficiently.
Please provide us with this data. Create an [issue](https://github.com/ierror/acid-chess/issues/new) and upload a ZIP
file as an attachment. `<3`

There are two ways to install ACID Chess.

1. as binary: for users who want to try ACID Chess and don't want to deal with installing Python etc.
2. check out the project via git and install the dependencies manually for people who want to develop on ACID Chess themselves.

Modern hardware, preferably NVIDIA GPU or Mac M`[0-9]+` is recommended!

# Known bugs and limitations
- after switching cameras you will see an "Image capture failed: timed out waiting for a preview frame" error in the logs. Workaroud: Select camara you want to use and restart the app

# Resources

## Documentation
[https://acid-chess.readthedocs.io](https://acid-chess.readthedocs.io)

## Sourcecode
[https://github.com/ierror/acid-chess](https://github.com/ierror/acid-chess)

# Contributing

Contributions are always welcome. Please discuss major changes via issue first before submitting a pull request.

# Data Attribution

[Google Programmable Search Engine](https://developers.google.com/custom-search) Rest API was used to search for
Creative Commons licensed images of chess boards used for training the neural network models.

- [Notebook](https://github.com/ierror/acid-chess/blob/main/notebooks/board_google_images_dl.ipynb) for collecting the data
- [CSV](https://github.com/ierror/acid-chess/blob/main/data/training/boards/attribution.csv) to document the Attribution

# Contact

- Mastodon [@boerni@chaos.social](https://chaos.social/@boerni)
- [Discord](https://discord.com/invite/wdMdBr6jxs)
