{"id":16420391,"url":"https://github.com/ierror/acid-chess","last_synced_at":"2025-10-17T05:52:26.552Z","repository":{"id":142933668,"uuid":"606573399","full_name":"ierror/acid-chess","owner":"ierror","description":"ACID Chess - The Chess Computer for nerds, by nerds.","archived":false,"fork":false,"pushed_at":"2024-01-22T22:20:40.000Z","size":68866,"stargazers_count":22,"open_issues_count":6,"forks_count":0,"subscribers_count":2,"default_branch":"main","last_synced_at":"2024-10-12T07:27:47.064Z","etag":null,"topics":["ai","chess","image-processing","neural-network","python","pytorch"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/ierror.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null}},"created_at":"2023-02-25T22:22:59.000Z","updated_at":"2024-01-24T20:18:18.000Z","dependencies_parsed_at":null,"dependency_job_id":"f4ecf515-7b71-48a2-b1c7-1a523d981c0f","html_url":"https://github.com/ierror/acid-chess","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ierror%2Facid-chess","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ierror%2Facid-chess/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ierror%2Facid-chess/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ierror%2Facid-chess/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ierror","download_url":"https://codeload.github.com/ierror/acid-chess/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":221811374,"owners_count":16884305,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["ai","chess","image-processing","neural-network","python","pytorch"],"created_at":"2024-10-11T07:27:54.037Z","updated_at":"2025-10-17T05:52:17.478Z","avatar_url":"https://github.com/ierror.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003cp align=\"center\"\u003e\n    \u003cimg src=\"docs/_static/images/logo/dark.png#gh-dark-mode-only\" class=\"only-dark\" align=\"center\" width=\"25%\" alt=\"Logo\"\u003e\n\u003c/p\u003e\n\n\u003cp align=\"center\"\u003e\n    \u003cimg src=\"docs/_static/images/logo/light.png#gh-light-mode-only\" class=\"only-light\" align=\"center\" width=\"25%\" alt=\"Logo\"\u003e\n\u003c/p\u003e\n\n\u0026nbsp;\n\n*The Chess Computer for nerds, by nerds.*\n\n[![RTFM badge](https://img.shields.io/readthedocs/acid-chess/latest?style=flat-square)](https://acid-chess.readthedocs.io/)\n[![Discord badge](https://img.shields.io/discord/1083067212803354624?style=flat-square\u0026logo=discord)](https://discord.com/invite/wdMdBr6jxs)\n[![License badge](https://img.shields.io/github/license/ierror/acid-chess?style=flat-square\u0026color=blue)](https://github.com/ierror/acid-chess/blob/main/LICENSE)\n\n\u0026nbsp;\n\n## Picture by Picture\n\nACID Chess is a chess computer written in Python, which can be used with any? board. By filming the board, the\ncontour of the board is recognized, and the positions of the individual pieces can be determined. \n\n\u003cimg src=\"docs/_static/images/over-the-board.jpg\" alt=\"How it works - over the board\" width=\"85%\"\u003e\n\nTwo [Neural Networks](https://acid-chess.readthedocs.io/en/latest/dev/neural_networks.html)\nwere trained for the board and squares recognition.\n\n### Board Segmentation Model\n\n\u003cimg src=\"docs/_static/images/board_segmentation.png\" alt=\"Board Segmentation\" width=\"85%\"\u003e\n\n### Square Classification Model\n\n~15585 square images \n\n\u003cimg src=\"docs/_static/images/square_classification.png\" alt=\"Board Segmentation\" width=\"85%\"\u003e\n\n# Current Release \n\n### 2023-11-23: v.0.2.0\n- added support to play on Lichess\n\ncomplete [Changelog](https://acid-chess.readthedocs.io/en/latest/changelog.html)\n\n# Features\n\nYou can play against an engine, Stockfish or Maia are available, or play a game against another human. In both variants,\na PGN is generated, which you can load later in the analysis board at Lichess, or so, for analysis.\n\n- Engine play against Stockfish or Maia\n- Use polyglot opening books\n- Play on Lichess\n- PGN exports\n\n\u003cimg src=\"docs/_static/images/gui.jpg\" alt=\"How it works - GUI\" width=\"85%\"\u003e\n\n# Planned Features\n\n- Clock\n- ... see [issues](https://github.com/ierror/acid-chess/issues/) for details\n\n# Technology\n\n- Python as a programming language\n- Qt (PySide6) as toolkit for the GUI (with own extension for reactive bindings)\n- PyTorch (Lightning ) for the development of AI models\n\n# I want to play against ACID!\n\nWe have tested ACID Chess with four different boards and were able to complete games without significant flaws. There\nwill be problems on unknown boards, but every tester makes ACID Chess better!\n\nRegardless of the chosen installation method: ACID Chess saves images of data that cannot be classified sufficiently.\nPlease provide us with this data. Create an [issue](https://github.com/ierror/acid-chess/issues/new) and upload a ZIP\nfile as an attachment. `\u003c3`\n\n[Installation](https://acid-chess.readthedocs.io/en/latest/installation.html)\n\n# Resources\n\n## Documentation\n[https://acid-chess.readthedocs.io](https://acid-chess.readthedocs.io)\n\n## Sourcecode\n[https://github.com/ierror/acid-chess](https://github.com/ierror/acid-chess)\n\n# Contributing\n\nContributions are always welcome. Please discuss major changes via issue first before submitting a pull request.\n\n# Data Attribution\n\n[Google Programmable Search Engine](https://developers.google.com/custom-search) Rest API was used to search for\nCreative Commons licensed images of chess boards used for training the neural network models.\n\n- [Notebook](https://github.com/ierror/acid-chess/blob/main/notebooks/board_google_images_dl.ipynb) for collecting the data\n- [CSV](https://github.com/ierror/acid-chess/blob/main/data/training/boards/attribution.csv) to document the Attribution\n\n# Contact\n\n- Mastodon [@boerni@chaos.social](https://chaos.social/@boerni)\n- [Discord](https://discord.com/invite/wdMdBr6jxs)\n\n\n\n\n\u0026nbsp;\n======","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fierror%2Facid-chess","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fierror%2Facid-chess","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fierror%2Facid-chess/lists"}