Science Score: 26.0%
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○CITATION.cff file
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✓codemeta.json file
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✓.zenodo.json file
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○Scientific vocabulary similarity
Low similarity (11.3%) to scientific vocabulary
Keywords
Repository
Chinese Chess Advanced Analytics
Basic Info
Statistics
- Stars: 10
- Watchers: 2
- Forks: 5
- Open Issues: 1
- Releases: 0
Topics
Metadata Files
README.md
ChessAI - Chinese Chess Game Analyzer
ChessAI is a groundbreaking tool that brings together computer vision, chess algorithms, and advanced analytics to revolutionize the Chinese Chess analytics landscape. With ChessAI, you don't need expensive electronic boards to analyze your games. Simply use your regular board, set up a camera to capture the position, and let ChessAI do the rest.
- Main source code:
chesssai. - Deep Learning / Data Preparation:
dnn_models/data_preparation- Currenly only support for Chinese Chess (XiangQi), contact me for the license and the source code of the data preparation tool. - Deep Learning / Training:
dnn_models/training.

Roadmap
- [x] Chess position detection.
- [x] Chess engine integration.
- [x] Move suggestion.
- [ ] Deep learning model for chess board detection (No need to use ARUCO markers).
Environment setup
- Requirements: Python 3.9, Conda, Node.js 18+.
- Clone this repository.
bash
git clone https://github.com/vietanhdev/chessai --recursive
- Create a new conda environment and the required packages.
bash
conda create -n chessai python=3.9
conda activate chessai
pip install -e .
- Install Node.js packages and build the frontend.
bash
cd chessai/frontend
npm install
cd ..
bash build_frontend.sh
Build chess engine
bash
cd godogpaw
go build
- Copy the executable file (
godogpaw*) to the ./data/engines folder.
Run the app
bash
ENGINE_PATH="data/engines/godogpaw-macos-arm" python -m chessai.app --run_app
Replace ENGINE_PATH with the path to the chess engine executable file.
Data preparation & Training
This project uses computer vision and deep learning to detect chess pieces and chess board position.
AI flow for chess position detection:

- Go to dnn_models folder and follow the instructions in the
README.mdfile to prepare the data and train the model. - NOTE: Only training source code and pretrained models are included in this repository. The data preparation scripts and the training datset are not included. Contact me for the license and the data.
References
- This project was initially built for Hackster's OpenCV AI Competition 2023. Hackster Project: ChessAI - Chinese Chess Game Analyzer.
- Object detection model (for chess pieces) is based on YOLOX - License: Apache 2.0.
- Chess engine: godogpaw - License: MIT.
- UI components: shadcn-ui - License: MIT.
Owner
- Name: Neural Research Lab
- Login: nrl-ai
- Kind: organization
- Email: contact@nrl.ai
- Location: Vietnam
- Website: https://nrl.ai
- Repositories: 1
- Profile: https://github.com/nrl-ai
Build Together, Grow Together!
GitHub Events
Total
- Issues event: 1
- Watch event: 4
- Fork event: 1
Last Year
- Issues event: 1
- Watch event: 4
- Fork event: 1
Committers
Last synced: 8 months ago
Top Committers
| Name | Commits | |
|---|---|---|
| Viet Anh Nguyen | v****v@g****m | 23 |
Issues and Pull Requests
Last synced: 8 months ago
All Time
- Total issues: 1
- Total pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Total issue authors: 1
- Total pull request authors: 0
- Average comments per issue: 0.0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 1
- Pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Issue authors: 1
- Pull request authors: 0
- Average comments per issue: 0.0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- tinkerdragon (1)
Pull Request Authors
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Dependencies
- 593 dependencies
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