Chess Detect

Inspiration

Our inspiration for Chess Detect was to create a tool that would make it easier for chess players to get feedback on their games. We wanted to make the evaluation process more accessible and convenient for players, especially those who do not have access to a chess coach or expert.

What it does

Chess Detect uses computer vision and machine learning algorithms to extract the chess position from a picture taken by a phone camera. It then sends this position to a backend server running the Stockfish chess engine, which calculates an evaluation score and suggests the best move for the player. The evaluation and best move are then sent back to the user's phone.

How we built it

We built Chess Detect using a combination of technologies, including Roboflow, OpenCV TensorFlow for computer vision and machine learning, Node.js and NestJS for the backend server, and React Native for the mobile app. We also used Stockfish for the chess engine.

Challenges we ran into

One of the biggest challenges we faced was developing an accurate algorithm for extracting the chess position from a picture. We had to experiment with different computer vision techniques and machine learning models to find the best approach. Another challenge was optimizing the system to work quickly and reliably, especially given the resource constraints of a mobile device.

Accomplishments that we're proud of

We tried.

What we learned

Through developing Chess Detect, we learned a lot about computer vision and machine learning techniques, as well as the challenges and opportunities of developing a real-time system for mobile devices. We also learned a lot about teamwork and collaboration, as we had to work together effectively to integrate the different components of the system.

What's next for Chess Detect

In the future, we hope to continue refining and improving the accuracy and performance of the system, as well as adding additional features such as game analysis and personalized training recommendations. We also hope to explore opportunities for commercializing the technology and making it available to a wider audience of chess players.

Built With

• javascript
• nest
• python
• roboflow
• stockfish
• typescript