Android Chess Board AR App

I'm looking for an experienced Android developer to create a Chess Board AR application. The app only function is to annotate the moves. It must be able to recognize the corners, chess pieces and validate the moves from the Phone's camera which is mounted on a tripod.

Key Requirements:
- Android Development: You should have a deep understanding of Android development, including experience with AR development.
- AR: Knowledge and experience in creating AR applications.
- It helps if you know how to play chess.

1. Computer Vision for Chess Piece Recognition (YOLOv8)

https://www.youtube.com/watch?v=dl7rCmvIyiI
https://github.com/Dilanya/Chess-Pieces-Detection.
https://public.roboflow.com/object-detection/chess-full

Image Capture: Use the phone's camera to capture images of the chessboard.
Preprocessing: Apply image preprocessing techniques (e.g., grayscale conversion, noise reduction) to improve image quality.
Board Detection: Detect the chessboard within the image, typically by finding the largest square in the frame.
Square Segmentation: Divide the detected chessboard into 64 squares.
Piece Recognition: Use a trained machine learning model (e.g., a convolutional neural network) to recognize the chess pieces on each square. You can train the model using a labeled dataset of chess piece images.

Please feel free to use any existing github code that is better.

2. Move Detection
Initial Board Setup: Capture an image of the initial chessboard setup.
Continuous Monitoring: Continuously capture images of the board at intervals to detect changes.
Difference Calculation: Compare the current board state with the previous state to identify which pieces have moved.
Move Validation: Validate the detected moves according to the rules of chess.

3. Annotation
Move Annotation: Annotate each detected move in standard chess notation (e.g., e4, Nf3).
User Interface: Display the annotated moves on the screen in a list format, allowing users to review the game history.

4. Implementation Tools
Programming Language: Java/Kotlin for Android development.
Machine Learning Frameworks: TensorFlow Lite or OpenCV for piece recognition.
Android Libraries: CameraX for camera integration, Android UI components for the interface.

Sample Workflow
Initialize Camera: Start the camera feed and display the live video on the screen.
Capture Initial Board State: Detect and store the initial state of the chessboard.
Monitor for Changes: Continuously capture images and analyze for changes in the board state.
Detect Moves: When a change is detected, identify the moved pieces and annotate the move.
Display Moves: Update the UI with the latest move annotation.

Resources and References
TensorFlow Lite: TensorFlow Lite Guide
OpenCV: OpenCV Documentation
Android CameraX: CameraX Guide


To reduce development time, you can leverage existing libraries and GitHub repositories that provide functionality for computer vision, chess recognition, and Android development. Here are some recommendations:

Chess-Specific Libraries
Chessboard.js

Description: A JavaScript library for displaying chessboards.
GitHub: chessboardjs/chessboardjs
Usage: Can be used as a reference for chessboard representation and move validation.
Chess.js

Description: A JavaScript chess library that is used for move generation, validation, and board state manipulation.
GitHub: jhlywa/chess.js
Usage: Useful for understanding move validation and generating annotations.
Android Development Libraries
CameraX

Description: A Jetpack library for integrating camera functionality into Android apps.
GitHub: android/camera-samples
Usage: Simplifies camera integration in your Android app.
Android TensorFlow Lite Examples

Description: Examples of TensorFlow Lite usage on Android.
GitHub: tensorflow/examples
Usage: Provides sample code for integrating TensorFlow Lite models in Android apps.
Example Projects on GitHub
Chessboard Recognition with OpenCV and TensorFlow

Description: Projects that combine OpenCV and TensorFlow for chessboard and piece recognition.
GitHub Examples:
DjangoChessRecognition
Chessboard Image Recognition
Mobile Chess Apps

Description: Open-source mobile apps that incorporate chess functionality.
GitHub Examples:
Android-Chess

Combining These Resources
By combining these resources, you can reduce your development time significantly:

Use TensorFlow Lite for loading and running pre-trained models for piece recognition.
Use OpenCV for image preprocessing and board detection.
Refer to chess-specific libraries like Chessboard.js and Chess.js for move generation and validation logic.
Leverage CameraX for integrating the camera into your Android app efficiently.