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Mohammadjalkhatib/
chess_yolo

Name: chess_yolo
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🧠 YOLOv8x Chess Piece Detector

This model is trained using Ultralytics YOLOv8x to detect and classify chess pieces from a top-down view of a chessboard. It was developed as part of a master's thesis project focused on automating chess gameplay with a robotic arm.

📦 Model Details

Architecture: YOLOv8x
Trained on: Custom dataset of top-view chessboard images
Classes:
- Chess_Board
- White_Pawn, White_Rook, White_Knight, White_Bishop, White_Queen, White_King
- Black_Pawn, Black_Rook, Black_Knight, Black_Bishop, Black_Queen, Black_King

🧪 Use Cases

Converting chessboard images to FEN notation
Automating real-world chess games with computer vision
HCI applications using robotic arms and vision-based interfaces

🚀 How to Use

python

from ultralytics import YOLO

model = YOLO("yolov8x_chess.pt")
results = model("your_image_path.jpg")

# Access detections
for r in results:
    print(r.boxes)

📊 Performance

The model performs accurately in controlled environments with a top-down camera. Real-time detection integrated with a QArm robotic arm achieved great results.

datasets:

name: chess_object_detection_alkhatib_dataset language:
en license: mit tags:
chess
computer-vision
object-detection
YOLO
robotics
HCI pretty_name: Chess Object Detection – AlKhatib Dataset task_categories:
object-detection size_categories:
1K<n<10K annotations_creators:
expert-annotated source_datasets:
original

📁 Citation / Credit

If you use this model, please consider citing or referencing this repository and the thesis project associated with it.

Mohammadjalkhatib/chess_yolo