| library_name: ultralytics | |
| tags: | |
| - object-detection | |
| - chess | |
| - computer-vision | |
| - yolo | |
| datasets: | |
| - chess-pieces | |
| pipeline_tag: object-detection | |
| # Chess Piece Detection Model | |
| This is a YOLO model trained to detect chess pieces on a chessboard. | |
| ## Model Details | |
| - **Model Type**: YOLO11 Object Detection | |
| - **Task**: Chess piece detection and classification | |
| - **Framework**: Ultralytics YOLO | |
| - **Repository**: dopaul/chess-board-segmentation | |
| ## Files | |
| The following files are included in this model: | |
| - `best.pt` | |
| ## Usage | |
| ```python | |
| from ultralytics import YOLO | |
| # Load the model | |
| model = YOLO('path/to/best.pt') | |
| # Run inference | |
| results = model('path/to/chess_image.jpg') | |
| # Display results | |
| results[0].show() | |
| ``` | |
| ## Model Performance | |
| This model can detect and classify various chess pieces including: | |
| - Pawns | |
| - Rooks | |
| - Knights | |
| - Bishops | |
| - Queens | |
| - Kings | |
| For both black and white pieces. | |
| ## Training Data | |
| The model was trained on chess piece datasets to achieve robust detection across different chess sets and lighting conditions. | |