Instructions to use dopaul/chess-piece-detector-merged with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use dopaul/chess-piece-detector-merged with ultralytics:
# Couldn't find a valid YOLO version tag. # Replace XX with the correct version. from ultralytics import YOLOvXX model = YOLOvXX.from_pretrained("dopaul/chess-piece-detector-merged") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
Chess Piece Detection Model
This is a YOLO model trained to detect chess pieces on a chessboard.
Model Details
- Model Type: YOLOv8/YOLOv11 Object Detection
- Task: Chess piece detection and classification
- Framework: Ultralytics YOLO
- Repository: dopaul/chess-piece-detector-merged
Files
The following files are included in this model:
best.pt
Usage
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.
- Downloads last month
- 62