volley-ref-ai

VOLLEY-REF AI Models

AI-powered volleyball referee system for automatic IN/OUT line call detection.

Models Included

1. Court Keypoints Model (yolo_court_keypoints.pt)

• Architecture: YOLOv11n-pose
• Task: Detect 14 keypoints of a volleyball court
• Training: 100 epochs on volleyball-court-keypoints dataset
• Performance: 99% box mAP@50, 29% pose mAP@50

2. Ball Detection Model (yolo_volleyball_ball.pt)

• Architecture: YOLOv11s
• Task: Detect volleyball in video frames
• Training: 57 epochs on volleyball_detection dataset
• Performance: 98.8% mAP@50

Usage

Download Models

from huggingface_hub import hf_hub_download

# Download court model
court_model = hf_hub_download(
    repo_id="David-dsv/volley-ref-ai",
    filename="yolo_court_keypoints.pt"
)

# Download ball model
ball_model = hf_hub_download(
    repo_id="David-dsv/volley-ref-ai",
    filename="yolo_volleyball_ball.pt"
)

Inference with Ultralytics

from ultralytics import YOLO

# Court keypoints detection
court_model = YOLO("yolo_court_keypoints.pt")
results = court_model("volleyball_frame.jpg")

# Ball detection
ball_model = YOLO("yolo_volleyball_ball.pt")
results = ball_model("volleyball_frame.jpg", conf=0.7)

Full Pipeline

See the GitHub repository for the complete VOLLEY-REF AI pipeline that combines both models for automatic IN/OUT detection.

Training Details

Court Model

• Base: yolo11n-pose.pt
• Dataset: volleyball-court-keypoints (495 images)
• Epochs: 100
• Image size: 640
• Augmentation: Default YOLO augmentations

Ball Model

• Base: yolo11s.pt
• Dataset: volleyball_detection (1091 images)
• Epochs: 57 (early stopped from 150)
• Image size: 640
• Augmentation: Default YOLO augmentations

Limitations

• Trained primarily on indoor volleyball footage
• Performance may vary with different camera angles
• Ball detection works best with clear visibility (no motion blur)
• Court detection requires visible court lines

License

MIT License

Citation

@software{volley_ref_ai_2025,
  author = {Vuong},
  title = {VOLLEY-REF AI: AI-Powered Volleyball Referee System},
  year = {2025},
  url = {https://github.com/David-dsv/volley-ref-ai}
}

Acknowledgments

• Ultralytics for YOLOv11
• Roboflow for the training datasets