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