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license: mit |
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# Hockey Rink Keypoint Detection |
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<div style="background-color:#f8f9fa; color:black; border-left: 6px solid #28a745; padding: 10px; margin: 10px 0;"> |
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🔗 This model is trained on the <span style="color:red">HockeyRink</span> dataset. |
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- 📊 Access the dataset used for training here: <a href="[DATASET_LINK]" style="color:blue;">https://huggingface.co/datasets/SimulaMet-HOST/HockeyRink</a> |
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- 🚀 Try the model in action with our interactive <span style="color:red">Hugging Face Space</span>: <a href="https://huggingface.co/spaces/SimulaMet-HOST/HockeyRink" style="color:blue;">https://huggingface.co/spaces/SimulaMet-HOST/HockeyRink</a> |
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</div> |
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This repository contains a YOLOv8-based model for detecting and mapping keypoints on ice hockey rinks. The model is trained on the HockeyRink dataset, which comprises precise annotations of hockey rink landmarks. |
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## Features |
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- Accurate detection of 56 keypoint landmarks on hockey rinks |
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- Real-time keypoint visualization with confidence scores |
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- Support for various camera angles and lighting conditions |
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- Handles player occlusions and dynamic game situations |
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- Trained on diverse SHL (Swedish Hockey League) game footage |
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## Model Details |
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- Architecture: YOLOv8-Large pose estimation |
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- Input: RGB images (any resolution) |
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- Output: 56 keypoint coordinates with confidence scores |
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- Average Performance: |
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- [email protected]: 97.48% |
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- [email protected]:0.95: 76.45% |
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- Precision: 96.21% |
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- Recall: 96.24% |
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## Applications |
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- Camera calibration and homography estimation |
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- 2D/3D scene mapping |
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- Player tracking and analysis |
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- Broadcast overlay generation |
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- Game analytics and statistics |
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- AR/VR applications |
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## Model Performance |
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- Performance tested across different hardware setups |
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- 13.64 FPS on Tesla T4 GPU |
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- 6.4 FPS on M3 MacBook Pro |
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- Handles varying lighting conditions and occlusions |
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<div style="background-color:#e7f3ff; color:black; border-left: 6px solid #0056b3; padding: 12px; margin: 10px 0;"> |
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<span style="color:black; font-weight:bold;">📩 For any questions regarding this project, or to discuss potential collaboration and joint research opportunities, please contact:</span> |
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<ul style="color:black;"> |
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<li><span style="font-weight:bold; color:black;">Mehdi Houshmand</span>: <a href="mailto:[email protected]" style="color:blue; text-decoration:none;">[email protected]</a></li> |
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<li><span style="font-weight:bold; color:black;">Cise Midoglu</span>: <a href="mailto:[email protected]" style="color:blue; text-decoration:none;">[email protected]</a></li> |
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<li><span style="font-weight:bold; color:black;">Pål Halvorsen</span>: <a href="mailto:[email protected]" style="color:blue; text-decoration:none;">[email protected]</a></li> |
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</ul> |
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</div> |
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