Object Detection
ultralytics
PyTorch
English
yolo
yolov11
tennis
racket
tennis-ball
court-detection
sports
computer-vision
courtside
Eval Results (legacy)
Instructions to use Davidsv/CourtSide-Computer-Vision-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use Davidsv/CourtSide-Computer-Vision-v1 with ultralytics:
from ultralytics import YOLOvv11 model = YOLOvv11.from_pretrained("Davidsv/CourtSide-Computer-Vision-v1") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
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Fine-tuned YOLOv11n model for comprehensive tennis analysis with **10-class detection**: rackets, balls, and court zones. The most complete model in the CourtSide Computer Vision suite.
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## Model Details
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- **Model Name**: CourtSide Computer Vision v1
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Fine-tuned YOLOv11n model for comprehensive tennis analysis with **10-class detection**: rackets, balls, and court zones. The most complete model in the CourtSide Computer Vision suite.
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## Model Details
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- **Model Name**: CourtSide Computer Vision v1
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