RoboflowSports
R
Roboflowsports
Overview :
roboflow/sports is an open-source computer vision toolkit focused on applications in the sports domain. It employs advanced image processing techniques, such as object detection, image segmentation, and keypoint detection, to tackle challenges in sports analysis. Developed by Roboflow, this toolkit aims to promote the application of computer vision technologies in sports and is continuously optimized through community contributions.
Target Users :
Target audience includes sports analysts, data scientists, and computer vision researchers. They can utilize this toolkit to enhance the accuracy and efficiency of sports game analysis, extract essential data, and provide valuable insights for coaches and athletes.
Total Visits: 474.6M
Top Region: US(19.34%)
Website Views : 46.6K
Use Cases
Use the ball tracking feature to analyze passes and shots in a soccer match.
Quickly compile scoring statistics in a basketball game using jersey number recognition technology.
Assess player performance and movement patterns in a football game using player tracking technology.
Features
Ball tracking: Track small and fast-moving balls in high-resolution videos.
Jersey number recognition: Accurately read jersey numbers even in cases of video blur, player rotations, or obscured numbers.
Player tracking: Maintain consistent player identification throughout the match despite potential obstructions from other players or objects on the field.
Player re-identification: Identify players who leave and re-enter the frame, especially when the camera moves or when players have similar appearances.
Camera calibration: Accurately adjust camera perspectives to extract advanced statistics such as player speed and movement distance.
How to Use
1. Visit Roboflow Universe to explore sports-related datasets.
2. Set up a Python environment, ensuring the version is 3.8 or higher.
3. Install the roboflow/sports toolkit from the source code.
4. Choose and apply tools such as object detection and image segmentation based on specific needs.
5. Use the example code in the toolkit or create custom scripts to perform specific tasks.
6. Analyze the results to extract key data and insights.
7. Optimize sports strategies or conduct further research based on the analysis results.
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