RoboflowSports

Computer vision toolkit for sports analysis.

CommonProductImageComputer VisionSports Analysis

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.

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.

\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.\

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.

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.

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