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Basketball Tracking, Object Detection dataset
Tracking is a deep learning process where the algorithm tracks the movement of an object.
The dataset consist of screenshots from videos of basketball games with the ball labeled with a bounging box. The dataset can be used to train a neural network in ball control recognition. The dataset is useful for automating the camera operator's work during a match, allowing the ball to be efficiently kept in frame.
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Dataset structure
- images - contains of original images of basketball players.
- boxes - includes bounding box labeling for a ball in the original images.
- annotations.xml - contains coordinates of the boxes and labels, created for the original photo
Data Format
Each image from img folder is accompanied by an XML-annotation in the annotations.xml file indicating the coordinates of the bounding boxes for the ball position. For each point, the x and y coordinates are provided.
Attributes
- occluded - the ball visability (true if the the ball is occluded by 30%)
- basket - the position related to the basket (true if the ball is covered with a basket on any distinguishable area)
Example of XML file structure
Basketball Tracking might be made in accordance with your requirements.
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