Datasets:
Training Data
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README.md
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license: cc-by-nc-nd-4.0
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---
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---
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license: cc-by-nc-nd-4.0
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task_categories:
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- image-classification
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language:
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- en
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tags:
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- code
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---
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# Basketball Tracking
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## Tracking is a deep learning process where the algorithm tracks the movement of an object.
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The dataset consist of screenshots from videos of basketball games with the ball labeled with a bounging box.
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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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# Get the Dataset
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## This is just an example of the data
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## Contact us via **[sales@trainingdata.pro](mailto:sales@trainingdata.pro)** or leave a request on **[https://trainingdata.pro/data-market](https://trainingdata.pro/data-market?utm_source=kaggle) to get the dataset**
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# Dataset structure
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- **img** - contains of original images of basketball players.
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- **boxes** - includes bounding box labeling for a ball in the original images.
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- **annotations.xml** - contains coordinates of the boxes and labels, created for the original photo
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# Data Format
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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.
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### Attributes
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- **occluded** - the ball visability (*true* if the the ball is occluded by 30%)
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- **basket** - the position related to the basket (*true* if the ball is covered with a basket on any distinguishable area)
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# Example of XML file structure
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# Basketball Tracking might be made in accordance with your requirements.
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## **[TrainingData](https://trainingdata.pro/data-market?utm_source=kaggle)** provides high-quality data annotation tailored to your needs
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