task_categories:image-classification language:en license:cc-by-nc-nd-4.0 code region:us
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.
@InProceedings{huggingface:dataset,
title = {basketball_tracking},
author = {TrainingDataPro},
year = {2023}
}
---
license: cc-by-nc-nd-4.0
task_categories:
- image-classification
language:
- en
tags:
- code
dataset_info:
  features:
  - name: image_id
    dtype: int32
  - name: image
    dtype: image
  - name: mask
    dtype: image
  - name: shapes
    dtype: string
  splits:
  - name: train
    num_bytes: 191244976
    num_examples: 70
  download_size: 191271989
  dataset_size: 191244976
---

# Basketball Tracking
## 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.

# Get the dataset

### This is just an example of the data

Leave a request on [**https://trainingdata.pro/data-market**](https://trainingdata.pro/data-market?utm_source=huggingface&utm_medium=cpc&utm_campaign=basketball_tracking) to discuss your requirements, learn about the price and buy the dataset.

![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2Ffebc78a960385a4fd6a0242b58c4056d%2Fbb.png?generation=1686731703497308&alt=media)

# Dataset structure
- **img** - 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
![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2F0d5c79a67be4c702b12540906b72c240%2Fcarbon.png?generation=1686731488719900&alt=media)

# Basketball Tracking might be made in accordance with your requirements.

## [TrainingData](https://trainingdata.pro/data-market?utm_source=huggingface&utm_medium=cpc&utm_campaign=basketball_tracking) provides high-quality data annotation tailored to your needs

More datasets in TrainingData's Kaggle account: **https://www.kaggle.com/trainingdatapro/datasets**

TrainingData's GitHub: **https://github.com/Trainingdata-datamarket/TrainingData_All_datasets**