---
license: cc-by-nc-nd-4.0
task_categories:
- image-classification
language:
- en
tags:
- object detection
- Basketball Tracking
- deep learning
- multi-object tracking
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
size_categories:
- 1K<n<10K
---

# 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.

# 💴 For Commercial Usage: To discuss your requirements, learn about the price and buy the dataset, leave a request on **[our website](https://unidata.pro/datasets/?utm_source=huggingface-td&utm_medium=referral&utm_campaign=basketball_tracking)** to buy the dataset

![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2Fea2edf89c2283260b8849c9b4f30f02e%2Fres.gif?generation=1690705622031552&alt=media)

# 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
![](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.

# 💴 Buy the Dataset: This is just an example of the data. Leave a request on **[our website](https://unidata.pro/datasets/?utm_source=huggingface-td&utm_medium=referral&utm_campaign=basketball_tracking)** to discuss your requirements, learn about the price and buy the dataset
Leave a request on [our website](https://unidata.pro/datasets/?utm_source=huggingface-td&utm_medium=referral&utm_campaign=basketball_tracking) to discuss your requirements, learn about the price and buy the dataset.

## [Our Team](https://unidata.pro/datasets/?utm_source=huggingface-td&utm_medium=referral&utm_campaign=basketball_tracking) provides high-quality data annotation tailored to your needs


*keywords: object detection dataset, tracking dataset, detection annotations, deep learning object tracking, multi-object tracking dataset, labeled web tracking dataset, large-scale object tracking dataset, sports datasets, sports actions dataset, sports data action detection, sports analytics dataset, sports management, sports classification dataset, sports scene, image dataset, basketball team performance, basketball game dataset, player tracking data*