Datasets:
metadata
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
Contact us via sales@trainingdata.pro or leave a request on https://trainingdata.pro/data-market to get the dataset**
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
Basketball Tracking might be made in accordance with your requirements.
TrainingData 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-pro