UCF Sports Action Dataset

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Visualization of UCF SPORTS action dataset in the Deep Lake UI

UCF Sports Action dataset

What is UCF Sports Action Dataset?

The UCF Sports dataset includes many images of sports collected from different games which were highlighted on TV stations like the BBC and ESPN. The video arrangements were obtained from a wide scope of stock video sequence websites including BBC Motion display and GettyImages. The dataset contains 150 groupings with a resolution of 720 x 480. The collection represents a natural pool of actions featured in a wide range of scenes and viewpoints.

Download UCF Sports Action Dataset in Python

Instead of downloading the UCF Sports Action dataset in Python, you can effortlessly load it in Python via our Deep Lake open-source with just one line of code.

Load UCF Sports Action Dataset Training Subset in Python

				
					import deeplake
ds = deeplake.load('hub://activeloop/ucf-sports-action')

UCF Sports Action Dataset Structure

UCF Sports Action Data Fields

images: tensor containing the image.

boxes: tensor to represent bounding boxes.

labels: tensor to classify the activities.

UCF Sports Action Data Splits

The UCF Sports Action dataset training set is composed of 17270.

How to use UCF Sports Action Dataset with PyTorch and TensorFlow in Python

Train a model on UCF Sports Action dataset with PyTorch in Python

Let’s use Deep Lake built-in PyTorch one-line dataloader to connect the data to the compute:

				
					dataloader = ds.pytorch(num_workers=0, batch_size=4, shuffle=False)

Train a model on the UCF Sports Action dataset with TensorFlow in Python

				
					dataloader = ds.tensorflow()

Additional Information about UCF Sports Action Dataset

UCF Sports Action Dataset Description

Homepage: https://www.crcv.ucf.edu/data/UCF_Sports_Action.php

Paper: Khurram Soomro and Amir R. Zamir, Action Recognition in Realistic Sports Videos, Computer Vision in Sports, Springer International Publishing, 2014.

Point of Contact: N/A

UCF Sports Action Dataset Curators

Khurram Soomro and Amir R. Zamir

UCF Sports Action Dataset Licensing Information

Deep Lake users may have access to a variety of publicly available datasets. We do not host or distribute these datasets, vouch for their quality or fairness, or claim that you have a license to use the datasets. It is your responsibility to determine whether you have permission to use the datasets under their license.

If you’re a dataset owner and do not want your dataset to be included in this library, please get in touch through a GitHub issue. Thank you for your contribution to the ML community!

UCF Sports Action Dataset Citation Information

				
					@inproceedings{danielczuk2019segmenting,
  title={Action Recognition in Realistic Sports Videos},
  author={Khurram Soomro and Amir R. Zamir,},
  booktitle={Computer Vision in Sports, Springer International Publishing},
  year={2014}
}

UCF Sports Action Dataset FAQs

What is the UCF Sports Action dataset for Python?

The UCF Sports dataset is made of video sequences obtained from a wide scope of stock image websites including BBC Motion display and GettyImages. The dataset contains 150 groupings with a resolution of 720 x 480. The collection represents a natural pool of actions featured in a wide range of scenes and viewpoints.

How can I use UCF Sports Action dataset in PyTorch or TensorFlow?

You can stream the UCF Sports Action dataset while training a model in PyTorch or TensorFlow with one line of code using the open-source package Activeloop Deep Lake in Python. See detailed instructions on how to train a model on the UCF Sports Action dataset with PyTorch in Python or train a model on the UCF Sports Action dataset with TensorFlow in Python.