tensorflow / tensorflow/datasets
[data request] Kinetics
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- Dominant language
- Python
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Description
- Name of dataset: Kinetics400, Kinetics600, Kinetics700
- URL of dataset: https://www.deepmind.com/open-source/kinetics
- License of dataset: licensed by Google Inc. under a Creative Commons Attribution 4.0 International License
- Short description of dataset and use case(s): A collection of large-scale, high-quality datasets of URL links of up to 650,000 video clips that cover 400/600/700 human action classes, depending on the dataset version. The videos include human-object interactions such as playing instruments, as well as human-human interactions such as shaking hands and hugging. Each action class has at least 400/600/700 video clips. Each clip is human annotated with a single action class and lasts around 10 seconds. Uses cases are mostly for video classification and video representation learning.
I saw this issue was opened in 2019 (https://github.com/tensorflow/datasets/issues/139#issue-416828841), however, since there is still no update, opened a new issue. I am at the same time working on adding this dataset to tfds, and if I make progress, I will write an update.
Folks who would also like to see this dataset in tensorflow/datasets, please thumbs-up so the developers can know which requests to prioritize.
And if you'd like to contribute the dataset (thank you!), see our guide to adding a dataset.
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start with docs/add_dataset.md, the guide linked in the issue, and review the Kinetics400, Kinetics600, and Kinetics700 dataset details, URL, and license. Done means the requested Kinetics dataset contribution is added to tensorflow/datasets with its video-classification and representation-learning use cases supported.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, tensorflow
- Domain
- data, machine-learning
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100