Need help with sports-1m-dataset?
Click the “chat” button below for chat support from the developer who created it, or find similar developers for support.
gtoderici

Description

Automatically exported from code.google.com/p/sports-1m-dataset

215 Stars 57 Forks Other 6 Commits 4 Opened issues

Services available

Need anything else?

The YouTube Sports-1M Dataset

We provide links to 1,133,158 YouTube videos annotated with 487 sports labels. The annotations were generated automatically using the the YouTube Topics, which has a public API accessible at:

https://developers.google.com/youtube/v3/guides/searchingbytopic

Compression: in order to save space, we compressed all the text files referenced below via gzip. To decompress run gzip -d in order to obtain the original filename that we refer to below.

The files included in this package are:

original/testpartition.txt - this contains the testing partition. original/trainpartition.txt - this contains the training partition.

The format for the training/testing partitions is as follows: URL

For example, the following line is a valid input: https://www.youtube.com/watch?v=UDqivjS-lpI 168,169

This assigns labels 168, and 169 to the video found at given URL.

labels.txt - this file contains the human-readable labels for the train/test partitions. The first line in the file is assumed to correspond to label 0 (boomerang), and the last corresponds to index 486 (model aircraft).

sports_mids.txt - this file contains the Machine IDs necessary to retrieve videos from youtube.com via the topics search API. Each line contains the human-readable class name, and the YouTube topic ID, which may be used to directly retrieve videos for the given class using the API below:

https://developers.google.com/youtube/v3/guides/searchingbytopic

Extra files: cross-validation/all_urls.txt - all URLs and labels bundled together (good starting point if you want to make cross-validation partitions). The format is as explained above.

cross-validation/sportsXtrain.txt & cross-validation/sportsXtest.txt for X having values from 0 to 9. These are partitions for 10-fold cross-validation. Since a video may have more than one label, it may appear both in training and in testing. For example, video ABPsSSS2uY0 appears in fold 0 with class 49 for training and class 26 for testing.

Additional Information

Wiki page: https://github.com/gtoderici/sports-1m-dataset/blob/wiki/ProjectHome.md

Citation: @inproceedings{KarpathyCVPR14, title = {Large-scale Video Classification with Convolutional Neural Networks}, author = {Andrej Karpathy and George Toderici and Sanketh Shetty and Thomas Leung and Rahul Sukthankar and Li Fei-Fei}, year = {2014}, booktitle = {CVPR} }

Supplemental materials: http://cs.stanford.edu/people/karpathy/deepvideo/

License

This data set is made available under a Creative Commons License: http://creativecommons.org/licenses/by/3.0/

Attribution 3.0 Unported (CC BY 3.0) Human-Readable Summary

You are free: - to Share -- to copy, distribute and transmit the work; - to Remix -- to adapt the work; and to make commercial use of the work.

Under the following conditions:

  • Attribution -- You must attribute the work in the manner specified by the author or licensor (but not in any way that suggests that they endorse you or your use of the work).

With the understanding that:

  • Waiver -- Any of the above conditions can be waived if you get permission from the copyright holder.

  • Public Domain -- Where the work or any of its elements is in the public domain under applicable law, the status is in no way affected by the license.

  • Other Rights -- In no way are any of the following rights affected by the license:

    • Your fair dealing or fair use rights, or other applicable copyright exceptions and limitations;
    • The author's moral rights;
    • Rights other persons may have either in the work itself or in how the work is used, such as publicity or privacy rights.
  • Notice -- For any reuse or distribution, you must make clear to others the license terms of this work. The best way to do this is with a link to this web page: http://creativecommons.org/licenses/by/3.0/

We use cookies. If you continue to browse the site, you agree to the use of cookies. For more information on our use of cookies please see our Privacy Policy.