e-Lab Video Data Set(s)
We are building and releasing sophisticated video data sets to train machines to recognise objects in our environment. Check the download section below!
We are building and releasing sophisticated video data sets to train machines to recognise objects in our environment. Check the download section below!
Plant
Shoes
Soda-can
Currently, e-VDS35 has 35 classes and a total of 2050 videos of roughly 10 seconds each (see histogram below). We are aiming to collect overall 1750 (50 × 35) videos with your help.
In the section below "raw data" stands for the video as they have been provided to us; no filtering and variable formats. "Processed data" stands for "raw data" which minor sides have been resized to 256 px, videos with less than 144 frames have been removed, clips longer than 564 frames have been trimmed, and everything has been re-encoded in MP4.
We also provide access to a 33-class image data set (33-image-set.tar) of 300k images, subset of the Open Images data set, fetched with our 9M-URLs crawler. These classes are very similar to the ones found in e-VDS, and each one has roughly 10k training samples and up to 500 validation samples. Therefore, this data set can be used to improve generalisation of your model.
@misc{e-VDS,
author = {Culurciello, Eugenio and Canziani, Alfredo},
title = {{e-Lab} Video Data Set},
howpublished = {\url{https://engineering.purdue.edu/elab/eVDS/}},
year={2017}
}
Television
Cup
Chair
We greatly appreciate our contributors for having a huge impact on our video data set.
We ask you to record 10-second videos of various household objects you have at home. Please Choose one or more items from the left of the following diagram. These videos are currently the most sought after. Save files in directories with exactly the same names as the categories (you can download this ZIP or TGZ file containing all the empty folders you may need).
Shoot us an e-mail by clicking here or use the following email and subject:
with a link to an online storage service (DropBox, Google Drive, Box, MediFire, Backblaze and similar) so that we can get your clips and add you to the leaderboard.