Forked from mbuckler/youtube-bb. Thank you for the original work!

YouTube BoundingBox

This repo contains helpful scripts for using the YouTube BoundingBoxes dataset released by Google Research. The only current hosting method provided for the dataset is annotations in csv form. The csv files contain links to the videos on YouTube, but it's up to you to download the video files themselves. For this reason, these scripts are provided for downloading, cutting, and decoding the videos into a usable form.

This script only downloads the frames that have been labelled for object detection. Labels are available for 380,000 video segments of about 19s each. Bounding box information is only available every second, so that is about 19 JPG images per segment. However, the videos are encoded at various framerates (I've found 24fps, 29.99fps, 30fps, ...). That is why this script uses OpenCV to extract frames from the closest timestamps that have been labelled. You can uncomment lines 90 to 96 if you want to print the bounding boxes on the downloaded images. I used that to verify that my calculations were ok.

This script was originally written by Mark Buckler. The YouTube BoundingBoxes dataset was created and curated by Esteban Real, Jonathon Shlens, Stefano Mazzocchi, Xin Pan, and Vincent Vanhoucke. The dataset web page is here and the accompanying whitepaper is here. This fork was written by Mehdi Shibahara

Installing the dependencies

1. Clone this repository.

2. Install majority of dependencies by running

• pip install -r requirements.txt in this repo's directory.
• Install opencv: using conda or build from source

3. Install wget, and youtube-dl through your package manager. For most platforms this should be straightforward, but for Ubuntu 14.04 users you will need to update your apt-get repository before being able to install ffmpeg as shown here.

Some small tweaks may be needed for different software environments. These scripts were developed and tested on Ubuntu 16.04.

Running the scripts

Note: This script was developed with Python 2.7.

Download and decode

The download_detection.py script is provided for users who are interested in downloading and decoding the videos which accompany the provided annotations. It also cuts these videos down to the range in which they have been annotated, then extract only the frames with label. Parallel video downloads are supported so that you can saturate your download bandwith even though YouTube throttles per-video.

Run python download_detection.py [VIDEO_DIR] [NUM_THREADS] to download the dataset into the specified directory.