This is a fork of the h36m-fetch tool by Aiden Nibali. Main difference is that the tar files are extracted in a manner such that subject based folder structure is preserved. Further it does not process the dataset in any manner, simply downloads and extracts the archives.

Human3.6M dataset fetcher

Human3.6M is a 3D human pose dataset containing 3.6 million human poses and corresponding images. The scripts in this repository make it easy to download, extract, and preprocess the images and annotations from Human3.6M.

Please do not ask me for a copy of the Human3.6M dataset. I do not own the data, nor do I have permission to redistribute it. Please visit http://vision.imar.ro/human3.6m/ in order to request access and contact the maintainers of the dataset.

Requirements

• Python 3
• requests
• tqdm
• axel

Alternatively, a Dockerfile is provided which has all of the requirements set up.

Usage

1. Firstly, you will need to create an account at http://vision.imar.ro/human3.6m/ to gain access to the dataset.

2. Once your account has been approved, log in and inspect your cookies to find your PHPSESSID.

3. Copy the configuration file config.ini.example to config.ini and fill in your PHPSESSID.

4. Build the docker container (must be in root of this repo)

docker-compose build

5. Use the download_all.py script to download the dataset as such:

$ docker-compose run --rm --user="$(id -u):$(id -g)" main python3 download_all.py

6. Extract the files using the provided script.

./extract_all.sh --source=archives --destination=/somewhere/Human3.6M

License

The code in this repository is licensed under the terms of the Apache License, Version 2.0.

Please read the license agreement for the Human3.6M dataset itself, which specifies citations you must make when using the data in your own research. The file metadata.xml is directly copied from the "Visualisation and large scale prediction software" bundle from the Human3.6M website, and is subject to the same license agreement.