• Git LFS
• Docker Engine

• curl -s https://packagecloud.io/install/repositories/github/git-lfs/script.deb.sh | sudo bash
• sudo apt-get install git-lfs
• git lfs install

• git lfs install --skip-smudge
• git clone https://github.com/ihdia/hindola.git
• git lfs pull
• git lfs install --force

Use the following link for detailed instructions on Docker installation: https://docs.docker.com/install/linux/docker-ce/ubuntu/

• Go to hindola/hindola
• If you want the GPU to be accessable through the docker container, then use the following link to install cuda and/or nvidia-docker2 libraries as necessary: https://devblogs.nvidia.com/gpu-containers-runtime/
• Or remove "--runtime=nvidia" (without the quotes) from hindola.sh file, if you don't want the GPU.
• Run ./hindola.sh
• After this step, you'll be asked to enter the absolute path to your dataset folder. Type it out and hit enter.
• Now, you'll be asked to enter the IP of your machine on the network you are connected to. Type it out and hit enter. If you want to run this tool only locally on a machine, just type out "0.0.0.0" (without the quotes).

• Run ./dataset_loader.sh

• If you have saved a session previously, run ./load.sh to resume.
• Password is 'root'.

• Run ./start.sh
• Use the same IP you used before to login through port 10000 on your host computer browser.

• Run ./stop.sh

• Run ./save.sh
• Password is 'root'.

• exit