We test the installation with general requirements:
- Ubuntu 20.04 or newer
- Python >= 3.8
- CUDA >= 11.1
- PyTorch >= 1.9.1
There are two different ways to use oikit, i.e. stand-alone and import-as-package.
- The stand-alone will create an isolated conda env called:
oakink
, all the dependencies will be set up in this env.
If you are new to OakInk, use stand-alone installation. - The import-as-package will install oikit as a package in your current conda env.
We suppose that python, cudatookit, and pytorch have already been installed.
$ conda env create -f environment.yaml
$ conda activate oakink
$ pip install -r requirements.txt
This environment provide you a base environment to load and visualize the OakInk dataset.
⚠️ In this case, you need to use the oikit inside the OakInk directory.
In most cases, you want to use oikit in other conda env. To be able to import oikit, you need:
- activate the destination env (we suppose that python, cudatookit, and pytorch have already been installed)
- cd to the
OakInk
directory and run:pip install .
Get the MANO hand model mano_v1_2.zip
from the MANO website.
- click
Download
on the top menu, this requires register & login. - on the Download page, navigate to Models & Code section, and click
Models & Code
.
Unzip mano_v1_2.zip
and copy it into the assets
folder.