Lixin Yang* · Kailin Li* · Xinyu Zhan* · Fei Wu · Anran Xu . Liu Liu · Cewu Lu
This repo contains the OakInk data toolkit (oikit) -- a Python package that provides data loading, splitting, and visualization tools for the OakInk knowledge repository.
OakInk contains three parts:
Clone the repo
$ git clone https://github.com/lixiny/OakInk.git
docs/install.md
docs/datasets.md
# visualize OakInk-Image mesh on sequence level:
# * --draw_mode [mesh, wireframe] to switch between mesh and wireframe
# * --seq_id: select sequence id from OAKINK_DIR/image/anno/seq_status.json to visualize
# * --view_id: select from [0, 1, 2, 3] for visualize from different views.
python scripts/viz_oakink_image_seq.py --draw_mode mesh --view_id 1
# use OakInkImage to load data_split: train, mode: subject (SP1) and visualize:
# * --data_split: select from [train, val, test, all]
# * --mode_split: select from [default, object, subject, handobject]
python scripts/viz_oakink_image.py --data_split train --mode_split subject
# use OakInkShape to load object category: teapot and intent: use:
# * --categories: select from OAKINK_DIR/shape/metaV2/yodaobject_cat.json, or "all"
# * --intent_mode: select from [use, hold, liftup, handover] or "all"
# * --data_split: select from [train, val, test, all]
python scripts/viz_oakink_shape.py --categories teapot --intent_mode use
# press `N` to load next sample
# use OakInkShape to load all the training grasps
python scripts/viz_oakink_shape.py --categories all --data_split train
# use OakInkShape to load all the training grasps in handover
python scripts/viz_oakink_shape.py --categories all --data_split train --intent_mode handover
If you find OakInk dataset and oikit useful for your research, please considering cite us:
@inproceedings{YangCVPR2022OakInk,
author = {Yang, Lixin and Li, Kailin and Zhan, Xinyu and Wu, Fei and Xu, Anran and Liu, Liu and Lu, Cewu},
title = {{OakInk}: A Large-Scale Knowledge Repository for Understanding Hand-Object Interaction},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
year = {2022},
}