metadata
license: other
license_name: other
license_link: https://github.com/hukenovs/hagrid/blob/master/license/en_us.pdf
dataset_info:
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': call
'1': dislike
'2': fist
'3': four
'4': grabbing
'5': grip
'6': hand_heart
'7': hand_heart2
'8': holy
'9': like
'10': little_finger
'11': middle_finger
'12': mute
'13': no_gesture
'14': ok
'15': one
'16': palm
'17': peace
'18': peace_inverted
'19': point
'20': rock
'21': stop
'22': stop_inverted
'23': take_picture
'24': three
'25': three2
'26': three3
'27': three_gun
'28': thumb_index
'29': thumb_index2
'30': timeout
'31': two_up
'32': two_up_inverted
'33': xsign
splits:
- name: train
num_bytes: 96145277803.94
num_examples: 821458
- name: validation
num_bytes: 11767694412.8
num_examples: 99200
- name: test
num_bytes: 19221400466
num_examples: 165500
download_size: 128293027578
dataset_size: 127134372682.74
configs:
- config_name: default
data_files:
- split: train
path: data/train/train-*
- split: validation
path: data/val/validation-*
- split: test
path: data/test/test-*
Dataset Description
Dataset Summary
HaGRIDv2 is a large-scale image dataset designed for hand gesture recognition (HGR). It contains 1,086,158 FullHD RGB images across 33 gesture classes and an additional "no_gesture" class, which represents natural hand postures. This dataset is ideal for developing HGR systems for applications like video conferencing, home automation, and automotive interfaces. While composed of static images, it also supports training models for dynamic gesture recognition.
Supported Tasks
- Image Classification: Classify images into one of the 33 gesture classes or the "no_gesture" class.
Citation Information
If you use this dataset, please cite the following:
@misc{nuzhdin2024hagridv21mimagesstatic,
title={HaGRIDv2: 1M Images for Static and Dynamic Hand Gesture Recognition},
author={Anton Nuzhdin and Alexander Nagaev and Alexander Sautin and Alexander Kapitanov and Karina Kvanchiani},
year={2024},
eprint={2412.01508},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2412.01508},
}
@InProceedings{Kapitanov_2024_WACV,
author = {Kapitanov, Alexander and Kvanchiani, Karina and Nagaev, Alexander and Kraynov, Roman and Makhliarchuk, Andrei},
title = {HaGRID -- HAnd Gesture Recognition Image Dataset},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year = {2024},
pages = {4572-4581}
}
More Information
For additional details and license, visit the GitHub repository.