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Hand Recognition Dataset for Machine Vision Researchers (YOLOv8 Format)

Alameer, Ali

Authors

Dr Ali Alameer A.Alameer1@salford.ac.uk
Lecturer in Artificial Intelligence



Abstract

This hand recognition dataset comprises a comprehensive collection of hand images from 65 individuals, including both left and right hands, annotated with YOLOv8 formatting.

The dataset encompasses 17 distinct classes, denoted as L-L1 to L-L9 for the left hand and R-R1 to R-R8 for the right hand. These classes capture various hand gestures and poses.

These images were captured using a standard mobile phone camera, offering a diverse set of images with varying angles and backgrounds. In total, the dataset comprises 405 high-quality images, with 222 representing left hands and 183 representing right hands. The left hand classes are distributed as follows: L-L1 (62 images), L-L2 (56 images), L-L3 (44 images), L-L4 (29 images), L-L5 (14 images), L-L6 (8 images), L-L7 (4 images), L-L8 (2 images), and L-L9 (3 images). Similarly, the right hand classes are distributed as R-R1 (53 images), R-R2 (48 images), R-R3 (38 images), R-R4 (24 images), R-R5 (14 images), R-R6 (4 images), R-R7 (1 image), and R-R8 (1 image).

We welcome the machine vision research community to utilise and build upon this dataset to advance the field of hand recognition and its applications.

Online Publication Date Oct 12, 2023
Publication Date Oct 12, 2023
Deposit Date Jan 20, 2025
DOI https://doi.org/10.17866/rd.salford.24032841.v1
Publisher URL https://salford.figshare.com/articles/dataset/Hand_Recognition_Dataset_for_Machine_Vision_Researchers_YOLOv8_Format_/24032841
Collection Date Oct 12, 2023