Global License Plate Dataset

Fuente: arXiv
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Main Author: Agrawal, Siddharth
Format: Preprint
Published: 2024
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author Agrawal, Siddharth
author_facet Agrawal, Siddharth
contents In the pursuit of advancing the state-of-the-art (SOTA) in road safety, traffic monitoring, surveillance, and logistics automation, we introduce the Global License Plate Dataset (GLPD). The dataset consists of over 5 million images, including diverse samples captured from 74 countries with meticulous annotations, including license plate characters, license plate segmentation masks, license plate corner vertices, as well as vehicle make, colour, and model. We also include annotated data on more classes, such as pedestrians, vehicles, roads, etc. We include a statistical analysis of the dataset, and provide baseline efficient and accurate models. The GLPD aims to be the primary benchmark dataset for model development and finetuning for license plate recognition.
format Preprint
id arxiv_https___arxiv_org_abs_2405_10949
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Global License Plate Dataset
Agrawal, Siddharth
Computer Vision and Pattern Recognition
In the pursuit of advancing the state-of-the-art (SOTA) in road safety, traffic monitoring, surveillance, and logistics automation, we introduce the Global License Plate Dataset (GLPD). The dataset consists of over 5 million images, including diverse samples captured from 74 countries with meticulous annotations, including license plate characters, license plate segmentation masks, license plate corner vertices, as well as vehicle make, colour, and model. We also include annotated data on more classes, such as pedestrians, vehicles, roads, etc. We include a statistical analysis of the dataset, and provide baseline efficient and accurate models. The GLPD aims to be the primary benchmark dataset for model development and finetuning for license plate recognition.
title Global License Plate Dataset
topic Computer Vision and Pattern Recognition
url https://arxiv.org/abs/2405.10949