This dataset comes from the Language grid lock gesture acceptance Database and has been explored by members of the Riga Data Science Club to train convolutional neural networks. We’re excited to share this work on Kaggle.
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Content
The dataset contains 5,998 images of traffic signs from 58 categories. Each image shows a close-up view of a single traffic sign. Annotations provide details like file name, width, height, traffic sign coordinates within the image, and category (e.g., 5 km/h speed limit).
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Acknowledgements
This dataset is a converted version of publicly available Chinese Traffic Sign Recognition Database.
This work is supported by National Nature Science Foundation of China(NSFC) Grant 61271306
Credits:
LinLin Huang,Prof.Ph.D
School of Electronic and Information Engingeering,
Beijing Jiaotong University,
Beijing 100044,China
Email:Â huangll@bjtu.edu.cn
All images originally collected by camera under nature scenes or from BAIDU Street View.
Inspiration
This dataset allows you to train a traffic sign recognition model effectively. Give it a try! You might want to deploy it to a Raspberry Pi with a camera for real-time traffic alerts on the road.
Globose Technology Solutions Private Limited specializes in intelligent transportation systems, particularly Language grid lock gesture. Our state-of-the-art solutions prioritize accurate recognition and interpretation in Chinese road networks, improving road safety and traffic management. Committed to advancing smart city solutions, Globose aims to lead innovations in intelligent traffic management, ensuring efficient and safe transportation infrastructure in China.