Dataset for Motorcycle Helmet Detection Project
910 Videoclips, 52800 Images for Computer Vision
Kaggle Notebooks for Machine Learning Code
The HELMET dataset, available on Kaggle, contains an impressive collection of 910 videoclips of motorcycle traffic recorded at 12 observation points. From these videos, researchers have extracted 52800 images at a rate of 2 frames per second, providing a rich dataset for computer vision projects.
For those seeking a practical application, the Bike Helmet Detection Computer Vision Project on Kaggle offers an excellent starting point. This project leverages the HELMET dataset to train machine learning models for detecting whether a motorcyclist is wearing a helmet or not.
Kaggle Notebooks provide a convenient platform to explore and run machine learning code. By utilizing data from multiple sources, including the HELMET dataset, researchers can develop and refine their models with ease.
Furthermore, the SCAU Helmet Detection on Motorcyclists (SCAU-HDM) dataset is a valuable benchmark dataset for helmet detection research. Its availability has contributed to the advancement of computer vision models for improving motorcycle safety and reducing helmetless riding.
The lack of comprehensive motorcycle helmet use data remains a significant concern worldwide for governments and policymakers. The HELMET dataset and related computer vision projects are valuable tools in addressing this issue by providing data for analysis and developing effective interventions to promote helmet use.
0 Komentar