Safety Helmet Detection for Construction Sites
Dataset of annotated site images for the automatic detection of safety helmets worn by workers.
Approximately 19,700 annotated images, annotations in YoLov5 format
Attribution 4.0 International (CC BY 4.0)
Description
The dataset Safety Helmet Detection for Construction Sites contains approximately 19,700 images annotated in YoLov5 format. It is specifically designed to detect safety helmets on construction sites, targeting industrial and construction environments. Precise annotations make it easy to train computer vision models for safety compliance.
What is this dataset for?
- Automating helmet detection to improve safety on construction sites
- Improving regulatory oversight and compliance at industrial sites
- Develop computer vision systems for industrial AI and object detection
Can it be enriched or improved?
Yes, it is possible to add additional annotations for other security equipment, to enrich the dataset with images from other environments, or to customize the categories of detected objects. Manual annotation also makes it possible to improve the quality and diversity of examples.
🔎 In summary
🧠 Recommended for
- Computer vision researchers
- Industrial AI developers
- On-site safety projects
🔧 Compatible tools
- YoloV5
- PyTorch
- TensorFlow
- Roboflow
- OpenCV
💡 Tip
To improve robustness, combine this dataset with other images of security equipment in a varied environment.
Frequently Asked Questions
Can this dataset be used to detect other security equipment?
Yes, by adding specific annotations, it is possible to extend the detection to other equipment such as gloves or glasses.
Is the dataset only suitable for YOLO models?
No, although formatted for YoLov5, images and annotations can be converted for other detection frameworks.
Is commercial use allowed with this dataset?
Yes, the CC BY 4.0 license allows commercial use as long as the attribution is respected.
