University of Windsor researchers released SH17, a 8,099-image open dataset for AI-driven detection of personal protective equipment (PPE) in manufacturing settings.
Key Details
- 1SH17 includes 8,099 images with 75,994 labeled PPE and body part instances across 17 categories.
- 2Dataset covers diverse PPE, such as helmets, gloves, safety glasses, and small items like earmuffs.
- 3AI models (e.g., YOLOv9) trained on SH17 achieved mean average precision of 70.9%.
- 4Images were sourced globally to reduce bias and reflect real-world manufacturing conditions.
- 5Both the dataset and trained model weights are publicly available for further research and development.
Why It Matters
SH17 offers a valuable resource for advancing vision-based PPE detection in industrial settings, demonstrating strong generalization and supporting scalable, non-invasive worker safety solutions. Its release enables further research and deployment of AI monitoring in manufacturing, potentially reducing accidents and improving compliance.
Source
EurekAlert
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