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---
license: other
license_name: aplux-model-farm-license
license_link: https://aiot.aidlux.com/api/v1/files/license/model_farm_license_en.pdf
pipeline_tag: object-detection
tags:
- AIoT
- QNN
---
## PPE-Detection: Object Detection
PPE-Detection (Personal Protective Equipment Detection) is a computer vision-based technology designed to automatically identify whether personnel are wearing essential safety gear, such as helmets, reflective vests, goggles, masks, and gloves. Using deep learning algorithms (e.g., YOLO, Faster R-CNN), this technology enables real-time detection and classification of safety equipment in high-risk environments like construction sites, factories, and healthcare facilities, significantly reducing occupational hazards. The system analyzes data from cameras or drones, integrating object detection and semantic segmentation to pinpoint non-compliant behaviors and trigger immediate alerts. Key challenges include handling occlusions in complex scenarios, multi-scale object recognition, and optimizing cross-device deployment. With advancements in edge computing and lightweight models, PPE-Detection is evolving toward cost-effective, intelligent safety management solutions, enhancing compliance and operational safety standards globally.
### Source model
- Input shape: 1x3x320x192
- Number of parameters: 5.92M
- Model size: 23.64M
- Output shape: [1x21x40x24],[1x21x20x12],[1x21x10x6]
The source model can be found [here](https://github.com/quic/ai-hub-models/blob/main/qai_hub_models/models/gear_guard_net/model.py)
## Performance Reference
Please search model by model name in [Model Farm](https://aiot.aidlux.com/en/models)
## Inference & Model Conversion
Please search model by model name in [Model Farm](https://aiot.aidlux.com/en/models)
## License
- Source Model: [BSD-3-CLAUSE](https://github.com/quic/ai-hub-models/blob/main/LICENSE)
- Deployable Model: [APLUX-MODEL-FARM-LICENSE](https://aiot.aidlux.com/api/v1/files/license/model_farm_license_en.pdf)
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