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--- |
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license: other |
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license_name: aplux-model-farm-license |
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license_link: https://aiot.aidlux.com/api/v1/files/license/model_farm_license_en.pdf |
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pipeline_tag: object-detection |
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tags: |
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- AIoT |
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- QNN |
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--- |
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## PPE-Detection: Object Detection |
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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. |
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### Source model |
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- Input shape: 1x3x320x192 |
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- Number of parameters: 5.92M |
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- Model size: 23.64M |
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- Output shape: [1x21x40x24],[1x21x20x12],[1x21x10x6] |
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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) |
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## Performance Reference |
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Please search model by model name in [Model Farm](https://aiot.aidlux.com/en/models) |
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## Inference & Model Conversion |
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Please search model by model name in [Model Farm](https://aiot.aidlux.com/en/models) |
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## License |
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- Source Model: [BSD-3-CLAUSE](https://github.com/quic/ai-hub-models/blob/main/LICENSE) |
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- Deployable Model: [APLUX-MODEL-FARM-LICENSE](https://aiot.aidlux.com/api/v1/files/license/model_farm_license_en.pdf) |
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