ConstructIQ Monitor - Construction Safety Detection (YOLOv11s)
This is a fine-tuned YOLOv11s object detection model designed specifically for construction site monitoring and safety compliance. It detects workers, heavy machinery, and Personal Protective Equipment (PPE) to automate hazard identification and site intelligence.
This model is a core component of the SiteSpectra / ConstructIQ computer vision pipeline.
🏗️ Supported Classes
The model detects 10 distinct classes relevant to construction reality-capture:
HardhatMaskNO-HardhatNO-MaskNO-Safety VestPersonSafety ConeSafety Vestmachineryvehicle
📊 Training & Validation Metrics
The model was fine-tuned for 20 epochs on a dataset of over 2,800 construction site images. It achieved strong validation metrics, particularly on critical safety and equipment classes:
- Overall mAP50: 80.6%
- Machinery mAP50: 92.0%
- Hardhat mAP50: 88.9%
- Safety Vest mAP50: 87.0%
- Person mAP50: 83.5%
🚀 How to Use
You can easily use this model in Python using the ultralytics library.
Installation
pip install ultralytics huggingface_hub
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from ultralytics import YOLOvv11 model = YOLOvv11.from_pretrained("sidaarth005/ConstructIQ-Monitor") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True)