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ConstructIQ Monitor

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...

Fuentehuggingface.co/sidaarth005/ConstructIQ-Monitor/tree/c149e958c3ce309919596d8ba6c620ddf6a9cc85
TipoOtherVersiónRevision c149e95Bcalidad

Fuente del modelo

Tipo
Other
Tamaño del archivo
18,3 MB
Versión
vRevision c149e95
Actualizado
21 oct 2026
Descargas
43
Fuente
Hugging Face

Descripción de la fuente

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:

  • Hardhat
  • Mask
  • NO-Hardhat
  • NO-Mask
  • NO-Safety Vest
  • Person
  • Safety Cone
  • Safety Vest
  • machinery
  • vehicle

📊 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

Fuentes

1 fuente
Hugging FacePrincipalVersión c149e958c3ce309919596d8ba6c620ddf6a9cc85
huggingface.co/sidaarth005/ConstructIQ-Monitor/tree/c149e958c3ce309919596d8ba6c620ddf6a9cc85

Verificado 21 oct

Artefactos del modelo

1 artefacto

best.pt

pt · 18,3 MB · SHA-256 e23c372fcd12…5496 · Hugging Face

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Extractos de fuentes

3 extractos
Readme5 agohuggingface.co/sidaarth005/ConstructIQ-Monitor

--- language: - en license: mit library_name: ultralytics tags: - object-detection - yolo - yolov11 - computer-vision - construction - safety - ppe datasets: - roboflow/construction-site-safety metrics: - mAP50 --- # 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](https://github.com/2005legend/ConstructIQ-Monitor)** computer vision pipeline. ## 🏗️ Supported Classes The model detects 10 distinct classes relevant to construction reality-capture: - `Hardhat` - `Mask` - `NO-Hardhat` - `NO-Mask` - `NO-Safety Vest` - `Person` - `Safety Cone` - `Safety Vest` - `machinery` - `vehicle` ## 📊 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 ```bash pip install ultralytics huggingface_hub

Note21 octhuggingface.co/sidaarth005/ConstructIQ-Monitor

Source context: 43 downloads · 0 likes · Pipeline object-detection · Library ultralytics · Repo sidaarth005/ConstructIQ-Monitor

Note5 agohuggingface.co/sidaarth005/ConstructIQ-Monitor

Source context: 58 downloads · 0 likes · Pipeline object-detection · Library ultralytics · Repo sidaarth005/ConstructIQ-Monitor