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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...

Fontehuggingface.co/sidaarth005/ConstructIQ-Monitor/tree/c149e958c3ce309919596d8ba6c620ddf6a9cc85
TipoOtherVersãoRevision c149e95Bnota

Fonte do modelo

Tipo
Other
Tamanho do arquivo
18,3 MB
Versão
vRevision c149e95
Atualizado
21 de out. de 2026
Downloads
43
Fonte
Hugging Face

Descrição da fonte

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

Fontes

1 fonte
Hugging FacePrimárioVersão c149e958c3ce309919596d8ba6c620ddf6a9cc85
huggingface.co/sidaarth005/ConstructIQ-Monitor/tree/c149e958c3ce309919596d8ba6c620ddf6a9cc85

Verificado 21 de out.

Artefatos de modelo

1 artefato

best.pt

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

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Trechos de fonte

3 trechos
Readme5 de ago.huggingface.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 de out.huggingface.co/sidaarth005/ConstructIQ-Monitor

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

Note5 de ago.huggingface.co/sidaarth005/ConstructIQ-Monitor

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