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metadata
license: mit
language:
  - en
  - zh
tags:
  - yolov8
  - tfjs
  - hard-hat
  - ultralytics
  - yolo
  - object-detection
library_name: ultralytics
library_version: 8.0.23
inference: false
datasets:
  - keremberke/hard-hat-detection
model-index:
  - name: keremberke/yolov8n-hard-hat-detection
    results:
      - task:
          type: object-detection
        dataset:
          type: keremberke/hard-hat-detection
          name: hard-hat-detection
          split: validation
        metrics:
          - type: precision
            value: 0.83633
            name: [email protected](box)

This model is built using tfjs and is based on the YOLOv8n architecture. It is capable of detecting two classes of objects: people wearing safety helmets and those who are not.

该模型使用tfjs构建,基于YOLOv8n架构,可以检测两类物体:戴安全帽的人和未戴安全帽的人。

This model is converted from https://huggingface.co/keremberke/yolov8n-hard-hat-detection

该模型转换自 https://huggingface.co/keremberke/yolov8n-hard-hat-detection

keremberke/yolov8n-hard-hat-detection

Supported Labels

["Hardhat", "NO-Hardhat"]

How to use