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---
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 # since mAP@0.5 is not available on hf.co/metrics
value: 0.83633 # min: 0.0 - max: 1.0
name: mAP@0.5(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
<div align="center">
<img width="640" alt="keremberke/yolov8n-hard-hat-detection" src="https://huggingface.co/keremberke/yolov8n-hard-hat-detection/resolve/main/thumbnail.jpg">
</div>
### Supported Labels
```JSON
["Hardhat", "NO-Hardhat"]
```
### How to use
- Clone [this github repo](https://github.com/lanseria/yolov8-tfjs-vue-webrtc-demo)
- Read this repo readme |