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
Supported Labels
["Hardhat", "NO-Hardhat"]
How to use
- Clone this github repo
- Read this repo readme