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Yolov8m Protective Equipment Detection

Developed by keremberke
An object detection model based on YOLOv8m, specifically designed for detecting protective equipment and its absence.
Downloads 405
Release Time : 1/29/2023

Model Overview

This model can detect protective equipment (such as gloves, goggles, helmets, masks, shoes) and their absence in images, suitable for safety monitoring and compliance inspection scenarios.

Model Features

Multi-category Detection
Capable of detecting 10 different types of protective equipment and their absence simultaneously.
Based on YOLOv8 Architecture
Utilizes the advanced YOLOv8m architecture, balancing detection accuracy and inference speed.
Adjustable Parameters
Supports adjusting confidence thresholds, IoU thresholds, and other parameters to adapt to different application scenarios.

Model Capabilities

Image Analysis
Object Detection
Safety Equipment Recognition
Compliance Inspection

Use Cases

Industrial Safety
Construction Site Safety Monitoring
Automatically detects whether workers are wearing necessary protective equipment.
Improves construction site safety compliance.
Factory Safety Inspection
Monitors the wearing of protective equipment by production line employees.
Reduces workplace accidents.
Medical Environment
Hospital Protective Monitoring
Detects the wearing of protective equipment such as masks and gloves by medical staff.
Ensures infection control measures are implemented.
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