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Yolov5s Forklift

Developed by keremberke
A forklift object detection model based on YOLOv5s, suitable for forklift recognition and positioning in industrial scenarios.
Downloads 96
Release Time : 1/1/2023

Model Overview

This model is trained using the YOLOv5s architecture, specifically designed for detecting forklift targets in images or videos, applicable to industrial scenarios such as warehouse management and logistics monitoring.

Model Features

High-precision Detection
Achieves 83.8% mAP@0.5 accuracy on the forklift object detection dataset.
Real-time Performance
Based on the lightweight YOLOv5s architecture, suitable for real-time detection applications.
Industrial Scenario Optimization
Specially optimized for forklift targets in industrial scenarios.

Model Capabilities

Forklift detection in images
Object localization
Real-time video stream analysis

Use Cases

Industrial Automation
Warehouse Management
Automatically detect the position and quantity of forklifts in warehouses.
Improves warehouse operation efficiency and safety.
Logistics Monitoring
Monitor the movement and working status of forklifts in logistics centers.
Optimizes logistics scheduling and resource allocation.
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