Yolov5m Forklift
A forklift object detection model based on the YOLOv5m architecture, trained on the keremberke/forklift object detection dataset, achieving an mAP@0.5 of 0.85.
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Release Time : 1/1/2023
Model Overview
This model is specifically designed for detecting forklift targets in images or videos, suitable for forklift recognition and tracking in industrial scenarios.
Model Features
High-precision Detection
Achieves an mAP@0.5 of 0.85 on the validation set, accurately identifying forklift targets.
YOLOv5 Architecture
Based on the mature YOLOv5m architecture, balancing detection accuracy and inference speed.
Industrial Scenario Optimization
Specifically trained and optimized for forklift detection scenarios.
Model Capabilities
Image Object Detection
Forklift Recognition
Real-time Detection
Use Cases
Industrial Automation
Warehouse Forklift Monitoring
Automatically detects and tracks forklift positions in warehouse environments.
Improves warehouse management efficiency and safety.
Logistics Management
Tracks forklift usage in logistics centers.
Optimizes logistics resource allocation.
Safety Monitoring
Forklift Safety Zone Monitoring
Detects whether forklifts enter hazardous areas.
Prevents industrial accidents.
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