Product Detection In Shelf Yolov8
A retail shelf object detection model based on YOLOv8, capable of identifying empty shelves and product locations, suitable for inventory management in supermarkets and malls.
Downloads 43
Release Time : 8/12/2023
Model Overview
This model is specifically designed for retail environments, accurately detecting products on shelves and empty shelf areas, supporting real-time inventory management and shelf layout optimization.
Model Features
High-precision Detection
Achieves an accuracy of 0.91 on the mAP@0.5(box) metric, accurately identifying products on shelves and empty shelf areas.
Real-time Processing Capability
Supports real-time video stream processing, suitable for real-time inventory monitoring needs in malls and supermarkets.
Retail Scene Optimization
Specifically optimized for shelf scenarios in retail environments, capable of handling typical lighting and product placement conditions.
Model Capabilities
Shelf Product Detection
Empty Shelf Area Identification
Real-time Inventory Monitoring
Shelf Layout Analysis
Use Cases
Retail Inventory Management
Automated Inventory Counting
Monitors product quantities on shelves in real-time via cameras and automatically generates inventory reports.
Reduces manual inventory workload and improves inventory accuracy.
Out-of-Stock Alerts
Detects empty shelf areas and promptly alerts for restocking.
Reduces out-of-stock rates and increases sales opportunities.
Retail Space Optimization
Shelf Layout Analysis
Analyzes product placement effectiveness to optimize shelf space utilization.
Enhances product display effectiveness and increases sales.
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