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Yoloe 11l Seg

Developed by jameslahm
YOLOE is a real-time visual omni-model that supports various vision tasks including zero-shot object detection.
Downloads 219
Release Time : 3/15/2025

Model Overview

YOLOE is an efficient real-time visual model capable of performing multiple vision tasks, including zero-shot object detection. It combines advanced vision and language model technologies, making it suitable for scenarios requiring fast and accurate visual analysis.

Model Features

Real-time Performance
The model is designed with a focus on real-time processing capabilities, making it suitable for applications requiring quick responses.
Zero-shot Detection
Supports zero-shot object detection, enabling recognition of new objects without training on specific categories.
Multi-model Integration
Combines the strengths of advanced vision-language models such as CLIP and MobileCLIP.

Model Capabilities

Zero-shot Object Detection
Real-time Visual Analysis
Multi-category Object Recognition

Use Cases

Smart Surveillance
Real-time Anomaly Detection
Detects anomalous objects or behaviors in surveillance videos in real-time.
Can quickly identify anomalous objects not previously trained on
Retail Analytics
Product Recognition
Automatically identifies products on shelves, even new ones not previously trained on.
Reduces the need for manual labeling and improves recognition efficiency
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