Yolov9 C All
Object detection model based on YOLOv9, adapted for Transformers.js, capable of running in a browser
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Release Time : 2/26/2024
Model Overview
YOLOv9 is an efficient object detection model. This version is in ONNX format, optimized for web use, and can detect various common objects in images in real-time
Model Features
Browser Execution
Perform object detection directly in the browser via Transformers.js without server support
Real-time Detection
Optimized ONNX version enables near real-time object detection performance
Multi-class Recognition
Capable of detecting various common objects including vehicles, pedestrians, traffic signs, etc.
Model Capabilities
Image Object Detection
Multi-class Recognition
Bounding Box Prediction
Confidence Scoring
Use Cases
Smart Transportation
Traffic Monitoring
Real-time analysis of vehicles and pedestrians in road surveillance footage
Accurately identifies vehicle types and pedestrian locations
Security Surveillance
Intrusion Detection
Detect abnormal persons and objects in monitored areas
Provides precise location information of suspicious targets
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