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Coreml YOLOv3
C
Coreml YOLOv3
Developed by apple
YOLOv3 is an efficient object detection model capable of real-time localization and classification of 80 different objects in images.
Downloads 53
Release Time : 6/13/2024
Model Overview
YOLOv3 (You Only Look Once version 3) is a popular real-time object detection model that predicts both object locations and categories in a single forward pass. Known for its speed and accuracy, it is suitable for various real-time vision tasks.
Model Features
Real-time detection
Performs object localization and classification in a single forward pass for efficient real-time processing.
Multi-scale prediction
Uses multi-scale feature fusion to improve detection capability for objects of varying sizes.
80-class object recognition
Can identify and classify 80 common object categories from the COCO dataset.
Multiple precision versions
Offers full-precision (32-bit), half-precision (16-bit), and 8-bit quantized versions to meet different hardware requirements.
Model Capabilities
Real-time object detection
Multi-object recognition
Object localization
Image analysis
Use Cases
Smart surveillance
Real-time security monitoring
Detects and tracks objects like people and vehicles in surveillance camera feeds
Can identify multiple security-related objects in real-time
Mobile applications
AR application object recognition
Identifies environmental objects in augmented reality applications
Provides environmental awareness for AR interactions
Autonomous driving
Road object detection
Identifies vehicles, pedestrians, traffic signs, etc. on roads
Provides environmental perception input for autonomous driving systems
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