YOLOv5 - AI Vision Models Tool

Overview

YOLOv5 is an open-source AI toolkit for object detection, image segmentation, and image classification built on PyTorch. It supports export to ONNX, CoreML, and TFLite and includes documentation for research and practical deployment.

Key Features

• Object detection with YOLO architecture
• Image segmentation and classification support
• Built on PyTorch for model building and deployment
• Exports to ONNX, CoreML, and TFLite
• Well-documented repository for research and practical use

Ideal Use Cases

• Real-time object detection in video streams
• Edge and mobile deployment using TFLite or CoreML
• Prototype and benchmark new detection models
• Integrate detection into robotics and automation systems

Getting Started

• Clone the YOLOv5 GitHub repository
• Install Python and compatible PyTorch version
• Install repository requirements via pip
• Prepare dataset and annotations in supported format
• Train or use pretrained models provided in repo
• Export models to ONNX, CoreML, or TFLite for deployment

Pricing

Open-source project; no commercial pricing specified in the repository.

Key Information

• Category: Vision Models
• Type: AI Vision Models Tool