YOLOv5 - AI Image Models Tool

Overview

YOLOv5 is a popular open-source AI tool for object detection, image segmentation, and image classification built on PyTorch. It supports exporting models to ONNX, CoreML, and TFLite and is documented to support research and practical deployment workflows.

Key Features

• Object detection, image segmentation, and image classification support
• PyTorch-based model building and deployment
• Exportable to ONNX, CoreML, and TFLite formats
• Well-documented repository for research and practical use
• Source code and examples available on GitHub

Ideal Use Cases

• Research and prototyping of computer vision models
• Deploying vision models on mobile and embedded platforms
• Training custom detectors on domain-specific datasets
• Integrating detection into robotics and automation pipelines

Getting Started

• Clone the official YOLOv5 GitHub repository
• Install Python and PyTorch dependencies per repository instructions
• Prepare and format your dataset following repository guidelines
• Train or fine-tune a model using provided training scripts
• Export the trained model to ONNX, CoreML, or TFLite for deployment
• Run inference using the repository's inference scripts or your integration

Pricing

Open-source project hosted on GitHub; no pricing information provided.

Limitations

• Requires familiarity with Python and PyTorch for training and customization
• No pricing or official commercial support information provided in repository

Key Information

• Category: Image Models
• Type: AI Image Models Tool