YOLOv8 - AI Vision Models Tool

Overview

YOLOv8 is a computer vision model for object detection, segmentation, pose estimation, and classification. It is designed for speed, accuracy, and ease of use and is maintained on GitHub.

Key Features

• Real-time object detection capabilities
• Instance and semantic segmentation support
• Pose estimation for keypoint detection
• Image classification models and workflows
• Designed for speed and inference efficiency
• Emphasis on accuracy across tasks
• User-friendly interfaces and example scripts

Ideal Use Cases

• Real-time object detection in video streams
• Instance segmentation for image analysis
• Human or object pose estimation applications
• Image classification for dataset labeling
• Rapid prototyping of vision models

Getting Started

• Clone the YOLOv8 GitHub repository
• Install required dependencies listed in the repo
• Choose a model variant or pretrained weights
• Prepare your dataset in a supported format
• Train or run inference using provided scripts
• Review examples and documentation in the repository

Key Information

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