Darknet is an open source neural network framework written in C and CUDA, developed by Joseph Redmon. It is best known as the original implementation of the YOLO (You Only Look Once) real-time object detection system. Darknet is lightweight, fast, and easy to compile, making it suitable for research and production use. The repository provides pre-trained models, configuration files, and tools for training custom object detection models. With GPU acceleration via CUDA and OpenCV integration, it achieves high performance in image recognition tasks. Its simplicity, combined with powerful capabilities, has made Darknet one of the most influential projects in the computer vision community.
Features
- Provides fast training and inference for neural networks
- Supports both CPU and GPU acceleration
- Includes the YOLO family of real-time object detectors
- Lightweight and easy to compile with minimal dependencies
- Offers pre-trained models for quick usage
- Written in C for efficiency with CUDA GPU support
Project Samples
License
GNU General Public License version 3.0 (GPLv3)Follow Darknet
You Might Also Like
Gen AI apps are built with MongoDB Atlas
MongoDB Atlas provides built-in vector search and a flexible document model so developers can build, scale, and run gen AI apps without stitching together multiple databases. From LLM integration to semantic search, Atlas simplifies your AI architecture—and it’s free to get started.
Rate This Project
Login To Rate This Project
User Reviews
Be the first to post a review of Darknet!