Download Dlib C++ Library – Machine Learning and Computer Vision Toolkit

Dlib is a modern, open-source C++ toolkit containing machine learning algorithms, image processing tools, and numerical optimization methods designed for real-world production use. Created by Davis King, it is one of the most widely used C++ libraries for computer vision and machine learning, valued for its clean API, thorough documentation, and high-performance implementations.

Dlib includes a state-of-the-art face detection and facial landmark estimation system, deep neural network training and inference support, support vector machines (SVM), image processing filters, and a wide variety of optimization algorithms. It is also accessible from Python via the dlib Python bindings, making it popular in the data science and AI research communities.

Dlib powers facial recognition, object detection, pose estimation, and many other computer vision applications in research, industry, and open-source projects worldwide. It compiles on Windows, Linux, and macOS and integrates easily with OpenCV.

Key Features

• State-of-the-art face detection (HOG + SVM and CNN-based) and 68-point facial landmark detection
• Deep neural network (DNN) framework for training and running custom models
• Support Vector Machines (SVM) for classification and regression tasks
• Image processing: filtering, feature extraction, histogram of oriented gradients (HOG)
• Numerical optimization algorithms including BFGS, conjugate gradient, and more
• Python bindings available via pip for easy integration in data science workflows
• Cross-platform — compiles on Windows, Linux, and macOS with minimal dependencies

How to Install

1. Click the download button below to get the Dlib source code archive.
2. For Python use, install via pip: pip install dlib (requires CMake and a C++ compiler).
3. For C++ projects, include the dlib headers and build using CMake: cmake .. && cmake --build .
4. Link your C++ project against dlib and include the desired headers (e.g., dlib/image_processing.h).
5. Refer to the extensive official documentation and examples at dlib.net to get started quickly.