dlib is a modern C++ toolkit for building real-world machine learning and data analysis applications. It provides machine learning algorithms and tools for creating complex C++ software that solves real-world problems.
Project overview
dlib deserves attention from developers who need a C++-focused toolkit for machine learning and data analysis, with documented paths for source builds, vcpkg, and Python use.
Project type
Data Processing · Infrastructure
Use cases
Data Analysis
Deployment
Refer to project documentation
License
BSL-1.0
Best for
Developers who need machine learning and data analysis tools for C++ applications, including complex software for real-world problems.
Key capabilities
Provides algorithms and tools for creating complex C++ software that solves real-world problems.
Supports compiling the dlib Python API for installation with pip and use in Python.
Provides example programs and a CMake tutorial for building C++ programs.
Provides a unit test suite that can be compiled and run to validate library functionality.
Limitations and risks
Visual Studio users should usually perform their work in 64-bit mode.
Getting started
Install with vcpkg or pip, or compile from source with CMake; then build the examples and execute the compiled programs. Source builds require CMake or vcpkg, while Python installation fetches and compiles through pip.
Evidence and sources
GitHub project description: A toolkit for making real world machine learning and data analysis applications in C++
README: Dlib is a modern C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems.
README: Finally, Visual Studio users should usually do everything in 64bit mode. By default Visual Studio is 32bit
README: Either fetch the latest stable release of dlib from PyPi and install that: ```bash pip install dlib ```
README: Type the following to compile and run the dlib unit test suite: