Practical overview
When it fits
Use dlib when you need a library integrated into your own C++ or Python software and want documented CMake, package-installation and example-build paths.
Who it is for
- C++ developers building machine-learning software
- Python developers using dlib’s machine-learning API
- Teams developing computer-vision applications
- Developers prototyping deep-learning or data-analysis tools
Documented uses
- Add machine-learning algorithms and tools to a C++ application
- Use a Python API for machine-learning development
- Build computer-vision software
- Prototype deep-learning applications
- Compile and evaluate the project’s example programs and unit tests
Requirements & limits
The repository is public and identified as open source under the BSL-1.0 license. The documented Python installation paths use PyPI or a source checkout; C++ integration can use CMake or vcpkg.
- Choose the C++ API when the application is being built as a native C++ project.
- Choose the Python API when Python package installation and scripting access fit the development workflow.
- CMake is central to the documented C++ example, library and test workflows.
- AVX is an optional build setting for CPUs that support it.
- Windows developers should account for the documented 64-bit Visual Studio configuration.
Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.
Build dlib’s C++ examples with CMake
Compile the repository’s example programs using the documented CMake workflow.
Before you start
- A local copy of the dlib repository
- CMake and a C++ build environment
Steps
Open the repository’s examples directory.
Create a build directory and enter it.
Run CMake configuration with
cmake ...Build the examples with
cmake --build ..For a supported CPU, add
-DUSE_AVX_INSTRUCTIONS=1during CMake configuration to enable the documented AVX option.
Expected outcome
The example programs are compiled through the repository’s CMake build process.
Guide limitations
- The source documents the build commands but does not establish that a particular compiler, operating-system configuration or CPU will succeed.
- AVX is applicable only when the CPU supports the required instructions.
- On Windows, the documented Visual Studio workflow uses 64-bit mode.
Install dlib’s Python API
Set up the Python interface from PyPI or from a local repository checkout.
Before you start
- Python and a Python package installation environment
- Either access to the dlib package on PyPI or a local clone of the dlib repository
Steps
Install the latest stable package with the command below, or clone the repository.
pip install dlibIf installing from the repository, enter the cloned dlib directory.
Run the command below to install the local Python package.
pip install .Use documented
setup.pyparameters orDLIB_*environment variables when changing build settings;DLIB_NO_GUI_SUPPORT=ONis given as an example.
Expected outcome
The dlib Python API is installed through the documented package or source-install route.
Guide limitations
- The source documents installation paths and build-setting examples but does not provide a particular application workflow or guarantee compatibility with a specific Python environment.
- Changing build settings can affect the resulting installation.
Sources & review
Source record details
- Source availability
- Active
- Sources checked
- 2 October 2026
- Original website title
- davisking/dlib · Official homepage title · retained in its source language