dlib
A toolkit for making real world machine learning and data analysis applications
Decision gist · record as of 2026-08-14
Yes, with conditions. dlib is worth installing if you need robust machine learning or computer vision capabilities and can tolerate the compilation overhead during setup. The library is actively maintained, has no known security vulnerabilities, and carries a permissive license. However, ensure your development environment has a working C++ compiler and CMake before attempting installation.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires a C++ compiler and CMake to build from source; compilation may take several minutes depending on system resources.
- Installation requires compilation from source (high friction).
- The package is actively maintained with a recent release and strong community adoption, but build dependencies and platform-specific compilation steps may complicate setup on some systems.
License · maintenance · safety
Boost Software License (unclear) — Licensed under Boost Software License, which permits use in both open-source and closed-source commercial software with minimal restrictions. License treatment is marked unclear in the metadata, so review the actual license terms before relying on this classification.
last release 2026-03-29 (138 days) · last repo commit 2026-08-11 · 14,433 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 198,043 downloads/mo, #9,742 on PyPI
Alternatives
Verify before relying
pip install dlib
import dlib
detector = dlib.get_frontal_face_detector()- Exact Python version support range (requires_python is unspecified in metadata)
- Whether pre-built wheels are available for all major platforms or if compilation is always required
- Availability and performance impact of optional AVX instruction support mentioned in documentation
- Whether face detection and landmark extraction are available in the Python API or C++-only features
What it is and what it does
dlib is a production-grade C++ toolkit for machine learning and computer vision that exposes its core algorithms through Python bindings. It provides building blocks for classification, regression, and image processing tasks. The package is designed for real-world applications and has been actively maintained since its early releases.
The main trade-off is installation friction: dlib compiles from source on most systems, requiring a C++ compiler and build tools. Once installed, it offers no runtime dependencies, making it lightweight for deployment. It's widely used in production systems and has strong community adoption.
Use it for
- Build machine learning classifiers on image or tabular data using dlib's algorithms.
- Perform image processing tasks like resizing, filtering, and feature extraction for computer vision workflows.
- Create real-time video analysis applications that require efficient C++ performance with Python ease-of-use.
- Develop data analysis applications combining machine learning with computer vision capabilities.
- Integrate machine learning models into C++ applications through the toolkit's native interface.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, with conditions.
dlib is worth installing if you need robust machine learning or computer vision capabilities and can tolerate the compilation overhead during setup. The library is actively maintained, has no known security vulnerabilities, and carries a permissive license. However, ensure your development environment has a working C++ compiler and CMake before attempting installation.
Install
dlib on PyPI
Before you install
Installation requires compilation from source (high friction). The package is actively maintained with a recent release and strong community adoption, but build dependencies and platform-specific compilation steps may complicate setup on some systems.
Requires a C++ compiler and CMake to build from source; compilation may take several minutes depending on system resources.
License in practice
Licensed under Boost Software License, which permits use in both open-source and closed-source commercial software with minimal restrictions. License treatment is marked unclear in the metadata, so review the actual license terms before relying on this classification.
Quickstart
pip install dlib
import dlib
detector = dlib.get_frontal_face_detector()Verify before relying
- Exact Python version support range (requires_python is unspecified in metadata)
- Whether pre-built wheels are available for all major platforms or if compilation is always required
- Availability and performance impact of optional AVX instruction support mentioned in documentation
- Whether face detection and landmark extraction are available in the Python API or C++-only features
Package facts
| License | Boost Software License unclear |
| Python support | Not specified |
| Install friction | High. Source build required |
| Runtime dependencies | None |
| Maintenance | Actively maintained 138 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 198,043 / month, #9,742 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableIntended Audience :: DevelopersIntended Audience :: Science/ResearchOperating System :: MacOS :: MacOS XOperating System :: MicrosoftOperating System :: Microsoft :: WindowsOperating System :: POSIXOperating System :: POSIX :: LinuxProgramming Language :: C++Programming Language :: PythonTopic :: Scientific/EngineeringTopic :: Scientific/Engineering :: Artificial IntelligenceTopic :: Scientific/Engineering :: Image RecognitionTopic :: Software Development |
Evidence: dlib-20.0.1.tar.gz
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