DLib C++ Library
DLib helps software developers and teams build applications involving machine learning and numerical analysis. It is designed for use in robotics, embedded devices, and high-performance computing environments.
At a glance
- Category
- Software Development
- Best for
- Software Companies, Development Teams, C++ Developers, Embedded Systems Engineers
- Pricing
- DLib is free and open source software.
- Key use cases
- Robotics Development, Embedded Device Software, Mobile Application Backend, High-Performance Computing
- Integrations
- BLAS, LAPACK, OpenCV, SQLite, Google Protocol Buffers
- Official website
- dlib.net
DLib is a C++ toolkit containing machine learning and numeric algorithms. It provides tools ranging from deep learning and Support Vector Machines to linear algebra and image processing within a portable C++ framework.
The library is intended for use in both industry and academia, particularly for development on Windows, Linux, and macOS. As it does not require external packages and relies on standard C++ and OS APIs, it may be used in environments such as mobile phones and embedded systems.
In addition to machine learning, DLib includes utilities for networking, threading, and GUI development. This allows developers to build C++ applications that require data processing or intelligence features.
Buyers should confirm that their team has the necessary C++ expertise, as the library requires compilation to implement.
Key Features
Supports the creation and training of deep neural networks.
Includes Support Vector Machines (SVM), Relevance Vector Machines, and multiclass classification tools.
Includes routines for reading and writing image formats, color space conversion, and face recognition.
Provides a matrix object for linear algebra and various non-linear optimization algorithms.
Offers a TCP sockets API and a threading API for POSIX and Windows systems.
Provides a core GUI API and a collection of windowing widgets.
Use Cases
Implementing machine learning and sensor data processing.
Integrating machine learning algorithms into hardware with limited resources.
Building C++ components for mobile phone software.
Performing numerical analysis and large-scale classification tasks.
Best For
Integrations
Pricing
DLib is free and open source software.
FAQ
Yes, DLib is open source and can be used free of charge in any application.
It is tested on MS Windows, Linux, and Mac OS X, and is designed to work on POSIX systems.
DLib may be compiled with CUDA enabled to use GPU acceleration for certain tasks, such as deep learning.
Source category: Software Development
Source subcategory: Machine Learning Framework
