davisking/dlib

★ 14,379C++Audience · developerComplexity · 4/5LicenseSetup · moderate

Mindmap

mindmap
  root((dlib))
    What it does
      Machine learning library
      Computer vision tools
      C++ with Python bindings
    Algorithms
      Face detection
      Face recognition
      SVM and neural nets
    Usage
      Python via pip
      C++ via CMake
      Example programs included
    License
      Boost Software License
      Commercial use allowed
      Open or closed source

mindmap root((dlib)) What it does Machine learning library Computer vision tools C++ with Python bindings Algorithms Face detection Face recognition SVM and neural nets Usage Python via pip C++ via CMake Example programs included License Boost Software License Commercial use allowed Open or closed source

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Things people build with this

USE CASE 1

Add face detection or face recognition to a Python application using dlib's pre-built models with a single pip install.

USE CASE 2

Integrate machine learning algorithms into a C++ desktop or embedded application without pulling in a large ML framework.

USE CASE 3

Use dlib's computer vision tools to analyze images or video in a Python script for research or rapid prototyping.

Tech stack

C++PythonCMakepip

Getting it running

Difficulty · moderate Time to first run · 30min

Python users install via pip, C++ users need CMake and a C++11 compiler, optional GPU acceleration requires CUDA.

Use freely in any project, open-source or commercial, with no restriction beyond keeping the copyright notice (Boost Software License).

In plain English

Dlib is a C++ library that provides tools for building machine learning applications and doing data analysis. It is aimed at software developers who want to integrate machine learning, computer vision, or data processing capabilities into their own programs. While the library is written in C++, it also has a Python interface, which means Python developers can use many of its features through the pip package manager without writing any C++ themselves. Machine learning, in this context, refers to software that learns patterns from data rather than following a fixed set of rules. Computer vision refers to software that analyzes and interprets images or video. Dlib packages a range of algorithms in both categories into a single library so developers do not have to implement them from scratch. To use dlib in a C++ project, you typically compile it along with your own code using a build tool called CMake, which automates the process of configuring and compiling large software projects. The repository includes a collection of example programs that demonstrate how to use different parts of the library, along with instructions for building them. For Python users, installation is a single pip command. The library is released under the Boost Software License, which is permissive: it can be used in open-source projects, closed-source products, and commercial software without restriction. Development has received partial support from the Intelligence Advanced Research Projects Activity (IARPA), a US government research organization, though the library is publicly available and not restricted to government use.

Copy-paste prompts

Prompt 1

Using dlib in Python, detect all faces in an image and draw bounding boxes around them. Show the pip install step and the complete script.

Prompt 2

I want to do face recognition with dlib in Python, how do I compare two face images to check if they show the same person?

Prompt 3

How do I compile a C++ program that uses dlib with CMake? Walk me through the CMakeLists.txt setup and the build commands.

Prompt 4

What machine learning algorithms does dlib provide for Python users, and when would I choose SVM over a neural network method from the library?

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