安装dlib C++

• Ubuntu18.04
• dlib19

下载

从github下载 dlib

git clone https://github.com/davisking/dlib.git

安装

在dlib目录下， 依次执行。

mkdir build; cd build; cmake .. ; cmake --build .

python setup.py install

安装成功

python_examples 目录下有很多例子， 可以试试

python opencv_webcam_face_detection.py # 打开电脑摄像头检测人脸

创建测试文件 3d_point_cloud_ex.cpp

#include <dlib/gui_widgets.h>
#include <dlib/image_transforms.h>
#include <cmath>

using namespace dlib;
using namespace std;

int main()
{
    // Let's make a point cloud that looks like a 3D spiral.
    std::vector<perspective_window::overlay_dot> points;
    dlib::rand rnd;
    for (double i = 0; i < 20; i+=0.001)
    {
        // Get a point on a spiral
        dlib::vector<double> val(sin(i),cos(i),i/4);

        // Now add some random noise to it
        dlib::vector<double> temp(rnd.get_random_gaussian(),
                                  rnd.get_random_gaussian(),
                                  rnd.get_random_gaussian());
        val += temp/20;

        // Pick a color based on how far we are along the spiral
        rgb_pixel color = colormap_jet(i,0,20);

        // And add the point to the list of points we will display
        points.push_back(perspective_window::overlay_dot(val, color));
    }

    // Now finally display the point cloud.
    perspective_window win;
    win.set_title("perspective_window 3D point cloud");
    win.add_overlay(points);
    win.wait_until_closed();
}

编写CMakelists.txt

project(test_dlib)
cmake_minimum_required(VERSION 2.8)

add_subdirectory(../dlib dlib_build) # 找到dlib下的源码文件
add_executable(hc 3d_point_cloud_ex.cpp) # 生成执行文件名字为hc 

target_link_libraries(hc dlib::dlib) # hc这个执行文件需要链接到 dlib

说明：../dlib 可以使相对路径也可以是绝对路径

编译

mkdir build 
cd build 
cmake ..
make

执行

.hc 

注：中间遇到一些warning没有关系

使用GPU则需要添加如下几个参数

git clone https://github.com/davisking/dlib.git
cd dlib
mkdir build
cd build
cmake .. -DDLIB_USE_CUDA=1 -DUSE_AVX_INSTRUCTIONS=1
cmake --build .

cmake 成功找到cuda和cudnn结果是这样的

-- Found CUDA: /usr/local/cuda-9.2 (found suitable version "9.2", minimum required is "7.5")
-- Looking for cuDNN install...
-- Found cuDNN: /usr/local/cuda-9.2/lib64/libcudnn.so
-- Building a CUDA test project to see if your compiler is compatible with CUDA...
-- Checking if you have the right version of cuDNN installed.
-- Enabling CUDA support for dlib.  DLIB WILL USE CUDA
-- C++11 activated.
-- Configuring done
-- Generating done
-- Build files have been written to: /home/xxx/dlib/build

给python使用。

cd ..
python setup.py install --set USE_AVX_INSTRUCTIONS=yes --set DLIB_USE_CUDA=yes
多数博客会写成这样 
#python setup.py install --yes USE_AVX_INSTRUCTIONS --yes DLIB_USE_CUDA  # dlib 已经取消yes参数了。

安装成功

import dlib
dlib.DLIB_USE_CUDA # 结果为True则可以使用了

• Using dlib
• Dlib github
• Ubuntu环境下配置使用GPU加速的dlib库