linux安装dlib,关键点检测
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Linux下安装dlib19.6 Face Landmark Detection
1、下载dlib
下载dlib-19.6.zip
2、 C++编译dlib
从官网下载的dlib文件如下:
从dlib的根目录执行下面语句即可:
>>首先进入dlib的根目录下
>>再执行如下语句:
cd examples #进入dlib下的examples文件夹
mkdir build #新建build文件夹,存放cmake编译后的执行文件
cd build #进入新建好的build文件夹
cmake .. #cmake编译examples整个文件夹
cmake --build . --config Release
这只是编译好了examples下的dlib,要想编译整个dlib库,则执行以下代码即可:
>>进入dlib根目录下
mkdir buildcd build
cmake ..
make release=1
Dlib 关键点检测代码实现:
#include <dlib/opencv.h>
#include <opencv2/opencv.hpp>
#include <dlib/image_processing/frontal_face_detector.h>
#include <dlib/image_processing/render_face_detections.h>
#include <dlib/image_processing.h>
#include <dlib/gui_widgets.h>
using namespace dlib;
using namespace std;
int main()
{
try
{
// Load face detection and pose estimation models.
frontal_face_detector detector = get_frontal_face_detector();
shape_predictor pose_model;
deserialize("shape_predictor_68_face_landmarks.dat") >> pose_model;
// Grab a frame
string path = "XZQ.jpg";
cv::Mat temp = cv::imread(path);
cv_image<bgr_pixel> cimg(temp);
// Detect faces
std::vector<rectangle> faces = detector(cimg);
// Find the pose of each face.
std::vector<full_object_detection> shapes;
for (unsigned long i = 0; i < faces.size(); ++i)
shapes.push_back(pose_model(cimg, faces[i]));
if (!shapes.empty()) {
for (int i = 0; i < 68; i++) {
circle(temp, cvPoint(shapes[0].part(i).x(), shapes[0].part(i).y()), 3, cv::Scalar(0, 0, 255), -1);
// shapes[0].part(i).x();//68个
}
}
//imshow("Dlib特征点", temp);
cv::imwrite("saveXZQ_landmark.jpg", temp);
//cv::waitKey(0);
}
catch (exception& e)
{
cout << e.what() << endl;
}
}
参考CMakeList.txt文件:
cmake_minimum_required(VERSION 2.8.4) #版本最小为2.8.4
PROJECT(dlib_facedetector) #设置工程名
SET(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++11 -O2 -DDLIB_JPEG_SUPPORT")
IF(CMAKE_CXX_COMPILER_ID STREQUAL "Clang")
SET(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -Weverything")
ELSEIF(CMAKE_CXX_COMPILER_ID STREQUAL "GNU")
SET(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -Wall -Wextra")
ENDIF()
# #INCLUDE OPENCV
# include_directories(/home/local/include/opencv/)
# include_directories(/home/local/include/opencv2/)
# include_directories(/home/local/include/)
# link_libraries(opencv_core)
# link_libraries(opencv_highgui)
# link_libraries(opencv_imgproc)
#INCLUDE OPENCV
FIND_PACKAGE(OpenCV REQUIRED)
INCLUDE_DIRECTORIES(${OpenCV_INCLUDE_DIRS})
message(STATUS "Opencv include dir found at ${OpenCV_INCLUDE_DIRS}")
#包含头文件
INCLUDE_DIRECTORIES(/dlib-19.6) #dlib根目录地址
LINK_DIRECTORIES(/dlib-19.6/build/dlib/) #dlib编译后bulid下dlib地址
#生产类似于.exe的可执行文件
ADD_EXECUTABLE(dlib_detector dilib_landmark.cpp)
#链接库
TARGET_LINK_LIBRARIES(dlib_detector dlib ${OpenCV_LIBS})
#TARGET_LINK_LIBRARIES(dlib_detector libjpeg.so)
编译执行,编译代码如下:
>>在自己建的工程文件夹下新建build文件夹
mkdir buildcd build
cmake ..
make -j8 #用make也行
然后再执行.cpp文件,执行代码如下:
>>在build文件夹下继续执行一行代码即可显示结果:
./dlib_detector
可能出现的问题:
make出现/usr/bin/ld: 找不到 -lopencv_dep_cudart错误时候
解决方法: 在cmake时候加上参数即可。
cmake -D CUDA_USE_STATIC_CUDA_RUNTIME=OFF .
测试结果:
参考:https://blog.csdn.net/qq_17448289/article/details/56494998
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