准备工作
- Visual Studio 2017
- cmake-3.12.0-rc2-win64-x64.msi
- dlib-19.13
通过cmake将dlib-19.13转换成vs项目
下图第4步选择带有win64的就是建64位的工程，会打出一个64位的静态lib包
通过vs编译dlib-19.13成window静态库lib文件
刚刚的dlib-19.13\dlib\build目录已经生成/转换为一个vs工程了，直接打开，生成，编译一个Release 64的windows静态库lib
vs创建一个空项目解决方案
- 源文件-添加dlib-19.13\dlib\all\source.cpp和dlib-19.13\examples\xxx.cpp任意一个栗子，我这里是face_landmark_detection_ex.cpp
- 项目属性页=》VC++目录=》包含目录添加dlib的解压路径dlib-19.13
- 项目属性页=》连接器=》常规=》附加库目录添加Release目录dlib-19.13\dlib\build\Release
- 项目属性页=》连接器=》输入=》附加库依赖项添加lib名字 dlib19.13.0_release_64bit_msvc1914.lib(不同系统可能名字不一样)
- 项目属性页=》C/C++=>预处理器添加DLIB_JPEG_SUPPORT和DLIB_JPEG_STATIC
封装自己的jna接口
头文件添加lib.h
#ifndef LIB_H
#define LIB_H
#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>
#include <dlib/image_io.h>
#include <iostream>
using namespace dlib;
using namespace std;
extern "C" __declspec(dllexport) int add(int x, int y);
extern "C" __declspec(dllexport) int get_face(char * out_para, const char * dat_file_path, const char * img_file_path);
#endif
源文件添加lib.cpp
#include "lib.h"
#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>
#include <dlib/image_io.h>
#include <iostream>
#include <stdlib.h>
#include <stdio.h>
using namespace dlib;
using namespace std;
// ----------------------------------------------------------------------------------------
//long转string
string ltos(long l)
{
ostringstream os;
os << l;
string result;
istringstream is(os.str());
is >> result;
return result;
}
int add(int x, int y)
{
return x + y;
}
int get_face(char * out_para, const char * dat_file_path, const char * img_file_path) {
try
{
//string dat_file_path = "D:\\test\\shape_predictor_68_face_landmarks.dat";
//string img_file_path = "D:\\test\\faces\\Tom_Cruise_avp_2014_4.jpg";
//创建人脸识别器
frontal_face_detector detector = get_frontal_face_detector();
//脸型预测器
shape_predictor sp;
deserialize(dat_file_path) >> sp;
//加载图片
array2d<rgb_pixel> img;
load_image(img, img_file_path);
//对图像进行上采用,检测更小的人脸,不使用可以提升速度
//pyramid_up(img);
//识别图片中有几张脸
std::vector<rectangle> dets = detector(img);
//没有识别到脸或者有多张脸
if (dets.size() != 1) {
cout << "did not recognize the face or have multiple faces" << endl;
return 0;
}
//特征对象
full_object_detection shape = sp(img, dets[0]);
//矩形
rectangle rect = shape.get_rect();
long top = rect.top();
long bottom = rect.bottom();
long left = rect.left();
long right = rect.right();
//显示矩形
cout << "left of rectangle: " << left << endl;
cout << "top of rectangle: " << top << endl;
cout << "right of rectangle: " << right << endl;
cout << "bottom of rectangle: " << bottom << endl;
string rtn_str = ltos(left);
rtn_str.append(",");
rtn_str.append(ltos(top));
rtn_str.append(",");
rtn_str.append(ltos(right));
rtn_str.append(",");
rtn_str.append(ltos(bottom));
//特征点数量
cout << "number of parts: " << shape.num_parts() << endl;
//显示68个特征点
for (int i = 0; i < 68; i++) {
cout << "pixel position of " << (i + 1) << " part: " << shape.part(i) << endl;
rtn_str.append(",");
rtn_str.append(ltos(shape.part(i).x()));
rtn_str.append(",");
rtn_str.append(ltos(shape.part(i).y()));
}
//输出变量
const char * p = (char*)rtn_str.data();
long p_len = strlen(p);
memcpy(out_para, p, p_len);
return p_len;
}
catch (exception& e)
{
cout << "\nexception thrown!" << endl;
cout << e.what() << endl;
}
return 0;
}
资源文件添加lib.def
LIBRARY dllTest
EXPORTS
add @ 1
get_face @ 2
以上定义了2个本地方法，同时需要将项目类型改成dll，然后重新生成即可生成dll文件。
