Question

尝试运行从Here下载的示例程序后，我理解使用jpeg文件，我必须将 #define DLIB_JPEG_SUPPORT 指令添加到项目中。但在此之前，下载jpeg库并将其添加到项目中是必要的。我做了这些步骤：

1.从here下载 jpegsr9a .zip并解压缩。

2.下载 WIN32.mak 并将其粘贴到jpeg根文件夹

3.从Visual Studio 2013工具中打开开发人员命令提示符

4.在命令提示符下键入： nmake -f makefile.vc setup-v10

5.创建jpeg.sln这些步骤后，注意事项是当我在VS2013中打开jpeg.sln消息时：

问题的根源可能从这里开始，我不知道

6.使用正确的配置构建jpeg.sln（我使用不同的配置多次构建它，最近我使用this构建它。）在构建错误结束时：＆＃34;无法启动jpeg.lib＆＃34; 但是在发布文件夹或调试文件夹（取决于配置）中创建了jpeg.lib

打开使用DLIB检测面部的主项目，我将jpeg根文件夹添加到Additonal Include Directory并将jepegroot / release添加到其他Libarary目录，然后将UseLibrary依赖项更改为＆＃34; yes＆＃34;我还将jpeg.lib添加到了dependecies。

在构建项目期间出现错误：

这是我尝试构建和运行的源代码

//#define HAVE_BOOLEAN
#define DLIB_JPEG_SUPPORT
#include <dlib/image_processing/frontal_face_detector.h>
#include <dlib/image_processing/render_face_detections.h>
#include <dlib/image_processing.h>
#include<dlib/image_transforms.h>
#include <dlib/gui_widgets.h>
#include <dlib/image_io.h>
#include <iostream>
//
using namespace dlib;
using namespace std;

// ----------------------------------------------------------------------------------------

int main(int argc, char** argv)
{
    try
    {
        // This example takes in a shape model file and then a list of images to
        // process.  We will take these filenames in as command line arguments.
        // Dlib comes with example images in the examples/faces folder so give
        // those as arguments to this program.
        if (argc == 1)
        {
            cout << "Call this program like this:" << endl;
            cout << "./face_landmark_detection_ex shape_predictor_68_face_landmarks.dat faces/*.jpg" << endl;
            cout << "\nYou can get the shape_predictor_68_face_landmarks.dat file from:\n";
            cout << "http://dlib.net/files/shape_predictor_68_face_landmarks.dat.bz2" << endl;
            return 0;
        }

        // We need a face detector.  We will use this to get bounding boxes for
        // each face in an image.
        frontal_face_detector detector = get_frontal_face_detector();
        // And we also need a shape_predictor.  This is the tool that will predict face
        // landmark positions given an image and face bounding box.  Here we are just
        // loading the model from the shape_predictor_68_face_landmarks.dat file you gave
        // as a command line argument.
        shape_predictor sp;
         deserialize(argv[1])>>sp;


        image_window win, win_faces;
        // Loop over all the images provided on the command line.
        for (int i = 2; i < argc; ++i)
        {
            cout << "processing image " << argv[i] << endl;
            array2d<rgb_pixel> img;
            load_image(img, argv[i]);
            // Make the image larger so we can detect small faces.
            pyramid_up(img);

            // Now tell the face detector to give us a list of bounding boxes
            // around all the faces in the image.
            std::vector<rectangle> dets = detector(img);
            cout << "Number of faces detected: " << dets.size() << endl;

            // Now we will go ask the shape_predictor to tell us the pose of
            // each face we detected.
            std::vector<full_object_detection> shapes;
            for (unsigned long j = 0; j < dets.size(); ++j)
            {
                full_object_detection shape = sp(img, dets[j]);
                cout << "number of parts: " << shape.num_parts() << endl;
                cout << "pixel position of first part:  " << shape.part(0) << endl;
                cout << "pixel position of second part: " << shape.part(1) << endl;
                // You get the idea, you can get all the face part locations if
                // you want them.  Here we just store them in shapes so we can
                // put them on the screen.
                shapes.push_back(shape);
            }

            // Now let's view our face poses on the screen.
            win.clear_overlay();
            win.set_image(img);
            win.add_overlay(render_face_detections(shapes));

            // We can also extract copies of each face that are cropped, rotated upright,
            // and scaled to a standard size as shown here:
            dlib::array<array2d<rgb_pixel> > face_chips;
            extract_image_chips(img, get_face_chip_details(shapes), face_chips);
            win_faces.set_image(tile_images(face_chips));

            cout << "Hit enter to process the next image..." << endl;
            cin.get();
        }
    }
    catch (exception& e)
    {
        cout << "\nexception thrown!" << endl;
        cout << e.what() << endl;
    }
}

// --------------------------------------------- -------------------------------------------

我可以选择其他选择，但我花了太多时间到达这里，我想知道如何解决这个问题并在使用DLIB时加载jpeg文件

我也阅读了这些链接：

Compiling libjpeg

http://www.dahlsys.com/misc/compiling_ijg_libjpeg/index.html

dlib load jpeg files

http://sourceforge.net/p/dclib/discussion/442518/thread/8a0d42dc/