如果要配置其他版本的vs和其他版本Dlib的请看这篇
https://blog.csdn.net/wilsonass/article/details/90581787
首先下载Dlib已经编译好的内容
https://pan.baidu.com/s/1uZN2DQ59gQokgTBEYZb_uw 提取码：hbn1下载完成后进行解压，解压后会有两个文件夹
这两个是编译好的VS17下Win64的Release版本
然后在VS中进行配置 include和lib
写入输入的附加依赖项
dlib19.17.0_release_64bit_msvc1916.lib;
写入测试代码
其中的string img_path = "001.jpg";是当前目录下的图片，通过把图片重命名移动到项目的当前目录下可进行测试
当前目录为：右键项目，选择在资源管理器中打开文件夹
#include <dlib/gui_widgets.h> #include <dlib/image_io.h> #include <dlib/image_transforms.h> #include <fstream> using namespace std; using namespace dlib; // ---------------------------------------------------------------------------- int main(int argc, char** argv) { try { // 声明图像 array2d<rgb_pixel> img; string img_path = "001.jpg"; load_image(img, img_path); // 高斯模糊 array2d<unsigned char> blurred_img; gaussian_blur(img, blurred_img); // sobel边缘检测 array2d<short> horz_gradient, vert_gradient; array2d<unsigned char> edge_image; sobel_edge_detector(blurred_img, horz_gradient, vert_gradient); //非极大边缘抑制 suppress_non_maximum_edges(horz_gradient, vert_gradient, edge_image); // 显示结果 image_window my_window(edge_image, "Normal Edge Image"); // We can also easily display the edge_image as a heatmap or using the jet color // scheme like so. image_window win_hot(heatmap(edge_image)); image_window win_jet(jet(edge_image)); // also make a window to display the original image image_window my_window2(img, "Original Image"); // Sometimes you want to get input from the user about which pixels are important // for some task. You can do this easily by trapping user clicks as shown below. // This loop executes every time the user double clicks on some image pixel and it // will terminate once the user closes the window. point p; while (my_window.get_next_double_click(p)) { cout << "User double clicked on pixel: " << p << endl; cout << "edge pixel value at this location is: " << (int)edge_image[p.y()][p.x()] << endl; } // wait until the user closes the windows before we let the program // terminate. win_hot.wait_until_closed(); my_window2.wait_until_closed(); // Finally, note that you can access the elements of an image using the normal [row][column] // operator like so: cout << horz_gradient[0][3] << endl; cout << "number of rows in image: " << horz_gradient.nr() << endl; cout << "number of columns in image: " << horz_gradient.nc() << endl; } catch (exception& e) { cout << "exception thrown: " << e.what() << endl; } }
测试成功
