人臉識別引擎SeetaFaceEngine中Detection模塊用于人臉檢測，以下是測試代碼：

int test_detection()
{std::vector<std::string> images{ "1.jpg", "2.jpg", "3.jpg", "4.jpeg", "5.jpeg", "6.jpg", "7.jpg", "8.jpg", "9.jpg", "10.jpg","11.jpeg", "12.jpg", "13.jpeg", "14.jpg", "15.jpeg", "16.jpg", "17.jpg", "18.jpg", "19.jpg", "20.jpg" };std::vector<int> count_faces{ 1, 2, 6, 0, 1, 1, 1, 2, 1, 1,1, 1, 1, 1, 1, 1, 1, 0, 8, 2 };const std::string path_images{ "E:/GitCode/Face_Test/testdata/" };seeta::FaceDetection detector("E:/GitCode/Face_Test/src/SeetaFaceEngine/FaceDetection/model/seeta_fd_frontal_v1.0.bin");detector.SetMinFaceSize(20);detector.SetMaxFaceSize(200);detector.SetScoreThresh(2.f);detector.SetImagePyramidScaleFactor(0.8f);detector.SetWindowStep(4, 4);for (int i = 0; i < images.size(); i++) {cv::Mat src_ = cv::imread(path_images + images[i], 1);if (src_.empty()) {fprintf(stderr, "read image error: %s\n", images[i].c_str());continue;}cv::Mat src;cv::cvtColor(src_, src, CV_BGR2GRAY);seeta::ImageData img_data;img_data.data = src.data;img_data.width = src.cols;img_data.height = src.rows;img_data.num_channels = 1;std::vector<seeta::FaceInfo> faces = detector.Detect(img_data);fprintf(stderr, "image_name: %s, faces_num: %d\n", images[i].c_str(), faces.size());for (int num = 0; num < faces.size(); num++) {fprintf(stderr, "    score = %f\n",/*, roll = %f, pitch = %f, yaw = %f*/faces[num].score/*, faces[num].roll, faces[num].pitch, faces[num].yaw*/);cv::rectangle(src_, cv::Rect(faces[num].bbox.x, faces[num].bbox.y,faces[num].bbox.width, faces[num].bbox.height), cv::Scalar(0, 255, 0), 2);}std::string save_result = path_images + "_" + images[i];cv::imwrite(save_result, src_);}int width = 200;int height = 200;cv::Mat dst(height * 5, width * 4, CV_8UC3);for (int i = 0; i < images.size(); i++) {std::string input_image = path_images + "_" + images[i];cv::Mat src = cv::imread(input_image, 1);if (src.empty()) {fprintf(stderr, "read image error: %s\n", images[i].c_str());return -1;}cv::resize(src, src, cv::Size(width, height), 0, 0, 4);int x = (i * width) % (width * 4);int y = (i / 4) * height;cv::Mat part = dst(cv::Rect(x, y, width, height));src.copyTo(part);}std::string output_image = path_images + "result.png";cv::imwrite(output_image, dst);return 0;
}

從網上找了20張圖像，驗證此庫的檢測率，檢測結果如下：

GitHub：https://github.com/fengbingchun/Face_Test