前言
最近又開始進行人臉檢測方向的內容，看到於仕琪老師的多角度檢測想試一下，還不清楚原理，先測試效果如何。
libfacedetect人臉檢測庫是深圳大學於仕琪老師發布的開源庫，與opencv自帶的人臉檢測器相比，在速度和精度上都有較大的優勢。
本文主要基於libfacedetect庫測試人臉檢測的效果。
環境
系統：win10_x64;
opencv版本：2410；
VisualStudio版本：VS2013；
注意，libfacedetect目前僅支持windows系統，86和64均可，且不支持多線程並行計算；
配置
1.下載libfacedetect開源庫；
於老師的github；
2.新建VS工程項目(此處為x64版本)，添加或者配置opencv的屬性表，opencv環境配置請參見here；
3.項目屬性中VC++目錄選項中添加opencv和libfacedetect的包含目錄和庫目錄；
libfacedetect包含目錄：
.\libfacedetection-master\include
libfacedetect庫目錄：
.\libfacedetection-master\lib
3.鏈接器選項添加庫文件到附加依賴項選項；
libfacedetect.lib ------------ x86
libfacedetect-x64.lib ------------ x64
4.將bin目錄下的dll文件放在exe的同一個目錄，對應版本同步驟3；
至此，完成項目的環境配置；
測試
code：
單張圖片測試
/* The MIT License (MIT) Copyright (c) 2015-2017 Shiqi Yu shiqi.yu@gmail.com Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. */ #include <stdio.h> #include <opencv2/opencv.hpp> #include "facedetect-dll.h" //#pragma comment(lib,"libfacedetect.lib") #pragma comment(lib,"libfacedetect-x64.lib") //define the buffer size. Do not change the size! #define DETECT_BUFFER_SIZE 0x20000 using namespace cv; //int main(int argc, char* argv[]) int main( ) { //load an image and convert it to gray (single-channel) char* image_name = ".\\..\\images\\chloecalmon.png"; std::cout << image_name << std::endl; Mat image = imread(image_name); if (image.empty()) { fprintf(stderr, "Can not load the image file %s.\n", image_name); return -1; } Mat gray; cvtColor(image, gray, CV_BGR2GRAY); int * pResults = NULL; //pBuffer is used in the detection functions. //If you call functions in multiple threads, please create one buffer for each thread! unsigned char * pBuffer = (unsigned char *)malloc(DETECT_BUFFER_SIZE); if (!pBuffer) { fprintf(stderr, "Can not alloc buffer.\n"); return -1; } int doLandmark = 1; /////////////////////////////////////////// // frontal face detection / 68 landmark detection // it's fast, but cannot detect side view faces ////////////////////////////////////////// //!!! The input image must be a gray one (single-channel) //!!! DO NOT RELEASE pResults !!! pResults = facedetect_frontal(pBuffer, (unsigned char*)(gray.ptr(0)), gray.cols, gray.rows, (int)gray.step, 1.2f, 2, 48, 0, doLandmark); printf("%d faces detected.\n", (pResults ? *pResults : 0)); Mat result_frontal = image.clone(); //print the detection results for (int i = 0; i < (pResults ? *pResults : 0); i++) { short * p = ((short*)(pResults + 1)) + 142 * i; int x = p[0]; int y = p[1]; int w = p[2]; int h = p[3]; int neighbors = p[4]; int angle = p[5]; printf("face_rect=[%d, %d, %d, %d], neighbors=%d, angle=%d\n", x, y, w, h, neighbors, angle); rectangle(result_frontal, Rect(x, y, w, h), Scalar(0, 255, 0), 2); if (doLandmark) { for (int j = 0; j < 68; j++) circle(result_frontal, Point((int)p[6 + 2 * j], (int)p[6 + 2 * j + 1]), 1, Scalar(0, 255, 0)); } } imshow("Results_frontal", result_frontal); /////////////////////////////////////////// // frontal face detection designed for video surveillance / 68 landmark detection // it can detect faces with bad illumination. ////////////////////////////////////////// //!!! The input image must be a gray one (single-channel) //!!! DO NOT RELEASE pResults !!! pResults = facedetect_frontal_surveillance(pBuffer, (unsigned char*)(gray.ptr(0)), gray.cols, gray.rows, (int)gray.step, 1.2f, 2, 48, 0, doLandmark); printf("%d faces detected.\n", (pResults ? *pResults : 0)); Mat result_frontal_surveillance = image.clone();; //print the detection results for (int i = 0; i < (pResults ? *pResults : 0); i++) { short * p = ((short*)(pResults + 1)) + 142 * i; int x = p[0]; int y = p[1]; int w = p[2]; int h = p[3]; int neighbors = p[4]; int angle = p[5]; printf("face_rect=[%d, %d, %d, %d], neighbors=%d, angle=%d\n", x, y, w, h, neighbors, angle); rectangle(result_frontal_surveillance, Rect(x, y, w, h), Scalar(0, 255, 0), 2); if (doLandmark) { for (int j = 0; j < 68; j++) circle(result_frontal_surveillance, Point((int)p[6 + 2 * j], (int)p[6 + 2 * j + 1]), 1, Scalar(0, 255, 0)); } } imshow("Results_frontal_surveillance", result_frontal_surveillance); /////////////////////////////////////////// // multiview face detection / 68 landmark detection // it can detect side view faces, but slower than facedetect_frontal(). ////////////////////////////////////////// //!!! The input image must be a gray one (single-channel) //!!! DO NOT RELEASE pResults !!! pResults = facedetect_multiview(pBuffer, (unsigned char*)(gray.ptr(0)), gray.cols, gray.rows, (int)gray.step, 1.2f, 2, 48, 0, doLandmark); printf("%d faces detected.\n", (pResults ? *pResults : 0)); Mat result_multiview = image.clone();; //print the detection results for (int i = 0; i < (pResults ? *pResults : 0); i++) { short * p = ((short*)(pResults + 1)) + 142 * i; int x = p[0]; int y = p[1]; int w = p[2]; int h = p[3]; int neighbors = p[4]; int angle = p[5]; printf("face_rect=[%d, %d, %d, %d], neighbors=%d, angle=%d\n", x, y, w, h, neighbors, angle); rectangle(result_multiview, Rect(x, y, w, h), Scalar(0, 255, 0), 2); if (doLandmark) { for (int j = 0; j < 68; j++) circle(result_multiview, Point((int)p[6 + 2 * j], (int)p[6 + 2 * j + 1]), 1, Scalar(0, 255, 0)); } } imshow("Results_multiview", result_multiview); /////////////////////////////////////////// // reinforced multiview face detection / 68 landmark detection // it can detect side view faces, better but slower than facedetect_multiview(). ////////////////////////////////////////// //!!! The input image must be a gray one (single-channel) //!!! DO NOT RELEASE pResults !!! pResults = facedetect_multiview_reinforce(pBuffer, (unsigned char*)(gray.ptr(0)), gray.cols, gray.rows, (int)gray.step, 1.2f, 3, 48, 0, doLandmark); printf("%d faces detected.\n", (pResults ? *pResults : 0)); Mat result_multiview_reinforce = image.clone();; //print the detection results for (int i = 0; i < (pResults ? *pResults : 0); i++) { short * p = ((short*)(pResults + 1)) + 142 * i; int x = p[0]; int y = p[1]; int w = p[2]; int h = p[3]; int neighbors = p[4]; int angle = p[5]; printf("face_rect=[%d, %d, %d, %d], neighbors=%d, angle=%d\n", x, y, w, h, neighbors, angle); rectangle(result_multiview_reinforce, Rect(x, y, w, h), Scalar(0, 255, 0), 2); if (doLandmark) { for (int j = 0; j < 68; j++) circle(result_multiview_reinforce, Point((int)p[6 + 2 * j], (int)p[6 + 2 * j + 1]), 1, Scalar(0, 255, 0)); } } imshow("Results_multiview_reinforce", result_multiview_reinforce); waitKey(100); //release the buffer free(pBuffer); return 0; }
camera測試
/* The MIT License (MIT) Copyright (c) 2015-2017 Shiqi Yu shiqi.yu@gmail.com Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. */ #include <stdio.h> #include <opencv2/opencv.hpp> #include "facedetect-dll.h" //#pragma comment(lib,"libfacedetect.lib") #pragma comment(lib,"libfacedetect-x64.lib") //define the buffer size. Do not change the size! #define DETECT_BUFFER_SIZE 0x20000 using namespace cv; //int main(int argc, char* argv[]) int main() { cv::VideoCapture capture; capture.open(0); if (!capture.isOpened()) { std::cout << "video capture failed..." << std::endl; return 0; } cv::Mat image; cv::namedWindow("video test", CV_WINDOW_NORMAL); while (true) { image.release(); capture >> image; cv::Mat gray; cv::cvtColor(image, gray, CV_BGR2GRAY); int * pResults = NULL; //pBuffer is used in the detection functions. //If you call functions in multiple threads, please create one buffer for each thread! unsigned char * pBuffer = (unsigned char *)malloc(DETECT_BUFFER_SIZE); if (!pBuffer) { fprintf(stderr, "Can not alloc buffer.\n"); return -1; } int doLandmark = 1; /////////////////////////////////////////// // frontal face detection / 68 landmark detection // it's fast, but cannot detect side view faces ////////////////////////////////////////// //!!! The input image must be a gray one (single-channel) //!!! DO NOT RELEASE pResults !!! pResults = facedetect_frontal(pBuffer, (unsigned char*)(gray.ptr(0)), gray.cols, gray.rows, (int)gray.step, 1.2f, 2, 48, 0, doLandmark); printf("%d faces detected.\n", (pResults ? *pResults : 0)); Mat result_frontal = image.clone(); //print the detection results for (int i = 0; i < (pResults ? *pResults : 0); i++) { short * p = ((short*)(pResults + 1)) + 142 * i; int x = p[0]; int y = p[1]; int w = p[2]; int h = p[3]; int neighbors = p[4]; int angle = p[5]; printf("face_rect=[%d, %d, %d, %d], neighbors=%d, angle=%d\n", x, y, w, h, neighbors, angle); rectangle(result_frontal, Rect(x, y, w, h), Scalar(0, 255, 0), 2); if (doLandmark) { for (int j = 0; j < 68; j++) circle(result_frontal, Point((int)p[6 + 2 * j], (int)p[6 + 2 * j + 1]), 1, Scalar(0, 255, 0)); } } imshow("video test", result_frontal); /////////////////////////////////////////// // frontal face detection designed for video surveillance / 68 landmark detection // it can detect faces with bad illumination. ////////////////////////////////////////// //!!! The input image must be a gray one (single-channel) //!!! DO NOT RELEASE pResults !!! pResults = facedetect_frontal_surveillance(pBuffer, (unsigned char*)(gray.ptr(0)), gray.cols, gray.rows, (int)gray.step, 1.2f, 2, 48, 0, doLandmark); printf("%d faces detected.\n", (pResults ? *pResults : 0)); Mat result_frontal_surveillance = image.clone();; //print the detection results for (int i = 0; i < (pResults ? *pResults : 0); i++) { short * p = ((short*)(pResults + 1)) + 142 * i; int x = p[0]; int y = p[1]; int w = p[2]; int h = p[3]; int neighbors = p[4]; int angle = p[5]; printf("face_rect=[%d, %d, %d, %d], neighbors=%d, angle=%d\n", x, y, w, h, neighbors, angle); rectangle(result_frontal_surveillance, Rect(x, y, w, h), Scalar(0, 255, 0), 2); if (doLandmark) { for (int j = 0; j < 68; j++) circle(result_frontal_surveillance, Point((int)p[6 + 2 * j], (int)p[6 + 2 * j + 1]), 1, Scalar(0, 255, 0)); } } imshow("video test", result_frontal_surveillance); /////////////////////////////////////////// // multiview face detection / 68 landmark detection // it can detect side view faces, but slower than facedetect_frontal(). ////////////////////////////////////////// //!!! The input image must be a gray one (single-channel) //!!! DO NOT RELEASE pResults !!! pResults = facedetect_multiview(pBuffer, (unsigned char*)(gray.ptr(0)), gray.cols, gray.rows, (int)gray.step, 1.2f, 2, 48, 0, doLandmark); printf("%d faces detected.\n", (pResults ? *pResults : 0)); Mat result_multiview = image.clone();; //print the detection results for (int i = 0; i < (pResults ? *pResults : 0); i++) { short * p = ((short*)(pResults + 1)) + 142 * i; int x = p[0]; int y = p[1]; int w = p[2]; int h = p[3]; int neighbors = p[4]; int angle = p[5]; printf("face_rect=[%d, %d, %d, %d], neighbors=%d, angle=%d\n", x, y, w, h, neighbors, angle); rectangle(result_multiview, Rect(x, y, w, h), Scalar(0, 255, 0), 2); if (doLandmark) { for (int j = 0; j < 68; j++) circle(result_multiview, Point((int)p[6 + 2 * j], (int)p[6 + 2 * j + 1]), 1, Scalar(0, 255, 0)); } } imshow("video test", result_multiview); /////////////////////////////////////////// // reinforced multiview face detection / 68 landmark detection // it can detect side view faces, better but slower than facedetect_multiview(). ////////////////////////////////////////// //!!! The input image must be a gray one (single-channel) //!!! DO NOT RELEASE pResults !!! pResults = facedetect_multiview_reinforce(pBuffer, (unsigned char*)(gray.ptr(0)), gray.cols, gray.rows, (int)gray.step, 1.2f, 3, 48, 0, doLandmark); printf("%d faces detected.\n", (pResults ? *pResults : 0)); Mat result_multiview_reinforce = image.clone();; //print the detection results for (int i = 0; i < (pResults ? *pResults : 0); i++) { short * p = ((short*)(pResults + 1)) + 142 * i; int x = p[0]; int y = p[1]; int w = p[2]; int h = p[3]; int neighbors = p[4]; int angle = p[5]; printf("face_rect=[%d, %d, %d, %d], neighbors=%d, angle=%d\n", x, y, w, h, neighbors, angle); rectangle(result_multiview_reinforce, Rect(x, y, w, h), Scalar(0, 255, 0), 2); if (doLandmark) { for (int j = 0; j < 68; j++) circle(result_multiview_reinforce, Point((int)p[6 + 2 * j], (int)p[6 + 2 * j + 1]), 1, Scalar(0, 255, 0)); } } imshow("video test", result_multiview_reinforce); waitKey(100); //release the buffer free(pBuffer); } return 0; }
其中的neighbours的含義是
int min_neighbors, //how many neighbors each candidate rectangle should have to retain it
注意，工程記得添加頭文件；
參考
1.github；
3.人臉檢測算法；
4.CSDN大神介紹；
完