libfacedetection 使用教程 人脸检测
libfacedetection 使用教程
github 下载地址：https://github.com/ShiqiYu/libfacedetection
//头文件
#ifndef FACEDETECT_DLL_H
#define FACEDETECT_DLL_H
#ifdef FACEDETECTDLL_EXPORTS
#define FACEDETECTDLL_API __declspec(dllexport)
#else
#ifdef __linux__
#define FACEDETECTDLL_API
#else
#define FACEDETECTDLL_API __declspec(dllimport)
#endif
#endif
FACEDETECTDLL_API int * facedetect_frontal(unsigned char * result_buffer, //buffer memory for storing face detection results, !!its size must be 0x20000 Bytes!!
unsigned char * gray_image_data, int width, int height, int step, //input image, it must be gray (single-channel) image!
float scale, //scale factor for scan windows
int min_neighbors, //how many neighbors each candidate rectangle should have to retain it
int min_object_width, //Minimum possible face size. Faces smaller than that are ignored.
int max_object_width = 0, //Maximum possible face size. Faces larger than that are ignored. It is the largest posible when max_object_width=0.
int doLandmark=0); // landmark detection
FACEDETECTDLL_API int * facedetect_frontal_surveillance(unsigned char * result_buffer, //buffer memory for storing face detection results, !!its size must be 0x20000 Bytes!!
unsigned char * gray_image_data, int width, int height, int step, //input image, it must be gray (single-channel) image!
float scale, //scale factor for scan windows
int min_neighbors, //how many neighbors each candidate rectangle should have to retain it
int min_object_width, //Minimum possible face size. Faces smaller than that are ignored.
int max_object_width = 0, //Maximum possible face size. Faces larger than that are ignored. It is the largest posible when max_object_width=0.
int doLandmark = 0); // landmark detection
FACEDETECTDLL_API int * facedetect_multiview(unsigned char * result_buffer, //buffer memory for storing face detection results, !!its size must be 0x20000 Bytes!!
unsigned char * gray_image_data, int width, int height, int step, //input image, it must be gray (single-channel) image!
float scale, //scale factor for scan windows
int min_neighbors, //how many neighbors each candidate rectangle should have to retain it
int min_object_width, //Minimum possible face size. Faces smaller than that are ignored.
int max_object_width = 0, //Maximum possible face size. Faces larger than that are ignored. It is the largest posible when max_object_width=0.
int doLandmark = 0); // landmark detection
FACEDETECTDLL_API int * facedetect_multiview_reinforce(unsigned char * result_buffer, //buffer memory for storing face detection results, !!its size must be 0x20000 Bytes!!
unsigned char * gray_image_data, int width, int height, int step, //input image, it must be gray (single-channel) image!
float scale, //scale factor for scan windows
int min_neighbors, //how many neighbors each candidate rectangle should have to retain it
int min_object_width, //Minimum possible face size. Faces smaller than that are ignored.
int max_object_width = 0, //Maximum possible face size. Faces larger than that are ignored. It is the largest posible when max_object_width=0.
int doLandmark = 0); // landmark detection
#endif
控制台程序
#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!
//定义缓冲区大小 不要改变大小！
#define DETECT_BUFFER_SIZE 0x20000
using namespace cv;
int main(int argc, char* argv[])
{
if(argc != 2)
{
printf("Usage: %s <image_file_name>\n", argv[0]);
return -1;
}
//load an image and convert it to gray (single-channel)
//加载图像并将其转换为灰色（单通道）
Mat image = imread(argv[1]);
if(image.empty())
{
fprintf(stderr, "Can not load the image file %s.\n", argv[1]);
return -1;
}
Mat gray;
cvtColor(image, gray, CV_BGR2GRAY);
int * pResults = NULL;
//pBuffer is used in the detection functions.
//pBuffer指针用于检测函数。
//If you call functions in multiple threads, please create one buffer for each thread!
//如果您在多个线程中调用函数，请为每个线程创建一个缓冲区！
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
//正面人脸检测/ 68标志性检测
// it's fast, but cannot detect side view faces
//它很快，但不能检测侧面的脸
//////////////////////////////////////////
//!!! 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
//正面人脸检测专为视频监控/ 68标志性检测而设计
// it can detect faces with bad illumination.
//它可以检测到不良照明的面部。
//////////////////////////////////////////
//!!! 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
//多视角人脸检测/ 68标志性检测
// it can detect side view faces, but slower than facedetect_frontal().
//它可以检测侧视面，但比facedetect_frontal（）慢。
//////////////////////////////////////////
//!!! 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
//加强多视图人脸检测/ 68标志性检测
// it can detect side view faces, better but slower than facedetect_multiview().
//它可以检测侧面视图，比facedetect_multiview（）更好但更慢。
//////////////////////////////////////////
//!!! 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();
//release the buffer
free(pBuffer);
return 0;
}
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