FDDB数据库上评测人脸检测分类器

使用FDDB数据库测试分类器

// fddb_roc.cpp : 定义控制台应用程序的入口点。
//

#include "stdafx.h"
#include <opencv2/opencv.hpp>
#include <iostream>
#include <fstream>

#include "facedetect-dll.h"

//define the buffer size. Do not change the size!
#define DETECT_BUFFER_SIZE 0xC004

using namespace cv;
using namespace std;

string Double_String(double x)
{
stringstream ss;
ss << x;
return ss.str();
}

string Int_String(int x)
{
stringstream ss;
ss << x;
return ss.str();
}
void detectAndDisplay(Mat gray, string line)
{
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 ;
}

//检测正脸-60~60
//pResults = facedetect_frontal(pBuffer, (unsigned char*)(gray.ptr(0)), gray.cols, gray.rows, (int)gray.step, 1.2f, 2, 48);

//视频监控中低照度下人脸-70~70
//pResults = facedetect_frontal_surveillance(pBuffer, (unsigned char*)(gray.ptr(0)), gray.cols, gray.rows, (int)gray.step, 1.2f, 2, 48);

//多角度人脸检测-90~90
//pResults = facedetect_multiview(pBuffer, (unsigned char*)(gray.ptr(0)), gray.cols, gray.rows, (int)gray.step, 1.2f, 2, 48);

//多角度人脸检测加强-90~90
pResults = facedetect_multiview_reinforce(pBuffer, (unsigned char*)(gray.ptr(0)), gray.cols, gray.rows, (int)gray.step, 1.08f, 2, 16);

//以下人脸的数量用face_number代替
string face_position_1 = line;
string face_position_2 = Int_String(pResults ? *pResults : 0);
vector<string> face;
for (int i = 0; i < (pResults ? *pResults : 0); i++) {

short * p = ((short*)(pResults + 1)) + 6 * i;
// <left_x top_y width height detection_score>
//we do it
string face_vector = Int_String(p[0]) + " " + Int_String(p[1]) + " " + Int_String(p[2]) + " " + Int_String(p[3]) + " " + Double_String(p[5]);//detect_score，根据官网上的介绍，分类器中应该就包含这个参数。如果你是用opencv,那么在detectMultiScale中可以找到
face.push_back(face_vector);
}
//首先打开txt
ofstream result("result.txt", ios::app);
result << face_position_1 << endl << face_position_2 << endl;
result.close();//先关闭一次
//把vector写入
for (vector<string>::iterator iter = face.begin(); iter != face.end(); ++iter) {
ofstream result_eachface("result.txt", ios::app);  //每一张脸
result_eachface << *iter << endl;
result_eachface.close();
}
face.clear();//清除这个
result.clear();
}

int _tmain(int argc, _TCHAR* argv[])
{
string file = "Fold_all.txt";
string line;
ifstream in(file);

if (in) // 有该文件
{
while (getline(in, line)) // line中不包括每行的换行符
{
string pic_road = line + ".jpg";
Mat gray = imread(pic_road, CV_LOAD_IMAGE_GRAYSCALE);//it is necessary that must have CV_LOAD_IMAGE_GRAYSCALE
detectAndDisplay(gray, line);
}
}
cout << "Finally we got it";
getchar();
return 0;
}

运行代码，检测结果会保存到txt文件中

新建评测项目，将evaluation的文件拷贝到项目中

运行代码，得到tempContROC.txt和tempDiscROC.txt

安装perl和gnuplot

配置perl

写评测pl文件

#!/usr/bin/perl -w
use strict;
#### VARIABLES TO EDIT ####
# where gnuplot is
my $GNUPLOT = "D:/Program Files (x86)/gnuplot/bin/gnuplot";
# where the binary is
my $evaluateBin = "evaluate";
# where the images are
my $imDir = "G:/code/face_opensource/fddb_roc"; #FDDB数据库的图片在哪
# where the folds are
my $fddbDir = "G:/code/face_opensource/fddb_roc"; #fddb图片的两个txt
# where the detections are
my $detDir = "G:/code/face_opensource/fddb_evaluate/"; #图片存放的位置
###########################

my $detFormat = 0; # 0: rectangle, 1: ellipse 2: pixels

sub makeGNUplotFile
{
my $rocFile = shift;
my $gnuplotFile = shift;
my $title = shift;
my $pngFile = shift;

open(GF, ">$gnuplotFile") or die "Can not open $gnuplotFile for writing\n";
#print GF "$GNUPLOT\n";
print GF "set term png\n";
print GF "set size 1,1\n";
print GF "set output \"$pngFile\"\n";
#print GF "set xtics 500\n";
print GF "set ytics 0.1\n";
print GF "set grid\n";
#print GF "set size ratio -1\n";
print GF "set ylabel \"True positive rate\"\n";
print GF "set xlabel \"False positives\"\n";
#print GF "set xr [0:2000]\n";
print GF "set yr [0:1.0]\n";
print GF "set key right bottom\n";
print GF "plot \"$rocFile\" using 2:1 title \"$title\" with lines lw 2 \n";
close(GF);
}

my $gpFile = "G:/code/face_opensource/fddb_evaluate/ContROC.p";
my $gpFile1 = "G:/code/face_opensource/fddb_evaluate/DistROC.p";
my $title = "multiview_reinforce";

# plot the two ROC curves using GNUplot
makeGNUplotFile("G:/code/face_opensource/fddb_evaluate/tempContROC.txt", $gpFile, $title, $detDir."ContROC.png");
makeGNUplotFile("G:/code/face_opensource/fddb_evaluate/tempDiscROC.txt", $gpFile1, $title, $detDir."DiscROC.png");

运行pl文件得到ContROC.p和DistROC.p

.p文件拖到gnuplot中，然后file->output即得到结果图片

参考资料