基於虹軟人臉識別API和Qt5的人臉識別
阿新 • • 發佈:2019-05-22
測試和使用了虹軟的人臉API在QT5環境下設計了一個簡單的人臉識別軟體,實現了對人臉的跟蹤和人臉識別。攝像頭的控制以及影象格式的轉換使用了Opencv,影象顯示使用的是QT5的Qimage控制元件。下面是詳細介紹
1基本流程
(1)載入儲存的參考影象資料和影象標籤,這裡簡單的使用影象的名字作為標籤
(2)使用虹軟人臉識別API計算參考影象的人臉位置資料並存儲
(3)使用opencv VideoCapture 類採集攝像頭影象資料
(2)採集的影象資料送入虹軟人臉識別API 計算人臉位置,並和參考人臉資料計算相似距離,返回最相似的人臉標籤
2 Visual Studio 下構建Qt工程
(1)工程目錄如下圖所示: 其中QtGuiApplication1.ui是介面檔案,Header File資料夾中的amcomdef.h
ammem.h arcsoft_fsdk_face_detection.h arcsoft_fsdk_face_recognition.h
asvloffscreen.h merror.h 是從虹軟庫中拷貝的標頭檔案未做任何修改
FaceDiscern.h 和FaceDiscern.cpp是自定義的一個人臉識別類
(2)工程屬性配置
點選工程屬性->聯結器->輸入中出了QT5的庫檔案,新增opencv_world340d.lib 點選工程屬性-》VC++目錄新增OpenCV的標頭檔案和庫檔案的路徑,其中包含目錄新增opencv的標頭檔案路徑,庫目錄新增opencv的dll路徑,如下圖
(1)QtGuiApplication1 ui類的原始檔如下所示,其中Mat2QImage函式將opencv採集的影象資料轉化為QImage支 持 的資料格式, VideoCapture 是Opencv用來操作攝像頭的類,QImage用來顯示採集的影象資料
#pragma once #include <QtWidgets/QMainWindow> #include "ui_QtGuiApplication1.h" #include "qmessagebox.h" #include "opencv2/core/core.hpp" #include "opencv2/highgui/highgui.hpp" #include "opencv2/imgproc/imgproc.hpp" #include <iostream> #include "qtimer.h" #include "FaceDiscern.h" #include "qrect.h" #include "qpainter.h" using namespace cv; using namespace std; class QtGuiApplication1 : public QMainWindow { Q_OBJECT public: QtGuiApplication1(QWidget *parent = Q_NULLPTR); ~QtGuiApplication1(); QImage Mat2QImage(cv::Mat cvImg); //影象格式轉換 QTimer *timer; Mat frame; //攝像頭直接獲得的資料 FaceDiscern *facediscern; //人臉識別類 private: Ui::QtGuiApplication1Class ui; VideoCapture capture; //採集攝像頭的資料 QImage qImg; //展示影象的控制元件 //---槽函式 用作事件觸發 public slots : void openVideo(); void stopVideo(); void nextFrame(); };
(2)QtGuiApplication1.cpp
#include "QtGuiApplication1.h"
QtGuiApplication1::QtGuiApplication1(QWidget *parent)
: QMainWindow(parent)
{
ui.setupUi(this);
ui.image->setScaledContents(true); //fit video to label area
facediscern = new FaceDiscern("F:\\trainimages");//載入參考影象資料和標籤
facediscern->Train();//計算參考資料影象資料的人臉位置等
}
QtGuiApplication1::~QtGuiApplication1()
{
if (capture.isOpened())
capture.release();
delete(timer);
}
void QtGuiApplication1::openVideo()
{
if (capture.isOpened())
capture.release(); //decide if capture is already opened; if so,close it
capture.open(0); //open the default camera
if (capture.isOpened())
{
double rate = capture.get(CV_CAP_PROP_FPS);
capture >> frame; //獲得攝像頭影象資料
if (!frame.empty())
{
QImage image = Mat2QImage(frame); //將攝像頭的影象資料轉換為QImage支援的格式
this->ui.image->setPixmap(QPixmap::fromImage(image));
timer = new QTimer(this); //迴圈獲得攝像頭資料
connect(timer, SIGNAL(timeout()), this, SLOT(nextFrame()));
timer->start(40);
}
}
}
void QtGuiApplication1::stopVideo()
{
if (capture.isOpened())
{
capture.release();
}
}
//迴圈獲得攝像頭資料
void QtGuiApplication1::nextFrame()
{
capture >> frame;
double rate = capture.get(CV_CAP_PROP_FPS);
if (!frame.empty())
{
QImage image = Mat2QImage(frame);
//通過人臉檢測API獲得人臉的位置並在Qimage上顯示人臉框
QRect rect;
//RecognizeFace識別人臉的位置並計算人臉所屬的標籤
string result = facediscern->RecognizeFace(&frame, rect);
static QTextCodec *codecForCStrings;
QString strQ = QString::fromLocal8Bit(result.c_str());
QString s1 = strQ;//這是在qlabel中顯示中文的辦法
this->ui.result->setText(s1); //在控制元件上顯示人臉所屬的標籤
QPainter painter(&image);
// 設定畫筆顏色
painter.setPen(QColor(255, 0, 0));
painter.drawRect(rect);//繪製人臉的框
this->ui.image->setPixmap(QPixmap::fromImage(image));
}
}
//將opencv 的cv::Mat 格式影象轉換為QImage影象
QImage QtGuiApplication1::Mat2QImage(cv::Mat cvImg)
{
if (cvImg.channels() == 3) //3 channels color image
{
cv::cvtColor(cvImg, cvImg, CV_BGR2RGB); //BGR 轉為 RGB
qImg = QImage((const unsigned char*)(cvImg.data),
cvImg.cols, cvImg.rows,
cvImg.cols*cvImg.channels(),
QImage::Format_RGB888);
}
else if (cvImg.channels() == 1) //grayscale image
{
qImg = QImage((const unsigned char*)(cvImg.data),
cvImg.cols, cvImg.rows,
cvImg.cols*cvImg.channels(),
QImage::Format_Indexed8);
}
else
{
qImg = QImage((const unsigned char*)(cvImg.data),
cvImg.cols, cvImg.rows,
cvImg.cols*cvImg.channels(),
QImage::Format_RGB888);
}
return qImg;
}
(3) FaceDiscern.h
FaceDiscern 是人臉識別的主類 執行了人臉位置檢測和人臉相似度計算等功能
#pragma once
#include <stdio.h>
#include <stdlib.h>
#include <stdint.h>
#include <Windows.h>
#include <iostream>
#include <vector>
#include <string>
#include <io.h>
#include <map>
#include "arcsoft_fsdk_face_recognition.h"
#include "merror.h"
#include "arcsoft_fsdk_face_detection.h"
#include "opencv2/core/core.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "qrect.h"
//動態載入人臉識別的API庫 libarcsoft_fsdk_face_detection是人臉檢測庫
//libarcsoft_fsdk_face_recognition.lib是人臉識別庫
#pragma comment(lib,"libarcsoft_fsdk_face_detection.lib")
#pragma comment(lib,"./libarcsoft_fsdk_face_recognition.lib")
using namespace cv;
#define WORKBUF_SIZE (40*1024*1024)
class FaceDiscern
{
public:
FaceDiscern(std::string _trainpath);
~FaceDiscern();
//將cv::Mat格式的影象轉換為Bitmap
void ConvertMatToBitmap(cv::Mat *img, uint8_t **imageData, int *pWidth, int *pHeight);
void getFiles(std::string path, std::vector<std::string>& files, std::vector<std::string> &ownname);
void Train();
bool readBmp24(const char* path, uint8_t **imageData, int *pWidth, int *pHeight);
std::string RecognizeFace(cv::Mat *img, QRect &rect);
//APPID是從網站上註冊的免費使用id
char APPID[45] = "9aEAsHDYzzzWapX9rH9BZHhdBz8CPTfws4WuF5xdmgnf";
char SDKKey[45] = "61MrwdsfKaMT8cm41uKPQBdCm4rKMLSELtJqs12p7WoV"; //SDKKey
char DETECTIONKKey[45] = "61MrwdsfKaMT8cm41uKPQBci7TocqKmAASGS7infomre";
std::string trainpath = "F:\\trainimages";
MRESULT nRet ;
MHandle hEngine ;
MInt32 nScale ;
MInt32 nMaxFace ;
MByte *pWorkMem;
std::vector<std::string> trainfullfiles;//完整路徑名
std::vector<std::string> trainnamefiles;
std::string *labels;
std::map<std::string, std::string> dicfilenametoname;
/* 初始化引擎和變數 */
MRESULT detectionnRet;
MHandle hdetectionEngine;
MInt32 ndetetionScale;
MInt32 ndetectionMaxFace ;
MByte *pdetectionWorkMem;
int trainCount = 0;
LPAFR_FSDK_FACEMODEL *trainfaceModels;
AFR_FSDK_FACEMODEL dectfaceModels;
};
(4)FaceDiscern.cpp
#include "FaceDiscern.h"
FaceDiscern::FaceDiscern(std::string _trainpath)
{
nRet = MERR_UNKNOWN;
hEngine = nullptr;
nScale = 16;
nMaxFace = 10;
pWorkMem = (MByte *)malloc(WORKBUF_SIZE);
/* 初始化引擎和變數 */
detectionnRet = MERR_UNKNOWN;
hdetectionEngine = nullptr;
ndetetionScale = 16;
ndetectionMaxFace = 10;
pdetectionWorkMem = (MByte *)malloc(WORKBUF_SIZE);
dicfilenametoname.insert(std::pair<std::string, std::string>("bingbing.bmp", "冰冰女神"));
dicfilenametoname.insert(std::pair<std::string, std::string>("fangfang.bmp", "村裡有個姑娘叫小芳"));
dicfilenametoname.insert(std::pair<std::string, std::string>("feifei.bmp", "劉亦菲"));
dicfilenametoname.insert(std::pair<std::string, std::string>("huihui.bmp", "冷工"));
dicfilenametoname.insert(std::pair<std::string, std::string>("shishi.bmp", "詩詩妹妹"));
dicfilenametoname.insert(std::pair<std::string, std::string>("xiaxia.bmp", "天上掉下個林妹妹"));
dicfilenametoname.insert(std::pair<std::string, std::string>("xudasong.bmp", "鬆哥"));
dicfilenametoname.insert(std::pair<std::string, std::string>("likunpeng.bmp", "李工"));
dicfilenametoname.insert(std::pair<std::string, std::string>("gaojianjun.bmp", "高建軍"));
dicfilenametoname.insert(std::pair<std::string, std::string>("liuzhen.bmp", "小鮮肉振哥"));
dicfilenametoname.insert(std::pair<std::string, std::string>("liting.bmp", "女王婷姐"));
dicfilenametoname.insert(std::pair<std::string, std::string>("wangxuetao.bmp", "雪濤"));
dicfilenametoname.insert(std::pair<std::string, std::string>("guowei.bmp", "郭大俠"));
dicfilenametoname.insert(std::pair<std::string, std::string>("mingxin.bmp", "寶寶鳴新"));
this->trainpath = _trainpath;
}
FaceDiscern::~FaceDiscern()
{
/* 釋放引擎和記憶體 */
detectionnRet = AFD_FSDK_UninitialFaceEngine(hdetectionEngine);
if (detectionnRet != MOK)
{
fprintf(stderr, "UninitialFaceEngine failed , errorcode is %d \n", detectionnRet);
}
free(pdetectionWorkMem);
for (int i = 0; i < trainCount; i++)
{
if (trainfaceModels[i]->pbFeature != NULL)
free(trainfaceModels[i]->pbFeature);
}
nRet = AFR_FSDK_UninitialEngine(hEngine);
if (nRet != MOK)
{
fprintf(stderr, "UninitialFaceEngine failed , errorcode is %d \n", nRet);
}
}
//載入所有的參考影象和影象名字作為參考庫
void FaceDiscern::getFiles(std::string path, std::vector<std::string>& files, std::vector<std::string> &ownname)
{
/*files儲存檔案的路徑及名稱(eg. C:\Users\WUQP\Desktop\test_devided\data1.txt)
4 ownname只儲存檔案的名稱(eg. data1.txt)*/
//檔案控制代碼
long long hFile = 0;
//檔案資訊
struct _finddata_t fileinfo;
std::string p;
if ((hFile = _findfirst(p.assign(path).append("\\*").c_str(), &fileinfo)) != -1)
{
do
{
//如果是目錄,迭代之
//如果不是,加入列表
if ((fileinfo.attrib & _A_SUBDIR))
{ /*
if(strcmp(fileinfo.name,".") != 0 && strcmp(fileinfo.name,"..") != 0)
getFiles( p.assign(path).append("\\").append(fileinfo.name), files, ownname ); */
}
else
{
files.push_back(p.assign(path).append("\\").append(fileinfo.name));
ownname.push_back(fileinfo.name);
}
} while (_findnext(hFile, &fileinfo) == 0);
_findclose(hFile);
}
}
//將cv::Mat轉換為Bitmap
void FaceDiscern::ConvertMatToBitmap(cv::Mat *img, uint8_t **imageData, int *pWidth, int *pHeight)
{
//======建立點陣圖資訊 ===========
int width, height, depth, channel;
width = img->cols;
height = img->rows;
depth = img->depth();
channel = img->channels();
*pWidth = width; //影象寬。高
*pHeight = height;
int linebyte = width * channel;
*imageData = (uint8_t *)malloc(linebyte * (*pHeight));
for (int i = 0; i<height; i++) {
for (int j = 0; j<width; j++) {
*((*imageData) + i * width*channel + j * channel) = (*img).at<Vec3b>(i, j)[2];// (uint8_t)(*(img + i * width*channel + j * width + 2));
*((*imageData) + i * width*channel + j * channel + 1) = (*img).at<Vec3b>(i, j)[1];
*((*imageData) + i * width*channel + j * channel + 2) = (*img).at<Vec3b>(i, j)[0];
} // end of line
}
}
//從檔案中讀取影象並轉化為bitmap
bool FaceDiscern::readBmp24(const char* path, uint8_t **imageData, int *pWidth, int *pHeight)
{
if (path == NULL || imageData == NULL || pWidth == NULL || pHeight == NULL)
{
return false;
}
FILE *fp = fopen(path, "rb");
if (fp == NULL)
{
return false;
}
fseek(fp, sizeof(BITMAPFILEHEADER), 0);
BITMAPINFOHEADER head;
fread(&head, sizeof(BITMAPINFOHEADER), 1, fp);
*pWidth = head.biWidth;
*pHeight = head.biHeight;
int biBitCount = head.biBitCount;
if (24 == biBitCount)
{
int lineByte = ((*pWidth) * biBitCount / 8 + 3) / 4 * 4;
*imageData = (uint8_t *)malloc(lineByte * (*pHeight));
uint8_t * data = (uint8_t *)malloc(lineByte * (*pHeight));
fseek(fp, 54, SEEK_SET);
fread(data, 1, lineByte * (*pHeight), fp);
for (int i = 0; i < *pHeight; i++)
{
for (int j = 0; j < *pWidth; j++)
{
memcpy((*imageData) + i * (*pWidth) * 3 + j * 3, data + (((*pHeight) - 1) - i) * lineByte + j * 3, 3);
}
}
free(data);
}
else
{
fclose(fp);
return false;
}
fclose(fp);
return true;
}
//載入所有的參考資料
void FaceDiscern::Train()
{
if (pWorkMem == nullptr)
{
return;
}
nRet = AFR_FSDK_InitialEngine(APPID, SDKKey, pWorkMem, WORKBUF_SIZE, &hEngine); //初始化引擎
if (nRet != MOK)
{
return;
}
getFiles(trainpath, trainfullfiles, trainnamefiles);
//生成訓練資料 特徵集合
if (trainfullfiles.size() > 0)
{
//參考影象資料的人臉特徵和標籤的儲存
trainfaceModels = new LPAFR_FSDK_FACEMODEL[trainfullfiles.size()];
labels = new std::string[trainfullfiles.size()];
}
else
{
return ;
}
for (int i = 0; i < trainfullfiles.size(); i++)
{
std::string filename = trainfullfiles[i];
/* 讀取第一張靜態圖片資訊,並儲存到ASVLOFFSCREEN結構體 (以ASVL_PAF_RGB24_B8G8R8格式為例) */
ASVLOFFSCREEN offInput = { 0 };
offInput.u32PixelArrayFormat = ASVL_PAF_RGB24_B8G8R8;
offInput.ppu8Plane[0] = nullptr;
const char * path = filename.c_str();
readBmp24(path, (uint8_t**)&offInput.ppu8Plane[0], &offInput.i32Width, &offInput.i32Height);
if (!offInput.ppu8Plane[0])
{
fprintf(stderr, "fail to ReadBmp(%s)\n", path);
AFR_FSDK_UninitialEngine(hEngine);
free(pWorkMem);
continue ;
}
offInput.pi32Pitch[0] = offInput.i32Width * 3;
AFR_FSDK_FACEMODEL *faceModels = new AFR_FSDK_FACEMODEL();
{
AFR_FSDK_FACEINPUT faceInput;
//第一張人臉資訊通過face detection\face tracking獲得
faceInput.lOrient = AFR_FSDK_FOC_0;//人臉方向
//人臉框位置
faceInput.rcFace.left = 0;
faceInput.rcFace.top = 0;
faceInput.rcFace.right = offInput.i32Width - 2;;
faceInput.rcFace.bottom = offInput.i32Height - 2;;
//提取第一張人臉特徵
AFR_FSDK_FACEMODEL LocalFaceModels = { 0 };
nRet = AFR_FSDK_ExtractFRFeature(hEngine, &offInput, &faceInput, &LocalFaceModels);
if (nRet != MOK)
{
fprintf(stderr, "fail to Extract 1st FR Feature, error code: %d\n", nRet);
}
/* 拷貝人臉特徵結果 */
faceModels->lFeatureSize = LocalFaceModels.lFeatureSize;
faceModels->pbFeature = (MByte*)malloc(faceModels->lFeatureSize);
memcpy(faceModels->pbFeature, LocalFaceModels.pbFeature, faceModels->lFeatureSize);
}
trainfaceModels[i] = faceModels;
labels[i] = trainnamefiles[i];
trainCount++;
}
if (pdetectionWorkMem == nullptr)
{
return;
}
//人臉檢測engine
detectionnRet = AFD_FSDK_InitialFaceEngine(APPID, DETECTIONKKey, pdetectionWorkMem, WORKBUF_SIZE, &hdetectionEngine, AFD_FSDK_OPF_0_HIGHER_EXT, ndetetionScale, ndetectionMaxFace);
if (detectionnRet != MOK)
{
return;
}
}
//簡單的通過距離相似計算出最相似的參考影象
std::string FaceDiscern::RecognizeFace(cv::Mat *img, QRect &rect)
{
/* 讀取靜態圖片資訊,並儲存到ASVLOFFSCREEN結構體 (以ASVL_PAF_RGB24_B8G8R8格式為例) */
/* 人臉檢測 */
ASVLOFFSCREEN offInput = { 0 };
offInput.u32PixelArrayFormat = ASVL_PAF_RGB24_B8G8R8;
offInput.ppu8Plane[0] = nullptr;
ConvertMatToBitmap(img, (uint8_t**)&offInput.ppu8Plane[0], &offInput.i32Width, &offInput.i32Height);
if (!offInput.ppu8Plane[0])
{
return "";
}
offInput.pi32Pitch[0] = offInput.i32Width * 3;
LPAFD_FSDK_FACERES FaceRes = nullptr;
detectionnRet = AFD_FSDK_StillImageFaceDetection(hdetectionEngine, &offInput, &FaceRes);
void *imgptr = offInput.ppu8Plane[0];
////識別人臉資訊
AFR_FSDK_FACEINPUT faceInput;
faceInput.lOrient = AFR_FSDK_FOC_0;//人臉方向 //人臉框位置
faceInput.rcFace.left =FaceRes->rcFace[0].left;
faceInput.rcFace.top = FaceRes->rcFace[0].top;
faceInput.rcFace.right = FaceRes->rcFace[0].right;
faceInput.rcFace.bottom = FaceRes->rcFace[0].bottom;
rect.setLeft(FaceRes->rcFace[0].left);
rect.setTop(FaceRes->rcFace[0].top);
rect.setRight(FaceRes->rcFace[0].right);
rect.setBottom(FaceRes->rcFace[0].bottom);
//提取人臉特徵
nRet = AFR_FSDK_ExtractFRFeature(hEngine, &offInput, &faceInput, &dectfaceModels);
free(imgptr);
if (nRet != MOK)
{
return "";
}
float maxscore = -1.0;
int index = -1;
for (int i = 0; i < trainCount; i++)
{
MFloat fSimilScore = 0.0f;
nRet = AFR_FSDK_FacePairMatching(hEngine, &dectfaceModels, trainfaceModels[i], &fSimilScore);
if (fSimilScore > maxscore)
{
maxscore = fSimilScore;
index = i;
}
}
if (index != -1)
{
double num = maxscore * 100.0;
std::string str;
char ctr[10];
_gcvt(num, 6, ctr);
str = ctr;
std::string nameresult = labels[index];
if (dicfilenametoname.find(nameresult) != dicfilenametoname.end())
{
nameresult = dicfilenametoname[nameresult];
}
return nameresult + "," + str;
}
//釋放
if(dectfaceModels.lFeatureSize>0)
free(dectfaceModels.pbFeature);
return "";
}
(3) 介面展示 最後是SDK下載地址 https://ai.arcsoft.com.cn/ucenter/user/reg?utm_source=csdn1&ut