人脸识别opencv

1楼-- · 2019-07-25 22:28

http://wiki.opencv.org.cn/index. ... 8%E6%A3%80%E6%B5%8B
看这篇文章
[mw_shl_code=cpp,true]#include "cv.h"
#include "highgui.h"

#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <assert.h>
#include <math.h>
#include <float.h>
#include <limits.h>
#include <time.h>
#include <ctype.h>

#ifdef _EiC
#define WIN32
#endif

static CvMemStorage* storage = 0;
static CvHaarClassifierCascade* cascade = 0;

void detect_and_draw( IplImage* image );

const char* cascade_name =
"haarcascade_frontalface_alt.xml";
/* "haarcascade_profileface.xml";*/

int main( int argc, char** argv )
{
CvCapture* capture = 0;
IplImage *frame, *frame_copy = 0;
int optlen = strlen("--cascade=");
const char* input_name;

if( argc > 1 && strncmp( argv[1], "--cascade=", optlen ) == 0 )
{
      cascade_name = argv[1] + optlen;
      input_name = argc > 2 ? argv[2] : 0;
}
else
{
      cascade_name = "../../data/haarcascades/haarcascade_frontalface_alt2.xml";
      //opencv装好后haarcascade_frontalface_alt2.xml的路径,
   //也可以把这个文件拷到你的工程文件夹下然后不用写路径名cascade_name= "haarcascade_frontalface_alt2.xml";
   //或者cascade_name ="C:\Program Files\OpenCV\data\haarcascades\haarcascade_frontalface_alt2.xml"
      input_name = argc > 1 ? argv[1] : 0;
}

cascade = (CvHaarClassifierCascade*)cvLoad( cascade_name, 0, 0, 0 );

if( !cascade )
{
      fprintf( stderr, "ERROR: Could not load classifier cascade " );
      fprintf( stderr,
      "Usage: facedetect --cascade="<cascade_path>" [filename|camera_index] " );
      return -1;
}
storage = cvCreateMemStorage(0);

if( !input_name || (isdigit(input_name[0]) && input_name[1] == '') )
      capture = cvCaptureFromCAM( !input_name ? 0 : input_name[0] - '0' );
else
      capture = cvCaptureFromAVI( input_name );

cvNamedWindow( "result", 1 );

if( capture )
{
      for(;;)
      {
         if( !cvGrabFrame( capture ))
            break;
         frame = cvRetrieveFrame( capture );
         if( !frame )
            break;
         if( !frame_copy )
            frame_copy = cvCreateImage( cvSize(frame->width,frame->height),
                                          IPL_DEPTH_8U, frame->nChannels );
         if( frame->origin == IPL_ORIGIN_TL )
            cvCopy( frame, frame_copy, 0 );
         else
            cvFlip( frame, frame_copy, 0 );

         detect_and_draw( frame_copy );

         if( cvWaitKey( 10 ) >= 0 )
            break;
      }

      cvReleaseImage( &frame_copy );
      cvReleaseCapture( &capture );
}
else
{
      const char* filename = input_name ? input_name : (char*)"lena.jpg";
      IplImage* image = cvLoadImage( filename, 1 );

      if( image )
      {
         detect_and_draw( image );
         cvWaitKey(0);
         cvReleaseImage( &image );
      }
      else
      {
         /* assume it is a text file containing the
            list of the image filenames to be processed - one per line */
         FILE* f = fopen( filename, "rt" );
         if( f )
         {
            char buf[1000+1];
            while( fgets( buf, 1000, f ) )
            {
                  int len = (int)strlen(buf);
                  while( len > 0 && isspace(buf[len-1]) )
                     len--;
                  buf[len] = '';
                  image = cvLoadImage( buf, 1 );
                  if( image )
                  {
                     detect_and_draw( image );
                     cvWaitKey(0);
                     cvReleaseImage( &image );
                  }
            }
            fclose(f);
         }
      }

}

cvDestroyWindow("result");

return 0;
}

void detect_and_draw( IplImage* img )
{
static CvScalar colors[] =
{
      {{0,0,255}},
      {{0,128,255}},
      {{0,255,255}},
      {{0,255,0}},
      {{255,128,0}},
      {{255,255,0}},
      {{255,0,0}},
      {{255,0,255}}
};

double scale = 1.3;
IplImage* gray = cvCreateImage( cvSize(img->width,img->height), 8, 1 );
IplImage* small_img = cvCreateImage( cvSize( cvRound (img->width/scale),
                     cvRound (img->height/scale)),
                  8, 1 );
int i;

cvCvtColor( img, gray, CV_BGR2GRAY );
cvResize( gray, small_img, CV_INTER_LINEAR );
cvEqualizeHist( small_img, small_img );
cvClearMemStorage( storage );

if( cascade )
{
      double t = (double)cvGetTickCount();
      CvSeq* faces = cvHaarDetectObjects( small_img, cascade, storage,
                                          1.1, 2, 0/*CV_HAAR_DO_CANNY_PRUNING*/,
                                          cvSize(30, 30) );
      t = (double)cvGetTickCount() - t;
      printf( "detection time = %gms ", t/((double)cvGetTickFrequency()*1000.) );
      for( i = 0; i < (faces ? faces->total : 0); i++ )
      {
         CvRect* r = (CvRect*)cvGetSeqElem( faces, i );
         CvPoint center;
         int radius;
         center.x = cvRound((r->x + r->width*0.5)*scale);
         center.y = cvRound((r->y + r->height*0.5)*scale);
         radius = cvRound((r->width + r->height)*0.25*scale);
         cvCircle( img, center, radius, colors[i%8], 3, 8, 0 );
      }
}

cvShowImage( "result", img );
cvReleaseImage( &gray );
cvReleaseImage( &small_img );
}[/mw_shl_code]

翱翔云端的鸟

2楼-- · 2019-07-26 00:15

opencv是开源的计算机视觉库，里面很多算法非常复杂，我就接触了一点点教程可以看毛星云的博客
我之前用opencv做手势识别，区分10个手势，用的是轮廓匹配的方法，效果还行(前提是背景 {MOD}不能跟手的颜 {MOD}一致，不然识别不了)

人脸识还要训练什么的好复杂没搞过了。

DreamWaterPro

3楼-- · 2019-07-26 00:59

如果学习openCV建议使用正常的电脑，或者是可以跑linux的嵌入式开发板；
OpenCV中应该是有部分函数，联合起来可以达到人脸识别的目的。个人没有深入学习过，不太清楚。

如果是在STM32上跑，建议参考OpenMV的设计，我没有记错的话是有人脸识别的功能的。

人脸识别是个非常复杂的工作，仅仅会调用库函数就能实现，那个不叫做会人脸识别。