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我正在使用OpenCV進行臉部和眼部檢測。首先，我測試了OpenCV/Samples/c/facedetect.cpp中的示例程序。我給這個facedetect.exe輸入了兩個圖像 - 一個是滿的，另一個是同一個人的裁剪面。現在，facedetect.cpp可以很好地處理完整圖像，但它甚至不會檢測到剪切圖像作爲輸入的人臉。facedetect.cpp檢測裁剪圖像中的眼睛
儘管裁剪後的圖像只包含使用OpenCV人臉檢測器裁剪的人臉，但在某些不好的情況下，我只會得到嘴巴或嘴脣或只是人臉的一部分。所以我的要求是檢查雙眼是否存在於圖像中。
下面是兩個示例圖片一個充滿圖像，我得到正確的輸出： 
下面是我需要使用facedetect.cpp檢測心目中的形象：
所以我的問題是如何檢測裁剪圖像中的眼睛？
的下面是樣品facedetect.cpp
#include "opencv2/objdetect/objdetect.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include <iostream>
#include <stdio.h>
using namespace std;
using namespace cv;
static void help()
{
cout << "\nThis program demonstrates the cascade recognizer. Now you can use Haar or LBP features.\n"
"This classifier can recognize many ~rigid objects, it's most known use is for faces.\n"
"Usage:\n"
"./facedetect [--cascade=<cascade_path> this is the primary trained classifier such as frontal face]\n"
" [--nested-cascade[=nested_cascade_path this an optional secondary classifier such as eyes]]\n"
" [--scale=<image scale greater or equal to 1, try 1.3 for example>\n"
" [filename|camera_index]\n\n"
"see facedetect.cmd for one call:\n"
"./facedetect --cascade=\"../../data/haarcascades/haarcascade_frontalface_alt.xml\" --nested-cascade=\"../../data/haarcascades/haarcascade_eye.xml\" --scale=1.3 \n"
"Hit any key to quit.\n"
"Using OpenCV version " << CV_VERSION << "\n" << endl;
}
void detectAndDraw(Mat& img,
CascadeClassifier& cascade, CascadeClassifier& nestedCascade,
double scale);
String cascadeName = "../../data/haarcascades/haarcascade_frontalface_alt.xml";
String nestedCascadeName = "../../data/haarcascades/haarcascade_eye_tree_eyeglasses.xml";
int main(int argc, const char** argv)
{
CvCapture* capture = 0;
Mat frame, frameCopy, image;
const String scaleOpt = "--scale=";
size_t scaleOptLen = scaleOpt.length();
const String cascadeOpt = "--cascade=";
size_t cascadeOptLen = cascadeOpt.length();
const String nestedCascadeOpt = "--nested-cascade";
size_t nestedCascadeOptLen = nestedCascadeOpt.length();
String inputName;
help();
CascadeClassifier cascade, nestedCascade;
double scale = 1;
for(int i = 1; i < argc; i++)
{
cout << "Processing " << i << " " << argv[i] << endl;
if(cascadeOpt.compare(0, cascadeOptLen, argv[i], cascadeOptLen) == 0)
{
cascadeName.assign(argv[i] + cascadeOptLen);
cout << " from which we have cascadeName= " << cascadeName << endl;
}
else if(nestedCascadeOpt.compare(0, nestedCascadeOptLen, argv[i], nestedCascadeOptLen) == 0)
{
if(argv[i][nestedCascadeOpt.length()] == '=')
nestedCascadeName.assign(argv[i] + nestedCascadeOpt.length() + 1);
if(!nestedCascade.load(nestedCascadeName))
cerr << "WARNING: Could not load classifier cascade for nested objects" << endl;
}
else if(scaleOpt.compare(0, scaleOptLen, argv[i], scaleOptLen) == 0)
{
if(!sscanf(argv[i] + scaleOpt.length(), "%lf", &scale) || scale < 1)
scale = 1;
cout << " from which we read scale = " << scale << endl;
}
else if(argv[i][0] == '-')
{
cerr << "WARNING: Unknown option %s" << argv[i] << endl;
}
else
inputName.assign(argv[i]);
}
if(!cascade.load(cascadeName))
{
cerr << "ERROR: Could not load classifier cascade" << endl;
cerr << "Usage: facedetect [--cascade=<cascade_path>]\n"
" [--nested-cascade[=nested_cascade_path]]\n"
" [--scale[=<image scale>\n"
" [filename|camera_index]\n" << endl ;
return -1;
}
if(inputName.empty() || (isdigit(inputName.c_str()[0]) && inputName.c_str()[1] == '\0'))
{
capture = cvCaptureFromCAM(inputName.empty() ? 0 : inputName.c_str()[0] - '0');
int c = inputName.empty() ? 0 : inputName.c_str()[0] - '0' ;
if(!capture) cout << "Capture from CAM " << c << " didn't work" << endl;
}
else if(inputName.size())
{
image = imread(inputName, 1);
if(image.empty())
{
capture = cvCaptureFromAVI(inputName.c_str());
if(!capture) cout << "Capture from AVI didn't work" << endl;
}
}
else
{
image = imread("lena.jpg", 1);
if(image.empty()) cout << "Couldn't read lena.jpg" << endl;
}
cvNamedWindow("result", 1);
if(capture)
{
cout << "In capture ..." << endl;
for(;;)
{
IplImage* iplImg = cvQueryFrame(capture);
frame = iplImg;
if(frame.empty())
break;
if(iplImg->origin == IPL_ORIGIN_TL)
frame.copyTo(frameCopy);
else
flip(frame, frameCopy, 0);
detectAndDraw(frameCopy, cascade, nestedCascade, scale);
if(waitKey(10) >= 0)
goto _cleanup_;
}
waitKey(0);
_cleanup_:
cvReleaseCapture(&capture);
}
else
{
cout << "In image read" << endl;
if(!image.empty())
{
detectAndDraw(image, cascade, nestedCascade, scale);
waitKey(0);
}
else if(!inputName.empty())
{
/* assume it is a text file containing the
list of the image filenames to be processed - one per line */
FILE* f = fopen(inputName.c_str(), "rt");
if(f)
{
char buf[1000+1];
while(fgets(buf, 1000, f))
{
int len = (int)strlen(buf), c;
while(len > 0 && isspace(buf[len-1]))
len--;
buf[len] = '\0';
cout << "file " << buf << endl;
image = imread(buf, 1);
if(!image.empty())
{
detectAndDraw(image, cascade, nestedCascade, scale);
c = waitKey(0);
if(c == 27 || c == 'q' || c == 'Q')
break;
}
else
{
cerr << "Aw snap, couldn't read image " << buf << endl;
}
}
fclose(f);
}
}
}
cvDestroyWindow("result");
return 0;
}
void detectAndDraw(Mat& img,
CascadeClassifier& cascade, CascadeClassifier& nestedCascade,
double scale)
{
int i = 0;
double t = 0;
vector<Rect> faces;
const static Scalar colors[] = { CV_RGB(0,0,255),
CV_RGB(0,128,255),
CV_RGB(0,255,255),
CV_RGB(0,255,0),
CV_RGB(255,128,0),
CV_RGB(255,255,0),
CV_RGB(255,0,0),
CV_RGB(255,0,255)} ;
Mat gray, smallImg(cvRound (img.rows/scale), cvRound(img.cols/scale), CV_8UC1);
cvtColor(img, gray, CV_BGR2GRAY);
resize(gray, smallImg, smallImg.size(), 0, 0, INTER_LINEAR);
equalizeHist(smallImg, smallImg);
t = (double)cvGetTickCount();
cascade.detectMultiScale(smallImg, faces,
1.1, 2, 0
//|CV_HAAR_FIND_BIGGEST_OBJECT
//|CV_HAAR_DO_ROUGH_SEARCH
|CV_HAAR_SCALE_IMAGE
,
Size(30, 30));
t = (double)cvGetTickCount() - t;
printf("detection time = %g ms\n", t/((double)cvGetTickFrequency()*1000.));
for(vector<Rect>::const_iterator r = faces.begin(); r != faces.end(); r++, i++)
{
Mat smallImgROI;
vector<Rect> nestedObjects;
Point center;
Scalar color = colors[i%8];
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);
circle(img, center, radius, color, 3, 8, 0);
if(nestedCascade.empty())
continue;
smallImgROI = smallImg(*r);
nestedCascade.detectMultiScale(smallImgROI, nestedObjects,
1.1, 2, 0
//|CV_HAAR_FIND_BIGGEST_OBJECT
//|CV_HAAR_DO_ROUGH_SEARCH
//|CV_HAAR_DO_CANNY_PRUNING
|CV_HAAR_SCALE_IMAGE
,
Size(30, 30));
for(vector<Rect>::const_iterator nr = nestedObjects.begin(); nr != nestedObjects.end(); nr++)
{
center.x = cvRound((r->x + nr->x + nr->width*0.5)*scale);
center.y = cvRound((r->y + nr->y + nr->height*0.5)*scale);
radius = cvRound((nr->width + nr->height)*0.25*scale);
circle(img, center, radius, color, 3, 8, 0);
}
}
cv::imshow("result", img);
}
非常感謝您的回覆。 +1的方式提出。我的意圖不是定位眼睛，而是確認裁剪圖像中眼睛的存在。我打算這樣做，以確認裁剪是否已通過我的臉部檢測程序正確完成。希望你現在得到我？再次爲您的迴應偉大的th ... ... – 2vision2
之後，你可以做一些圓檢測或橢圓檢測。 – isrish