int main()
{
VideoCapture capture(0);
if(!capture.isOpened())
{
cout<<"Camera could not be opened";
exit(0);
}
Mat frame;
capture.read(frame);
Rect rect(220,100,170,170);
Mat imageROI= frame(rect);
Mat hsv;
ColorHistogram hc;
ContentFinder finder;
int minSat=65;int channels[]={0};
namedWindow("image 2");
while(1)
{
MatND colorhist=hc.getHueHistogram(imageROI,minSat);
finder.setHistogram(colorhist);
int a=capture.read(frame);
if(!a)
{
exit(0);
}
cv::cvtColor(frame, hsv, CV_BGR2HSV);
std::vector<cv::Mat> v;
cv::split(hsv,v);
threshold(v[1],v[1],minSat,255,cv::THRESH_BINARY);
// Get back-projection of hue histogram
Mat result= finder.find(hsv,0.0f,180.0f,channels,1);
// Eliminate low stauration pixels
cv::bitwise_and(result,v[1],result);
cv::TermCriteria criteria(cv::TermCriteria::MAX_ITER,10,0.01);
cv::CamShift(result,rect,criteria);
cv::rectangle(frame, rect, cv::Scalar(0,0,255));
imshow("image 2",frame);
int c= cvWaitKey(10);
if(char(c)==27)
{
exit(0);
}
//cv::imshow("Image",result);
Mat imageROI= frame(rect);
}
cv::waitKey(0);
return 0;
}
int main()
{
// Read input image
cv::Mat image= cv::imread("waves.jpg",0);
if (!image.data)
return 0;
// define image ROI
cv::Mat imageROI;
imageROI= image(cv::Rect(216,33,24,30)); // Cloud region
// Display reference patch
cv::namedWindow("Reference");
cv::imshow("Reference",imageROI);
// Find histogram of reference
Histogram1D h;
cv::Mat hist= h.getHistogram(imageROI);
cv::namedWindow("Reference Hist");
cv::imshow("Reference Hist",h.getHistogramImage(imageROI));
// Create the content finder
ContentFinder finder;
// set histogram to be back-projected
finder.setHistogram(hist);
finder.setThreshold(-1.0f);
// Get back-projection
cv::Mat result1;
result1= finder.find(image);
// Create negative image and display result
cv::Mat tmp;
result1.convertTo(tmp,CV_8U,-1.0,255.0);
cv::namedWindow("Backprojection result");
cv::imshow("Backprojection result",tmp);
// Get binary back-projection
finder.setThreshold(0.12f);
result1= finder.find(image);
// Draw a rectangle around the reference area
cv::rectangle(image, cv::Rect(216, 33, 24, 30), cv::Scalar(0, 0, 0));
// Display image
cv::namedWindow("Image");
cv::imshow("Image",image);
// Display result
cv::namedWindow("Detection Result");
cv::imshow("Detection Result",result1);
// Load color image
ColorHistogram hc;
cv::Mat color= cv::imread("waves.jpg");
// extract region of interest
imageROI= color(cv::Rect(0,0,100,45)); // blue sky area
// Get 3D colour histogram (8 bins per channel)
hc.setSize(8); // 8x8x8
cv::Mat shist= hc.getHistogram(imageROI);
// set histogram to be back-projected
finder.setHistogram(shist);
finder.setThreshold(0.05f);
// Get back-projection of color histogram
result1= finder.find(color);
cv::namedWindow("Color Detection Result");
cv::imshow("Color Detection Result",result1);
// Second color image
cv::Mat color2= cv::imread("dog.jpg");
cv::namedWindow("Second Image");
cv::imshow("Second Image",color2);
// Get back-projection of color histogram
cv::Mat result2= finder.find(color2);
cv::namedWindow("Result color (2)");
cv::imshow("Result color (2)",result2);
// Get ab color histogram
hc.setSize(256); // 256x256
cv::Mat colorhist= hc.getabHistogram(imageROI);
// display 2D histogram
colorhist.convertTo(tmp,CV_8U,-1.0,255.0);
cv::namedWindow("ab histogram");
cv::imshow("ab histogram",tmp);
// set histogram to be back-projected
finder.setHistogram(colorhist);
finder.setThreshold(0.05f);
// Convert to Lab space
cv::Mat lab;
cv::cvtColor(color, lab, CV_BGR2Lab);
// Get back-projection of ab histogram
int ch[2]={1,2};
result1= finder.find(lab,0,256.0f,ch);
cv::namedWindow("Result ab (1)");
cv::imshow("Result ab (1)",result1);
// Second colour image
cv::cvtColor(color2, lab, CV_BGR2Lab);
// Get back-projection of ab histogram
result2= finder.find(lab,0,256.0,ch);
cv::namedWindow("Result ab (2)");
cv::imshow("Result ab (2)",result2);
// Draw a rectangle around the reference sky area
cv::rectangle(color,cv::Rect(0,0,100,45),cv::Scalar(0,0,0));
cv::namedWindow("Color Image");
cv::imshow("Color Image",color);
// Get Hue colour histogram
hc.setSize(180); // 180 bins
colorhist= hc.getHueHistogram(imageROI);
// set histogram to be back-projected
finder.setHistogram(colorhist);
// Convert to HSV space
cv::Mat hsv;
cv::cvtColor(color, hsv, CV_BGR2HSV);
// Get back-projection of hue histogram
ch[0]=0;
result1= finder.find(hsv,0.0f,180.0f,ch);
cv::namedWindow("Result Hue (1)");
cv::imshow("Result Hue (1)",result1);
// Second colour image
color2= cv::imread("dog.jpg");
// Convert to HSV space
cv::cvtColor(color2, hsv, CV_BGR2HSV);
// Get back-projection of hue histogram
result2= finder.find(hsv,0.0f,180.0f,ch);
cv::namedWindow("Result Hue (2)");
cv::imshow("Result Hue (2)",result2);
cv::waitKey();
return 0;
}
int main(int argc, char *argv[])
{
QCoreApplication a(argc, argv);
/*
//创建ColorHistogram 对象
ColorHistogram ch;
// load the image
Mat image = imread("/Users/Haoyang/Downloads/Pics/waves.jpg");
namedWindow("Origianl");
imshow("Original",image);
if(image.data) {
// reduce color
colorReduce(image,32);
// set ROI
Mat blueROI = image(Rect(0,0,165,75));
namedWindow("ROI");
imshow("ROI",blueROI);
// compute the histogram
cv::MatND hist = ch.getColorHistogram(blueROI);
// 创建ContentFinder 对象
ContentFinder *finder = new ContentFinder;
finder->setHistogram(hist);
finder->setThreshold(0.05f);
// std::cout << finder->getThreshold() << std::endl;
std::cout << finder->getMinValue() << std::endl;
std::cout << finder->getMaxValue() << std::endl;
// Get back-projection of color histgram
cv::Mat result = finder->find(image,finder->getMinValue(),
finder->getMaxValue(),finder->getChannels(),
3);
namedWindow("Result");
imshow("Result",result);
}
else
std::cerr << "你妹，读文件出错！" << std::endl;
*/
/*****************************************************************/
/********************** MEAN SHIFT ALGORITHM *********************/
// 读入第一张图片
Mat image1 = imread("/Users/Haoyang/Downloads/Pics/baboon1.jpg");
// 获取脸部，作为ROI
Mat image1ROI = image1(Rect(110,260,35,40));
// namedWindow("temp",cv::WINDOW_AUTOSIZE);
// imshow("temp",image1ROI);
// Get the hue histogram
int minSat = 65;
ColorHistogram hc;
cv::MatND colorhist = hc.getHueHistogram(image1ROI,minSat);
ContentFinder *finder = new ContentFinder;
// 将得到的脸部的 1D hue histogram作为参数输入，
// 用来设置ContentFinder 的私有变量
finder->setHistogram(colorhist);
// 打开第二张图像
Mat image2 = imread("/Users/Haoyang/Downlaods/Pics/baboon2.jpg");
// Convert to hsv color space
Mat hsv;
cv::cvtColor(image2, hsv,CV_BGR2HSV);
// split the image
std::vector<Mat> v;
cv::split(image2,v);
// Identify pixels with low saturation
cv::threshold(v[1],v[1],minSat,255,cv::THRESH_BINARY);
// next, obtain the back-projection of the hue channel of this image
// using the previously obtained histogram
// Get back - projection of hue histogram, using find method
Mat result = finder->find(hsv,0.0f,180,hc.getChannel(),1);
// Eliminate low staturation pixels
cv::bitwise_and(result,v[1],result);
Rect rect(110,260,35,40);
cv::rectangle(image2,rect,cv::Scalar(0,0,255));
TermCriteria criteria(TermCriteria::MAX_ITER,10,0.01);
// cv::meanShift(result,rect,criteria);
cv::meanShift(result,rect,criteria);
namedWindow("Result");
imshow("Result",result);
return a.exec();
}
int main(){
ColorHistogtam hc;
Mat image = imread("baboon1.jpg");
Mat imageROI = image(Rect(110, 260,35,40));
rectangle(image, Rect(110, 260, 35, 40), Scalar(0,0,255));
Mat window(image, Rect(0, 2*image.rows/5, image.cols, image.rows/2));
namedWindow("Image");
imshow("Image", window);
int minSat = 65;
MatND colorhist = hc.getHueHistogram(imageROI,minSat);
ContentFinder finder;
finder.setHistogram(colorhist);
finder.setThreshold(0.2f);
Mat hsv;
cvtColor(image, hsv, CV_BGR2HSV);
vector<Mat> v;
split(hsv,v);
threshold(v[1],v[1], minSat, 255, THRESH_BINARY);
namedWindow("Satruation mask");
imshow("Satruation mask", v[1]);
image = imread("baboon4.jpg");
Mat window2(image, Rect(0, 2*image.rows/5, image.cols, image.rows /2));
namedWindow("Image 2");
imshow("Image 2", window2);
cvtColor(image, hsv, CV_BGR2HSV);
int ch[1] = {0};
finder.setThreshold(-1.0f);
Mat result = finder.find(hsv, 0.0f, 180.0f, ch, 1);
namedWindow("Backprojection on second image");
imshow("Backprojection on second image", result);
Rect rect(110, 260, 35, 40);
rectangle(image, rect, Scalar(0,0,255));
TermCriteria criteria(TermCriteria::MAX_ITER,10, 0.01);
cout <<"meanshif = "<< cv::meanShift(result, rect, criteria)<<endl;
rectangle(image, rect, Scalar(0, 255, 0));
Mat window2r(image, Rect(0,2*image.rows/5, image.cols, image.rows/2));
namedWindow("Image 2 result");
imshow("image 2 result", window2r);
waitKey();
}
