void dispRefinement::boundaryDetect(Mat& src, Mat& guid, Mat& dest, Mat& mask)
{
int d = 2*r+1;
Size kernel = Size(d,d);
Mat trimap = Mat::zeros(src.size(),CV_8U);
Mat trimask = Mat::zeros(src.size(),CV_8U);
Mat dmax,dmin;
maxFilter(src,dmax,kernel);
minFilter(src,dmin,kernel);
for(int i = 0; i < src.size().area(); i++)
{
uchar maxdiff = dmax.data[i] - src.data[i];
uchar mindiff = src.data[i] - dmin.data[i];
if(dmax.data[i]-dmin.data[i]<th)
{
// non boudnary region
trimap.data[i] = 128;
trimask.data[i] = 255;
}
else // boundary region
{
if(abs(src.data[i]-dmax.data[i])<abs(src.data[i]-dmin.data[i]))
{
trimap.data[i]=255; // foreground region
}
else
{
trimap.data[i]=0; // background region
}
}
}
Mat trimax, trimin;
for(int i=0;i<iter_ex;i++)
{
maxFilter(trimap,trimax,Size(3,3));
compare(trimap,0,mask,CMP_NE);
trimax.copyTo(trimap,mask);
minFilter(trimap,trimin,Size(3,3));
compare(trimap,255,mask,CMP_NE);
trimin.copyTo(trimap,mask);
}
trimap.copyTo(dest);
trimask.copyTo(mask);
}
void dispRefinement::dispRefine(Mat& src, Mat& guid, Mat& guid_mask, Mat& alpha)
{
Mat guid_;guid.copyTo(guid_);
Mat tmp;
compare(alpha,255.0*((double)th_r/100.0),tmp,CMP_GT);
guid_.setTo(255,tmp);
compare(alpha,255.0*((double)th_r/100.0),tmp,CMP_LT);
guid_.setTo(0,tmp);
guid_.setTo(128,guid_mask);
int d = 2*r_flip+1;
Size kernel = Size(d,d);
Mat dmax, dmin;
maxFilter(src,dmax,kernel);
minFilter(src,dmin,kernel);
for(int i=0;i<guid.size().area();i++)
{
if(guid.data[i]!=128)
{
if(guid.data[i]==0 && guid_.data[i]==255)
{
src.data[i] = dmax.data[i];
}
else if(guid.data[i]==255 && guid_.data[i]==0)
{
src.data[i] = dmin.data[i];
}
}
}
}
void mattingMethod::getAmap(Mat& img)
{
Mat mask;
Mat trimax;
Mat trimin;
for(int i=0;i<iter;i++)
{
maxFilter(trimap,trimax,Size(3,3));
compare(trimap,0,mask,CMP_NE);
trimax.copyTo(trimap,mask);
minFilter(trimap,trimin,Size(3,3));
compare(trimap,255,mask,CMP_NE);
trimin.copyTo(trimap,mask);
}
Mat tmp;
Mat imgG;cvtColor(img,imgG,CV_BGR2GRAY);
for(int i=0;i<iter_g;i++)
{
guidedFilter(trimap,imgG,tmp,r_g,eps_g/100.0f);
tmp.copyTo(trimap);
}
}
void mattingMethod::boundaryDetect(Mat& disp)
{
int d = 2*r+1;
Size kernel = Size(d,d);
Mat dmax;
Mat dmin;
maxFilter(disp,dmax,kernel);
minFilter(disp,dmin,kernel);
for(int i=0;i<disp.size().area();i++)
{
uchar maxdiff = dmax.data[i] - disp.data[i];
uchar mindiff = disp.data[i] - dmin.data[i];
if(dmax.data[i]-dmin.data[i] < th)
{
trimap.data[i] = 128;
trimask.data[i] = 255;
}
else
{
if(abs(disp.data[i]-dmax.data[i])<abs(disp.data[i]-dmin.data[i]))
{
trimap.data[i] = 255;
}
else
{
trimap.data[i] = 0;
}
}
}
}
int CDataset::extractFeatures(const CConfig& conf){
int imgRow = this->img.at(0)->rows, imgCol = this->img.at(0)->cols;
cv::Mat *integralMat;
if(conf.learningMode != 1){
if(conf.rgbFeature == 1){ // if got rgb image only, calc hog feature
feature.clear();
feature.resize(32);
for(int i = 0; i < 32; ++i)
feature.at(i) = new cv::Mat(imgRow, imgCol, CV_8UC1);
cv::cvtColor(*img.at(0), *(feature.at(0)), CV_RGB2GRAY);
cv::Mat I_x(imgRow, imgCol, CV_16SC1);
cv::Mat I_y(imgRow, imgCol, CV_16SC1);
cv::Sobel(*(feature.at(0)), I_x, CV_16S, 1, 0);
cv::Sobel(*(feature.at(0)), I_y, CV_16S, 0, 1);
cv::convertScaleAbs(I_x, *(feature[3]), 0.25);
cv::convertScaleAbs(I_y, *(feature[4]), 0.25);
// Orientation of gradients
for(int y = 0; y < img.at(0)->rows; y++)
for(int x = 0; x < img.at(0)->cols; x++) {
// Avoid division by zero
float tx = (float)I_x.at<short>(y, x) + (float)copysign(0.000001f, I_x.at<short>(y, x));
// Scaling [-pi/2 pi/2] -> [0 80*pi]
feature.at(1)->at<uchar>(y, x) = (uchar)(( atan((float)I_y.at<short>(y, x) / tx) + 3.14159265f / 2.0f ) * 80);
//std::cout << "scaling" << std::endl;
feature.at(2)->at<uchar>(y, x) = (uchar)sqrt((float)I_x.at<short>(y, x)* (float)I_x.at<short>(y, x) + (float)I_y.at<short>(y, x) * (float)I_y.at<short>(y, x));
}
// Magunitude of gradients
for(int y = 0; y < img.at(0)->rows; y++)
for(int x = 0; x < img.at(0)->cols; x++ ) {
feature.at(2)->at<uchar>(y, x) = (uchar)sqrt(I_x.at<short>(y, x)*I_x.at<short>(y, x) + I_y.at<short>(y, x) * I_y.at<short>(y, x));
}
hog.extractOBin(feature[1], feature[2], feature, 7);
// calc I_xx I_yy
cv::Sobel(*(feature.at(0)), I_x, CV_16S, 2, 0);
cv::Sobel(*(feature.at(0)), I_y, CV_16S, 0, 2);
cv::convertScaleAbs(I_x, *(feature[5]), 0.25);
cv::convertScaleAbs(I_y, *(feature[6]), 0.25);
cv::Mat img_Lab;
cv::cvtColor(*img.at(0), img_Lab, CV_RGB2Lab);
cv::vector<cv::Mat> tempfeature(3);
cv::split(img_Lab, tempfeature);
for(int i = 0; i < 3; ++i)
tempfeature.at(i).copyTo(*(feature.at(i)));
// min max filter
for(int c = 0; c < 16; ++c)
minFilter(feature[c], feature[c + 16], 5);
for(int c = 0; c < 16; ++c)
maxFilter(feature[c], feature[c], 5);
}else{
feature.clear();
// calc gray integral image
cv::Mat grayImg(imgRow + 1, imgCol, CV_8U);
cv::cvtColor(*img.at(0), grayImg, CV_RGB2GRAY);
integralMat = new cv::Mat(imgRow + 1, imgCol + 1, CV_64F);
cv::integral(grayImg, *integralMat, CV_64F);
feature.push_back(integralMat);
// calc r g b integral image
std::vector<cv::Mat> splittedRgb;
cv::split(*img.at(0), splittedRgb);
for(int i = 0; i < splittedRgb.size(); ++i){
integralMat = new cv::Mat(imgRow + 1, imgCol + 1, CV_64F);
cv::integral(splittedRgb.at(i), *integralMat, CV_64F);
feature.push_back(integralMat);
}
featureFlag = 1;
}
}
if(img.size() > 1){
cv::Mat tempDepth = cv::Mat(img.at(0)->rows, img.at(0)->cols, CV_8U);// = *img.at(1);
if(img.at(1)->type() != CV_8U)
img.at(1)->convertTo(tempDepth, CV_8U, 255.0 / (double)(conf.maxdist - conf.mindist));
else
tempDepth = *img.at(1);
integralMat = new cv::Mat(imgRow + 1, imgCol + 1, CV_64F);
cv::integral(tempDepth, *integralMat, CV_64F);
feature.push_back(integralMat);
featureFlag = 1;
}
return 0;
}
void maxFilter(InputArray src, OutputArray dest, int radius)
{
maxFilter(src, dest, Size(2 * radius + 1, 2 * radius + 1));
}
