OneObjectRow::OneObjectRow(ContourFamily cont_fam,const cv::Mat& raw_img):
m_n_in_clust(cont_fam.n_per_clust),m_valid(true),m_ROI(1)
{
m_rrect = cv::minAreaRect(cont_fam.contours[0]);
m_rad = Features::calculateWH(cont_fam.contours[0]).x;
cv::Rect rect = cv::boundingRect(cont_fam.contours[0]);
cv::Mat mini_mask(rect.height,rect.width,CV_8UC1,cv::Scalar(0));
cv::Mat mini_img;
raw_img(rect).copyTo(mini_img);
cv::drawContours(mini_mask,cont_fam.contours,0,cv::Scalar(255),-1,8, cont_fam.hierarchies, 2, cv::Point(-rect.x,-rect.y));
cv::Mat mean, stddev;
cv::meanStdDev(mini_img, mean, stddev, mini_mask);
m_area = cv::countNonZero(mini_mask);
stddev +=1;
m_BGR_mean = mean.at<cv::Scalar>(0,0);
m_BGR_sd = stddev.at<cv::Scalar>(0,0);
cv::Mat one_pix(1,1,CV_8UC3,m_BGR_mean);
cv::cvtColor(one_pix,one_pix,CV_BGR2HLS);
cv::Scalar mean_sc = cv::mean(one_pix); //?
m_hue_mean =((int) mean_sc [0])*2;
m_sat_mean = (int) mean_sc [2];
}
std::vector<bool> Step_FiltHS::filter(const Result& in_numerical_result){
std::vector<bool> valid(in_numerical_result.size(),true);
for(unsigned int i = 0; i < valid.size(); i++){
const OneObjectRow& oor = in_numerical_result.getRow(i);
cv::Scalar mean = oor.getBGRMean();
cv::Mat one_pix(1,1,CV_8UC3,mean);
cv::cvtColor(one_pix,one_pix,CV_BGR2HLS);
mean = cv::mean(one_pix);
int mean_hue =((int) mean[0])*2;
float aa = (float) mean_hue * 3.1416 /180;
float bb = (float) m_centr_hue * 3.1416 /180;
int diff = abs(atan2(sin(aa-bb), cos(aa-bb)) * 180 / 3.1416);
int mean_sat = (int) mean[2];
if(diff > m_tol_hue || mean_sat > m_max_sat || mean_sat < m_min_sat)
valid[i] = false;
else
valid[i] = oor.isValid();
}
return valid;
}
