本文整理汇总了C++中eigen::VectorXd::allFinite方法的典型用法代码示例。如果您正苦于以下问题：C++ VectorXd::allFinite方法的具体用法？C++ VectorXd::allFinite怎么用？C++ VectorXd::allFinite使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类eigen::VectorXd的用法示例。
在下文中一共展示了VectorXd::allFinite方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的C++代码示例。
示例1: nextContainer
/**
* Receives images as well the optical flow to calculate the focus of expansion
*/
void DirectionOfMovement::nextContainer(odcore::data::Container &a_c)
{
if(a_c.getDataType() == odcore::data::image::SharedImage::ID()){
odcore::data::image::SharedImage mySharedImg =
a_c.getData<odcore::data::image::SharedImage>();
// std::cout<<mySharedImg.getName()<<std::endl;
std::shared_ptr<odcore::wrapper::SharedMemory> sharedMem(
odcore::wrapper::SharedMemoryFactory::attachToSharedMemory(
mySharedImg.getName()));
const uint32_t nrChannels = mySharedImg.getBytesPerPixel();
const uint32_t imgWidth = mySharedImg.getWidth();
const uint32_t imgHeight = mySharedImg.getHeight();
IplImage* myIplImage = cvCreateImage(cvSize(imgWidth,imgHeight), IPL_DEPTH_8U,
nrChannels);
cv::Mat tmpImage = cv::Mat(myIplImage);
if(!sharedMem->isValid()){
return;
}
sharedMem->lock();
{
memcpy(tmpImage.data, sharedMem->getSharedMemory(),
imgWidth*imgHeight*nrChannels);
}
sharedMem->unlock();
m_image.release();
m_image = tmpImage.clone();
cvReleaseImage(&myIplImage);
return;
}
if(a_c.getDataType() == opendlv::sensation::OpticalFlow::ID()){
opendlv::sensation::OpticalFlow message =
a_c.getData<opendlv::sensation::OpticalFlow>();
uint16_t nPoints = message.getNumberOfPoints();
std::vector<opendlv::model::Direction> directions =
message.getListOfDirections();
std::vector<float> u = message.getListOfU();
std::vector<float> v = message.getListOfV();
Eigen::MatrixXd flow(nPoints, 4);
Eigen::MatrixXd A(nPoints,2);
Eigen::MatrixXd B(nPoints,1);
for(uint8_t i = 0; i < nPoints; ++i){
flow.row(i) << directions[i].getAzimuth(), directions[i].getZenith(),
u[i], v[i];
}
A.col(0) = flow.col(3);
A.col(1) = -flow.col(2);
B.col(0) = flow.col(3).cwiseProduct(flow.col(0))-flow.col(1).cwiseProduct(flow.col(2));
// FOE = (A * A^T)^-1 * A^T * B
Eigen::VectorXd FoeMomentum = ((A.transpose()*A).inverse() * A.transpose() * B) - m_foePix;
if(FoeMomentum.allFinite()){
if(FoeMomentum.norm() > 10){
m_foePix = m_foePix + FoeMomentum/FoeMomentum.norm()*10;
}
else{
m_foePix = m_foePix + FoeMomentum/20;
}
}
// SendContainer();
std::cout<< m_foePix.transpose() << std::endl;
cv::circle(m_image, cv::Point2f(m_foePix(0),m_foePix(1)), 3, cv::Scalar(0,0,255), -1, 8);
const int32_t windowWidth = 640;
const int32_t windowHeight = 480;
cv::Mat display;
cv::resize(m_image, display, cv::Size(windowWidth, windowHeight), 0, 0,
cv::INTER_CUBIC);
cv::imshow("FOE", display);
cv::waitKey(1);
return;
}
}