mat

Perspectively transform points

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After we get the transformation matrix 'trans_mat' from the 'getPerspectiveTransform', we can transform a point in this way

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        cv::Point2f src = cv::Point2f(123, 456);
        std::vector<cv::Point2f> in_pts, out_pts;
        in_pts.push_back(src);
        cv::perspectiveTransform(in_pts, out_pts, trans_mat);
        cv::Point2f dst = out_pts.front();

refer to:
https://blog.csdn.net/xiaowei_cqu/article/details/26478135

Render video from OpenCV Mat using Direct3d

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mainwindow.h

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#include "vren_thread.h"
 
class MainWindow : public QMainWindow
{
	Q_OBJECT
	...
	vren_thread vren_;
};

mainwindow.c

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#include "mainwindow.h"
#include <opencv2/opencv.hpp>
#include <opencv2/imgproc/types_c.h>
 
void CALLBACK DecCBFun(long nPort, char* pBuf, long nSize, FRAME_INFO* pFrameInfo, long nReserved1, long nReserved2)
{
	long lFrameType = pFrameInfo->nType;
 
	if (lFrameType == T_YV12)
	{
		MainWindow* win = port2MainWindow[nPort];
		if (nullptr == win)
		{
			qDebug() << "lookup main window from " << nPort << " failed.";
			return;
		}
 
		win->realYuvCallback(pBuf, nSize, pFrameInfo->nStamp, pFrameInfo->nWidth, pFrameInfo->nHeight);
	}
}
 
void MainWindow::realYuvCallback(const char* pBuf, int len, int64_t nStamp, int width, int height)
{
	cv::Mat dst(height, width, CV_8UC3);
	cv::Mat src(height + height / 2, width, CV_8UC1, (uchar*)pBuf);
	cv::cvtColor(src, dst, CV_YUV2RGBA_YV12); // CV_YUV2BGR_YV12);
	cv::line(dst, cv::Point(0, 0), cv::Point(100, 100), cv::Scalar(255, 0, 0), 10);
 
	vren_.Render_d3d(dst);
}
 
void CALLBACK fRealDataCallBack(LONG lRealHandle, DWORD dwDataType, BYTE* pBuffer, DWORD dwBufSize, void* pUser)
{
	MainWindow* pThis = (MainWindow*)pUser;
	pThis->realDataCallback(lRealHandle, dwDataType, pBuffer, dwBufSize);
}
 
void MainWindow::realDataCallback(LONG lRealHandle, DWORD dwDataType, BYTE* pBuffer, DWORD dwBufSize)
{
	DWORD dRet = 0;
	BOOL inData = FALSE;
 
	switch (dwDataType)
	{
	case NET_DVR_SYSHEAD:
		if (!PlayM4_GetPort(&port_))
		{
			break;
		}
 
		port2MainWindow[port_] = this;
		playWnd_ = (HWND)ui->widgetVideo->winId();
		vren_.SetParam(playWnd_);
 
		if (!PlayM4_OpenStream(port_, pBuffer, dwBufSize, 1024 * 1024))
		{
			dRet = PlayM4_GetLastError(port_);
			break;
		}
 
		if (!PlayM4_SetDecCallBackEx(port_, DecCBFun, NULL, NULL))
		{
			dRet = PlayM4_GetLastError(port_);
			break;
		}
 
		if (!PlayM4_Play(port_, NULL)) // playWnd_))
		{
			dRet = PlayM4_GetLastError(port_);
			break;
		}
	}
}

vren_thread.h

Read more

OpenCV备忘录

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mat的遍历方法
refer to: https://blog.csdn.net/koibiki/article/details/85954121

如何使用opencv给视频添加水印并保存
refer to: https://blog.csdn.net/weixin_44903147/article/details/102969715

bool solvePnP(InputArray objectPoints, InputArray imagePoints, InputArray cameraMatrix, InputArray distCoeffs, OutputArray rvec, OutputArray tvec, bool useExtrinsicGuess=false, int flags=ITERATIVE )

objectPoints为特征点的世界坐标，特征点通常为4个，坐标值需为float型，不能为double型，可以输入mat类型，也可以直接输入vector 。
imagePoints为特征点在图像中的坐标，需要与前面的输入一一对应。同样可以输入mat类型，也可以直接输入vector 。
cameraMatrix为相机内参数矩阵，大小为3×3。事先通过OpenCV自带例程求出相机标定参数。
distCoeffs输入为相机的畸变参数，为1×5的矩阵。事先通过OpenCV自带例程求出相机标定参数。
rvec输出解得的旋转向量。
tvec输出平移向量。
useExtrinsicGuess为true后似乎会对输出进行优化。
flags：
CV_ITERATIVE，默认值，它通过迭代求出重投影误差最小的解作为问题的最优解。
CV_P3P则是使用非常经典的Gao的P3P问题求解算法。
CV_EPNP使用文章《EPnP: Efficient Perspective-n-Point Camera Pose Estimation》中的方法求解。

//最小二乘法，解A*X=B中的X
bool cv::solve(InputArray A, InputArray B, OutputArray X, int flags = DECOMP_LU)

refer to:
https://www.cnblogs.com/singlex/p/pose_estimation_1.html
https://www.csdn.net/tags/NtTakgysNTA0NDQtYmxvZwO0O0OO0O0O.html