import numpy as np
'''
#T_cam_imu
body_T_cam0: !!opencv-matrix
   rows: 4
   cols: 4
   dt: d
   data: [0.003489987080434578, -0.9999876012230461, 0.003552096614378108, 0.012750626916321976,
          -0.999991882276288, -0.0034971112689532436, -0.002001398086459798, -0.023424853764869122,
          0.0020137953486698786, -0.003545082925974641, -0.9999916884731308, -0.017826923591925007,
          0, 0, 0, 1]
#T_cam_imu
body_T_cam1: !!opencv-matrix
   rows: 4
   cols: 4
   dt: d
   data: [0.00446047102202006, -0.9999665817340186, -0.006851249042621769, -0.10819639255862219,
          -0.9999868688575744, -0.0044430650273882405, -0.002553680791861416, -0.024732250583609703,
          0.002523154907262282, 0.0068625496970663846, -0.9999732691932166, -0.017439737925768566,
          0, 0, 0, 1]
'''
T1=[]
T1.append([0.003489987080434578, -0.9999876012230461, 0.003552096614378108, 0.012750626916321976])
T1.append([-0.999991882276288, -0.0034971112689532436, -0.002001398086459798, -0.023424853764869122])
T1.append([0.0020137953486698786, -0.003545082925974641, -0.9999916884731308, -0.017826923591925007])
T1.append([0, 0, 0, 1])
T2=[]
T2.append([0.00446047102202006, -0.9999665817340186, -0.006851249042621769, -0.10819639255862219])
T2.append([-0.9999868688575744, -0.0044430650273882405, -0.002553680791861416, -0.024732250583609703])
T2.append([0.002523154907262282, 0.0068625496970663846, -0.9999732691932166, -0.017439737925768566])
T2.append([0, 0, 0, 1])
# 矩阵对象可以通过 .I 更方便的求逆
T1_N = np.matrix(T1)
T2_N = np.matrix(T2)
print(T1_N.I)
print(T2_N.I)
 
  
 
 
            //=========================对原始图像畸变矫正==========================
			double fx= 355.0974745605948;
			double fy= 355.47832693317105;
			double cx= 357.7074039567714;
			double cy= 351.0244037313849;
			double k1= -0.023790306606729556;
			double k2= -0.0007571494794293715;
			double p1= 0.00016452517056601848;
			double p2= -0.0005743824914513448;
            cv::Mat cameraMatrix = (cv::Mat_<double>(3, 3) << fx, 0, cx, 0, fy, cy, 0, 0, 1);
            cv::Mat distCoeffs = (cv::Mat_<float>(4, 1) << k1, k2, p1, p2);
			cv::Mat dst_Left;
			// 普通图像畸变矫正
            //undistort(imLeft, dst_Left, cameraMatrix, distCoeffs);
		
	
			cv::Size corrected_size(imLeft.cols,imLeft.rows);
			cv::Mat mapx, mapy;
            // 鱼眼图像畸变矫正
		    cv::fisheye::initUndistortRectifyMap(cameraMatrix, distCoeffs, cv::Matx33d::eye(), cameraMatrix, corrected_size, CV_16SC2, mapx, mapy);
            remap(imLeft, dst_Left, mapx, mapy, cv::INTER_LINEAR, cv::BORDER_TRANSPARENT);
		    
			// cv::imshow("leftImage", imLeft);
			// cv::imshow("dst_Left", dst_Left);
			// cv::waitKey(2);
			imLeft=dst_Left;
            //=========================对原始图像畸变矫正==========================