% Gather a set of calibration images.images = imageDatastore(fullfile(toolboxdir('vision'),'visiondata',...'calibration','gopro')); imageFileNames = images.Files;% Detect calibration pattern.[imagePoints, boardSize] = detectCheckerboardPoints(imageFileNames);% Generate world coordinates of the corners of the squares.squareSize = 0.029;% Square size in metersworldPoints = generateCheckerboardPoints(boardSize, squareSize);% Calibrate the camera.I = readimage(images, 1); imageSize = [size(I, 1), size(I, 2)]; params = estimateFisheyeParameters(imagePoints, worldPoints, imageSize);

% Load a different image of the same checkerboard, where the checkerboard% is placed on the flat ground. Its X-axis is pointing to the right of the% vehicle, and its Y-axis is pointing to the camera. The image includes% noticeable distortion, such as along the wall next to the checkerboard.imageFileName = fullfile(toolboxdir('driving'),'drivingdata','checkerboard.png'); I = imread(imageFileName); imshow(I) title('Distorted Checkerboard Image');

[imagePoints, boardSize] = detectCheckerboardPoints(I);% Generate coordinates of the corners of the squares.squareSize = 0.029;% Square size in metersworldPoints = generateCheckerboardPoints(boardSize, squareSize);% Estimate the parameters for configuring the monoCamera object.% Height of the checkerboard is zero here, since the pattern is% directly on the ground.originHeight = 0; [pitch, yaw, roll, height] = estimateMonoCameraParameters(params.Intrinsics,...imagePoints, worldPoints, originHeight);

% Undistort the image and extract the synthetic pinhole camera intrinsics.[J1, camIntrinsics] = undistortFisheyeImage(I, params.Intrinsics,'Output','full'); imshow(J1) title('Undistorted Image');

% Set up monoCamera with the synthetic pinhole camera intrinsics.% Note that the synthetic camera has removed the distortion.sensor = monoCamera(camIntrinsics, height,'pitch', pitch,'yaw'偏航,'roll', roll);

% Define bird's-eye-view transformation parametersdistAheadOfSensor = 6;% in metersspaceToOneSide = 2.5;% look 2.5 meters to the right and 2.5 meters to the leftbottomOffset = 0.2;% look 0.2 meters ahead of the sensoroutView = [bottomOffset, distAheadOfSensor, -spaceToOneSide, spaceToOneSide]; outImageSize = [NaN,1000];% output image width in pixelsbirdsEyeConfig = birdsEyeView(sensor, outView, outImageSize);% Transform input image to bird's-eye-view image and display itB = transformImage(birdsEyeConfig, J1);% Place a 2-meter marker ahead of the sensor in bird's-eye viewimagePoint0 = vehicleToImage(birdsEyeConfig, [2, 0]); offset = 5;% offset marker from text label by 5 pixelsannotatedB = insertMarker(B, imagePoint0 - offset); annotatedB = insertText(annotatedB, imagePoint0,'2 meters'); figure imshow(annotatedB) title('Bird''s-Eye View')