（matlab程序）使用激光雷达检测分类跟踪车辆仿真.rar

classdef helperLidarObjectDetectionDisplay < handle %helperLidarObjectDetectionDisplay helper class to display segmented % point cloud data with oriented bounding box visualization. % Copyright 2019-2020 The Mathworks Inc. properties PositionIndex = [1 3 6]; VelocityIndex = [2 4 7]; DimensionIndex = [9 10 11]; YawIndex = 8; end properties (Access = private) % Image handle for visualizing segmented 2D images of organized % point cloud SegmentedImageH; % Axes handle for point cloud visualization PcPlotAxes; % Axes handle for point cloud with oriented bounding box % visualization PcPlotBboxAxes; % Scatter plot handle for visualizing segmented colored point cloud % from network ScatterPlotH; % Scatter plot handle for visualizing point cloud with oriented % bounding box ScatterPlotWithBboxH; % Image handle for visualizing ground truth labels Lidar2DImageH; % Rgb image axes handle ImageAxesH; % Property for holding all the holding frames from figure handle % frames used for writing output video PFrames; % Main gui figure handle FigureH; % Range in x direction XRange; % Range in y direction YRange; % Range in z direction ZRange; % Set it if want to write a video output for the results WriteVideo end properties (Constant, Access = protected) CuboidFaces = [1 5 8 4; ... %far 2 3 7 6; ... %near 5 6 7 8; ... %top 2 1 4 3; ... %bot 3 4 8 7; ... %left 5 6 2 1; ... %right ]; % Calibration matrix used for projecting 3D point to image Calibration=[]; % Default range in X direction DefaultXRange = [-30,30]; % x range to crop display % Default range in y direction DefaultYRange =[-12,12];% y range to crop display % Default range in z direction DefaultZRange =[-3,8]; % Default value to write video DefaultWriteVideo = false; end methods %-------------------------------------------------------------------------- function obj = helperLidarObjectDetectionDisplay(varargin) %% Parse name value parser argument parser = inputParser; parser.CaseSensitive = false; % Parameter Validator validScalarPosNum = @(x) (isequal(size(x),[1,2])); validCalibration = @(x) (isequal(size(x),[3,4])); validVideo = @(x) (islogical(x)); % Optional argument parsers addOptional(parser,'XLimits',obj.DefaultXRange,validScalarPosNum); addOptional(parser,'YLimits',obj.DefaultYRange,validScalarPosNum); addOptional(parser,'ZLimits',obj.DefaultZRange,validScalarPosNum); addOptional(parser,'Calibration',obj.Calibration,validCalibration); addOptional(parser,'Video',obj.DefaultWriteVideo,validVideo); % Parse input arguments parse(parser,varargin{:}); obj.XRange=parser.Results.XLimits; obj.YRange=parser.Results.YLimits; obj.ZRange=parser.Results.ZLimits; obj.WriteVideo = parser.Results.Video; %% Initialize main figure obj.FigureH = figure('Visible','off','Position',[0, 0, 1200, 640],... 'Name','Object Detection','color',[0 0 0],'InvertHardcopy','off'); %% Initialize panel for point cloud visualization pointCloudPanel = uipanel('Parent',obj.FigureH,'Position',[0.01,0,0.50,0.58],... 'BackgroundColor',[0 0 0],'Title','Oriented Bounding Box Detection',... 'ForegroundColor',[1,1,1],'FontSize',15); obj.PcPlotAxes = axes('Parent',pointCloudPanel,'Color',[0 0 0],... 'Position',[0,0,1,1],'NextPlot','replacechildren',... 'XLim',obj.XRange,'YLim',obj.YRange,'ZLim',obj.ZRange); axis(obj.PcPlotAxes,'equal'); obj.PcPlotAxes.XLimMode = 'manual'; obj.PcPlotAxes.YLimMode = 'manual'; obj.PcPlotAxes.ZLimMode = 'manual'; obj.ScatterPlotH = scatter3(obj.PcPlotAxes,nan,nan,nan, 7, '.'); view(obj.PcPlotAxes,3); campos([-169.3414 -242.6887 131.6010]); %% Bounding box point cloud visualizationWriteVideo pointCloudPanel1 = uipanel('Parent',obj.FigureH,'Position',[0.5,0,0.50,0.58],... 'BackgroundColor',[0 0 0],'Title','Top View'... ,'ForegroundColor',[1,1,1],'FontSize',15); obj.PcPlotBboxAxes = axes('Parent',pointCloudPanel1,'Color',[0 0 0],... 'NextPlot','replacechildren','Position' , [0,0,1,1],... 'XLim',obj.XRange,'YLim',obj.YRange,'ZLim',obj.ZRange); obj.PcPlotBboxAxes.Title.Color = [1 1 1]; axis(obj.PcPlotBboxAxes,'equal'); obj.PcPlotBboxAxes.XLimMode = 'manual'; obj.PcPlotBboxAxes.YLimMode = 'manual'; obj.PcPlotBboxAxes.ZLimMode = 'manual'; obj.ScatterPlotWithBboxH = scatter3(obj.PcPlotBboxAxes,nan,nan,nan, 7, '.'); view(obj.PcPlotBboxAxes,3); campos([0 0 323.5756]); %% Segmented Point CLoud Image visualization hFrontView1 = uipanel(obj.FigureH, 'Position', [0.05 0.58 0.90 0.2],... 'Title','Segmented Image','FontSize',15); ImageAxes1 = axes('Parent',hFrontView1); obj.SegmentedImageH = imshow([],'Parent',ImageAxes1,'DisplayRange',[0,70]); ImageAxes1.NextPlot = 'add'; ImageAxes1.Position = [0,0,1,1]; hFrontView1.BackgroundColor = [0 0 0]; hFrontView1.ForegroundColor = [1 1 1]; axis(ImageAxes1,'tight'); %% Range Lidar Image visualization hFrontView2 = uipanel(obj.FigureH, 'Position', [0.05 0.78 0.90 0.2]... ,'Title','Lidar Range Image','FontSize',15); ImageAxes2 = axes('Parent',hFrontView2); obj.Lidar2DImageH = imshow([],'Parent',ImageAxes2,'DisplayRange',[0,40]); ImageAxes2.NextPlot = 'add'; ImageAxes2.Position = [0,0,1,1]; hFrontView2.BackgroundColor = [0 0 0]; hFrontView2.ForegroundColor = [1 1 1]; colormap(ImageAxes2,'jet'); axis(ImageAxes2,'tight'); end %-------------------------------------------------------------------------- function updateSegmentedImage(obj, segmentedImageLabel, lidarImage) %updateSegmentedImage Method to update display with segmented % image label and lidar range or intensity image. % % Inputs: % segmentedImageLabel Segmented output lidar image from the % segmentation network % % rawInput Range or Intensity image from lidar % data obj.Lidar2DImageH.CData = lidarImage; obj.SegmentedImageH.CData = segmentedImageLabel; end %-------------------------------------------------------------------------- function updatePointCloud(obj, pc) %updatePC Method to update display with point cloud. % Inputs: % pc pointCloud type object location = pc.Location; s = size(