《Matlab计算机视觉与深度学习实战》代码 基于光流场的交通汽车检测跟踪.zip

clear all videofile = 'viptraffic.avi'; info = mmfileinfo(videofile); cols=info.Video.Width; rows=info.Video.Height; hReader = vision.VideoFileReader(videofile,... 'ImageColorSpace', 'RGB',... 'VideoOutputDataType', 'single'); hFlow = vision.OpticalFlow( ... 'OutputValue', 'Horizontal and vertical components in complex form', ... 'ReferenceFrameDelay', 3,... 'Method','Horn-Schunck'); hMean1 = vision.Mean; hMean2 = vision.Mean('RunningMean', true); hFilter = vision.MedianFilter; hClose = vision.MorphologicalClose('Neighborhood', strel('line',5,45)); hBlob = vision.BlobAnalysis(... 'CentroidOutputPort', false,... 'AreaOutputPort', true, ... 'BoundingBoxOutputPort', true,... 'OutputDataType', 'double', ... 'MinimumBlobArea', 250,... 'MaximumBlobArea', 3600,... 'MaximumCount', 80); hErode = vision.MorphologicalErode('Neighborhood', strel('square',2)); hShape1 = vision.ShapeInserter(... 'BorderColor', 'Custom', ... 'CustomBorderColor', [0 1 0]); hShape2 = vision.ShapeInserter(... 'Shape','Lines', ... 'BorderColor', 'Custom', ... 'CustomBorderColor', [255 255 0]); hText = vision.TextInserter(... 'Text', '%4d',... 'Location', [1 1], ... 'Color', [1 1 1],... 'FontSize', 12); sz = get(0,'ScreenSize'); pos = [(sz(3)-4*(cols+75))/2, (sz(4)-rows)/2 cols+60 rows+80]; hVideo1 = vision.VideoPlayer('Name','Original Video','Position',pos); pos(1) = pos(1)+cols+75; hVideo2 = vision.VideoPlayer('Name','Motion Vector','Position',pos); pos(1) = pos(1)+cols+75; hVideo3 = vision.VideoPlayer('Name','Thresholded Video','Position',pos); pos(1) = pos(1)+cols+75; hVideo4 = vision.VideoPlayer('Name','Results Video','Position',pos); [xpos,ypos]=meshgrid(1:5:cols,1:5:rows); xpos=xpos(:); ypos=ypos(:); locs=sub2ind([rows,cols],ypos,xpos); while ~isDone(hReader) pause(0.3); frame = step(hReader); gray = rgb2gray(frame); flow = step(hFlow, gray); lines = [xpos, ypos, xpos+20*real(flow(locs)), ypos+20*imag(flow(locs))]; vector = step(hShape2, frame, lines); magnitude = flow .* conj(flow); threshold = 0.5 * step(hMean2, step(hMean1, magnitude)); carobj = step(hFilter, magnitude >= threshold); carobj = step(hClose, step(hErode, carobj)); [area, bbox] = step(hBlob, carobj); grow=22; idx = bbox(:,1) > grow; ratio = zeros(length(idx), 1); ratio(idx) = single(area(idx,1))./single(bbox(idx,3).*bbox(idx,4)); flag = ratio > 0.4; count = int32(sum(flag)); bbox(~flag, :) = int32(-1); result = step(hShape1, frame, bbox); result(grow:grow+1,:,:) = 1; result(1:15,1:30,:) = 0; result = step(hText, result, count); step(hVideo1, frame); step(hVideo2, vector); step(hVideo3, carobj); step(hVideo4, result); end release(hReader);