filename = 'coba.mp4.mp4';
hvfr = vision.VideoFileReader(filename, 'ImageColorSpace', 'RGB');
hcsc = vision.ColorSpaceConverter('Conversion', 'RGB to intensity');
hfdet = vision.ForegroundDetector(...
'NumTrainingFrames', 10, ... % only 5 because of short video
'InitialVariance', (30/255)^2); % initial standard deviation of 30/255
hblob = robotics.ParticleFilter;
hshapeins = vision.ShapeInserter( ...
'BorderColor', 'Custom', ...
'CustomBorderColor', [0 255 0]);
htextins = vision.TextInserter( ...
'Text', '%4d', ...
'Location', [1 1], ...
'Color', [255 255 255], ...
'FontSize', 12);
sz = get(0,'ScreenSize');
pos = [20 sz(4)-300 200 200];
hVideoOrig = vision.VideoPlayer('Name', 'Original', 'Position', pos);
pos(1) = pos(1)+220; % move the next viewer to the right
hVideoFg = vision.VideoPlayer('Name', 'Foreground', 'Position', pos);
pos(1) = pos(1)+220;
hVideoRes = vision.VideoPlayer('Name', 'Results', 'Position', pos);
line_row = 23; % Define region of interest (ROI)
while ~isDone(hvfr)
image = step(hvfr); % Read input video frame
y = step(hcsc, image); % Convert color image to intensity
% Remove the effect of sudden intensity changes due to camera's
% auto white balancing algorithm.
y = y-mean(y(:));
fg_image = step(hfdet, y); % Detect foreground
% Estimate the area and bounding box of the blobs in the foreground
% image.
[area, bbox, extent] = step(hblob, fg_image);
image_out = image;
image_out(22:23,:,:) = 255; % Count cars only below this white line
image_out(1:15,1:30,:) = 0; % Black background for displaying count
Idx = bbox(:,2) > line_row; % Select boxes which are in the ROI.
% Based on blob sizes, filter out objects which are unlikely to be
% cars. When the extent property of a blob exceeds 0.4 (40%),
% classify it as a car.
isCar = extent > 0.4;
numCars = sum(isCar); % Number of cars
bbox(~isCar, :) = []; % Keep only the bounding boxes for objects
% classifed as cars.
% Draw bounding rectangles around the detected cars.
image_out = step(hshapeins, image_out, bbox);
% Display the number of cars tracked and a white line showing the ROI.
image_out = step(htextins, image_out, int32(numCars));
step(hVideoOrig, image); % Original video
step(hVideoFg, fg_image); % Foreground
step(hVideoRes, image_out); % Bounding boxes around cars
end
% Close the video file
release(hvfr);
