counting object

[tavajo9]

سلام

می تونید تو این برنامه کمکم کنید لطفا ببینیدش

این برنامه تعداد خودرو ها رو شمارش می کند و به صورت کلی بیان می کند
من می خوام این شمارش روی هر خودرو نوشته بشه مثل همون باکس های سبزی که دور هر خودرو میکشه ممنون

clc;clear;close all
%Tracking Cars Using Optical Flow

%This demo tracks cars in a video by detecting motion using optical flow. The cars are segmented from the background by thresholding the motion vector magnitudes. Then, blob analysis is used to identify the cars. 

%Initialization

%Create the System objects outside of the main video processing loop.
% Object for reading video file.
filename = 'viptraffic.avi';
hVidReader = vision.VideoFileReader(filename, 'ImageColorSpace', 'RGB',...
               'VideoOutputDataType', 'single');

%Optical flow object for estimating direction and speed of object motion.
hOpticalFlow = vision.OpticalFlow( ...
  'OutputValue', 'Horizontal and vertical components in complex form', ...
  'ReferenceFrameDelay', 3);

%Create two objects for analyzing optical flow vectors.
hMean1 = vision.Mean;
hMean2 = vision.Mean('RunningMean', true);

%Filter object for removing speckle noise introduced during segmentation.
hMedianFilt = vision.MedianFilter;

%Morphological closing object for filling holes in blobs.
hclose = vision.MorphologicalClose('Neighborhood', strel('line',5,45));

%Create a blob analysis System object to segment cars in the video.
hblob = vision.BlobAnalysis(...
  'CentroidOutputPort', false, 'AreaOutputPort', true, ...
  'BoundingBoxOutputPort', true, 'OutputDataType', 'double', ...
  'MinimumBlobArea', 250, 'MaximumBlobArea', 3600, 'MaximumCount', 80);

%Morphological erosion object for removing portions of the road and other unwanted objects.
herode = vision.MorphologicalErode('Neighborhood', strel('square',2));

%Create objects for drawing the bounding boxes and motion vectors.
hshapeins1 = vision.ShapeInserter('BorderColor', 'Custom', ...
                 'CustomBorderColor', [0 1 0]);
hshapeins2 = vision.ShapeInserter( 'Shape','Lines', ...
                  'BorderColor', 'Custom', ...
                  'CustomBorderColor', [255 255 0]);



%This object will write the number of tracked cars in the output image.
htextins = vision.TextInserter('Text', '%4d', 'Location', [1 1], ...
                'Color', [1 1 1], 'FontSize', 12);         



%Create System objects to display the original video, motion vector video, the thresholded video and the final result.
sz = get(0,'ScreenSize');
pos = [20 sz(4)-300 200 200];
hVideo1 = vision.VideoPlayer('Name','Original Video','Position',pos);
pos(1) = pos(1)+220; % move the next viewer to the right
hVideo2 = vision.VideoPlayer('Name','Motion Vector','Position',pos);
pos(1) = pos(1)+220;
hVideo3 = vision.VideoPlayer('Name','Thresholded Video','Position',pos);
pos(1) = pos(1)+220;
hVideo4 = vision.VideoPlayer('Name','Results','Position',pos);

% Initialize variables used in plotting motion vectors.
lineRow  = 22;
firstTime = true;
motionVecGain = 20;
borderOffset  = 5;
decimFactorRow = 5;
decimFactorCol = 5;



%Tracking Cars in Video

%Create the processing loop to track the cars in video.
while ~isDone(hVidReader) % Stop when end of file is reached
  frame = step(hVidReader); % Read input video frame
  grayFrame = rgb2gray(frame);
  ofVectors = step(hOpticalFlow, grayFrame);  % Estimate optical flow

  % The optical flow vectors are stored as complex numbers. Compute their
  % magnitude squared which will later be used for thresholding.
  y1 = ofVectors .* conj(ofVectors);
  % Compute the velocity threshold from the matrix of complex velocities.
  vel_th = 0.5 * step(hMean2, step(hMean1, y1));

  % Threshold the image and then filter it to remove speckle noise.
  segmentedObjects = step(hMedianFilt, y1 >= vel_th);

  % Thin-out the parts of the road and fill holes in the blobs.
  segmentedObjects = step(hclose, step(herode, segmentedObjects));

  % Estimate the area and bounding box of the blobs.
  [area, bbox] = step(hblob, segmentedObjects);
  % Select boxes inside ROI (below white line).
  Idx = bbox(:,1) > lineRow;

  % Based on blob sizes, filter out objects which can not be cars.
  % When the ratio between the area of the blob and the area of the
  % bounding box is above 0.4 (40%), classify it as a car.
  ratio = zeros(length(Idx), 1);
  ratio(Idx) = single(area(Idx,1))./single(bbox(Idx,3).*bbox(Idx,4));
  ratiob = ratio > 0.4;
  count = int32(sum(ratiob));  % Number of cars
  bbox(~ratiob, :) = int32(-1);

  % Draw bounding boxes around the tracked cars.
  y2 = step(hshapeins1, frame, bbox);

  % Display the number of cars tracked and a white line showing the ROI.
  y2(22:23,:,:)  = 1;  % The white line.
  y2(1:15,1:30,:) = 0;  % Background for displaying count
  result = step(htextins, y2, count);

  % Generate coordinates for plotting motion vectors.
  if firstTime
   [R C] = size(ofVectors);      % Height and width in pixels
   RV = borderOffset:decimFactorRow:(R-borderOffset);
   CV = borderOffset:decimFactorCol:(C-borderOffset);
   [Y X] = meshgrid(CV,RV);
   firstTime = false;
  end

  % Calculate and draw the motion vectors.
  tmp = ofVectors(RV,CV) .* motionVecGain;
  lines = [Y(:), X(:), Y(:) + real(tmp(:)), X(:) + imag(tmp(:))];
  motionVectors = step(hshapeins2, frame, lines);

  % Display the results
  step(hVideo1, frame);      % Original video
  step(hVideo2, motionVectors);  % Video with motion vectors
  step(hVideo3, segmentedObjects); % Thresholded video
  step(hVideo4, result);      % Video with bounding boxes
end

release(hVidReader);

[potter_h112]

پاسخ : counting object

سلام،
اتفاقاً دو شب پیش من رو این کد داشتم کار می کردم ، من هم متاسفانه نتونسته بودم بفهمم x , y خودرو دیتکت شده رو چطور باید بدست آورد و یا بهتر بگم، مختصات bounding boxes در کدوم متغییر هست .
ممنون میشم بچه های اهل فن یک نگاهی به این کد بیاندزن ...