I need help optimizing my program that currently puts boxes of the respective color around notes in guitar hero 3. It does not do it fast enough or accurately enough.

3 次查看（过去 30 天）
Hershey Wiseman
Hershey Wiseman 2018-5-17
评论： sloppydisk 2018-5-18
My code will all be below, my new idea is to put each scan to be run in parallel with the others by using parallel processing, but this is a new concept to me so I was wondering is it something worth looking into for this project. This is the code
function ObjectTrack()
clear all;
imaqreset;
a = imaqhwinfo;
[camera_name, camera_id, format] = getCameraInfo(a);
%Capture the video frames using the videoinput function
% You have to replace the resolution & your installed adaptor name.
cam = webcam('Logitech Camera');
snapshot(cam);
vid = videoinput('macvideo', camera_id, format);
% Set the properties of the video object
set(vid, 'FramesPerTrigger', Inf);
set(vid, 'ReturnedColorspace', 'rgb')
vid.FrameGrabInterval = 1; %the app grabs a frame every this number of frames
%start the video aquisition here
start(vid)
% Set a loop that stop after 100 frames of aquisition
while(vid.FramesAcquired<=800)
% Get the snapshot of the current frame
data = getsnapshot(vid);
cropData = imcrop(data, [950, 470, 550, 400]);
% comment
[BWgreen, greenImage] = createMaskGreen(cropData);
[BWred, redImage] = createMaskRed(cropData);
[BWyellow, yellowImage] = createMaskYellow(cropData);
[BWblue, blueImage] = createMaskBlue(cropData);
[BWorange, orangeImage] = createMaskOrange(cropData);
% Remove all those pixels less than 300px
BWgreen = bwareafilt(BWgreen,[20, 60]);
BWred = bwareafilt(BWred,[20, 60]);
BWyellow = bwareafilt(BWyellow,[20, 60]);
BWblue = bwareafilt(BWblue,[20, 60]);
BWorange = bwareafilt(BWorange,[20, 60]);
% Label all the connected components in the image.
bwG = bwlabel(BWgreen, 8);
bwR = bwlabel(BWred, 8);
bwY = bwlabel(BWyellow, 8);
bwB = bwlabel(BWblue, 8);
bwO = bwlabel(BWorange, 8);
% Here we do the image blob analysis.
% We get a set of properties for each labeled region.
statsG = regionprops(bwG, 'BoundingBox', 'Centroid');
statsR = regionprops(bwR, 'BoundingBox', 'Centroid');
statsY = regionprops(bwY, 'BoundingBox', 'Centroid');
statsB = regionprops(bwB, 'BoundingBox', 'Centroid');
statsO = regionprops(bwO, 'BoundingBox', 'Centroid');
% Display the image
imshow(cropData)
hold on
line([000, 550],[350, 350],'Color','black','LineWidth',7)
hold on
%This is a loop to bound the green objects in a rectangular box.
for object = 1:length(statsG)
bb = statsG(object).BoundingBox;
bc = statsG(object).Centroid;
rectangle('Position',bb,'EdgeColor','g','LineWidth',2)
plot(bc(1),bc(2), '-m+')
% a=text(bc(1)+15,bc(2), strcat('X: ', num2str(round(bc(1))), ' Y: ', num2str(round(bc(2)))));
% set(a, 'FontName', 'Arial', 'FontWeight', 'bold', 'FontSize', 12, 'Color', 'green');
end
%This is a loop to bound the red objects in a rectangular box.
for object = 1:length(statsR)
bb = statsR(object).BoundingBox;
bc = statsR(object).Centroid;
rectangle('Position',bb,'EdgeColor','r','LineWidth',2)
plot(bc(1),bc(2), '-m+')
% a=text(bc(1)+15,bc(2), strcat('X: ', num2str(round(bc(1))), ' Y: ', num2str(round(bc(2)))));
% set(a, 'FontName', 'Arial', 'FontWeight', 'bold', 'FontSize', 12, 'Color', 'red');
end
%This is a loop to bound the yellow objects in a rectangular box.
for object = 1:length(statsY)
bb = statsY(object).BoundingBox;
bc = statsY(object).Centroid;
rectangle('Position',bb,'EdgeColor','y','LineWidth',2)
plot(bc(1),bc(2), '-m+')
% a=text(bc(1)+15,bc(2), strcat('X: ', num2str(round(bc(1))), ' Y: ', num2str(round(bc(2)))));
% set(a, 'FontName', 'Arial', 'FontWeight', 'bold', 'FontSize', 12, 'Color', 'yellow');
end
%This is a loop to bound the blue objects in a rectangular box.
for object = 1:length(statsB)
bb = statsB(object).BoundingBox;
bc = statsB(object).Centroid;
rectangle('Position',bb,'EdgeColor','b','LineWidth',2)
plot(bc(1),bc(2), '-m+')
% a=text(bc(1)+15,bc(2), strcat('X: ', num2str(round(bc(1))), ' Y: ', num2str(round(bc(2)))));
% set(a, 'FontName', 'Arial', 'FontWeight', 'bold', 'FontSize', 12, 'Color', 'blue');
end
%This is a loop to bound the orange objects in a rectangular box.
for object = 1:length(statsO)
bb = statsO(object).BoundingBox;
bc = statsO(object).Centroid;
rectangle('Position',bb,'EdgeColor','k','LineWidth',2)
plot(bc(1),bc(2), '-m+')
% a=text(bc(1)+15,bc(2), strcat('X: ', num2str(round(bc(1))), ' Y: ', num2str(round(bc(2)))));
% set(a, 'FontName', 'Arial', 'FontWeight', 'bold', 'FontSize', 12, 'Color', 'black');
end
hold off
end
% Both the loops end here.
hold off
% Stop the video aquisition.
stop(vid);
% Flush all the image data stored in the memory buffer.
flushdata(vid);
% Clear all variables
clear all
sprintf('%s','Program has now ended')
%%getCameraInfo class
function [camera_name, camera_id, resolution] = getCameraInfo(a)
camera_name = 'Logitech Camera';
camera_info = imaqhwinfo('macvideo');
camera_id = 2;
resolution = 'YCbCr422_1920x1080';
%%createMaskGreen class
function [BW,maskedRGBImage] = createMaskGreen(RGB)
%createMask Threshold RGB image using auto-generated code from colorThresholder app.
% [BW,MASKEDRGBIMAGE] = createMask(RGB) thresholds image RGB using
% auto-generated code from the colorThresholder app. The colorspace and
% range for each channel of the colorspace were set within the app. The
% segmentation mask is returned in BW, and a composite of the mask and
% original RGB images is returned in maskedRGBImage.
% Auto-generated by colorThresholder app on 14-May-2018 %------------------------------------------------------
% Convert RGB image to chosen color space
I = rgb2hsv(RGB);
% Define thresholds for channel 1 based on histogram settings
channel1Min = 0.269;
channel1Max = 0.420;
% Define thresholds for channel 2 based on histogram settings
channel2Min = 0.266;
channel2Max = 0.512;
% Define thresholds for channel 3 based on histogram settings
channel3Min = 0.422;
channel3Max = 1.000;
% Create mask based on chosen histogram thresholds
sliderBW = (I(:,:,1) >= channel1Min ) & (I(:,:,1) <= channel1Max) & ...
(I(:,:,2) >= channel2Min ) & (I(:,:,2) <= channel2Max) & ...
(I(:,:,3) >= channel3Min ) & (I(:,:,3) <= channel3Max);
BW = sliderBW;
% Initialize output masked image based on input image.
maskedRGBImage = RGB;
% Set background pixels where BW is false to zero.
maskedRGBImage(repmat(~BW,[1 1 3])) = 0;
end
%%createMaskRed class
function [BW,maskedRGBImage] = createMaskRed(RGB)
%createMask Threshold RGB image using auto-generated code from colorThresholder app.
% [BW,MASKEDRGBIMAGE] = createMask(RGB) thresholds image RGB using
% auto-generated code from the colorThresholder app. The colorspace and
% range for each channel of the colorspace were set within the app. The
% segmentation mask is returned in BW, and a composite of the mask and
% original RGB images is returned in maskedRGBImage.
% Auto-generated by colorThresholder app on 14-May-2018 %------------------------------------------------------
% Convert RGB image to chosen color space
I = rgb2hsv(RGB);
% Define thresholds for channel 1 based on histogram settings
channel1Min = 0.971;
channel1Max = 0.036;
% Define thresholds for channel 2 based on histogram settings
channel2Min = 0.217;
channel2Max = 0.453;
% Define thresholds for channel 3 based on histogram settings
channel3Min = 0.487;
channel3Max = 1.000;
% Create mask based on chosen histogram thresholds sliderBW = ( (I(:,:,1) >= channel1Min) | (I(:,:,1) <= channel1Max) ) & ... (I(:,:,2) >= channel2Min ) & (I(:,:,2) <= channel2Max) & ... (I(:,:,3) >= channel3Min ) & (I(:,:,3) <= channel3Max); BW = sliderBW;
% Initialize output masked image based on input image.
maskedRGBImage = RGB;
% Set background pixels where BW is false to zero. maskedRGBImage(repmat(~BW,[1 1 3])) = 0;
end
%%createMaskYellow class
function [BW,maskedRGBImage] = createMaskYellow(RGB)
%createMask Threshold RGB image using auto-generated code from colorThresholder app.
% [BW,MASKEDRGBIMAGE] = createMask(RGB) thresholds image RGB using
% auto-generated code from the colorThresholder app. The colorspace and
% range for each channel of the colorspace were set within the app. The
% segmentation mask is returned in BW, and a composite of the mask and
% original RGB images is returned in maskedRGBImage.
% Auto-generated by colorThresholder app on 14-May-2018 %------------------------------------------------------
% Convert RGB image to chosen color space I = rgb2hsv(RGB);
% Define thresholds for channel 1 based on histogram settings
channel1Min = 0.244;
channel1Max = 0.413;
% Define thresholds for channel 2 based on histogram settings
channel2Min = 0.292;
channel2Max = 0.483;
% Define thresholds for channel 3 based on histogram settings
channel3Min = 0.596;
channel3Max = 1.000;
% Create mask based on chosen histogram thresholds
sliderBW = (I(:,:,1) >= channel1Min ) & (I(:,:,1) <= channel1Max) & ...
(I(:,:,2) >= channel2Min ) & (I(:,:,2) <= channel2Max) & ...
(I(:,:,3) >= channel3Min ) & (I(:,:,3) <= channel3Max);
BW = sliderBW;
% Initialize output masked image based on input image. maskedRGBImage = RGB;
% Set background pixels where BW is false to zero. maskedRGBImage(repmat(~BW,[1 1 3])) = 0;
end
%%createMaskBlue class function [BW,maskedRGBImage] = createMaskBlue(RGB) %createMask Threshold RGB image using auto-generated code from colorThresholder app. % [BW,MASKEDRGBIMAGE] = createMask(RGB) thresholds image RGB using % auto-generated code from the colorThresholder app. The colorspace and % range for each channel of the colorspace were set within the app. The % segmentation mask is returned in BW, and a composite of the mask and % original RGB images is returned in maskedRGBImage.
% Auto-generated by colorThresholder app on 14-May-2018 %------------------------------------------------------
%Convert RGB image to chosen color space
I = rgb2hsv(RGB);
%Define thresholds for channel 1 based on histogram settings
channel1Min = 0.538;
channel1Max = 0.635;
% Define thresholds for channel 2 based on histogram settings
channel2Min = 0.337;
channel2Max = 0.566;
% Define thresholds for channel 3 based on histogram settings
channel3Min = 0.703;
channel3Max = 1.000;
% Create mask based on chosen histogram thresholds
sliderBW = (I(:,:,1) >= channel1Min ) & (I(:,:,1) <= channel1Max) & ...
(I(:,:,2) >= channel2Min ) & (I(:,:,2) <= channel2Max) & ...
(I(:,:,3) >= channel3Min ) & (I(:,:,3) <= channel3Max);
BW = sliderBW;
% Initialize output masked image based on input image.
maskedRGBImage = RGB;
% Set background pixels where BW is false to zero.
maskedRGBImage(repmat(~BW,[1 1 3])) = 0;
end
%%createMaskOrange class
function [BW,maskedRGBImage] = createMaskOrange(RGB)
%createMask Threshold RGB image using auto-generated code from colorThresholder app.
% [BW,MASKEDRGBIMAGE] = createMask(RGB) thresholds image RGB using
% auto-generated code from the colorThresholder app. The colorspace and
% range for each channel of the colorspace were set within the app. The
% segmentation mask is returned in BW, and a composite of the mask and
% original RGB images is returned in maskedRGBImage.
% Auto-generated by colorThresholder app on 14-May-2018 %------------------------------------------------------
% Convert RGB image to chosen color space
I = rgb2hsv(RGB);
% Define thresholds for channel 1 based on histogram settings channel1Min = 0.085; channel1Max = 0.203;
% Define thresholds for channel 2 based on histogram settings
channel2Min = 0.225;
channel2Max = 0.401;
% Define thresholds for channel 3 based on histogram settings
channel3Min = 0.625;
channel3Max = 1.000;
% Create mask based on chosen histogram thresholds
sliderBW = (I(:,:,1) >= channel1Min ) & (I(:,:,1) <= channel1Max) & ...
(I(:,:,2) >= channel2Min ) & (I(:,:,2) <= channel2Max) & ...
(I(:,:,3) >= channel3Min ) & (I(:,:,3) <= channel3Max);
BW = sliderBW;
% Initialize output masked image based on input image.
maskedRGBImage = RGB;
% Set background pixels where BW is false to zero.
maskedRGBImage(repmat(~BW,[1 1 3])) = 0;
end
  2 个评论
Florian Morsch
Florian Morsch 2018-5-18
One thing i noticed might help you right on the spot:
Move every fixed values out of a loop. For example in your first while loop you have
% Set a loop that stop after 100 frames of aquisition
while(vid.FramesAcquired<=800)
% Get the snapshot of the current frame
data = getsnapshot(vid);
cropData = imcrop(data, [950, 470, 550, 400]);
% comment
[BWgreen, greenImage] = createMaskGreen(cropData);
[BWred, redImage] = createMaskRed(cropData);
[BWyellow, yellowImage] = createMaskYellow(cropData);
[BWblue, blueImage] = createMaskBlue(cropData);
[BWorange, orangeImage] = createMaskOrange(cropData);
With every run through the loop you re-asign the crop box. Move that out of the loop.
CropMask = [950, 470, 550, 400];
% Set a loop that stop after 100 frames of aquisition
while(vid.FramesAcquired<=800)
% Get the snapshot of the current frame
data = getsnapshot(vid);
cropData = imcrop(data, CropMask);
% comment
[BWgreen, greenImage] = createMaskGreen(cropData);
[BWred, redImage] = createMaskRed(cropData);
[BWyellow, yellowImage] = createMaskYellow(cropData);
[BWblue, blueImage] = createMaskBlue(cropData);
[BWorange, orangeImage] = createMaskOrange(cropData);
Things like that dont look like much, but can add up pretty quickly.
This link migh have some usefull information for you:
https://de.mathworks.com/matlabcentral/answers/114515-how-to-make-matlab-code-execute-faster
https://de.mathworks.com/help/matlab/matlab_prog/techniques-for-improving-performance.html

请先登录，再进行评论。

请先登录，再回答此问题。

回答（0 个）

类别

在 Help Center 和 File Exchange 中查找有关 Point Grey Hardware 的更多信息

标签

产品

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by