I found this script below in https://blogs.mathworks.com/steve/2010/07/30/visualizing-regionprops-ellipse-measurements/
I wish to plot also the MajorAxisLength and the MinorAxisLength, how can I do it?
Script:
url = 'https://blogs.mathworks.com/images/steve/2010/rice_binary.png';
bw = imread(url);
imshow(bw)
s = regionprops(bw, 'Orientation', 'MajorAxisLength', ...
'MinorAxisLength', 'Eccentricity', 'Centroid');
imshow(bw)
hold on
phi = linspace(0,2*pi,50);
cosphi = cos(phi);
sinphi = sin(phi);
for k = 1:length(s)
xbar = s(k).Centroid(1);
ybar = s(k).Centroid(2);
a = s(k).MajorAxisLength/2;
b = s(k).MinorAxisLength/2;
theta = pi*s(k).Orientation/180;
R = [ cos(theta) sin(theta)
-sin(theta) cos(theta)];
xy = [a*cosphi; b*sinphi];
xy = R*xy;
x = xy(1,:) + xbar;
y = xy(2,:) + ybar;
plot(x,y,'r','LineWidth',2);
end
hold off
You have a lot of unnecessary code in what you posted. I don't think you actually attempted to adjust it for what you say you want to plot. Given what you said you are trying to do in the comments, I think this is the code you want in order to plot the Major Axis Length vs. Minor Axis Length
url = 'https://blogs.mathworks.com/images/steve/2010/rice_binary.png';
bw = imread(url);
s = regionprops(bw, 'Orientation', 'MajorAxisLength', ...
'MinorAxisLength', 'Eccentricity', 'Centroid'); %Get region props
Major=zeros(size(s));
Minor=zeros(size(s));
for k = 1:length(s)
Major(k)= s(k).MajorAxisLength; %get your y values
Minor(k)= s(k).MinorAxisLength; %get your x values
end
figure %create a new figure because you don't want to plot on top of the image
plot(Minor, Major, 'o') %plot
xlabel('Minor Axis Length')
ylabel('Major Axis Length')
Related
I wish to generate a .gif file of a sphere that grows in size(radius) over time based on a specified function relating radius and time. I'm having some trouble with how to formulate the animation.
Here is what I have so far:
%% Parameters
dt = 0.05;
time = 0:dt:1;
radius = 1
%% generate sphere
[X, Y, Z] = sphere(25);
X=X*radius;
Y=Y*radius;
Z=Z*radius;
mySphere = surf(X,Y,Z, 'FaceLighting','gouraud');
axis equal
shading interp
mySphere.FaceAlpha = 0.3
view([61 15])
colormap bone
hold on
%% generate gif
filename = 'Sizechange.gif';
for n = 1:20
radius = 1 + time(n)
im = frame2im(getframe(1));
[imind,cm] = rgb2ind(im,256);
if n == 1;
imwrite(imind,cm,filename,'gif', 'Loopcount',inf,'DelayTime',dt);
else
imwrite(imind,cm,filename,'gif','WriteMode','append','DelayTime',dt);
end
end
Here I am trying to get it to go from radius 1 to radius 2 in steps of 0.05.
When I run this however, the gif stays still at 1 and there is no animation.
Any help would be greatly appreciated.
As #cris-luengo said, you should redraw your sphere for each iteration on the radius.
%% Parameters
dt = 0.05;
time = 0:dt:1;
radius = 1 ;
%% generate sphere
[X, Y, Z] = sphere(25);
X=X*radius;
Y=Y*radius;
Z=Z*radius;
%figure;
%mySphere = surf(X,Y,Z, 'FaceLighting','gouraud');
% axis equal
% shading interp
% mySphere.FaceAlpha = 0.3;
% view([61 15])
% colormap bone
% hold on
%% generate gif
filename = 'Sizechange.gif';
figure;
for n = 1:20
radius = 1+ time(n);
%====================================================
X=X*radius;
Y=Y*radius;
Z=Z*radius;
mySphere = surf(X,Y,Z, 'FaceLighting','gouraud');
axis equal
shading interp
mySphere.FaceAlpha = 0.3;
view([61 15])
colormap bone
%====================================================
im = frame2im(getframe(1));
[imind,cm] = rgb2ind(im,256);
if n == 1
imwrite(imind,cm,filename,'gif', 'Loopcount',inf,'DelayTime',dt);
else
imwrite(imind,cm,filename,'gif','WriteMode','append','DelayTime',dt);
end
end
I need to extract the isoline coordinates of a 4D variable from a 3D surface defined using a triangulated mesh in MATLAB. I need the isoline coordinates to be a ordered in such a manner that if they were followed in order they would trace the path i.e. the order of the points a 3D printer would follow.
I have found a function that can calculate the coordinates of these isolines (see Isoline function here) but the problem is this function does not consider the isolines to be joined in the correct order and is instead a series of 2 points separated by a Nan value. This makes this function only suitable for visualisation purposes and not the path to follow.
Here is a MWE of the problem of a simplified problem, the surface I'm applying it too is much more complex and I cannot share it. Where x, y and z are nodes, with TRI providing the element connectivity list and v is the variable of which I want the isolines extracted from and is not equal to z.
If anyone has any idea on either.....
A function to extract isoline values in the correct order for a 3D tri mesh.
How to sort the data given by the function Isoline so that they are in the correct order.
.... it would be very much appreciated.
Here is the MWE,
% Create coordinates
[x y] = meshgrid( -10:0.5:10, -10:0.5:10 );
z = (x.^2 + y.^2)/20; % Z height
v = x+y; % 4th dimension value
% Reshape coordinates into list to be converted to tri mesh
x = reshape(x,[],1); y = reshape(y,[],1); z = reshape(z,[],1); v = reshape(v,[],1);
TRI = delaunay(x,y); % Convertion to a tri mesh
% This function calculates the isoline coordinates
[xTows, yTows, zTows] = IsoLine( {TRI,[x, y, z]}, v, -18:2:18);
% Plotting
figure(1); clf(1)
subplot(1,2,1)
trisurf(TRI,x,y,z,v)
hold on
for i = 1:size(xTows,1)
plot3( xTows{i,1}, yTows{i,1}, zTows{i,1}, '-k')
end
hold off
shading interp
xlabel('x'); ylabel('y'); zlabel('z'); title('Isolines'), axis equal
%% This section is solely to show that the isolines are not in order
for i = 1:size(xTows,1)
% Arranging data into colums and getting rid of Nans that appear
xb = xTows{i,1}; yb = yTows{i,1}; zb = zTows{i,1};
xb = reshape(xb, 3, [])'; xb(:,3) = [];
yb = reshape(yb, 3, [])'; yb(:,3) = [];
zb = reshape(zb, 3, [])'; zb(:,3) = [];
subplot(1,2,2)
trisurf(TRI,x,y,z,v)
shading interp
view(2)
xlabel('x'); ylabel('y'); zlabel('z'); title('Plotting Isolines in Order')
axis equal; axis tight; hold on
for i = 1:size(xb,1)
plot3( [xb(i,1) xb(i,2)], [yb(i,1) yb(i,2)], [zb(i,1) zb(i,2)], '-k')
drawnow
end
end
and here is the function Isoline, which I have slightly adpated.
function [xTows, yTows, zTows] = IsoLine(Surf,F,V,Col)
if length(Surf)==3 % convert mesh to triangulation
P = [Surf{1}(:) Surf{2}(:) Surf{3}(:)];
Surf{1}(end,:) = 1i;
Surf{1}(:,end) = 1i;
i = find(~imag(Surf{1}(:)));
n = size(Surf{1},1);
T = [i i+1 i+n; i+1 i+n+1 i+n];
else
T = Surf{1};
P = Surf{2};
end
f = F(T(:));
if nargin==2
V = linspace(min(f),max(f),22);
V = V(2:end-1);
elseif numel(V)==1
V = linspace(min(f),max(f),V+2);
V = V(2:end-1);
end
if nargin<4
Col = 'k';
end
H = NaN + V(:);
q = [1:3 1:3];
% -------------------------------------------------------------------------
% Loop over iso-values ----------------------------------------------------
xTows = [];
yTows = [];
zTows = [];
for k = 1:numel(V)
R = {[],[]};
G = F(T) - V(k);
C = 1./(1-G./G(:,[2 3 1]));
f = unique(T(~isfinite(C))); % remove degeneracies by random perturbation
F(f) = F(f).*(1+1e-12*rand(size(F(f)))) + 1e-12*rand(size(F(f)));
G = F(T) - V(k);
C = 1./(1-G./G(:,[2 3 1]));
C(C<0|C>1) = -1;
% process active triangles
for i = 1:3
f = any(C>=0,2) & C(:,i)<0;
for j = i+1:i+2
w = C(f,q([j j j]));
R{j-i} = [R{j-i}; w.*P(T(f,q(j)),:)+(1-w).*P(T(f,q(j+1)),:)];
end
end
% define isoline
for i = 1:3
X{i} = [R{1}(:,i) R{2}(:,i) nan+R{1}(:,i)]';
% X{i} = [R{1}(:,i) R{2}(:,i)]'; % Changed by Matt
X{i} = X{i}(:)';
end
% plot isoline
if ~isempty(R{1})
% hold on
% H(k) = plot3(X{1},X{2},X{3},Col);
% Added by M.Thomas
xTows{k,1} = X{1};
yTows{k,1} = X{2};
zTows{k,1} = X{3};
end
end
What you will notice is that the isolines (xTows, yTows and zTows) are not in order there "jump around" when plotted sequentially. I need to sort the tows so that they give a smooth plot in order.
I would like to plot the surface of this function in Matlab:
w=(m*(1-p))/(h-1+m*(1-p))
Where
h=0.98;
P=[0.05:0.001:0.98];
M=[0:0.001:1];
The graph should look like this:
I tried to implement the graphing function as:
h=0.98;
P=[0.05:0.001:0.98];
M=[0:0.001:1];
W=[];
for i=1:size(P, 2)
for j=1:size(M, 2)
p=P(i);
m=M(j);
w=(m*(1-p))/(h-1+m*(1-p));
if w>1000
w=1000;
end
if w<0
w=0;
end
W(i, j) = w;
end
end
mesh(M, P, W);
But since the function changes rapidly around the boundary condition, my graph ended up looking like this:
How can I smooth out the curve and give it a nice, uniform grid like in the first picture?
Here's a way to do what you want. See comments in the code for more information.
%% //Definitions
w = #(h,m,p)(m.*(1-p))./(h-1+m.*(1-p)); %// w as a function handle
w_min = 0; w_max = 10; %// For plots
cMap = hot(200); cMap = cMap(floor(0.5*length(cMap)):ceil(0.7*length(cMap)),:);
h = 0.98;
m_start = 0; m_end = 1; m_step = [0.02 0.01 0.001];
p_start = 0.05; p_end = 0.98; p_step = [0.1 0.01 0.001];
%// Definitions of the mesh used in plotting (same for all charts)
mesh_m_step = 0.05; mesh_p_step = 0.05;
[meshM,meshP] = meshgrid(m_start:mesh_m_step:m_end,p_start:mesh_p_step:p_end);
meshW = w(h,meshM,meshP);
%% //Evaluation and plotting:
figure(); set(gcf,'Position',[240,500,1391,376]); subplot(1,3,1);
for ind1 = 1:3
%% // Evaluate equation
[MM,PP] = meshgrid(m_start:m_step(ind1):m_end,p_start:p_step(ind1):p_end);
WW = w(h,MM,PP);
%% // Plot
subplot(1,3,ind1);
surf(MM,PP,WW,'EdgeColor','none'); view([45,45]);
hold on; mesh(meshM,meshP,meshW,'EdgeColor','k','FaceColor','none');
colormap(cMap); %// Fix the colormap
zlim([w_min,w_max]); caxis(zlim) %// Modify zlim
end
Which results in:
This is a continuation from the question already posted here. I used the method that #Andrey suggested. But there seems to be a limitation. the set(handle, 'XData', x) command seems to work as long as x is a vector. what if x is a matrix?
Let me explain with an example.
Say we want to draw 3 rectangles whose vertices are given by the matrices x_vals (5,3 matrix) and y_vals (5,3 matrix). The command that will be used to plot is simply plot(x,y).
Now, we want to update the above plot. This time we want to draw 4 rectangles. whose vertices are present in the matrices x_new(5,4 matrix) and y_new (5,4 matrix) that we obtain after some calculations. Now using the command set(handle, 'XData', x, 'YData', y) after updating x and y with new values results in an error that states
Error using set
Value must be a column or row vector
Any way to solve this problem?
function [] = visualizeXYZ_struct_v3(super_struct, start_frame, end_frame)
% create first instance
no_objs = length(super_struct(1).result);
x = zeros(1,3000);
y = zeros(1,3000);
box_x = zeros(5, no_objs);
box_y = zeros(5, no_objs);
fp = 1;
% cascade values across structures in a frame so it can be plot at once;
for i = 1:1:no_objs
XYZ = super_struct(1).result(i).point_xyz;
[r,~] = size(XYZ);
x(fp:fp+r-1) = XYZ(:,1);
y(fp:fp+r-1) = XYZ(:,2);
% z(fp:fp+r-1) = xyz):,3);
fp = fp + r;
c = super_struct(1).result(i).box;
box_x(:,i) = c(:,1);
box_y(:,i) = c(:,2);
end
x(fp:end) = [];
y(fp:end) = [];
fig = figure('position', [50 50 1280 720]);
hScatter = scatter(x,y,1);
hold all
hPlot = plot(box_x,box_y,'r');
axis([-10000, 10000, -10000, 10000])
xlabel('X axis');
ylabel('Y axis');
hold off
grid off
title('Filtered Frame');
tic
for num = start_frame:1:end_frame
no_objs = length(super_struct(num).result);
x = zeros(1,3000);
y = zeros(1,3000);
box_x = zeros(5, no_objs);
box_y = zeros(5, no_objs);
fp = 1;
% cascade values accross structures in a frame so it can be plot at once;
for i = 1:1:no_objs
XYZ = super_struct(num).result(i).point_xyz;
[r,~] = size(XYZ);
x(fp:fp+r-1) = XYZ(:,1);
y(fp:fp+r-1) = XYZ(:,2);
fp = fp + r;
c = super_struct(num).result(i).box;
box_x(:,i) = c(:,1);
box_y(:,i) = c(:,2);
end
x(fp:end) = [];
y(fp:end) = [];
set(hScatter, 'XData', x, 'YData', y);
set(hPlot, 'XData', box_x, 'YData', box_y); % This is where the error occurs
end
toc
end
Each line on the plot has its own XData and YData properties, and each can be set to a vector individually. See the reference. I am not at a Matlab console right now, but as I recall...
kidnum = 1
h_axis = gca % current axis - lines are children of the axis
kids = get(h_axis,'Children')
for kid = kids
kid_type = get(kid,'type')
if kid_type == 'line'
set(kid,'XData',x_new(:,kidnum))
set(kid,'YData',y_new(:,kidnum))
kidnum = kidnum+1
end
end
Hope that helps! See also the overall reference to graphics objects and properties.
To add a series, say
hold on % so each "plot" won't touch the lines that are already there
plot(x_new(:,end), y_new(:,end)) % or whatever parameters you want to plot
After that, the new series will be a child of h_axis and can be modified.
I have a video when in some place the video rotated ... I don't know the angle and to what Direction it move. I tried to use:
function [ output_args ] = aaa( filename )
hVideoSrc = vision.VideoFileReader(filename, 'ImageColorSpace', 'Intensity');
imgA = step(hVideoSrc); % Read first frame into imgA
imgB = step(hVideoSrc); % Read second frame into imgB
figure; imshowpair(imgA, imgB, 'montage');
title(['Frame A', repmat(' ',[1 70]), 'Frame B']);
figure; imshowpair(imgA,imgB,'ColorChannels','red-cyan');
title('Color composite (frame A = red, frame B = cyan)');
ptThresh = 0.1;
pointsA = detectFASTFeatures(imgA, 'MinContrast', ptThresh);
pointsB = detectFASTFeatures(imgB, 'MinContrast', ptThresh);
% Display corners found in images A and B.
figure; imshow(imgA); hold on;
plot(pointsA);
title('Corners in A');
figure; imshow(imgB); hold on;
plot(pointsB);
title('Corners in B');
% Extract FREAK descriptors for the corners
[featuresA, pointsA] = extractFeatures(imgA, pointsA);
[featuresB, pointsB] = extractFeatures(imgB, pointsB);
indexPairs = matchFeatures(featuresA, featuresB);
pointsA = pointsA(indexPairs(:, 1), :);
pointsB = pointsB(indexPairs(:, 2), :);
figure; showMatchedFeatures(imgA, imgB, pointsA, pointsB);
legend('A', 'B');
[tform, pointsBm, pointsAm] = estimateGeometricTransform(...
pointsB, pointsA, 'affine');
imgBp = imwarp(imgB, tform, 'OutputView', imref2d(size(imgB)));
pointsBmp = transformPointsForward(tform, pointsBm.Location);
figure;
showMatchedFeatures(imgA, imgBp, pointsAm, pointsBmp);
legend('A', 'B');
% Extract scale and rotation part sub-matrix.
H = tform.T;
R = H(1:2,1:2);
% Compute theta from mean of two possible arctangents
theta = mean([atan2(R(2),R(1)) atan2(-R(3),R(4))]);
% Compute scale from mean of two stable mean calculations
scale = mean(R([1 4])/cos(theta));
% Translation remains the same:
translation = H(3, 1:2);
% Reconstitute new s-R-t transform:
HsRt = [[scale*[cos(theta) -sin(theta); sin(theta) cos(theta)]; ...
translation], [0 0 1]'];
tformsRT = affine2d(HsRt);
imgBold = imwarp(imgB, tform, 'OutputView', imref2d(size(imgB)));
imgBsRt = imwarp(imgB, tformsRT, 'OutputView', imref2d(size(imgB)));
figure(2), clf;
imshowpair(imgBold,imgBsRt,'ColorChannels','red-cyan'), axis image;
title('Color composite of affine and s-R-t transform outputs');
% Reset the video source to the beginning of the file.
reset(hVideoSrc);
hVPlayer = vision.VideoPlayer; % Create video viewer
% Process all frames in the video
movMean = step(hVideoSrc);
imgB = movMean;
imgBp = imgB;
correctedMean = imgBp;
ii = 2;
Hcumulative = eye(3);
while ~isDone(hVideoSrc) && ii < 10
% Read in new frame
imgA = imgB; % z^-1
imgAp = imgBp; % z^-1
imgB = step(hVideoSrc);
movMean = movMean + imgB;
% Estimate transform from frame A to frame B, and fit as an s-R-t
H = cvexEstStabilizationTform(imgA,imgB);
HsRt = cvexTformToSRT(H);
Hcumulative = HsRt * Hcumulative;
imgBp = imwarp(imgB,affine2d(Hcumulative),'OutputView',imref2d(size(imgB)));
% Display as color composite with last corrected frame
step(hVPlayer, imfuse(imgAp,imgBp,'ColorChannels','red-cyan'));
correctedMean = correctedMean + imgBp;
ii = ii+1;
end
correctedMean = correctedMean/(ii-2);
movMean = movMean/(ii-2);
% Here you call the release method on the objects to close any open files
% and release memory.
release(hVideoSrc);
release(hVPlayer);
figure; imshowpair(movMean, correctedMean, 'montage');
title(['Raw input mean', repmat(' ',[1 50]), 'Corrected sequence mean']);
end
Code from here
http://www.mathworks.com/help/vision/examples/video-stabilization-using-point-feature-matching.html,
but the MatLab doesn't recognize the function detectFASTFeatures
Someone can help me ?
Maybe someone have other function that find this points.
It seems to be a function in the computer vision toolbox that only comes with MATLAB r2014a:
http://www.mathworks.com/help/vision/ref/detectfastfeatures.html
If you have an older version of the MATLAB with Computer Vision System Toolbox, you can use the vision.CornerDetector object.