Hi,

I need to display a permil (textperthousand) in my xlabel but I cannot get it to work.
I’m using the following
ylabel(‘$mathrm{^{34/32}varepsilon^{mic}_{sulfate-pyrite} (textperthousand)}$’,’FontSize’,16,’Interpreter’,’latex’)Hi,

I need to display a permil (textperthousand) in my xlabel but I cannot get it to work.
I’m using the following
ylabel(‘$mathrm{^{34/32}varepsilon^{mic}_{sulfate-pyrite} (textperthousand)}$’,’FontSize’,16,’Interpreter’,’latex’) Hi,

I need to display a permil (textperthousand) in my xlabel but I cannot get it to work.
I’m using the following
ylabel(‘$mathrm{^{34/32}varepsilon^{mic}_{sulfate-pyrite} (textperthousand)}$’,’FontSize’,16,’Interpreter’,’latex’) latex, xlabel MATLAB Answers — New Questions

​

I am currently working on a fairly large Matlab OOP codebase, with listeners defined all over the place. Unfortunately the guy who created this codebase left the company and there is not really any documentation available.

As there are so many listeners all over the place, simply querying or changing some object property frequently has unexpected side effects, making debugging very painful. Is there a simple way to get a list of all the listeners for a given property? E.g. something to the extent of getlisteners(obj.myProperty)? This would really help in figuring out what on earth the code is actually doing…

I would have expected this to be a quite basic question but somehow can not find a simple answer anywhere.

Thanks!
GijsI am currently working on a fairly large Matlab OOP codebase, with listeners defined all over the place. Unfortunately the guy who created this codebase left the company and there is not really any documentation available.

As there are so many listeners all over the place, simply querying or changing some object property frequently has unexpected side effects, making debugging very painful. Is there a simple way to get a list of all the listeners for a given property? E.g. something to the extent of getlisteners(obj.myProperty)? This would really help in figuring out what on earth the code is actually doing…

I would have expected this to be a quite basic question but somehow can not find a simple answer anywhere.

Thanks!
Gijs I am currently working on a fairly large Matlab OOP codebase, with listeners defined all over the place. Unfortunately the guy who created this codebase left the company and there is not really any documentation available.

As there are so many listeners all over the place, simply querying or changing some object property frequently has unexpected side effects, making debugging very painful. Is there a simple way to get a list of all the listeners for a given property? E.g. something to the extent of getlisteners(obj.myProperty)? This would really help in figuring out what on earth the code is actually doing…

I would have expected this to be a quite basic question but somehow can not find a simple answer anywhere.

Thanks!
Gijs events, listeners MATLAB Answers — New Questions

​

downlink 5G waveform for mixed numerology is given in the toolbox examples.
How to analyse that for BER and internumerlogoy interference?
How to deal generated resource grid containing PSS, SSS, PBCH, DM-RS?downlink 5G waveform for mixed numerology is given in the toolbox examples.
How to analyse that for BER and internumerlogoy interference?
How to deal generated resource grid containing PSS, SSS, PBCH, DM-RS? downlink 5G waveform for mixed numerology is given in the toolbox examples.
How to analyse that for BER and internumerlogoy interference?
How to deal generated resource grid containing PSS, SSS, PBCH, DM-RS? ini analysis MATLAB Answers — New Questions

​

Hello everyone
I’m trying to change the marker color in the pzplot graph. I’m using version 2024b.

Apparently, in this version, a new object(?) called "PZPlot Properties" was introduced, which is great.
Using this new object, I can easily change the size and line thickness of all markers. But I can also only change the colour of all markers. I’d like to change the colours of the markers for the poles and zeros separately.

I tried using the "findobj" method and found, that the PZPlot apparently consists of two Scatter-Plots called "PZPoleScatter" and "PZZeroScatter", and I tried changing the color of the markers in those Scatter plots, but this does not seem to have an effect on the markers.
When I change the colour of the markers using the PZPlot properties Object, I see the color definition of the markers in both scatter plots change, and I can also see that the colours change if I directly access the properties and change the colour, but the plot isn’t drawn with those correct colors.
I tried using refresh after changing the values, but that doesn’t have any effect either.

See my code below:
s = tf(‘s’);

f = (1 + 1/s)

pzp = pzplot(f);
% See https://ch.mathworks.com/help/ident/ref/controllib.chart.pzplot-properties.html for new PZPlot-properties object
pzp.Responses.MarkerSize = 10;
pzp.Responses.LineWidth = 2;
%pzp.Responses.Color = ‘green’; % Changes colour of all markers
oPole = findobj(gca, ‘Tag’, ‘PZPoleScatter’);
oPole.MarkerEdgeColor = ‘red’;
oZero = findobj(gca, ‘Tag’, ‘PZZeroScatter’);
oZero.MarkerEdgeColor = ‘blue’;

rsp = findobj(gca, ‘Tag’, ‘PZPoleScatter’); % read object again to see if properties got changed correctly

I also found the following two topics, but they do not work anymore as there is no "Line" child in the PZPlot object.
https://ch.mathworks.com/matlabcentral/answers/276605-change-pzplot-marker-size
https://ch.mathworks.com/matlabcentral/answers/431293-i-am-using-pole-zero-map-pzmap-and-i-want-to-enhance-the-size-of-pole-or-zero-or-in-other-words-iHello everyone
I’m trying to change the marker color in the pzplot graph. I’m using version 2024b.

Apparently, in this version, a new object(?) called "PZPlot Properties" was introduced, which is great.
Using this new object, I can easily change the size and line thickness of all markers. But I can also only change the colour of all markers. I’d like to change the colours of the markers for the poles and zeros separately.

I tried using the "findobj" method and found, that the PZPlot apparently consists of two Scatter-Plots called "PZPoleScatter" and "PZZeroScatter", and I tried changing the color of the markers in those Scatter plots, but this does not seem to have an effect on the markers.
When I change the colour of the markers using the PZPlot properties Object, I see the color definition of the markers in both scatter plots change, and I can also see that the colours change if I directly access the properties and change the colour, but the plot isn’t drawn with those correct colors.
I tried using refresh after changing the values, but that doesn’t have any effect either.

See my code below:
s = tf(‘s’);

f = (1 + 1/s)

pzp = pzplot(f);
% See https://ch.mathworks.com/help/ident/ref/controllib.chart.pzplot-properties.html for new PZPlot-properties object
pzp.Responses.MarkerSize = 10;
pzp.Responses.LineWidth = 2;
%pzp.Responses.Color = ‘green’; % Changes colour of all markers
oPole = findobj(gca, ‘Tag’, ‘PZPoleScatter’);
oPole.MarkerEdgeColor = ‘red’;
oZero = findobj(gca, ‘Tag’, ‘PZZeroScatter’);
oZero.MarkerEdgeColor = ‘blue’;

rsp = findobj(gca, ‘Tag’, ‘PZPoleScatter’); % read object again to see if properties got changed correctly

I also found the following two topics, but they do not work anymore as there is no "Line" child in the PZPlot object.
https://ch.mathworks.com/matlabcentral/answers/276605-change-pzplot-marker-size
https://ch.mathworks.com/matlabcentral/answers/431293-i-am-using-pole-zero-map-pzmap-and-i-want-to-enhance-the-size-of-pole-or-zero-or-in-other-words-i Hello everyone
I’m trying to change the marker color in the pzplot graph. I’m using version 2024b.

Apparently, in this version, a new object(?) called "PZPlot Properties" was introduced, which is great.
Using this new object, I can easily change the size and line thickness of all markers. But I can also only change the colour of all markers. I’d like to change the colours of the markers for the poles and zeros separately.

I tried using the "findobj" method and found, that the PZPlot apparently consists of two Scatter-Plots called "PZPoleScatter" and "PZZeroScatter", and I tried changing the color of the markers in those Scatter plots, but this does not seem to have an effect on the markers.
When I change the colour of the markers using the PZPlot properties Object, I see the color definition of the markers in both scatter plots change, and I can also see that the colours change if I directly access the properties and change the colour, but the plot isn’t drawn with those correct colors.
I tried using refresh after changing the values, but that doesn’t have any effect either.

See my code below:
s = tf(‘s’);

f = (1 + 1/s)

pzp = pzplot(f);
% See https://ch.mathworks.com/help/ident/ref/controllib.chart.pzplot-properties.html for new PZPlot-properties object
pzp.Responses.MarkerSize = 10;
pzp.Responses.LineWidth = 2;
%pzp.Responses.Color = ‘green’; % Changes colour of all markers
oPole = findobj(gca, ‘Tag’, ‘PZPoleScatter’);
oPole.MarkerEdgeColor = ‘red’;
oZero = findobj(gca, ‘Tag’, ‘PZZeroScatter’);
oZero.MarkerEdgeColor = ‘blue’;

rsp = findobj(gca, ‘Tag’, ‘PZPoleScatter’); % read object again to see if properties got changed correctly

I also found the following two topics, but they do not work anymore as there is no "Line" child in the PZPlot object.
https://ch.mathworks.com/matlabcentral/answers/276605-change-pzplot-marker-size
https://ch.mathworks.com/matlabcentral/answers/431293-i-am-using-pole-zero-map-pzmap-and-i-want-to-enhance-the-size-of-pole-or-zero-or-in-other-words-i pzplot, marker, customization MATLAB Answers — New Questions

​

i write this code but i cant get number of rbc and this is my input image
clear all;
close all;
clc;
count=0;
RC_Im = imread(‘red_cells.png’);
RC_Im = rgb2gray(RC_Im);
level=graythresh(RC_Im);
RC_Im_BW = im2bw(RC_Im,level);
figure;
imshow(RC_Im_BW,[])
[x,z]=size(RC_Im_BW);
for R=0:1:60
SE = strel(‘disk’,R);
afteropen=imopen(RC_Im_BW,SE);
if RC_Im_BW==1
count=count+1;
end
end
figure;
imshow(afteropen,[])i write this code but i cant get number of rbc and this is my input image
clear all;
close all;
clc;
count=0;
RC_Im = imread(‘red_cells.png’);
RC_Im = rgb2gray(RC_Im);
level=graythresh(RC_Im);
RC_Im_BW = im2bw(RC_Im,level);
figure;
imshow(RC_Im_BW,[])
[x,z]=size(RC_Im_BW);
for R=0:1:60
SE = strel(‘disk’,R);
afteropen=imopen(RC_Im_BW,SE);
if RC_Im_BW==1
count=count+1;
end
end
figure;
imshow(afteropen,[]) i write this code but i cant get number of rbc and this is my input image
clear all;
close all;
clc;
count=0;
RC_Im = imread(‘red_cells.png’);
RC_Im = rgb2gray(RC_Im);
level=graythresh(RC_Im);
RC_Im_BW = im2bw(RC_Im,level);
figure;
imshow(RC_Im_BW,[])
[x,z]=size(RC_Im_BW);
for R=0:1:60
SE = strel(‘disk’,R);
afteropen=imopen(RC_Im_BW,SE);
if RC_Im_BW==1
count=count+1;
end
end
figure;
imshow(afteropen,[]) imopen, rbc, loop, se MATLAB Answers — New Questions

​

Hello, I’m trying to optimize a simple Simulink model output by using Genetic Algorithm. Three different output values are implemented in this model. The first one is used as cost value. Hovewer, the other two values are not assigned to anything. I want to get these outputs as timeseries after the Genetic Algorithm calculations, like "The second output of Generation XX Individual YY is …". When the calculations are done with single core, I can get all the results I want, but when the parallel toolbox is used, only the last generation and last individual is visible after the calculations. How can I fix that parallel calculation? Here is my simple code that gives all individuals and cost values for me, but I need the other two outputs of simulation. Thanks.

clear all;clc;,
%%
tic
saveFlag = 0;
rng(‘shuffle’);
objectiveFunction = @(params) nlaSimResults(params);

lowerBound = [1000 0.2];
upperBound = [25000 0.8];

popSize = 10;
genSize = 20;

options = optimoptions(‘ga’,’UseParallel’,true,’UseVectorized’,false,’PopulationSize’,popSize,’MaxGenerations’,genSize,’OutputFcn’,@gaOutputFunction,’Display’,’iter’);

[bestParams, minCost, ~, optResults, optPop, optScores] = ga(objectiveFunction,2,[],[],[],[],lowerBound,upperBound,[],options);
optimTime = toc;

if saveFlag == 1; save(‘OptimResulst’,’bestParams’,’minCost’,’optResults’,’optScores’,’optimTime’,’popSize’,’genSize’); end

function cost = nlaSimResults(params)
global otherVars

Altitude = params(1);
Mach = params(2);

assignin(‘base’,’Altitude’,Altitude);
assignin(‘base’,’Mach’,Mach);

sim(‘debugModel’,10); % Simulation Model with Altitude and Mach inputs
cost = logsout{1}.Values.Data(1); % The first output of the model is assigned as cost

if isempty(otherVars)
otherVars = {};
end

otherVars = [otherVars; logsout{2}.Values.Data logsout{3}.Values.Data];

assignin(‘base’,’otherVars’,otherVars);
end

function [state, options, flag] = gaOutputFunction(options, state, flag)
persistent popHistory bestValues bestIndividuals otherVarsHistory
global otherVars

if isempty(popHistory)
popHistory = {};
bestValues = [];
bestIndividuals = [];
otherVarsHistory = {};
end

[bestScore, bestIdx] = min(state.Score);
bestValues = [bestValues; bestScore];
bestIndividuals = [bestIndividuals; state.Population(bestIdx, :)];

popHistory(state.Generation + 1) = {state.Population};

otherVarsHistory{state.Generation + 1} = otherVars;
otherVars = [];

assignin(‘base’,’popHistory’,popHistory);
assignin(‘base’,’bestValues’,bestValues);
assignin(‘base’,’bestIndividuals’,bestIndividuals);
assignin(‘base’,’otherVarsHistory’,otherVarsHistory);
end

My model is so simple, just returning the sum, product and division of the altitude and mach values.Hello, I’m trying to optimize a simple Simulink model output by using Genetic Algorithm. Three different output values are implemented in this model. The first one is used as cost value. Hovewer, the other two values are not assigned to anything. I want to get these outputs as timeseries after the Genetic Algorithm calculations, like "The second output of Generation XX Individual YY is …". When the calculations are done with single core, I can get all the results I want, but when the parallel toolbox is used, only the last generation and last individual is visible after the calculations. How can I fix that parallel calculation? Here is my simple code that gives all individuals and cost values for me, but I need the other two outputs of simulation. Thanks.

clear all;clc;,
%%
tic
saveFlag = 0;
rng(‘shuffle’);
objectiveFunction = @(params) nlaSimResults(params);

lowerBound = [1000 0.2];
upperBound = [25000 0.8];

popSize = 10;
genSize = 20;

options = optimoptions(‘ga’,’UseParallel’,true,’UseVectorized’,false,’PopulationSize’,popSize,’MaxGenerations’,genSize,’OutputFcn’,@gaOutputFunction,’Display’,’iter’);

[bestParams, minCost, ~, optResults, optPop, optScores] = ga(objectiveFunction,2,[],[],[],[],lowerBound,upperBound,[],options);
optimTime = toc;

if saveFlag == 1; save(‘OptimResulst’,’bestParams’,’minCost’,’optResults’,’optScores’,’optimTime’,’popSize’,’genSize’); end

function cost = nlaSimResults(params)
global otherVars

Altitude = params(1);
Mach = params(2);

assignin(‘base’,’Altitude’,Altitude);
assignin(‘base’,’Mach’,Mach);

sim(‘debugModel’,10); % Simulation Model with Altitude and Mach inputs
cost = logsout{1}.Values.Data(1); % The first output of the model is assigned as cost

if isempty(otherVars)
otherVars = {};
end

otherVars = [otherVars; logsout{2}.Values.Data logsout{3}.Values.Data];

assignin(‘base’,’otherVars’,otherVars);
end

function [state, options, flag] = gaOutputFunction(options, state, flag)
persistent popHistory bestValues bestIndividuals otherVarsHistory
global otherVars

if isempty(popHistory)
popHistory = {};
bestValues = [];
bestIndividuals = [];
otherVarsHistory = {};
end

[bestScore, bestIdx] = min(state.Score);
bestValues = [bestValues; bestScore];
bestIndividuals = [bestIndividuals; state.Population(bestIdx, :)];

popHistory(state.Generation + 1) = {state.Population};

otherVarsHistory{state.Generation + 1} = otherVars;
otherVars = [];

assignin(‘base’,’popHistory’,popHistory);
assignin(‘base’,’bestValues’,bestValues);
assignin(‘base’,’bestIndividuals’,bestIndividuals);
assignin(‘base’,’otherVarsHistory’,otherVarsHistory);
end

My model is so simple, just returning the sum, product and division of the altitude and mach values. Hello, I’m trying to optimize a simple Simulink model output by using Genetic Algorithm. Three different output values are implemented in this model. The first one is used as cost value. Hovewer, the other two values are not assigned to anything. I want to get these outputs as timeseries after the Genetic Algorithm calculations, like "The second output of Generation XX Individual YY is …". When the calculations are done with single core, I can get all the results I want, but when the parallel toolbox is used, only the last generation and last individual is visible after the calculations. How can I fix that parallel calculation? Here is my simple code that gives all individuals and cost values for me, but I need the other two outputs of simulation. Thanks.

clear all;clc;,
%%
tic
saveFlag = 0;
rng(‘shuffle’);
objectiveFunction = @(params) nlaSimResults(params);

lowerBound = [1000 0.2];
upperBound = [25000 0.8];

popSize = 10;
genSize = 20;

options = optimoptions(‘ga’,’UseParallel’,true,’UseVectorized’,false,’PopulationSize’,popSize,’MaxGenerations’,genSize,’OutputFcn’,@gaOutputFunction,’Display’,’iter’);

[bestParams, minCost, ~, optResults, optPop, optScores] = ga(objectiveFunction,2,[],[],[],[],lowerBound,upperBound,[],options);
optimTime = toc;

if saveFlag == 1; save(‘OptimResulst’,’bestParams’,’minCost’,’optResults’,’optScores’,’optimTime’,’popSize’,’genSize’); end

function cost = nlaSimResults(params)
global otherVars

Altitude = params(1);
Mach = params(2);

assignin(‘base’,’Altitude’,Altitude);
assignin(‘base’,’Mach’,Mach);

sim(‘debugModel’,10); % Simulation Model with Altitude and Mach inputs
cost = logsout{1}.Values.Data(1); % The first output of the model is assigned as cost

if isempty(otherVars)
otherVars = {};
end

otherVars = [otherVars; logsout{2}.Values.Data logsout{3}.Values.Data];

assignin(‘base’,’otherVars’,otherVars);
end

function [state, options, flag] = gaOutputFunction(options, state, flag)
persistent popHistory bestValues bestIndividuals otherVarsHistory
global otherVars

if isempty(popHistory)
popHistory = {};
bestValues = [];
bestIndividuals = [];
otherVarsHistory = {};
end

[bestScore, bestIdx] = min(state.Score);
bestValues = [bestValues; bestScore];
bestIndividuals = [bestIndividuals; state.Population(bestIdx, :)];

popHistory(state.Generation + 1) = {state.Population};

otherVarsHistory{state.Generation + 1} = otherVars;
otherVars = [];

assignin(‘base’,’popHistory’,popHistory);
assignin(‘base’,’bestValues’,bestValues);
assignin(‘base’,’bestIndividuals’,bestIndividuals);
assignin(‘base’,’otherVarsHistory’,otherVarsHistory);
end

My model is so simple, just returning the sum, product and division of the altitude and mach values. genetic algorithm, parallel computing toolbox MATLAB Answers — New Questions

​

I’m suppose to plot the 3D Joint PDF of these two functions and compare it to the 3D Joint PDF of gaussian normal distribution, so I mulitplied them together but when I try to plot them I’m getting the (Z must be a matrix, not a scalar or vector error).
Question:

Code:
>> mu = 0;sigma = 1; %mean = 0, variance = 1
>> L = 100000; %length of random vector
>> x1 = rand(L,1); %x1 uniformly distributed U(0,1)
>> x2 = rand(L,1); %x2 uniformly distributed U(0,1)
>> w1 = sqrt(-2*log(x1)).*cos(2*pi*x2); %w1 pdf declared
>> w2 = sqrt(-2*log(x1)).*sin(2*pi*x2); %w2 pdf declared
>> w = w1.*w2; %joint pdf declared
>> X = -10:0.1:10;
>> Y = X;
>> gaussNormal = pdf(‘Normal’,X,mu,sigma); %declare gaussian normal pdf
>> [x,y] = meshgrid[X,Y];
>> mesh(x,y,w);
Error using mesh (line 71)
Z must be a matrix, not a scalar or vector.I’m suppose to plot the 3D Joint PDF of these two functions and compare it to the 3D Joint PDF of gaussian normal distribution, so I mulitplied them together but when I try to plot them I’m getting the (Z must be a matrix, not a scalar or vector error).
Question:

Code:
>> mu = 0;sigma = 1; %mean = 0, variance = 1
>> L = 100000; %length of random vector
>> x1 = rand(L,1); %x1 uniformly distributed U(0,1)
>> x2 = rand(L,1); %x2 uniformly distributed U(0,1)
>> w1 = sqrt(-2*log(x1)).*cos(2*pi*x2); %w1 pdf declared
>> w2 = sqrt(-2*log(x1)).*sin(2*pi*x2); %w2 pdf declared
>> w = w1.*w2; %joint pdf declared
>> X = -10:0.1:10;
>> Y = X;
>> gaussNormal = pdf(‘Normal’,X,mu,sigma); %declare gaussian normal pdf
>> [x,y] = meshgrid[X,Y];
>> mesh(x,y,w);
Error using mesh (line 71)
Z must be a matrix, not a scalar or vector. I’m suppose to plot the 3D Joint PDF of these two functions and compare it to the 3D Joint PDF of gaussian normal distribution, so I mulitplied them together but when I try to plot them I’m getting the (Z must be a matrix, not a scalar or vector error).
Question:

Code:
>> mu = 0;sigma = 1; %mean = 0, variance = 1
>> L = 100000; %length of random vector
>> x1 = rand(L,1); %x1 uniformly distributed U(0,1)
>> x2 = rand(L,1); %x2 uniformly distributed U(0,1)
>> w1 = sqrt(-2*log(x1)).*cos(2*pi*x2); %w1 pdf declared
>> w2 = sqrt(-2*log(x1)).*sin(2*pi*x2); %w2 pdf declared
>> w = w1.*w2; %joint pdf declared
>> X = -10:0.1:10;
>> Y = X;
>> gaussNormal = pdf(‘Normal’,X,mu,sigma); %declare gaussian normal pdf
>> [x,y] = meshgrid[X,Y];
>> mesh(x,y,w);
Error using mesh (line 71)
Z must be a matrix, not a scalar or vector. mesh error pdf joint gaussian normal uniform distribution MATLAB Answers — New Questions

​

Hi there,
Sorry if this is a newbie question but I’d like to get my ideas straight before start doing what I want to.

I understand there’s a way to use MATLAB code in C++ (i.e. calling it from C++). But my questions are:

– I have a bunch of functions all of which called by a script, is possible to call such script and retrieve the output. I can also wrap the script around another functions, but still, can I call a function that call another function (and so forth) even if those are in different files?

– I am in extreme needs of the image toolbox in my functions. Is this possible in the moment I call the code from C++?

– In which format I can obtain the output. Can I just map a MATLAB matrix in a C++ matrix?

– Can I pass the code an Image from C++ as a unsigned char matrix?

I understand there may be a documentation out there about this, but I found very fragmented sources, can you in case link me to a good one?

Thank you very muchHi there,
Sorry if this is a newbie question but I’d like to get my ideas straight before start doing what I want to.

I understand there’s a way to use MATLAB code in C++ (i.e. calling it from C++). But my questions are:

– I have a bunch of functions all of which called by a script, is possible to call such script and retrieve the output. I can also wrap the script around another functions, but still, can I call a function that call another function (and so forth) even if those are in different files?

– I am in extreme needs of the image toolbox in my functions. Is this possible in the moment I call the code from C++?

– In which format I can obtain the output. Can I just map a MATLAB matrix in a C++ matrix?

– Can I pass the code an Image from C++ as a unsigned char matrix?

I understand there may be a documentation out there about this, but I found very fragmented sources, can you in case link me to a good one?

Thank you very much Hi there,
Sorry if this is a newbie question but I’d like to get my ideas straight before start doing what I want to.

I understand there’s a way to use MATLAB code in C++ (i.e. calling it from C++). But my questions are:

– I have a bunch of functions all of which called by a script, is possible to call such script and retrieve the output. I can also wrap the script around another functions, but still, can I call a function that call another function (and so forth) even if those are in different files?

– I am in extreme needs of the image toolbox in my functions. Is this possible in the moment I call the code from C++?

– In which format I can obtain the output. Can I just map a MATLAB matrix in a C++ matrix?

– Can I pass the code an Image from C++ as a unsigned char matrix?

I understand there may be a documentation out there about this, but I found very fragmented sources, can you in case link me to a good one?

Thank you very much c++ MATLAB Answers — New Questions

​

I am trying to calibrate my battery parameters using the MBC tool, but I encountered the following issue. I input the HPPC experimental data into the MBC tool and waited for it to fit the parameters, such as Em, R0, R1, etc. However, the results were disappointing. The fitting did not converge, and the curve could not be fitted at all. The result is shown in Figure 1 below. Could you please help me identify the issue? Is it a problem with my parameter settings in the MBC tool, or is there an issue with my HPPC experimental data?I am trying to calibrate my battery parameters using the MBC tool, but I encountered the following issue. I input the HPPC experimental data into the MBC tool and waited for it to fit the parameters, such as Em, R0, R1, etc. However, the results were disappointing. The fitting did not converge, and the curve could not be fitted at all. The result is shown in Figure 1 below. Could you please help me identify the issue? Is it a problem with my parameter settings in the MBC tool, or is there an issue with my HPPC experimental data? I am trying to calibrate my battery parameters using the MBC tool, but I encountered the following issue. I input the HPPC experimental data into the MBC tool and waited for it to fit the parameters, such as Em, R0, R1, etc. However, the results were disappointing. The fitting did not converge, and the curve could not be fitted at all. The result is shown in Figure 1 below. Could you please help me identify the issue? Is it a problem with my parameter settings in the MBC tool, or is there an issue with my HPPC experimental data? simscape, mbc, battery_system_management MATLAB Answers — New Questions

​

Good afternoon,
I have been trying to deploy a tflite model onto my raspberry pi using MATLAB 2024a.
To start i am using:
Example code (SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample).
Mex code setup i am using ‘Microsoft Visual C++ 2022’
Built Tensorflow 2.15 on Windows with Bazel 6.10
Downloaded and setup Raspberry pi Matlab config
Raspberry pi 32 bit bullseye (python 3.9.2)
created all of the paths accordingly as stated in Prerequisites for Deep Learning with TensorFlow Lite Models
When i run the code it has no errors. The problem starts once i run:
codegen -config cfg tflite_semantic_predict -args ones(257,257,3,’single’)
The error is as follows:
codegen -config cfg tflite_semantic_predict -args ones(257,257,3,’single’)
————————————————————————
Error executing command "touch -c /home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict/*.*;make -j$(($(nproc)+1)) -Otarget -f tflite_semantic_predict_rtw.mk all MATLAB_WORKSPACE="/home/bmblaylock42/MATLAB_ws/R2024a" LINUX_TARGET_LIBS_MACRO="" -C /home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict LC_ALL=C". Details:

STDERR: In file included from /home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/tflite_interface/invokeinterpreter/export/include/invokeinterpreter/tensorflow/lite/core/model.h:26,
from /home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/tflite_interface/invokeinterpreter/export/include/invokeinterpreter/tensorflow/lite/core/kernels/register.h:22,
from /home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/tflite_interface/invokeinterpreter/export/include/invokeinterpreter/kernels/register.h:18,
from /home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/tflite_interface/invokeinterpreter/export/include/invokeinterpreter/invokeinterpreter.hpp:16,
from /home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/tflite_interface/invokeinterpreter/invokeinterpreter.cpp:6:
/home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/tflite_interface/invokeinterpreter/export/include/invokeinterpreter/tensorflow/lite/core/interpreter_builder.h:33:10: fatal error: flatbuffers/flatbuffers.h: No such file or directory
33 | #include "flatbuffers/flatbuffers.h"
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~
compilation terminated.
make: *** [tflite_semantic_predict_rtw.mk:382: invokeinterpreter.cpp.o] Error 1
make: *** Waiting for unfinished jobs….
In file included from /home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/tflite_interface/invokeinterpreter/export/include/invokeinterpreter/tensorflow/lite/core/model.h:26,
from /home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/tflite_interface/invokeinterpreter/export/include/invokeinterpreter/tensorflow/lite/core/kernels/register.h:22,
from /home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/tflite_interface/invokeinterpreter/export/include/invokeinterpreter/kernels/register.h:18,
from /home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/tflite_interface/invokeinterpreter/export/include/invokeinterpreter/invokeinterpreter.hpp:16,
from /home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict/tflite_semantic_predict.cpp:15:
/home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/tflite_interface/invokeinterpreter/export/include/invokeinterpreter/tensorflow/lite/core/interpreter_builder.h:33:10: fatal error: flatbuffers/flatbuffers.h: No such file or directory
33 | #include "flatbuffers/flatbuffers.h"
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~
compilation terminated.
make: *** [tflite_semantic_predict_rtw.mk:398: tflite_semantic_predict.cpp.o] Error 1

STDOUT: make: Entering directory ‘/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict’
g++ -c -MMD -MP -MF"tflite_semantic_predict_data.cpp.dep" -MT"tflite_semantic_predict_data.cpp.o" -fpermissive -O2 -DMW_NUM_CORES=4 -pthread -fopenmp -std=c++17 -D__MW_TARGET_USE_HARDWARE_RESOURCES_H__ -D__linux__ -DARM_PROJECT -D_USE_TARGET_UDP_ -D_RUNONTARGETHARDWARE_BUILD_ -DSTACK_SIZE=200000 -DMODEL=tflite_semantic_predict -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/tflite_interface/invokeinterpreter/export/include/invokeinterpreter -I -I/tensorflow/lite -I/tensorflow/lite/tools/make/downloads/flatbuffers/include -I/flatbuffers/include -I/home/bmblaylock42/MATLAB_ws/R2024a/C/ProgramData/MATLAB/SupportPackages/R2024a/toolbox/realtime/targets/raspi/include -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/coder/rtiostream/src/utils -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/extern/include -o "tflite_semantic_predict_data.cpp.o" "/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict/tflite_semantic_predict_data.cpp"
make: Leaving directory ‘/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict’
make: Entering directory ‘/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict’
g++ -c -MMD -MP -MF"tflite_semantic_predict_terminate.cpp.dep" -MT"tflite_semantic_predict_terminate.cpp.o" -fpermissive -O2 -DMW_NUM_CORES=4 -pthread -fopenmp -std=c++17 -D__MW_TARGET_USE_HARDWARE_RESOURCES_H__ -D__linux__ -DARM_PROJECT -D_USE_TARGET_UDP_ -D_RUNONTARGETHARDWARE_BUILD_ -DSTACK_SIZE=200000 -DMODEL=tflite_semantic_predict -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/tflite_interface/invokeinterpreter/export/include/invokeinterpreter -I -I/tensorflow/lite -I/tensorflow/lite/tools/make/downloads/flatbuffers/include -I/flatbuffers/include -I/home/bmblaylock42/MATLAB_ws/R2024a/C/ProgramData/MATLAB/SupportPackages/R2024a/toolbox/realtime/targets/raspi/include -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/coder/rtiostream/src/utils -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/extern/include -o "tflite_semantic_predict_terminate.cpp.o" "/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict/tflite_semantic_predict_terminate.cpp"
make: Leaving directory ‘/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict’
make: Entering directory ‘/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict’
g++ -c -MMD -MP -MF"tflite_semantic_predict_initialize.cpp.dep" -MT"tflite_semantic_predict_initialize.cpp.o" -fpermissive -O2 -DMW_NUM_CORES=4 -pthread -fopenmp -std=c++17 -D__MW_TARGET_USE_HARDWARE_RESOURCES_H__ -D__linux__ -DARM_PROJECT -D_USE_TARGET_UDP_ -D_RUNONTARGETHARDWARE_BUILD_ -DSTACK_SIZE=200000 -DMODEL=tflite_semantic_predict -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/tflite_interface/invokeinterpreter/export/include/invokeinterpreter -I -I/tensorflow/lite -I/tensorflow/lite/tools/make/downloads/flatbuffers/include -I/flatbuffers/include -I/home/bmblaylock42/MATLAB_ws/R2024a/C/ProgramData/MATLAB/SupportPackages/R2024a/toolbox/realtime/targets/raspi/include -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/coder/rtiostream/src/utils -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/extern/include -o "tflite_semantic_predict_initialize.cpp.o" "/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict/tflite_semantic_predict_initialize.cpp"
make: Leaving directory ‘/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict’
make: Entering directory ‘/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict’
g++ -c -MMD -MP -MF"invokeinterpreter.cpp.dep" -MT"invokeinterpreter.cpp.o" -fpermissive -O2 -DMW_NUM_CORES=4 -pthread -fopenmp -std=c++17 -D__MW_TARGET_USE_HARDWARE_RESOURCES_H__ -D__linux__ -DARM_PROJECT -D_USE_TARGET_UDP_ -D_RUNONTARGETHARDWARE_BUILD_ -DSTACK_SIZE=200000 -DMODEL=tflite_semantic_predict -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/tflite_interface/invokeinterpreter/export/include/invokeinterpreter -I -I/tensorflow/lite -I/tensorflow/lite/tools/make/downloads/flatbuffers/include -I/flatbuffers/include -I/home/bmblaylock42/MATLAB_ws/R2024a/C/ProgramData/MATLAB/SupportPackages/R2024a/toolbox/realtime/targets/raspi/include -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/coder/rtiostream/src/utils -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/extern/include -o "invokeinterpreter.cpp.o" "/home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/tflite_interface/invokeinterpreter/invokeinterpreter.cpp"
make: Leaving directory ‘/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict’
make: Entering directory ‘/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict’
g++ -c -MMD -MP -MF"tflite_semantic_predict.cpp.dep" -MT"tflite_semantic_predict.cpp.o" -fpermissive -O2 -DMW_NUM_CORES=4 -pthread -fopenmp -std=c++17 -D__MW_TARGET_USE_HARDWARE_RESOURCES_H__ -D__linux__ -DARM_PROJECT -D_USE_TARGET_UDP_ -D_RUNONTARGETHARDWARE_BUILD_ -DSTACK_SIZE=200000 -DMODEL=tflite_semantic_predict -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/tflite_interface/invokeinterpreter/export/include/invokeinterpreter -I -I/tensorflow/lite -I/tensorflow/lite/tools/make/downloads/flatbuffers/include -I/flatbuffers/include -I/home/bmblaylock42/MATLAB_ws/R2024a/C/ProgramData/MATLAB/SupportPackages/R2024a/toolbox/realtime/targets/raspi/include -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/coder/rtiostream/src/utils -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/extern/include -o "tflite_semantic_predict.cpp.o" "/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict/tflite_semantic_predict.cpp"
make: Leaving directory ‘/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict’

————————————————————————
Build error: C++ compiler produced errors. See the Build Log for further details.
More information
Code generation failed: View Error Report

Error using codegen

Thank you so much i have tried to download the flatbuffers by CMake and bazel but i had no luck since they are 64 bit codes and mine is a 32bit aarch64.Good afternoon,
I have been trying to deploy a tflite model onto my raspberry pi using MATLAB 2024a.
To start i am using:
Example code (SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample).
Mex code setup i am using ‘Microsoft Visual C++ 2022’
Built Tensorflow 2.15 on Windows with Bazel 6.10
Downloaded and setup Raspberry pi Matlab config
Raspberry pi 32 bit bullseye (python 3.9.2)
created all of the paths accordingly as stated in Prerequisites for Deep Learning with TensorFlow Lite Models
When i run the code it has no errors. The problem starts once i run:
codegen -config cfg tflite_semantic_predict -args ones(257,257,3,’single’)
The error is as follows:
codegen -config cfg tflite_semantic_predict -args ones(257,257,3,’single’)
————————————————————————
Error executing command "touch -c /home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict/*.*;make -j$(($(nproc)+1)) -Otarget -f tflite_semantic_predict_rtw.mk all MATLAB_WORKSPACE="/home/bmblaylock42/MATLAB_ws/R2024a" LINUX_TARGET_LIBS_MACRO="" -C /home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict LC_ALL=C". Details:

STDERR: In file included from /home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/tflite_interface/invokeinterpreter/export/include/invokeinterpreter/tensorflow/lite/core/model.h:26,
from /home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/tflite_interface/invokeinterpreter/export/include/invokeinterpreter/tensorflow/lite/core/kernels/register.h:22,
from /home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/tflite_interface/invokeinterpreter/export/include/invokeinterpreter/kernels/register.h:18,
from /home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/tflite_interface/invokeinterpreter/export/include/invokeinterpreter/invokeinterpreter.hpp:16,
from /home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/tflite_interface/invokeinterpreter/invokeinterpreter.cpp:6:
/home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/tflite_interface/invokeinterpreter/export/include/invokeinterpreter/tensorflow/lite/core/interpreter_builder.h:33:10: fatal error: flatbuffers/flatbuffers.h: No such file or directory
33 | #include "flatbuffers/flatbuffers.h"
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~
compilation terminated.
make: *** [tflite_semantic_predict_rtw.mk:382: invokeinterpreter.cpp.o] Error 1
make: *** Waiting for unfinished jobs….
In file included from /home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/tflite_interface/invokeinterpreter/export/include/invokeinterpreter/tensorflow/lite/core/model.h:26,
from /home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/tflite_interface/invokeinterpreter/export/include/invokeinterpreter/tensorflow/lite/core/kernels/register.h:22,
from /home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/tflite_interface/invokeinterpreter/export/include/invokeinterpreter/kernels/register.h:18,
from /home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/tflite_interface/invokeinterpreter/export/include/invokeinterpreter/invokeinterpreter.hpp:16,
from /home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict/tflite_semantic_predict.cpp:15:
/home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/tflite_interface/invokeinterpreter/export/include/invokeinterpreter/tensorflow/lite/core/interpreter_builder.h:33:10: fatal error: flatbuffers/flatbuffers.h: No such file or directory
33 | #include "flatbuffers/flatbuffers.h"
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~
compilation terminated.
make: *** [tflite_semantic_predict_rtw.mk:398: tflite_semantic_predict.cpp.o] Error 1

STDOUT: make: Entering directory ‘/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict’
g++ -c -MMD -MP -MF"tflite_semantic_predict_data.cpp.dep" -MT"tflite_semantic_predict_data.cpp.o" -fpermissive -O2 -DMW_NUM_CORES=4 -pthread -fopenmp -std=c++17 -D__MW_TARGET_USE_HARDWARE_RESOURCES_H__ -D__linux__ -DARM_PROJECT -D_USE_TARGET_UDP_ -D_RUNONTARGETHARDWARE_BUILD_ -DSTACK_SIZE=200000 -DMODEL=tflite_semantic_predict -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/tflite_interface/invokeinterpreter/export/include/invokeinterpreter -I -I/tensorflow/lite -I/tensorflow/lite/tools/make/downloads/flatbuffers/include -I/flatbuffers/include -I/home/bmblaylock42/MATLAB_ws/R2024a/C/ProgramData/MATLAB/SupportPackages/R2024a/toolbox/realtime/targets/raspi/include -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/coder/rtiostream/src/utils -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/extern/include -o "tflite_semantic_predict_data.cpp.o" "/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict/tflite_semantic_predict_data.cpp"
make: Leaving directory ‘/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict’
make: Entering directory ‘/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict’
g++ -c -MMD -MP -MF"tflite_semantic_predict_terminate.cpp.dep" -MT"tflite_semantic_predict_terminate.cpp.o" -fpermissive -O2 -DMW_NUM_CORES=4 -pthread -fopenmp -std=c++17 -D__MW_TARGET_USE_HARDWARE_RESOURCES_H__ -D__linux__ -DARM_PROJECT -D_USE_TARGET_UDP_ -D_RUNONTARGETHARDWARE_BUILD_ -DSTACK_SIZE=200000 -DMODEL=tflite_semantic_predict -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/tflite_interface/invokeinterpreter/export/include/invokeinterpreter -I -I/tensorflow/lite -I/tensorflow/lite/tools/make/downloads/flatbuffers/include -I/flatbuffers/include -I/home/bmblaylock42/MATLAB_ws/R2024a/C/ProgramData/MATLAB/SupportPackages/R2024a/toolbox/realtime/targets/raspi/include -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/coder/rtiostream/src/utils -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/extern/include -o "tflite_semantic_predict_terminate.cpp.o" "/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict/tflite_semantic_predict_terminate.cpp"
make: Leaving directory ‘/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict’
make: Entering directory ‘/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict’
g++ -c -MMD -MP -MF"tflite_semantic_predict_initialize.cpp.dep" -MT"tflite_semantic_predict_initialize.cpp.o" -fpermissive -O2 -DMW_NUM_CORES=4 -pthread -fopenmp -std=c++17 -D__MW_TARGET_USE_HARDWARE_RESOURCES_H__ -D__linux__ -DARM_PROJECT -D_USE_TARGET_UDP_ -D_RUNONTARGETHARDWARE_BUILD_ -DSTACK_SIZE=200000 -DMODEL=tflite_semantic_predict -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/tflite_interface/invokeinterpreter/export/include/invokeinterpreter -I -I/tensorflow/lite -I/tensorflow/lite/tools/make/downloads/flatbuffers/include -I/flatbuffers/include -I/home/bmblaylock42/MATLAB_ws/R2024a/C/ProgramData/MATLAB/SupportPackages/R2024a/toolbox/realtime/targets/raspi/include -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/coder/rtiostream/src/utils -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/extern/include -o "tflite_semantic_predict_initialize.cpp.o" "/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict/tflite_semantic_predict_initialize.cpp"
make: Leaving directory ‘/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict’
make: Entering directory ‘/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict’
g++ -c -MMD -MP -MF"invokeinterpreter.cpp.dep" -MT"invokeinterpreter.cpp.o" -fpermissive -O2 -DMW_NUM_CORES=4 -pthread -fopenmp -std=c++17 -D__MW_TARGET_USE_HARDWARE_RESOURCES_H__ -D__linux__ -DARM_PROJECT -D_USE_TARGET_UDP_ -D_RUNONTARGETHARDWARE_BUILD_ -DSTACK_SIZE=200000 -DMODEL=tflite_semantic_predict -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/tflite_interface/invokeinterpreter/export/include/invokeinterpreter -I -I/tensorflow/lite -I/tensorflow/lite/tools/make/downloads/flatbuffers/include -I/flatbuffers/include -I/home/bmblaylock42/MATLAB_ws/R2024a/C/ProgramData/MATLAB/SupportPackages/R2024a/toolbox/realtime/targets/raspi/include -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/coder/rtiostream/src/utils -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/extern/include -o "invokeinterpreter.cpp.o" "/home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/tflite_interface/invokeinterpreter/invokeinterpreter.cpp"
make: Leaving directory ‘/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict’
make: Entering directory ‘/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict’
g++ -c -MMD -MP -MF"tflite_semantic_predict.cpp.dep" -MT"tflite_semantic_predict.cpp.o" -fpermissive -O2 -DMW_NUM_CORES=4 -pthread -fopenmp -std=c++17 -D__MW_TARGET_USE_HARDWARE_RESOURCES_H__ -D__linux__ -DARM_PROJECT -D_USE_TARGET_UDP_ -D_RUNONTARGETHARDWARE_BUILD_ -DSTACK_SIZE=200000 -DMODEL=tflite_semantic_predict -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/tflite_interface/invokeinterpreter/export/include/invokeinterpreter -I -I/tensorflow/lite -I/tensorflow/lite/tools/make/downloads/flatbuffers/include -I/flatbuffers/include -I/home/bmblaylock42/MATLAB_ws/R2024a/C/ProgramData/MATLAB/SupportPackages/R2024a/toolbox/realtime/targets/raspi/include -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/coder/rtiostream/src/utils -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/extern/include -o "tflite_semantic_predict.cpp.o" "/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict/tflite_semantic_predict.cpp"
make: Leaving directory ‘/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict’

————————————————————————
Build error: C++ compiler produced errors. See the Build Log for further details.
More information
Code generation failed: View Error Report

Error using codegen

Thank you so much i have tried to download the flatbuffers by CMake and bazel but i had no luck since they are 64 bit codes and mine is a 32bit aarch64. Good afternoon,
I have been trying to deploy a tflite model onto my raspberry pi using MATLAB 2024a.
To start i am using:
Example code (SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample).
Mex code setup i am using ‘Microsoft Visual C++ 2022’
Built Tensorflow 2.15 on Windows with Bazel 6.10
Downloaded and setup Raspberry pi Matlab config
Raspberry pi 32 bit bullseye (python 3.9.2)
created all of the paths accordingly as stated in Prerequisites for Deep Learning with TensorFlow Lite Models
When i run the code it has no errors. The problem starts once i run:
codegen -config cfg tflite_semantic_predict -args ones(257,257,3,’single’)
The error is as follows:
codegen -config cfg tflite_semantic_predict -args ones(257,257,3,’single’)
————————————————————————
Error executing command "touch -c /home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict/*.*;make -j$(($(nproc)+1)) -Otarget -f tflite_semantic_predict_rtw.mk all MATLAB_WORKSPACE="/home/bmblaylock42/MATLAB_ws/R2024a" LINUX_TARGET_LIBS_MACRO="" -C /home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict LC_ALL=C". Details:

STDERR: In file included from /home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/tflite_interface/invokeinterpreter/export/include/invokeinterpreter/tensorflow/lite/core/model.h:26,
from /home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/tflite_interface/invokeinterpreter/export/include/invokeinterpreter/tensorflow/lite/core/kernels/register.h:22,
from /home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/tflite_interface/invokeinterpreter/export/include/invokeinterpreter/kernels/register.h:18,
from /home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/tflite_interface/invokeinterpreter/export/include/invokeinterpreter/invokeinterpreter.hpp:16,
from /home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/tflite_interface/invokeinterpreter/invokeinterpreter.cpp:6:
/home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/tflite_interface/invokeinterpreter/export/include/invokeinterpreter/tensorflow/lite/core/interpreter_builder.h:33:10: fatal error: flatbuffers/flatbuffers.h: No such file or directory
33 | #include "flatbuffers/flatbuffers.h"
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~
compilation terminated.
make: *** [tflite_semantic_predict_rtw.mk:382: invokeinterpreter.cpp.o] Error 1
make: *** Waiting for unfinished jobs….
In file included from /home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/tflite_interface/invokeinterpreter/export/include/invokeinterpreter/tensorflow/lite/core/model.h:26,
from /home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/tflite_interface/invokeinterpreter/export/include/invokeinterpreter/tensorflow/lite/core/kernels/register.h:22,
from /home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/tflite_interface/invokeinterpreter/export/include/invokeinterpreter/kernels/register.h:18,
from /home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/tflite_interface/invokeinterpreter/export/include/invokeinterpreter/invokeinterpreter.hpp:16,
from /home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict/tflite_semantic_predict.cpp:15:
/home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/tflite_interface/invokeinterpreter/export/include/invokeinterpreter/tensorflow/lite/core/interpreter_builder.h:33:10: fatal error: flatbuffers/flatbuffers.h: No such file or directory
33 | #include "flatbuffers/flatbuffers.h"
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~
compilation terminated.
make: *** [tflite_semantic_predict_rtw.mk:398: tflite_semantic_predict.cpp.o] Error 1

STDOUT: make: Entering directory ‘/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict’
g++ -c -MMD -MP -MF"tflite_semantic_predict_data.cpp.dep" -MT"tflite_semantic_predict_data.cpp.o" -fpermissive -O2 -DMW_NUM_CORES=4 -pthread -fopenmp -std=c++17 -D__MW_TARGET_USE_HARDWARE_RESOURCES_H__ -D__linux__ -DARM_PROJECT -D_USE_TARGET_UDP_ -D_RUNONTARGETHARDWARE_BUILD_ -DSTACK_SIZE=200000 -DMODEL=tflite_semantic_predict -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/tflite_interface/invokeinterpreter/export/include/invokeinterpreter -I -I/tensorflow/lite -I/tensorflow/lite/tools/make/downloads/flatbuffers/include -I/flatbuffers/include -I/home/bmblaylock42/MATLAB_ws/R2024a/C/ProgramData/MATLAB/SupportPackages/R2024a/toolbox/realtime/targets/raspi/include -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/coder/rtiostream/src/utils -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/extern/include -o "tflite_semantic_predict_data.cpp.o" "/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict/tflite_semantic_predict_data.cpp"
make: Leaving directory ‘/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict’
make: Entering directory ‘/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict’
g++ -c -MMD -MP -MF"tflite_semantic_predict_terminate.cpp.dep" -MT"tflite_semantic_predict_terminate.cpp.o" -fpermissive -O2 -DMW_NUM_CORES=4 -pthread -fopenmp -std=c++17 -D__MW_TARGET_USE_HARDWARE_RESOURCES_H__ -D__linux__ -DARM_PROJECT -D_USE_TARGET_UDP_ -D_RUNONTARGETHARDWARE_BUILD_ -DSTACK_SIZE=200000 -DMODEL=tflite_semantic_predict -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/tflite_interface/invokeinterpreter/export/include/invokeinterpreter -I -I/tensorflow/lite -I/tensorflow/lite/tools/make/downloads/flatbuffers/include -I/flatbuffers/include -I/home/bmblaylock42/MATLAB_ws/R2024a/C/ProgramData/MATLAB/SupportPackages/R2024a/toolbox/realtime/targets/raspi/include -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/coder/rtiostream/src/utils -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/extern/include -o "tflite_semantic_predict_terminate.cpp.o" "/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict/tflite_semantic_predict_terminate.cpp"
make: Leaving directory ‘/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict’
make: Entering directory ‘/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict’
g++ -c -MMD -MP -MF"tflite_semantic_predict_initialize.cpp.dep" -MT"tflite_semantic_predict_initialize.cpp.o" -fpermissive -O2 -DMW_NUM_CORES=4 -pthread -fopenmp -std=c++17 -D__MW_TARGET_USE_HARDWARE_RESOURCES_H__ -D__linux__ -DARM_PROJECT -D_USE_TARGET_UDP_ -D_RUNONTARGETHARDWARE_BUILD_ -DSTACK_SIZE=200000 -DMODEL=tflite_semantic_predict -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/tflite_interface/invokeinterpreter/export/include/invokeinterpreter -I -I/tensorflow/lite -I/tensorflow/lite/tools/make/downloads/flatbuffers/include -I/flatbuffers/include -I/home/bmblaylock42/MATLAB_ws/R2024a/C/ProgramData/MATLAB/SupportPackages/R2024a/toolbox/realtime/targets/raspi/include -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/coder/rtiostream/src/utils -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/extern/include -o "tflite_semantic_predict_initialize.cpp.o" "/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict/tflite_semantic_predict_initialize.cpp"
make: Leaving directory ‘/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict’
make: Entering directory ‘/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict’
g++ -c -MMD -MP -MF"invokeinterpreter.cpp.dep" -MT"invokeinterpreter.cpp.o" -fpermissive -O2 -DMW_NUM_CORES=4 -pthread -fopenmp -std=c++17 -D__MW_TARGET_USE_HARDWARE_RESOURCES_H__ -D__linux__ -DARM_PROJECT -D_USE_TARGET_UDP_ -D_RUNONTARGETHARDWARE_BUILD_ -DSTACK_SIZE=200000 -DMODEL=tflite_semantic_predict -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/tflite_interface/invokeinterpreter/export/include/invokeinterpreter -I -I/tensorflow/lite -I/tensorflow/lite/tools/make/downloads/flatbuffers/include -I/flatbuffers/include -I/home/bmblaylock42/MATLAB_ws/R2024a/C/ProgramData/MATLAB/SupportPackages/R2024a/toolbox/realtime/targets/raspi/include -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/coder/rtiostream/src/utils -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/extern/include -o "invokeinterpreter.cpp.o" "/home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/tflite_interface/invokeinterpreter/invokeinterpreter.cpp"
make: Leaving directory ‘/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict’
make: Entering directory ‘/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict’
g++ -c -MMD -MP -MF"tflite_semantic_predict.cpp.dep" -MT"tflite_semantic_predict.cpp.o" -fpermissive -O2 -DMW_NUM_CORES=4 -pthread -fopenmp -std=c++17 -D__MW_TARGET_USE_HARDWARE_RESOURCES_H__ -D__linux__ -DARM_PROJECT -D_USE_TARGET_UDP_ -D_RUNONTARGETHARDWARE_BUILD_ -DSTACK_SIZE=200000 -DMODEL=tflite_semantic_predict -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/tflite_interface/invokeinterpreter/export/include/invokeinterpreter -I -I/tensorflow/lite -I/tensorflow/lite/tools/make/downloads/flatbuffers/include -I/flatbuffers/include -I/home/bmblaylock42/MATLAB_ws/R2024a/C/ProgramData/MATLAB/SupportPackages/R2024a/toolbox/realtime/targets/raspi/include -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/toolbox/coder/rtiostream/src/utils -I/home/bmblaylock42/MATLAB_ws/R2024a/C/Program_Files/MATLAB/R2024a/extern/include -o "tflite_semantic_predict.cpp.o" "/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict/tflite_semantic_predict.cpp"
make: Leaving directory ‘/home/bmblaylock42/MATLAB_ws/R2024a/C/Users/BransonBlaylock/SemanticSegmentationUsingTFLiteModelOnHostAndRasPiExample/codegen/lib/tflite_semantic_predict’

————————————————————————
Build error: C++ compiler produced errors. See the Build Log for further details.
More information
Code generation failed: View Error Report

Error using codegen

Thank you so much i have tried to download the flatbuffers by CMake and bazel but i had no luck since they are 64 bit codes and mine is a 32bit aarch64. tensorflow, matlab, code generation MATLAB Answers — New Questions

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