I am trying to get familiar with the Image category classification using deep learning. I am trying to run the Matlab example available on
http://uk.mathworks.com/help/vision/examples/image-category-classification-using-deep-learning.html
However running this example is giving me the following error
Error using message/getString
Unable to load a message catalog 'nnet_cnn:layer:Layer'. Please check
the file location and format.
Error in nnet.cnn.layer.Layer/getVectorHeader (line 113)
header = getString( message( ...
Error in nnet.cnn.layer.Layer/displayNonScalarObject (line 86)
header = sprintf( ' %s\n', getVectorHeader( layers )
);
Error in cnn (line 150)
convnet.Layers
Moreover if I pass and ignore this error, I will get the following error later for the line
trainingFeatures = activations(convnet, trainingSet, featureLayer, ...
'MiniBatchSize', 32, 'OutputAs', 'columns')
Undefined variable "nnet" or class "nnet.internal.cnngpu.convolveForward2D".
Error in nnet.internal.cnn.layer.Convolution2D/doForward (line 218)
Z = nnet.internal.cnngpu.convolveForward2D( ...
Error in nnet.internal.cnn.layer.Convolution2D/forwardNormal (line 195)
Z = this.doForward(X,this.Weights.Value,this.Bias.Value);
Error in nnet.internal.cnn.layer.Convolution2D/forward (line 98)
[Z, memory] = this.forwardNormal( X );
Error in nnet.internal.cnn.SeriesNetwork/activations (line 50)
output = this.Layers{currentLayer}.forward( output );
Error in SeriesNetwork/activations (line 269)
YChannelFormat = predictNetwork.activations(X, layerID);
Error in cnn (line 262)
trainingFeatures = activations(convnet, trainingSet, featureLayer, ...
Can please someone tell me the possibilities for getting this error and how to solve it.
Regards
Related
I have another question about running narx with bigg data. I tried increase the hidden size, to get better model.
seems like 300 is some upper limit for the hidden units allowed- memory error. So for 1000 it clearly says no.
with the narxnet of :
net = narxnet(1:25,1:25,1000);
I get this error .e file
{Error using zeros
Requested 1000x54373200 (405.1GB) array exceeds maximum array size preference
(377.4GB). This might cause MATLAB to become unresponsive.
Error in nnet.internal.configure.inputWeight (line 25)
net.IW{i,j} = zeros(newSize);
Error in nnet.internal.configure.input (line 42)
net = nnet.internal.configure.inputWeight(net,j,i,x);
Error in network/configure (line 244)
net = nnet.internal.configure.input(net,i,X{i});
Error in preparets (line 302)
net = configure(net,'input',xx(i,:),i);
}
with the size 600 i get - out of memeory error, How to fix it to able to use the NARX for big data:
net = narxnet(1:25,1:25,600);
we get the following
{Out of memory.
Error in normr (line 27)
xi(~isfinite(xi)) = 0;
Error in randnr>new_value_from_rows_cols (line 152)
x = normr(rands(rows,cols));
Error in randnr (line 98)
out1 = new_value_from_rows_cols(in1,in2);
Error in initnw>calcnw (line 287)
wDir = randnr(s,r);
Error in initnw>initialize_layer (line 212)
[w,b] = calcnw(range,net.layers{i}.size,active);
Error in initnw (line 101)
out1 = initialize_layer(in1,in2);
Error in initlay>initialize_network (line 155)
net = feval(initFcn,net,i);
Error in initlay (line 97)
out1 = initialize_network(in1);
Error in network/init (line 31)
net = feval(initFcn,net);
Error in network/configure (line 253)
net = init(net);
Error in preparets (line 302)
net = configure(net,'input',xx(i,:),i);
}
Also, the matlab code do not scale up with more cpu count . Like I get same time for 24 cpu and 120 cpu.
I am new to MATLAB image processing and trying to extract image features on the basis of colour thresholding but unable to go further. Right after selecting image pixel and I receive the following errors:
Error using getpts (line 174)
Interruption during mouse point selection.
Error in impixel>parse_inputs (line 199)
[xi,yi] = getpts(ancestor(h,'axes'));
Error in impixel (line 76)
[a,cm,xi,yi,x,y] = parse_inputs(varargin{:});
Error in featureextraction (line 5)
pval = impixel(a);
Here is my code:
oneToolImg = 'E:\Ujala Documents\hfu ss\forschungspraktikum\oneTool.jpg';
a = imread(oneToolImg);
figure(1)
imshow(a)
pval = impixel(a);
tool = (a(:,:,1)>91) & (a(:,:,2)>82) & (a(:,:,3)<252);
figure,imshow(tool)
I have a 10^5 square sparse matrix called pbAttack. Each element represents if there is connection between node i and node j. If there is connection, pbAttack(i,j) = 1. Otherwise, pbAttack (i,j) = 0. Then I want to use it following this tutorial: Matlab Autoencoders. I use the same code as in the linked Matlab tutorial. I only change it to use my data.
However, I got following errors:
Error using bsxfun
Out of memory. Type HELP MEMORY for your options.
Error in mapminmax.apply (line 8)
y = bsxfun(#plus,y,settings.ymin);
Error in mapminmax.create (line 44)
y = mapminmax.apply(x,settings);
Error in mapminmax (line 51)
[y,settings] = mapminmax.create(x,param);
Error in nnet.internal.configure.input (line 31)
[x,config] = feval(processFcns{j},x,processParams{j});
Error in network/configure (line 234)
net = nnet.internal.configure.input(net,i,X{i});
Error in nntraining.config (line 116)
net = configure(network(net),X,T);
Error in nntraining.setup>setupPerWorker (line 68)
[net,X,Xi,Ai,T,EW,Q,TS,err] = nntraining.config(net,X,Xi,Ai,T,EW,configNetEnable);
Error in nntraining.setup (line 43)
[net,data,tr,err] = setupPerWorker(net,trainFcn,X,Xi,Ai,T,EW,enableConfigure);
Error in network/train (line 335)
[net,data,tr,err] = nntraining.setup(net,net.trainFcn,X,Xi,Ai,T,EW,enableConfigure,isComposite);
Error in Autoencoder.train (line 490)
net = train(net,X,X,'useGPU',iYesOrNo(useGPU));
Error in trainAutoencoder (line 105)
autoenc = Autoencoder.train(X, autonet, paramsStruct.UseGPU);
Error in workflow_autoencoder (line 8)
autoenc1 = trainAutoencoder(pbAttack,hiddenSize,...
Are all these errors caused by the huge size of the matrix? Is there a work around so that it does not need so much memory? Thank you so much.
It just means that you don't have enough memory for this (since your matrix is not so sparse). You can try to repeat your code by reducing the size of the matrix.
I have variable (type table) in matlab:
and I'm using fitcnb for training naive bayes. I execute code:
Mdl = fitcnb(data,'class')
But I get an error :
Error using classreg.learning.FullClassificationRegressionModel.prepareDataCR (line 129) X must be a numeric matrix.
Error in classreg.learning.classif.FullClassificationModel.prepareData (line 455) [X,Y,W,dataSummary] = ...
Error in classreg.learning.FitTemplate/fit (line 205 [X,Y,dataPrepOut{1:this.NDataPrepOut}] = ...
Error in ClassificationNaiveBayes.fit (line 127) this = fit(temp,X,Y);
Error in fitcnb (line 219) this = ClassificationNaiveBayes.fit(X,Y,varargin{:});
fitcnb call's syntax is correct
Mdl = fitcnb(tbl,ResponseVarName)
But why I get an error ?
I am trying to run the example at:
http://nl.mathworks.com/help/stats/group-comparisons-using-categorical-arrays.html
using Matlab R2013b.
clear
load('carsmall')
cars = table(MPG,Weight,Model_Year);
cars.Model_Year = nominal(cars.Model_Year);
fit = fitlm(cars,'MPG~Weight*Model_Year')
Unfortunatelly I get the error:
Error using classreg.regr.FitObject/assignData (line 257)
Predictor and response variables must have the same length.
Error in classreg.regr.TermsRegression/assignData (line 349)
model = assignData#classreg.regr.ParametricRegression(model,X,y,w,asCat,varNames,excl);
Error in LinearModel.fit (line 852)
model = assignData(model,X,y,weights,asCatVar,dummyCoding,model.Formula.VariableNames,exclude);
Error in fitlm (line 111)
model = LinearModel.fit(X,varargin{:});
Any clue why?