您好，

在学习做matlab nerual network toolbox 帮助中的例子时，遇到了以下问题：

错误使用 trainNetwork (line 154)

尝试确定 "readData" 是否是函数名称时出错。

出错 temp2 (line 55)

net = trainNetwork(imdsTrain,layers,options);

原因:

尝试确定 "readData" 是否是函数名称时出错。

无法重新加载 'D:\Program Files\MATLAB\R2018a\bin\win64\sl_graphical_classes.dll'

求解决办法。

%% 源程序————————————————————————————

clc

clear varaibles

close all

%%

digitDatasetPath = fullfile(matlabroot,'toolbox','nnet','nndemos', ...

'nndatasets','DigitDataset');%图片所在文件夹

imds = imageDatastore(digitDatasetPath, ...

'IncludeSubfolders',true,'LabelSource','foldernames');

%%

figure;

perm = randperm(10000,20);

for i = 1:20

subplot(4,5,i);

imshow(imds.Files{perm(i)});

end

%%

labelCount = countEachLabel(imds);

%%

img = readimage(imds,1);

size(img)

%% Divide the data into training and validation data sets

numTrainFiles = 750;

[imdsTrain,imdsValidation] = splitEachLabel(imds,numTrainFiles,'randomize');

%% Define Network Architecture

layers = [

imageInputLayer([28 28 1])

convolution2dLayer(3,8,'Padding',1)

batchNormalizationLayer

reluLayer

maxPooling2dLayer(2,'Stride',2)

convolution2dLayer(3,16,'Padding',1)

batchNormalizationLayer

reluLayer

maxPooling2dLayer(2,'Stride',2)

convolution2dLayer(3,32,'Padding',1)

batchNormalizationLayer

reluLayer

fullyConnectedLayer(10)

softmaxLayer

classificationLayer];

%% Specify Training Options

options = trainingOptions('sgdm', ...

'MaxEpochs',4, ...

'ValidationData',imdsValidation, ...

'ValidationFrequency',30, ...

'Verbose',false, ...

'Plots','training-progress');

%% Train Network Using Training Data

net = trainNetwork(imdsTrain,layers,options);

%% Classify Validation Images and Compute Accuracy

YPred = classify(net,imdsValidation);

YValidation = imdsValidation.Labels;

accuracy = sum(YPred == YValidation)/numel(YValidation);