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I was using CNN3D model. But its total uncelar how the data should be loaded for network to train.

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Sujit Roy
Sujit Roy on 23 Sep 2019
Commented: Binu on 30 Oct 2019
I was using CNN3D model. But its total uncelar how the data should be loaded for network to train. It can either be table, or array. My image size is 22x198x153x3 and i have 100 sample. another way of looking at it is i have 22 3d matrices stacked over other.
I converted it to struct2table of 100 rows, not working, it says too many arguments.
Please advise how to load data for training in cnn3d.

  2 Comments

Sujit Roy
Sujit Roy on 25 Sep 2019
ok.
I have 100 mat data file named like tube001.mat which has dimension of 22x198x153x3, where 22 is the depth 196 is the length and 153 is width and 3 is for rgb.
So I loaded them all in traindata which is now of size 1x100 struct; 100 representing the number of file. then i converted them to table as network requirement by struct2table(traindata).
similarly I have labels if 1x100 double which is converted to categorical.
for cnn training
image3dInputLayer(size(traindata.tube{1,1}))
and then when i run
net = trainNetwork(traindata, categorical(labels),layers,options);
error @@@@
Error using trainNetwork (line 165)
Too many input arguments.
Caused by:
Error using trainNetwork>iParseInputArguments (line 290)
Too many input arguments.
@@@@

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Answers (1)

Shivam Sardana
Shivam Sardana on 27 Sep 2019
You can use imageDatastore to store image data.

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