Classify requires at least 3 arguments

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Raphael Ruschel
Raphael Ruschel 2018-11-1
评论： Walter Roberson 2023-8-2
Hi,
I am having trouble when trying to use the "classify" function to evaluate the performance of my neural network.
I am using the following code:
net = load('mynet.mat'); %this returns my previsouly trained SeriesNetwork object
test_folder = './test_data';
test_images = imageDatastore(test_folder,'FileExtensions','.jpg');
[Y,scores] = classify(net,test_images);
But the classify function throws me an error that it requires at least 3 arguments, which means it is trying to use the classify function from the statistics package.
What can I make do force the use of the classify from the deep learning package?
Thanks,
Raphael

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Walter Roberson
Walter Roberson 2018-11-1
编辑：Walter Roberson 2018-11-5
net = load('mynet.mat'); %this returns my previsouly trained SeriesNetwork object
Not exactly. The output of load applied to a mat file, is a struct that has one field for each variable loaded. So you would need net.net where the first net is the struct returned from load and the second is the variable loaded.
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Moh. Saadat
Moh. Saadat 2023-8-2
Hi Walter,
I was trying to figure out whether using the layerGraph() function on a DAGNetwork (trained model) removes the trained weights. So I loaded my trained model which is a DAGNetwork:
load(RESTORE_CKPT); % RESTORE_CKPT is the full path to the mat file containing my trained network
Then, I used layerGraph() function to convert the DAGNetwork to a layer graph:
net = layerGraph(net);
But then, I use classify to infer the results, it throws me this 'requires at least 3 arguments' error:
[pred,score] = classify(net,data); % data is a cell array
Does this mean the weights have been removed from net?

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更多回答（4 个）

Walter Roberson
Walter Roberson 2020-6-2
编辑：Walter Roberson 2020-12-6
There are multiple functions named classify()
Most of the classify() routines are methods of particular data type, and will only be considered to be invoked if the first input argument is an object of the proper data type.
The only classify() that accepts general input arguments (rather than objects) is classify() from the Statistics and Machine Learning Toolbox. That classify() happens to require at least 3 input arguments, so if you get an unexpected error message about classify requiring at least three input arguments, then you have accidentally invoked the classify() from the Statistics and Machine Learning Toolbox, and the cause of the problem is that your first parameter is not a proper member of the datatype that your desired function acts upon.
For example you might have accidentally provided the name of a dataset (as a character vector), or you might have accidentally provided a datastore, or you might have accidentally provided a description of a deep learning network instead of a trained instance of the network.
classify() can be used with:
classify() is not the correct function for some other cases:
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Yushan Zhang
Yushan Zhang 2022-11-17
Hi Walter,
Thanks for your quick support.
trained_net is a DAGNetwork.
I am trying to combine my Matlab codes with Labview. At first, I tired to use NET.dll. However, compiler sdk needs to be paid extra. Then, I am trying standalone application and now I have this problem. I have codes for object detection using yolov4 and image classification, they all have similar probelms when compiling the application.
Walter Roberson
Walter Roberson 2022-11-17
Try
%#function DAGNetwork
as a comment in your code. The compiler will recognize it and know to include the DAGNetwork class.

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Alaa ElDin ElHilaly
I face the same problem. would you please elaborate more about your suggested solution. I have trained the network and keeps giving me (required at least 3 arguments)
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Walter Roberson
Walter Roberson 2019-1-22
When you load() a .mat file and you assign to output, the output is not directly any of the variables saved in the .mat file. Instead the output is a struct with one field for each variable loaded from the .mat file. For example if the .mat file contained the variables 'puppy' and 'butterfly', then
net = load('mynet.mat');
is not going to directly store puppy or butterfly in net, and it is not going to store into variables named puppy and butterfly in the environment of the function. Instead net would become a struct with fields named puppy and butterfly and net.puppy would hold whatever was in the puppy variable in mynet.mat
You are probably accidentally invoking https://www.mathworks.com/help/stats/classify.html instead of https://www.mathworks.com/help/deeplearning/ref/classify.html
Muhammad Suri
Muhammad Suri 2020-9-28
yes I am accidentally invoking stats/classify vs ref/classify. How can I change that. Thanks

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hana razak
hana razak 2019-2-19
Hi,
Me too. I've got same ERROR when using webcam to classify the fast RCNN
camera = videoinput('winvideo', 2, 'MJPG_1024x576');
net = load('detector200.mat');
while true
picture = getsnapshot(camera);
picture = imresize(picture,[150,150]);
label = classify(net, picture);
image(picture);
title(char(label));
drawnow;
end
Here are the errors,
Error using classify (line 123)
Requires at least three arguments.
Error in webcam_object_classification (line 7)
label = classify(net, picture);
I've tried net.net as suggested in command window and it showed this,
>> net.detector200
ans =
fasterRCNNObjectDetector with properties:
ModelName: 'normal'
Network: [1×1 vision.cnn.FastRCNN]
RegionProposalNetwork: [1×1 vision.cnn.RegionProposalNetwork]
MinBoxSizes: [39 30]
BoxPyramidScale: 1.2000
NumBoxPyramidLevels: 14
ClassNames: {'normal' 'abnormal' 'Background'}
MinObjectSize: [18 18]
BUT I don't know how to use it in the code.
Any help would be greatly appreciated.
Thank you so much
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hana razak
hana razak 2019-2-20
It didn't work. I got the same error.
Is there any other solution?
Thank you

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Kinjal Joshi
Kinjal Joshi 2019-12-19
net=patternnet(10);
[net,tr]=train(net,trainoflow,op);
[ypred,scores]=classify(net,testoflow);
The above code give me error at classify function that Requires atleast three arguments. trainoflow is training features,testoflow is testdata features and op is train data labels.
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Walter Roberson
Walter Roberson 2019-12-19
patternnet() does not support a classify() function. To invoke the network on testoflow, use it by name:
ypred = net(testoflow);
to get scores, you might want to use perform()

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