[bug?]Deep​LearningIm​ageClassif​icationExa​mple not getting the expected classification accuracy

2016 9 16
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更新时间：2018 3 5
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Hello, I've running the DeepLearningImageClassificationExample from MATLAB.
http://uk.mathworks.com/help/vision/examples/image-category-classification-using-deep-learning.html
Unfortunately I keep getting unexpected classification accuracy. On the website the mean accuracy suppose to be 1 however the result I got was 0.3.
confMat =
0 1.0000 0
0 1.0000 0
0.0213 0.9787 0
ans =
0.3333
label =
airplanes
I noticed for some reason the trainingFeatures are the same for all the images, after the following line:
trainingFeatures = activations(convnet, trainingSet, featureLayer, ... 'MiniBatchSize', 32, 'OutputAs', 'columns');
I'm using MATLAB 2016a and I have cuda GPU. Can someone please help to test on your machine seee if you also have the problem? Thanks a lot

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Joss Knight
Joss Knight 2016-9-19

0 个投票

Do you have a new Pascal GPU like the GeForce GTX 1080? If so, this is your issue:
https://www.mathworks.com/support/bugreports/details/1439741
I do apologise for this. We are waiting on a fix from NVIDIA.

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khcy82dyc
khcy82dyc 2016-9-19
Yes i do! I've then tried the function on my laptop with the 980m and it worked! Thx for letting me know :)
Akash Maity
Akash Maity 2017-1-18
Even after installing the patch, I am getting the following error while trying to run CNN classification:
Error using nnet.internal.cnngpu.convolveForward2D Unexpected error calling cuDNN: CUDNN_STATUS_BAD_PARAM. 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 SeriesNetwork/predict (line 139) Y(:,:,:,i) = predictNetwork.predict(X);
Is there anything that needs to be done other than installing the patch?
Joss Knight
Joss Knight 2017-1-18
Hi. I ran the entire demo on a GTX 1080 in MATLAB R2016b and got no errors. Can you describe your environment in a bit more detail? What version of MATLAB, what OS, what GPU, what are the reproduction steps? It may simply be that you have an invalid network that you trained before you installed the patch, perhaps?
Hossam Elshahaby
Hossam Elshahaby 2018-3-3
编辑：Hossam Elshahaby 2018-3-3
I have same problem after replacing the file cudnn64_70.dll inside the bin folder. I have Windows 10 , Matlab 2016 a , NVIDIA GEFORCE GTX , I re-trained the following net after I had replaced the file:
layers = [ imageInputLayer([40 200 1]) convolution2dLayer(10 , 96 , 'Stride',2,'Padding',0) reluLayer
maxPooling2dLayer(2,'Stride',2)
convolution2dLayer(3,256, 'Stride',1,'Padding',1)
reluLayer
maxPooling2dLayer(2,'Stride',2)
convolution2dLayer(3,384, 'Stride',1,'Padding',1)
reluLayer
convolution2dLayer(3,384, 'Stride',1,'Padding',1)
reluLayer
convolution2dLayer(3,256, 'Stride',1,'Padding',1)
reluLayer
maxPooling2dLayer(2,'Stride',2)
fullyConnectedLayer(1024)
fullyConnectedLayer(2)
softmaxLayer
classificationLayer
];
khcy82dyc
khcy82dyc 2018-3-5
coming back to this question I'd say the best answer is to upgrade matlab...

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