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I 500 pictures of tables and chairs each (849x849) and want to train a convolutional neural net to classify new pictures accordingly. This is my code so far: 

cfiles = Import["D:\\Mathematica11\\bo_sample\\chairs\\*"];
tfiles = Import["D:\\Mathematica11\\bo_sample\\tables\\*"];

$train = 300;
trainingData = Join[
 Thread[cfiles[[;; $train]] -> "chairs"],
 Thread[tfiles[[;; $train]] -> "tables"]
 ];
testingData = Join[
  Thread[cfiles[[$train + 1 ;;]] -> "chairs"] ,
  Thread[tfiles[[$train + 1 ;;]] -> "tables"]
  ];

lenet = NetChain[{ConvolutionLayer[20, 5], 
              Ramp, 
              PoolingLayer[2, 2], 
              ConvolutionLayer[50, 5], 
              Ramp, 
              PoolingLayer[2, 2], 
              FlattenLayer[],
              500, 
              Ramp, 
              2, 
              SoftmaxLayer[]}, 
              "Output" -> NetDecoder[{"Class", Range[0, 1]}], 
              "Input" -> NetEncoder[{"Image", {849, 849}, "RGB"}]];


trainedNN =  NetTrain[lenet, trainingData, ValidationSet -> testingData,  MaxTrainingRounds -> 3];

...Failure GPU Memory exhausted

It seems the usage of NetTrain is not correct in both cases but the error-messages are not clear to me. Can someone take a look please?

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6
  • $\begingroup$ Probably you need to NetInitialize your graph first. $\endgroup$
    – swish
    Commented Jan 18, 2017 at 17:49
  • $\begingroup$ Hi. I tried initNN = NetInitialize[lenet] but I get the same error-message with trainedNN. $\endgroup$
    – user3483676
    Commented Jan 18, 2017 at 18:02
  • $\begingroup$ RandomSample doesn't work as you expect there, fix it first. $\endgroup$
    – swish
    Commented Jan 18, 2017 at 18:08
  • $\begingroup$ I deleted the first NetTrain segment (lenet = NetTrain[lenet, RandomSample.... which produced the first error message. This was just a different approach which did not work. Actually I would prefer the second approach with trainedNN = NetTrain... to work. $\endgroup$
    – user3483676
    Commented Jan 18, 2017 at 18:13
  • $\begingroup$ Reverse the arrows in your Association, outputs should be on the right. $\endgroup$
    – swish
    Commented Jan 18, 2017 at 18:23

1 Answer 1

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5
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  1. Make proper data format as list of rules $(Image \rightarrow Class)$

    trainingData = Join[
    Thread[cfiles[[;; $train]] -> "chairs"],
    Thread[tfiles[[;; $train]] -> "tables"]
];
testingData = Join[
    Thread[cfiles[[$train + 1 ;;]] -> "chairs"] ,
    Thread[tfiles[[$train + 1 ;;]] -> "tables"]
];

  2. NetDecoder should look like this

    NetDecoder[{"Class", {"chairs", "tables"}}]

This works for me:

cfiles = Array[RandomImage[1, {100, 100}] &, {100}, 
   ColorSpace -> "RGB"];
tfiles = Array[RandomImage[1, {100, 100}] &, {100}, 
   ColorSpace -> "RGB"];

$train = 80;
trainingData = Join[
   Thread[cfiles[[;; $train]] -> "chairs"],
   Thread[tfiles[[;; $train]] -> "tables"]
   ];
testingData = Join[
   Thread[cfiles[[$train + 1 ;;]] -> "chairs"] ,
   Thread[tfiles[[$train + 1 ;;]] -> "tables"]
   ];
lenet = NetChain[{ConvolutionLayer[20, 5], Ramp, PoolingLayer[2, 2], 
    ConvolutionLayer[50, 5], Ramp, PoolingLayer[2, 2], FlattenLayer[],
     500, Ramp, 2, SoftmaxLayer[]}, 
   "Output" -> NetDecoder[{"Class", {"chairs", "tables"}}], 
   "Input" -> NetEncoder[{"Image", {100, 100}, "RGB"}]];
trainedNN = 
 NetTrain[lenet, trainingData, ValidationSet -> testingData, 
  MaxTrainingRounds -> 3]
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3
  • $\begingroup$ I tried your code but still get the same error. $\endgroup$
    – user3483676
    Commented Jan 18, 2017 at 19:06
  • $\begingroup$ I tried your code. It works but if I use it on my imported pictures I get error-message GPU memory exhausted. I probably have to resize them because your trainingset is smaller and also the size of the random images. $\endgroup$
    – user3483676
    Commented Jan 19, 2017 at 4:32
  • $\begingroup$ Ok. The training is now running. Thx for the support. $\endgroup$
    – user3483676
    Commented Jan 19, 2017 at 16:14

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