Out-of-Core Image Classification
Train a network to distinguish the digits 1 from 2, and only load small batches of images into memory from disk at a time.
Download a set of images and unzip them.
In[1]:=
zip = URLDownload["https://wolfr.am/ebyHmnkR", "characters12.zip"];
dir = CreateDirectory[];
ExtractArchive[First @ zip, dir] // LengthOut[1]=
Obtain the image file paths and obtain the classes from the folder names.
In[2]:=
loadFiles[dir_] :=
Map[File[#] -> FileNameTake[#, {-2}] &,
FileNames["*.jpg", dir, Infinity]];
trainingData = loadFiles[FileNameJoin[{dir, "characters", "train"}]];
testData = loadFiles[FileNameJoin[{dir, "characters", "test"}]];The training data is a list of rules from File objects to classes.
In[3]:=
RandomSample[trainingData, 3]Out[3]=
Define a simple network.
In[4]:=
net = NetChain[
{FlattenLayer[], DotPlusLayer[2], SoftmaxLayer[]},
"Output" -> NetDecoder[{"Class", {"1", "2"}}],
"Input" -> NetEncoder[{"Image", {28, 28}, "Grayscale"}]
]Out[4]=
Train the network.
In[5]:=
trained =
NetTrain[net, trainingData, ValidationSet -> testData,
MaxTrainingRounds -> 600, BatchSize -> 64]Out[6]=
Classify images directly from file paths.
In[7]:=
ims = Keys@RandomSample[testData, 3]
trained /@ imsOut[7]=
Out[7]=
Or evaluate directly on an image and obtain the classification probabilities.
In[8]:=
trained[\!\(\*
GraphicsBox[
TagBox[RasterBox[CompressedData["
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"], {{0, 28}, {
28, 0}}, {0, 255},
ColorFunction->RGBColor],
BoxForm`ImageTag["Byte", ColorSpace -> "RGB", Interleaving -> True],
Selectable->False],
DefaultBaseStyle->"ImageGraphics",
ImageSize->Automatic,
ImageSizeRaw->{28, 28},
PlotRange->{{0, 28}, {0, 28}}]\), "Probabilities"]Out[8]=
