Image Retrieval Based on Semantic Features
Content-based image retrieval consists of finding images from a dataset that are most similar to a query image. Using FeatureExtraction, you can assess the similarity among images of world landmarks.
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"], {{0, 48}, {75, 0}}, {0, 255},
ColorFunction->RGBColor],
BoxForm`ImageTag[
"Byte", ColorSpace -> "RGB", Interleaving -> True,
Magnification -> 0.5],
Selectable->False],
DefaultBaseStyle->"ImageGraphics",
ImageSize->Magnification[0.5],
ImageSizeRaw->{75, 48},
PlotRange->{{0, 75}, {0, 48}}]\)};
Build a semantic feature extractor for this dataset.
In[2]:=
fe = FeatureExtraction[trainingset, "ImageFeatures"]
Out[2]=
Retrieving an image amounts to looking up the training images with the nearest descriptors.
In[3]:=
nf = Nearest[fe[trainingset] -> Automatic];
ImageRetrieve[query_, topmost_: 1] :=
Image[#, Magnification -> 1] & /@
trainingset[[nf[fe[query], topmost]]];
Retrieve the top 4 images for different query images.
In[4]:=
Table[{Image[i, Magnification -> 1] ->
Row[ImageRetrieve[i, 4], " "]}, {i, {\!\(\*
GraphicsBox[
TagBox[RasterBox[CompressedData["
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ColorFunction->RGBColor],
BoxForm`ImageTag[
"Byte", ColorSpace -> "RGB", Interleaving -> True,
Magnification -> Rational[1, 2]],
Selectable->False],
DefaultBaseStyle->"ImageGraphics",
ImageSize->Magnification[0.5],
ImageSizeRaw->{75, 57},
PlotRange->{{0, 75}, {0, 57}}]\)}}] // Grid
Out[4]=