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2014-01-17 19:39:17 +01:00
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</head><body><h1>ImageClassifier</h1><h2>Brief Description</h2>Performs a classification of the input image according to a model file.<h2>Tags</h2>Learning<h2>Long Description</h2>This application performs an image classification based on a model file produced by the TrainImagesClassifier application. Pixels of the output image will contain the class labels decided by the classifier (maximal class label = 65535). The input pixels can be optionally centered and reduced according to the statistics file produced by the ComputeImagesStatistics application. An optional input mask can be provided, in which case only input image pixels whose corresponding mask value is greater than 0 will be classified. The remaining of pixels will be given the label 0 in the output image.<h2>Parameters</h2><ul><li><b>[param] -in</b> &lt;string&gt; The input image to classify.. Mandatory: True. Default Value: &quot;&quot;</li><li><b>[param] -mask</b> &lt;string&gt; The mask allows restricting classification of the input image to the area where mask pixel values are greater than 0.. Mandatory: False. Default Value: &quot;&quot;</li><li><b>[param] -model</b> &lt;string&gt; A model file (produced by TrainImagesClassifier application, maximal class label = 65535).. Mandatory: True. Default Value: &quot;&quot;</li><li><b>[param] -imstat</b> &lt;string&gt; A XML file containing mean and standard deviation to center and reduce samples before classification (produced by ComputeImagesStatistics application).. Mandatory: False. Default Value: &quot;&quot;</li><li><b>[param] -out</b> &lt;string&gt; Output image containing class labels. Mandatory: True. Default Value: &quot;&quot;</li><li><b>[param] -ram</b> &lt;int32&gt; Available memory for processing (in MB). Mandatory: False. Default Value: &quot;128&quot;</li></ul><h2>Limitations</h2>The input image must have the same type, order and number of bands than the images used to produce the statistics file and the SVM model file. If a statistics file was used during training by the TrainImagesClassifier, it is mandatory to use the same statistics file for classification. If an input mask is used, its size must match the input image size.<h2>Authors</h2>OTB-Team<h2>See Also</h2>TrainImagesClassifier, ValidateImagesClassifier, ComputeImagesStatistics<h2>Example of use</h2><ul><li><p style=" margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;">in: QB_1_ortho.tif</p></li><li><p style=" margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;">imstat: EstimateImageStatisticsQB1.xml</p></li><li><p style=" margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;">model: clsvmModelQB1.svm</p></li><li><p style=" margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;">out: clLabeledImageQB1.tif</p></li></ul></body></html>