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80 lines
2.9 KiB
XML
80 lines
2.9 KiB
XML
<root>
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<key>KMeansClassification</key>
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<exec>otbcli_KMeansClassification</exec>
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<longname>Unsupervised KMeans image classification</longname>
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<group>Learning</group>
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<description>Unsupervised KMeans image classification</description>
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<parameter>
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<parameter_type source_parameter_type="ParameterType_InputImage">ParameterRaster</parameter_type>
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<key>in</key>
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<name>Input Image</name>
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<description>Input image to classify.</description>
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<optional>False</optional>
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</parameter>
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<parameter>
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<parameter_type source_parameter_type="ParameterType_OutputImage">OutputRaster</parameter_type>
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<key>out</key>
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<name>Output Image</name>
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<description>Output image containing the class indexes.</description>
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<hidden />
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</parameter>
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<parameter>
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<parameter_type source_parameter_type="ParameterType_RAM">ParameterNumber</parameter_type>
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<key>ram</key>
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<name>Available RAM (Mb)</name>
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<description>Available memory for processing (in MB)</description>
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<minValue />
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<maxValue />
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<default>128</default>
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</parameter>
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<parameter>
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<parameter_type source_parameter_type="ParameterType_InputImage">ParameterRaster</parameter_type>
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<key>vm</key>
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<name>Validity Mask</name>
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<description>Validity mask. Only non-zero pixels will be used to estimate KMeans modes.</description>
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<optional>True</optional>
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</parameter>
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<parameter>
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<parameter_type source_parameter_type="ParameterType_Int">ParameterNumber</parameter_type>
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<key>ts</key>
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<name>Training set size</name>
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<description>Size of the training set (in pixels).</description>
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<minValue />
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<maxValue />
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<default>100</default>
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</parameter>
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<parameter>
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<parameter_type source_parameter_type="ParameterType_Int">ParameterNumber</parameter_type>
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<key>nc</key>
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<name>Number of classes</name>
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<description>Number of modes, which will be used to generate class membership.</description>
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<minValue />
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<maxValue />
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<default>5</default>
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</parameter>
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<parameter>
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<parameter_type source_parameter_type="ParameterType_Int">ParameterNumber</parameter_type>
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<key>maxit</key>
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<name>Maximum number of iterations</name>
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<description>Maximum number of iterations for the learning step.</description>
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<minValue />
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<maxValue />
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<default>1000</default>
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</parameter>
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<parameter>
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<parameter_type source_parameter_type="ParameterType_Float">ParameterNumber</parameter_type>
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<key>ct</key>
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<name>Convergence threshold</name>
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<description>Convergence threshold for class centroid (L2 distance, by default 0.0001).</description>
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<minValue />
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<maxValue />
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<default>0.0001</default>
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</parameter>
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<parameter>
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<parameter_type source_parameter_type="ParameterType_OutputFilename">OutputFile</parameter_type>
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<key>outmeans</key>
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<name>Centroid filename</name>
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<description>Output text file containing centroid positions</description>
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</parameter>
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</root>
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