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<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.0//ENhttp://www.w3.org/TR/REC-html40/strict.dtd"><html><head><meta name="qrichtext" content="1" /><style type="text/css">p, li { white-space: pre-wrap; }</style></head><body style=" font-family:'Sans Serif'; font-size:9pt; font-weight:400; font-style:normal;"></style></head><body style=" font-family:'Sans Serif'; font-size:9pt; font-weight:400; font-style:normal;"><p align="center" style=" margin-top:16px; margin-bottom:12px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px; font-size:x-large; font-weight:600;"><span style=" font-size:x-large;">Image SVM Classification</span></p><p style=" margin-top:14px; margin-bottom:12px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px; font-size:large; font-weight:600;"><span style=" font-size:large;">Brief Description</span></p><p style=" margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;">Performs a SVM classification of the input image according to a SVM model file.</p><p style=" margin-top:14px; margin-bottom:12px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px; font-size:large; font-weight:600;"><span style=" font-size:large;">Tags</span></p><p style=" margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;">Learning</p><p style=" margin-top:14px; margin-bottom:12px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px; font-size:large; font-weight:600;"><span style=" font-size:large;">Long Description</span></p><p style=" margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;">This application performs a SVM image classification based on a SVM model file (*.svm extension) produced by the TrainSVMImagesClassifier application. Pixels of the output image will contain the class label decided by the SVM classifier. The input pixels can be optionnaly 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.</p><p style=" margin-top:14px; margin-bottom:12px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px; font-size:large; font-weight:600;"><span style=" font-size:large;">Parameters</span></p><ul><li><p style=" margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;"><span style=" font-family:'Courier New, courier'; font-weight:600;"; >[param] Input Image (-in): </span>The input Image to classify.</p></li><li><p style=" margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;"><span style=" font-family:'Courier New, courier'; font-weight:600;"; >[param] Input Mask (-mask): </span>The mask allows to restrict classification of the input image to the area where mask pixel values are greater than 0.</p></li><li><p style=" margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;"><span style=" font-family:'Courier New, courier'; font-weight:600;"; >[param] SVM Model file (-svm): </span>A SVM model file.</p></li><li><p style=" margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;"><span style=" font-family:'Courier New, courier'; font-weight:600;"; >[param] Statistics file (-imstat): </span>A XML file containing mean and standard deviation to center and reduce samples before classification.</p></li><li><p style=" margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;"><span style=" font-family:'Courier New, courier'; font-weight:600;"; >[param] Output Image (-out): </span>Output image labeled with class labels</p></li><li><p style=" margin-top:0px; margin-bottom:0px; mar
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