diff --git a/python/plugins/processing/otb/OTBAlgorithm.py b/python/plugins/processing/otb/OTBAlgorithm.py index 40afaabc8545..45b8fb70ecf2 100644 --- a/python/plugins/processing/otb/OTBAlgorithm.py +++ b/python/plugins/processing/otb/OTBAlgorithm.py @@ -6,7 +6,13 @@ --------------------- Date : August 2012 Copyright : (C) 2012 by Victor Olaya + (C) 2013 by CS Systemes d'information (CS SI) Email : volayaf at gmail dot com + otb at c-s dot fr (CS SI) + Contributors : Victor Olaya + Julien Malik (CS SI) - Changing the way to load algorithms first version + Oscar Picas (CS SI) - Changing the way to load algorithms + Alexia Mondot (CS SI) - Add hdf5 support *************************************************************************** * * * This program is free software; you can redistribute it and/or modify * @@ -20,37 +26,33 @@ __author__ = 'Victor Olaya' __date__ = 'August 2012' __copyright__ = '(C) 2012, Victor Olaya' - # This will get replaced with a git SHA1 when you do a git archive - __revision__ = '$Format:%H$' import os -from qgis.core import * -from PyQt4.QtCore import * -from PyQt4.QtGui import * - +import re +import PyQt4.QtGui from processing.core.GeoAlgorithm import GeoAlgorithm -from processing.core.GeoAlgorithmExecutionException import \ - GeoAlgorithmExecutionException -from processing.core.WrongHelpFileException import WrongHelpFileException -from processing.core.ProcessingLog import ProcessingLog from processing.parameters.ParameterMultipleInput import ParameterMultipleInput from processing.parameters.ParameterRaster import ParameterRaster from processing.parameters.ParameterVector import ParameterVector from processing.parameters.ParameterBoolean import ParameterBoolean from processing.parameters.ParameterSelection import ParameterSelection -from processing.parameters.ParameterExtent import ParameterExtent +from processing.core.GeoAlgorithmExecutionException import GeoAlgorithmExecutionException +from processing.core.ProcessingLog import ProcessingLog +from processing.core.ProcessingUtils import ProcessingUtils +from processing.core.WrongHelpFileException import WrongHelpFileException from processing.parameters.ParameterFactory import ParameterFactory from processing.outputs.OutputFactory import OutputFactory -from processing.tools.system import * - from processing.otb.OTBUtils import OTBUtils - +from processing.parameters.ParameterExtent import ParameterExtent +import xml.etree.ElementTree as ET +import traceback +import inspect class OTBAlgorithm(GeoAlgorithm): - REGION_OF_INTEREST = 'ROI' + REGION_OF_INTEREST = "ROI" def __init__(self, descriptionfile): GeoAlgorithm.__init__(self) @@ -58,7 +60,11 @@ def __init__(self, descriptionfile): self.descriptionFile = descriptionfile self.defineCharacteristicsFromFile() self.numExportedLayers = 0 - self.hasROI = None + self.hasROI = None; + + + def __str__(self): + return( "Algo : " + self.name + " from app : " + self.cliName + " in : " + self.group ) def getCopy(self): newone = OTBAlgorithm(self.descriptionFile) @@ -66,74 +72,109 @@ def getCopy(self): return newone def getIcon(self): - return QIcon(os.path.dirname(__file__) + '/../images/otb.png') + return PyQt4.QtGui.QIcon(os.path.dirname(__file__) + "/../images/otb.png") def helpFile(self): - folder = os.path.join(OTBUtils.otbDescriptionPath(), 'doc') - helpfile = os.path.join(str(folder), self.appkey + '.html') + folder = os.path.join( OTBUtils.otbDescriptionPath(), 'doc' ) + helpfile = os.path.join( str(folder), self.appkey + ".html") if os.path.exists(helpfile): return helpfile else: - raise WrongHelpFileException( - 'Could not find help file for this algorithm. If you \ - have it put it in: ' + str(folder)) + raise WrongHelpFileException("Could not find help file for this algorithm. \nIf you have it put it in: \n"+str(folder)) + + + def adapt_list_to_string(self, c_list): + a_list = c_list[1:] + if a_list[0] in ["ParameterVector", "ParameterMultipleInput"]: + if c_list[0] == "ParameterType_InputImageList": + a_list[3] = 3 + else: + a_list[3] = -1 + + a_list[1] = "-%s" % a_list[1] + def mystr(par): + if type(par) == type([]): + return ";".join(par) + return str(par) + b_list = map(mystr, a_list) + res = "|".join(b_list) + return res + + def get_list_from_node(self, myet): + all_params = [] + for parameter in myet.iter('parameter'): + rebuild = [] + par_type = parameter.find('parameter_type').text + key = parameter.find('key').text + name = parameter.find('name').text + source_par_type = parameter.find('parameter_type').attrib['source_parameter_type'] + rebuild.append(source_par_type) + rebuild.append(par_type) + rebuild.append(key) + rebuild.append(name) + for each in parameter[4:]: + if not each.tag in ["hidden"]: + if len(each.getchildren()) == 0: + rebuild.append(each.text) + else: + rebuild.append([item.text for item in each.iter('choice')]) + all_params.append(rebuild) + return all_params + def defineCharacteristicsFromFile(self): - lines = open(self.descriptionFile) - line = lines.readline().strip('\n').strip() - self.appkey = line - line = lines.readline().strip('\n').strip() - self.cliName = line - line = lines.readline().strip('\n').strip() - self.name = line - line = lines.readline().strip('\n').strip() - self.group = line - while line != '': + content = open(self.descriptionFile).read() + dom_model = ET.fromstring(content) + + self.appkey = dom_model.find('key').text + self.cliName = dom_model.find('exec').text + self.name = dom_model.find('longname').text + self.group = dom_model.find('group').text + + ProcessingLog.addToLog(ProcessingLog.LOG_ERROR, "Reading parameters... for %s" % self.appkey) + + rebu = None + the_result = None + + try: + rebu = self.get_list_from_node(dom_model) + the_result = map(self.adapt_list_to_string,rebu) + except Exception, e: + ProcessingLog.addToLog(ProcessingLog.LOG_ERROR, "Could not open OTB algorithm: " + self.descriptionFile + "\n" + traceback.format_exc()) + raise e + + for line in the_result: try: - line = line.strip('\n').strip() - if line.startswith('Parameter'): + if line.startswith("Parameter"): param = ParameterFactory.getFromString(line) - # Hack for initializing the elevation parameters - # from Processing configuration - if param.name == '-elev.dem.path' or param.name \ - == '-elev.dem': + # Hack for initializing the elevation parameters from Processing configuration + if param.name == "-elev.dem.path" or param.name == "-elev.dem" or "elev.dem" in param.name: param.default = OTBUtils.otbSRTMPath() - elif param.name == '-elev.dem.geoid' or param.name \ - == '-elev.geoid': + elif param.name == "-elev.dem.geoid" or param.name == "-elev.geoid" or "elev.geoid" in param.name: param.default = OTBUtils.otbGeoidPath() self.addParameter(param) - elif line.startswith('*Parameter'): + elif line.startswith("*Parameter"): param = ParameterFactory.getFromString(line[1:]) param.isAdvanced = True self.addParameter(param) - elif line.startswith('Extent'): - self.addParameter(ParameterExtent(self.REGION_OF_INTEREST, - 'Region of interest', '0,1,0,1')) + elif line.startswith("Extent"): + self.addParameter(ParameterExtent(self.REGION_OF_INTEREST, "Region of interest", "0,1,0,1")) self.hasROI = True else: self.addOutput(OutputFactory.getFromString(line)) - line = lines.readline().strip('\n').strip() - except Exception, e: - ProcessingLog.addToLog(ProcessingLog.LOG_ERROR, - 'Could not open OTB algorithm: ' - + self.descriptionFile + '\n' + line) + except Exception,e: + ProcessingLog.addToLog(ProcessingLog.LOG_ERROR, "Could not open OTB algorithm: " + self.descriptionFile + "\n" + line) raise e - lines.close() - def checkBeforeOpeningParametersDialog(self): - path = OTBUtils.otbPath() - libpath = OTBUtils.otbLibPath() - if path == '' or libpath == '': - return 'OTB folder is not configured.\nPlease configure it \ - before running OTB algorithms.' + def processAlgorithm(self, progress): + currentOs = os.name + path = OTBUtils.otbPath() libpath = OTBUtils.otbLibPath() - if path == '' or libpath == '': - raise GeoAlgorithmExecutionException( - 'OTB folder is not configured.\nPlease configure it \ - before running OTB algorithms.') + if path == "" or libpath == "": + raise GeoAlgorithmExecutionException("OTB folder is not configured.\nPlease configure it before running OTB algorithms.") commands = [] commands.append(path + os.sep + self.cliName) @@ -141,28 +182,91 @@ def processAlgorithm(self, progress): self.roiVectors = {} self.roiRasters = {} for param in self.parameters: - if param.value is None or param.value == '': + # get the given input(s) + if param.name in ["-il", "-in"] : + newparams = "" + listeParameters = param.value.split(";") + for inputParameter in listeParameters : + # if HDF5 file + if "HDF5" in inputParameter : + if currentOs == "posix" : + data = inputParameter[6:] + else : + data = inputParameter[5:] + dataset = data + + #on windows, there isn't " + #if data[-1] == '"': + if currentOs == "posix" : + data = data[:data.index('"')] + else : + data = data[:data.index('://')] + #try : + if currentOs == "posix" : + dataset.index('"') + dataset = os.path.basename( data ) + dataset[dataset.index('"'):] + #except ValueError : + else : + #dataset = os.path.basename( data ) + '"' + dataset[dataset.index('://'):] + dataset = dataset[dataset.index('://'):] + + #get index of the subdataset with gdal + if currentOs == "posix" : + commandgdal = "gdalinfo " + data + " | grep '" + dataset + "$'" + else : + commandgdal = "gdalinfo " + data + " | findstr \"" + dataset + "$\"" + resultGDAL = os.popen( commandgdal ).readlines() + indexSubdataset = -1 + if resultGDAL : + indexSubdatasetString = re.search("SUBDATASET_(\d+)_", resultGDAL[0]) + if indexSubdatasetString : + #match between () + indexSubdataset = indexSubdatasetString.group(1) + else : + indexSubdataset = -1 + else : + print "Error : no match of ", dataset, "$ in gdalinfo " + data + indexSubdataset = -1 + + + if not indexSubdataset == -1 : + indexSubdataset = int(indexSubdataset) -1 + newParam = "\'" + data + "?&sdataidx=" + str(indexSubdataset) + "\'" + + else : + newParam = inputParameter + + newparams += newParam + # no hdf5 + else : + newparams += inputParameter + newparams += ";" + if newparams[-1] == ";": + newparams = newparams[:-1] + param.value = newparams + + if param.value == None or param.value == "": continue if isinstance(param, ParameterVector): commands.append(param.name) if self.hasROI: - roiFile = getTempFilename('shp') + roiFile = ProcessingUtils.getTempFilename('shp') commands.append(roiFile) self.roiVectors[param.value] = roiFile else: - commands.append('"' + param.value + '"') + commands.append("\"" + param.value+ "\"") elif isinstance(param, ParameterRaster): commands.append(param.name) if self.hasROI: - roiFile = getTempFilename('tif') + roiFile = ProcessingUtils.getTempFilename('tif') commands.append(roiFile) self.roiRasters[param.value] = roiFile else: - commands.append('"' + param.value + '"') + commands.append("\"" + param.value+ "\"") elif isinstance(param, ParameterMultipleInput): commands.append(param.name) - files = str(param.value).split(';') - paramvalue = ' '.join(['"' + f + '"' for f in files]) + files = str(param.value).split(";") + paramvalue = " ".join(["\"" + f + "\"" for f in files]) commands.append(paramvalue) elif isinstance(param, ParameterSelection): commands.append(param.name) @@ -173,7 +277,7 @@ def processAlgorithm(self, progress): commands.append(param.name) commands.append(str(param.value).lower()) elif isinstance(param, ParameterExtent): - self.roiValues = param.value.split(',') + self.roiValues = param.value.split(",") else: commands.append(param.name) commands.append(str(param.value)) @@ -181,54 +285,63 @@ def processAlgorithm(self, progress): for out in self.outputs: commands.append(out.name) commands.append('"' + out.value + '"') - for (roiInput, roiFile) in self.roiRasters.items(): - (startX, startY) = (float(self.roiValues[0]), - float(self.roiValues[1])) + for roiInput, roiFile in self.roiRasters.items(): + startX, startY = float(self.roiValues[0]), float(self.roiValues[1]) sizeX = float(self.roiValues[2]) - startX sizeY = float(self.roiValues[3]) - startY helperCommands = [ - 'otbcli_ExtractROI', - '-in', - roiInput, - '-out', - roiFile, - '-startx', - str(startX), - '-starty', - str(startY), - '-sizex', - str(sizeX), - '-sizey', - str(sizeY), - ] + "otbcli_ExtractROI", + "-in", roiInput, + "-out", roiFile, + "-startx", str(startX), + "-starty", str(startY), + "-sizex", str(sizeX), + "-sizey", str(sizeY)] ProcessingLog.addToLog(ProcessingLog.LOG_INFO, helperCommands) progress.setCommand(helperCommands) OTBUtils.executeOtb(helperCommands, progress) if self.roiRasters: supportRaster = self.roiRasters.itervalues().next() - for (roiInput, roiFile) in self.roiVectors.items(): + for roiInput, roiFile in self.roiVectors.items(): helperCommands = [ - 'otbcli_VectorDataExtractROIApplication', - '-vd.in', - roiInput, - '-io.in', - supportRaster, - '-io.out', - roiFile, - '-elev.dem.path', - OTBUtils.otbSRTMPath(), - ] + "otbcli_VectorDataExtractROIApplication", + "-vd.in", roiInput, + "-io.in", supportRaster, + "-io.out", roiFile, + "-elev.dem.path", OTBUtils.otbSRTMPath()] ProcessingLog.addToLog(ProcessingLog.LOG_INFO, helperCommands) progress.setCommand(helperCommands) OTBUtils.executeOtb(helperCommands, progress) loglines = [] - loglines.append('OTB execution command') + loglines.append("OTB execution command") for line in commands: loglines.append(line) progress.setCommand(line) ProcessingLog.addToLog(ProcessingLog.LOG_INFO, loglines) + import processing.otb.OTBSpecific_XMLLoading + module = processing.otb.OTBSpecific_XMLLoading + + found = False + if 'adapt%s' % self.appkey in dir(module): + found = True + commands = getattr(module, 'adapt%s' % self.appkey)(commands) + else: + the_key = 'adapt%s' % self.appkey + if '-' in the_key: + base_key = the_key.split("-")[0] + if base_key in dir(module): + found = True + commands = getattr(module, base_key)(commands) + + if not found: + ProcessingLog.addToLog(ProcessingLog.LOG_INFO, "Adapter for %s not found" % the_key) + frames = inspect.getouterframes(inspect.currentframe())[1:] + for a_frame in frames: + frame,filename,line_number,function_name,lines,index = a_frame + ProcessingLog.addToLog(ProcessingLog.LOG_INFO, "%s %s %s %s %s %s" % (frame,filename,line_number,function_name,lines,index)) + OTBUtils.executeOtb(commands, progress) diff --git a/python/plugins/processing/otb/OTBAlgorithmProvider.py b/python/plugins/processing/otb/OTBAlgorithmProvider.py index f03ac6b72385..e2f0fed9a84e 100644 --- a/python/plugins/processing/otb/OTBAlgorithmProvider.py +++ b/python/plugins/processing/otb/OTBAlgorithmProvider.py @@ -6,7 +6,12 @@ --------------------- Date : August 2012 Copyright : (C) 2012 by Victor Olaya + (C) 2013 by CS Systemes d'information Email : volayaf at gmail dot com + otb at c-s dot fr + Contributors : Victor Olaya + Julien Malik - Changing the way to load algorithms : loading from xml + Oscar Picas - Changing the way to load algorithms : loading from xml *************************************************************************** * * * This program is free software; you can redistribute it and/or modify * @@ -20,19 +25,16 @@ __author__ = 'Victor Olaya' __date__ = 'August 2012' __copyright__ = '(C) 2012, Victor Olaya' - # This will get replaced with a git SHA1 when you do a git archive - __revision__ = '$Format:%H$' import os -from PyQt4.QtGui import * +import PyQt4.QtGui from processing.core.AlgorithmProvider import AlgorithmProvider from processing.core.ProcessingConfig import ProcessingConfig, Setting -from processing.core.ProcessingLog import ProcessingLog from processing.otb.OTBUtils import OTBUtils from processing.otb.OTBAlgorithm import OTBAlgorithm - +from processing.core.ProcessingLog import ProcessingLog class OTBAlgorithmProvider(AlgorithmProvider): @@ -41,14 +43,15 @@ def __init__(self): self.activate = True self.createAlgsList() + def getDescription(self): - return 'Orfeo Toolbox (Image analysis)' + return "Orfeo Toolbox (Image analysis)" def getName(self): - return 'otb' + return "otb" def getIcon(self): - return QIcon(os.path.dirname(__file__) + '/../images/otb.png') + return PyQt4.QtGui.QIcon(os.path.dirname(__file__) + "/../images/otb.png") def _loadAlgorithms(self): self.algs = self.preloadedAlgs @@ -57,36 +60,24 @@ def createAlgsList(self): self.preloadedAlgs = [] folder = OTBUtils.otbDescriptionPath() for descriptionFile in os.listdir(folder): - if descriptionFile.endswith('txt'): + if descriptionFile.endswith("xml"): try: alg = OTBAlgorithm(os.path.join(folder, descriptionFile)) - if alg.name.strip() != '': + + if alg.name.strip() != "": self.preloadedAlgs.append(alg) else: - ProcessingLog.addToLog(ProcessingLog.LOG_ERROR, - 'Could not open OTB algorithm: ' - + descriptionFile) - except Exception, e: - ProcessingLog.addToLog(ProcessingLog.LOG_ERROR, - 'Could not open OTB algorithm: ' + descriptionFile) + ProcessingLog.addToLog(ProcessingLog.LOG_ERROR, "Could not open OTB algorithm: " + descriptionFile) + except Exception,e: + ProcessingLog.addToLog(ProcessingLog.LOG_ERROR, "Could not open OTB algorithm: " + descriptionFile) + def initializeSettings(self): AlgorithmProvider.initializeSettings(self) - ProcessingConfig.addSetting(Setting(self.getDescription(), - OTBUtils.OTB_FOLDER, - 'OTB command line tools folder', - OTBUtils.otbPath())) - ProcessingConfig.addSetting(Setting(self.getDescription(), - OTBUtils.OTB_LIB_FOLDER, - 'OTB applications folder', - OTBUtils.otbLibPath())) - ProcessingConfig.addSetting(Setting(self.getDescription(), - OTBUtils.OTB_SRTM_FOLDER, - 'SRTM tiles folder', - OTBUtils.otbSRTMPath())) - ProcessingConfig.addSetting(Setting(self.getDescription(), - OTBUtils.OTB_GEOID_FILE, 'Geoid file', - OTBUtils.otbGeoidPath())) + ProcessingConfig.addSetting(Setting(self.getDescription(), OTBUtils.OTB_FOLDER, "OTB command line tools folder", OTBUtils.otbPath())) + ProcessingConfig.addSetting(Setting(self.getDescription(), OTBUtils.OTB_LIB_FOLDER, "OTB applications folder", OTBUtils.otbLibPath())) + ProcessingConfig.addSetting(Setting(self.getDescription(), OTBUtils.OTB_SRTM_FOLDER, "SRTM tiles folder", OTBUtils.otbSRTMPath())) + ProcessingConfig.addSetting(Setting(self.getDescription(), OTBUtils.OTB_GEOID_FILE, "Geoid file", OTBUtils.otbGeoidPath())) def unload(self): AlgorithmProvider.unload(self) diff --git a/python/plugins/processing/otb/OTBSpecific_XMLLoading.py b/python/plugins/processing/otb/OTBSpecific_XMLLoading.py new file mode 100644 index 000000000000..583a5930a37a --- /dev/null +++ b/python/plugins/processing/otb/OTBSpecific_XMLLoading.py @@ -0,0 +1,326 @@ +# -*- coding: utf-8 -*- + +""" +*************************************************************************** + OTBUtils.py + --------------------- + Date : 11-12-13 + Copyright : (C) 2013 by CS Systemes d'information (CS SI) + Email : otb at c-s dot fr (CS SI) + Contributors : Julien Malik (CS SI) - creation of otbspecific + Oscar Picas (CS SI) - + Alexia Mondot (CS SI) - split otbspecific into 2 files + add functions +*************************************************************************** +* * +* This program is free software; you can redistribute it and/or modify * +* it under the terms of the GNU General Public License as published by * +* the Free Software Foundation; either version 2 of the License, or * +* (at your option) any later version. * +* * +*************************************************************************** + +When an OTB algorithms is run, this file allows to adapt user parameter to fit the otbapplication. + +Most of the following functions are like follows : + adaptNameOfTheOTBApplication(commands_list) +The command list is a list of all parameters of the given algorithm with all user values. +""" + + +__author__ = 'Julien Malik, Oscar Picas, Alexia Mondot' +__date__ = 'December 2013' +__copyright__ = '(C) 2013, CS Systemes d\'information (CS SI)' +# This will get replaced with a git SHA1 when you do a git archive +__revision__ = '$Format:%H$' +__version__ = "3.8" + +import os + +try: + import processing +except ImportError, e: + raise Exception("Processing must be installed and available in PYTHONPATH") + +from processing.core.ProcessingLog import ProcessingLog +from processing.core.ProcessingConfig import ProcessingConfig + +from processing.otb.OTBUtils import * + + + +def adaptBinaryMorphologicalOperation(commands_list): + val = commands_list[commands_list.index("-filter") + 1] + + def replace_dilate(param, value): + if ".dilate" in str(param): + return param.replace("dilate", value) + else: + return param + + import functools + com_list = map(functools.partial(replace_dilate, value=val), commands_list) + + val = com_list[com_list.index("-structype.ball.xradius") + 1] + + pos = com_list.index("-structype.ball.xradius") + 2 + + com_list.insert(pos, '-structype.ball.yradius') + com_list.insert(pos + 1, val) + + return com_list + + +def adaptEdgeExtraction(commands_list): + """ + Add filter.touzi.yradius as the same value as filter.touzi.xradius + """ + val = commands_list[commands_list.index("-filter") + 1] + if val == 'touzi': + bval = commands_list[commands_list.index("-filter.touzi.xradius") + 1] + pos = commands_list.index("-filter.touzi.xradius") + 2 + commands_list.insert(pos, "-filter.touzi.yradius") + commands_list.insert(pos + 1, bval) + return commands_list + + +def adaptGrayScaleMorphologicalOperation(commands_list): + """ + Add structype.ball.yradius as the same value as structype.ball.xradius (as it is a ball) + """ + val = commands_list[commands_list.index("-structype.ball.xradius") + 1] + pos = commands_list.index("-structype.ball.xradius") + 2 + commands_list.insert(pos, "-structype.ball.yradius") + commands_list.insert(pos + 1, val) + return commands_list + + +def adaptSplitImage(commands_list): + """ + Ran by default, the extension of output file is .file. Replace it with ".tif" + If no extension given, put ".tif" at the end of the filename. + """ + commands_list2 = [] + for item in commands_list: + if ".file" in item: + item = item.replace(".file", ".tif") + if item == "-out": + index = commands_list.index(item) + if not "." in os.path.basename(commands_list[index + 1] ): + commands_list[index + 1] = commands_list[index + 1][:-1] + ".tif" + commands_list[index + 1][-1] + commands_list2.append(item) + return commands_list2 + + +def adaptLSMSVectorization(commands_list): + """ + Ran by default, the extension of output file is .file. Replace it with ".shp" + If no extension given, put ".shp" at the end of the filename. + """ + commands_list2 = [] + for item in commands_list: + if ".file" in item: + item = item.replace(".file", ".shp") + if item == "-out": + index = commands_list.index(item) + if not "." in os.path.basename(commands_list[index + 1] ): + commands_list[index + 1] = commands_list[index + 1][:-1] + ".shp" + commands_list[index + 1][-1] + commands_list2.append(item) + + return commands_list2 + +def adaptComputeImagesStatistics(commands_list): + """ + Ran by default, the extension of output file is .file. Replace it with ".xml" + If no extension given, put ".shp" at the end of the filename. + """ + commands_list2 = [] + for item in commands_list: + if ".file" in item: + item = item.replace(".file", ".xml") + commands_list2.append(item) + if item == "-out": + index = commands_list.index(item) + if not "." in os.path.basename(commands_list[index + 1] ): + commands_list[index + 1] = commands_list[index + 1][:-1] + ".xml" + commands_list[index + 1][-1] + + return commands_list2 + + +def adaptKmzExport(commands_list): + """ + Ran by default, the extension of output file is .file. Replace it with ".kmz" + If no extension given, put ".kmz" at the end of the filename. + Check geoid file, srtm folder and given elevation and manage arguments. + """ + adaptGeoidSrtm(commands_list) + commands_list2 = [] + for item in commands_list: + if ".file" in item: + item = item.replace(".file", ".kmz") + if item == "-out": + index = commands_list.index(item) + if not "." in os.path.basename(commands_list[index + 1] ): + commands_list[index + 1] = commands_list[index + 1][:-1] + ".kmz" + commands_list[index + 1][-1] + + commands_list2.append(item) + return commands_list2 + + +def adaptColorMapping(commands_list): + """ + The output of this algorithm must be in uint8. + """ + indexInput = commands_list.index("-out") + commands_list[indexInput+1] = commands_list[indexInput+1] + " uint8" + return commands_list + + + +def adaptStereoFramework(commands_list): + """ + Remove parameter and user value instead of giving None. + Check geoid file, srtm folder and given elevation and manage arguments. + """ + commands_list2 = commands_list + adaptGeoidSrtm(commands_list2) + for item in commands_list: + if "None" in item: + index = commands_list2.index(item) + argumentToRemove = commands_list2[index-1] + commands_list2.remove(item) + commands_list2.remove(argumentToRemove) + #commands_list2.append(item) + return commands_list2 + + +def adaptComputeConfusionMatrix(commands_list): + """ + Ran by default, the extension of output file is .file. Replace it with ".csv" + If no extension given, put ".csv" at the end of the filename. + """ + commands_list2 = [] + for item in commands_list: + if ".file" in item: + item = item.replace(".file", ".csv") + if item == "-out": + index = commands_list.index(item) + if not "." in os.path.basename(commands_list[index + 1] ): + commands_list[index + 1] = commands_list[index + 1][:-1] + ".csv" + commands_list[index + 1][-1] + + commands_list2.append(item) + return commands_list2 + + +def adaptRadiometricIndices(commands_list): + """ + Replace indice nickname by its corresponding entry in the following dictionnary : + indices = {"ndvi" : "Vegetation:NDVI", "tndvi" : "Vegetation:TNDVI", "rvi" : "Vegetation:RVI", "savi" : "Vegetation:SAVI", + "tsavi" : "Vegetation:TSAVI", "msavi" : "Vegetation:MSAVI", "msavi2" : "Vegetation:MSAVI2", "gemi" : "Vegetation:GEMI", + "ipvi" : "Vegetation:IPVI", + "ndwi" : "Water:NDWI", "ndwi2" : "Water:NDWI2", "mndwi" :"Water:MNDWI" , "ndpi" : "Water:NDPI", + "ndti" : "Water:NDTI", + "ri" : "Soil:RI", "ci" : "Soil:CI", "bi" : "Soil:BI", "bi2" : "Soil:BI2"} + """ +# "laindvilog" : , "lairefl" : , "laindviformo" : , + indices = {"ndvi" : "Vegetation:NDVI", "tndvi" : "Vegetation:TNDVI", "rvi" : "Vegetation:RVI", "savi" : "Vegetation:SAVI", + "tsavi" : "Vegetation:TSAVI", "msavi" : "Vegetation:MSAVI", "msavi2" : "Vegetation:MSAVI2", "gemi" : "Vegetation:GEMI", + "ipvi" : "Vegetation:IPVI", + "ndwi" : "Water:NDWI", "ndwi2" : "Water:NDWI2", "mndwi" :"Water:MNDWI" , "ndpi" : "Water:NDPI", + "ndti" : "Water:NDTI", + "ri" : "Soil:RI", "ci" : "Soil:CI", "bi" : "Soil:BI", "bi2" : "Soil:BI2"} + for item in commands_list: + if item in indices: + commands_list[commands_list.index(item)] = indices[item] + return commands_list + + +def adaptDisparityMapToElevationMap(commands_list): + """ + Check geoid file, srtm folder and given elevation and manage arguments. + """ + adaptGeoidSrtm(commands_list) + return commands_list + + +def adaptConnectedComponentSegmentation(commands_list): + """ + Remove parameter and user value instead of giving None. + """ + commands_list2 = commands_list + adaptGeoidSrtm(commands_list2) + for item in commands_list: + if "None" in item: + index = commands_list2.index(item) + argumentToRemove = commands_list2[index-1] + commands_list2.remove(item) + commands_list2.remove(argumentToRemove) + #commands_list2.append(item) + return commands_list2 + + +def adaptSuperimpose(commands_list): + """ + Check geoid file, srtm folder and given elevation and manage arguments. + """ + adaptGeoidSrtm(commands_list) + return commands_list + + +def adaptOrthoRectification(commands_list): + """ + Check geoid file, srtm folder and given elevation and manage arguments. + """ + adaptGeoidSrtm(commands_list) + return commands_list + + +def adaptExtractROI(commands_list): + """ + Check geoid file, srtm folder and given elevation and manage arguments. + """ + adaptGeoidSrtm(commands_list) + return commands_list + + +def adaptTrainImagesClassifier(commands_list): + """ + Check geoid file, srtm folder and given elevation and manage arguments. + """ + adaptGeoidSrtm(commands_list) + return commands_list + +def adaptGeoidSrtm(commands_list): + """ + Check geoid file, srtm folder and given elevation and manage arguments. + """ + srtm, geoid = ckeckGeoidSrtmSettings() + + + if srtm : + if commands_list[0].endswith("ExtractROI") : + commands_list.append("-mode.fit.elev.dem") + commands_list.append(srtm) + else : + commands_list.append("-elev.dem") + commands_list.append(srtm) + if geoid : + if commands_list[0].endswith("ExtractROI") : + commands_list.append("-mode.fit.elev.geoid") + commands_list.append(geoid) + else : + commands_list.append("-elev.geoid") + commands_list.append(geoid) + + + +def ckeckGeoidSrtmSettings(): + folder = ProcessingConfig.getSetting(OTBUtils.OTB_SRTM_FOLDER) + if folder == None: + folder ="" + + filepath = ProcessingConfig.getSetting(OTBUtils.OTB_GEOID_FILE) + if filepath == None: + filepath ="" + + return folder, filepath diff --git a/python/plugins/processing/otb/OTBUtils.py b/python/plugins/processing/otb/OTBUtils.py index 3603d3c4575a..15678c2d820e 100644 --- a/python/plugins/processing/otb/OTBUtils.py +++ b/python/plugins/processing/otb/OTBUtils.py @@ -6,7 +6,12 @@ --------------------- Date : August 2012 Copyright : (C) 2012 by Victor Olaya + (C) 2013 by CS Systemes d'information (CS SI) Email : volayaf at gmail dot com + otb at c-s dot fr (CS SI) + Contributors : Victor Olaya + Julien Malik, Oscar Picas (CS SI) - add functions to manage xml tree + Alexia Mondot (CS SI) - add a trick for OTBApplication SplitImages *************************************************************************** * * * This program is free software; you can redistribute it and/or modify * @@ -20,78 +25,80 @@ __author__ = 'Victor Olaya' __date__ = 'August 2012' __copyright__ = '(C) 2012, Victor Olaya' - # This will get replaced with a git SHA1 when you do a git archive - __revision__ = '$Format:%H$' import os -import subprocess +import glob from qgis.core import QgsApplication +import subprocess from processing.core.ProcessingConfig import ProcessingConfig from processing.core.ProcessingLog import ProcessingLog -from processing.tools.system import * +from processing.core.ProcessingUtils import ProcessingUtils +import logging +import xml.etree.ElementTree as ET +import traceback +from processing.core.QGisLayers import QGisLayers +import qgis.core +import PyQt4.QtGui class OTBUtils: - OTB_FOLDER = 'OTB_FOLDER' - OTB_LIB_FOLDER = 'OTB_LIB_FOLDER' - OTB_SRTM_FOLDER = 'OTB_SRTM_FOLDER' - OTB_GEOID_FILE = 'OTB_GEOID_FILE' + OTB_FOLDER = "OTB_FOLDER" + OTB_LIB_FOLDER = "OTB_LIB_FOLDER" + OTB_SRTM_FOLDER = "OTB_SRTM_FOLDER" + OTB_GEOID_FILE = "OTB_GEOID_FILE" @staticmethod def otbPath(): folder = ProcessingConfig.getSetting(OTBUtils.OTB_FOLDER) - if folder is None: - folder = '' - - # Try to configure the path automatically - if isMac(): - testfolder = os.path.join(str(QgsApplication.prefixPath()), - 'bin') - if os.path.exists(os.path.join(testfolder, 'otbcli')): + if folder == None: + folder = "" + #try to configure the path automatically + if ProcessingUtils.isMac(): + testfolder = os.path.join(str(QgsApplication.prefixPath()), "bin") + if os.path.exists(os.path.join(testfolder, "otbcli")): folder = testfolder else: - testfolder = '/usr/local/bin' - if os.path.exists(os.path.join(testfolder, 'otbcli')): + testfolder = "/usr/local/bin" + if os.path.exists(os.path.join(testfolder, "otbcli")): folder = testfolder - elif isWindows(): + elif ProcessingUtils.isWindows(): testfolder = os.path.dirname(str(QgsApplication.prefixPath())) testfolder = os.path.dirname(testfolder) - testfolder = os.path.join(testfolder, 'bin') - path = os.path.join(testfolder, 'otbcli.bat') + testfolder = os.path.join(testfolder, "bin") + path = os.path.join(testfolder, "otbcli.bat") if os.path.exists(path): folder = testfolder else: - testfolder = '/usr/bin' - if os.path.exists(os.path.join(testfolder, 'otbcli')): + testfolder = "/usr/bin" + if os.path.exists(os.path.join(testfolder, "otbcli")): folder = testfolder return folder @staticmethod def otbLibPath(): folder = ProcessingConfig.getSetting(OTBUtils.OTB_LIB_FOLDER) - if folder is None: - folder = '' - # Try to configure the path automatically - if isMac(): - testfolder = os.path.join(str(QgsApplication.prefixPath()), - 'lib/otb/applications') + if folder == None: + folder ="" + #try to configure the path automatically + if ProcessingUtils.isMac(): + testfolder = os.path.join(str(QgsApplication.prefixPath()), "lib/otb/applications") if os.path.exists(testfolder): folder = testfolder else: - testfolder = '/usr/local/lib/otb/applications' + testfolder = "/usr/local/lib/otb/applications" if os.path.exists(testfolder): folder = testfolder - elif isWindows(): + elif ProcessingUtils.isWindows(): testfolder = os.path.dirname(str(QgsApplication.prefixPath())) - testfolder = os.path.join(testfolder, 'orfeotoolbox') - testfolder = os.path.join(testfolder, 'applications') + testfolder = os.path.join(testfolder, "orfeotoolbox") + testfolder = os.path.join(testfolder, "applications") if os.path.exists(testfolder): folder = testfolder else: - testfolder = '/usr/lib/otb/applications' + testfolder = "/usr/lib/otb/applications" if os.path.exists(testfolder): folder = testfolder return folder @@ -99,42 +106,135 @@ def otbLibPath(): @staticmethod def otbSRTMPath(): folder = ProcessingConfig.getSetting(OTBUtils.OTB_SRTM_FOLDER) - if folder is None: - folder = '' + if folder == None: + folder ="" return folder @staticmethod def otbGeoidPath(): filepath = ProcessingConfig.getSetting(OTBUtils.OTB_GEOID_FILE) - if filepath is None: - filepath = '' + if filepath == None: + filepath ="" return filepath @staticmethod def otbDescriptionPath(): - return os.path.join(os.path.dirname(__file__), 'description') + return os.path.join(os.path.dirname(__file__), "description") @staticmethod def executeOtb(commands, progress): loglines = [] - loglines.append('OTB execution console output') + loglines.append("OTB execution console output") os.putenv('ITK_AUTOLOAD_PATH', OTBUtils.otbLibPath()) fused_command = ''.join(['"%s" ' % c for c in commands]) - proc = subprocess.Popen( - fused_command, - shell=True, - stdout=subprocess.PIPE, - stdin=subprocess.PIPE, - stderr=subprocess.STDOUT, - universal_newlines=True, - ).stdout - for line in iter(proc.readline, ''): - if '[*' in line: - idx = line.find('[*') - perc = int(line[idx - 4:idx - 2].strip(' ')) + proc = subprocess.Popen(fused_command, shell=True, stdout=subprocess.PIPE, stdin=subprocess.PIPE,stderr=subprocess.STDOUT, universal_newlines=True).stdout + for line in iter(proc.readline, ""): + if "[*" in line: + idx = line.find("[*") + perc = int(line[idx-4:idx-2].strip(" ")) if perc != 0: progress.setPercentage(perc) else: loglines.append(line) progress.setConsoleInfo(line) + ProcessingLog.addToLog(ProcessingLog.LOG_INFO, loglines) + + + +def get_choices_of(doc, parameter): + choices = [] + try: + t5 = [item for item in doc.findall('.//parameter') if item.find('key').text == parameter] + choices = [item.text for item in t5[0].findall('options/choices/choice')] + except: + logger = logging.getLogger('OTBGenerator') + logger.warning(traceback.format_exc()) + return choices + +def remove_dependant_choices(doc, parameter, choice): + choices = get_choices_of(doc, parameter) + choices.remove(choice) + for a_choice in choices: + t4 = [item for item in doc.findall('.//parameter') if '.%s' % a_choice in item.find('key').text] + for t5 in t4: + doc.remove(t5) + +def renameValueField(doc, textitem, field, newValue): + t4 = [item for item in doc.findall('.//parameter') if item.find('key').text == textitem] + for t5 in t4: + t5.find(field).text = newValue + + +def remove_independant_choices(doc, parameter, choice): + choices = [] + choices.append(choice) + for a_choice in choices: + t4 = [item for item in doc.findall('.//parameter') if '.%s' % a_choice in item.find('key').text] + for t5 in t4: + doc.remove(t5) + +def remove_parameter_by_key(doc, parameter): + t4 = [item for item in doc.findall('.//parameter') if item.find('key').text == parameter] + for t5 in t4: + doc.remove(t5) + +def remove_other_choices(doc, parameter, choice): + t5 = [item for item in doc.findall('.//parameter') if item.find('key').text == parameter] + if len(t5) > 0: + choices = [item for item in t5[0].findall('options/choices/choice') if item.text != choice] + choice_root = t5[0].findall('options/choices')[0] + for a_choice in choices: + choice_root.remove(a_choice) + +def remove_choice(doc, parameter, choice): + t5 = [item for item in doc.findall('.//parameter') if item.find('key').text == parameter] + if len(t5) > 0: + choices = [item for item in t5[0].findall('options/choices/choice') if item.text == choice] + choice_root = t5[0].findall('options/choices')[0] + for a_choice in choices: + choice_root.remove(a_choice) + +def split_by_choice(doc, parameter): + """ + splits the given doc into several docs according to the given parameter + returns a dictionnary of documents + """ + result = {} + choices = get_choices_of(doc, parameter) + import copy + for choice in choices: + #creates a new copy of the document + working_copy = copy.deepcopy(doc) + remove_dependant_choices(working_copy, parameter, choice) + #remove all other choices except the current one + remove_other_choices(working_copy, parameter, choice) + #set a new name according to the choice + old_app_name = working_copy.find('key').text + working_copy.find('key').text = '%s-%s' % (old_app_name, choice) + old_longname = working_copy.find('longname').text + working_copy.find('longname').text = '%s (%s)' % (old_app_name, choice) + #add it to the dictionnary + result[choice] = working_copy + return result + +def remove_parameter_by_criteria(doc, criteria): + t4 = [item for item in doc.findall('./parameter') if criteria(item)] + for t5 in t4: + doc.getroot().remove(t5) + +def defaultWrite(available_app, original_dom_document): + fh = open("description/%s.xml" % available_app, "w") + the_root = original_dom_document + logger = logging.getLogger('OTBGenerator') + ET.ElementTree(the_root).write(fh) + fh.close() + +def defaultSplit(available_app, original_dom_document, parameter): + the_root = original_dom_document + splitted = split_by_choice(the_root, parameter) + the_list = [] + for key in splitted: + defaultWrite('%s-%s' % (available_app, key), splitted[key]) + the_list.append(splitted[key]) + return the_list diff --git a/python/plugins/processing/otb/description/BandMath.txt b/python/plugins/processing/otb/description/BandMath.txt deleted file mode 100644 index a3f13deb6799..000000000000 --- a/python/plugins/processing/otb/description/BandMath.txt +++ /dev/null @@ -1,8 +0,0 @@ -BandMath -otbcli_BandMath -Band Math -Miscellaneous -ParameterMultipleInput|-il|Input image list|3|False -OutputRaster|-out|Output Image -ParameterNumber|-ram|Available RAM (Mb)|None|None|128 -ParameterString|-exp|Expression| diff --git a/python/plugins/processing/otb/description/BandMath.xml b/python/plugins/processing/otb/description/BandMath.xml new file mode 100644 index 000000000000..ca4a9359939d --- /dev/null +++ b/python/plugins/processing/otb/description/BandMath.xml @@ -0,0 +1,41 @@ + + BandMath + otbcli_BandMath + Band Math + Miscellaneous + Perform a mathematical operation on monoband images + + ParameterMultipleInput + il + Input image list + Image list to perform computation on. + + False + + + OutputRaster + out + Output Image + Output image. + + + + ParameterNumber + ram + Available RAM (Mb) + Available memory for processing (in MB) + + + 128 + + + ParameterString + exp + Expression + The mathematical expression to apply. +Use im1b1 for the first band, im1b2 for the second one... + + + False + + diff --git a/python/plugins/processing/otb/description/BinaryMorphologicalOperation-closing.xml b/python/plugins/processing/otb/description/BinaryMorphologicalOperation-closing.xml new file mode 100644 index 000000000000..9593d1af4d02 --- /dev/null +++ b/python/plugins/processing/otb/description/BinaryMorphologicalOperation-closing.xml @@ -0,0 +1,72 @@ + + BinaryMorphologicalOperation-closing + otbcli_BinaryMorphologicalOperation + BinaryMorphologicalOperation (closing) + Feature Extraction + Performs morphological operations on an input image channel + + ParameterRaster + in + Input Image + The input image to be filtered. + False + + + OutputRaster + out + Feature Output Image + Output image containing the filtered output image. + + + + ParameterNumber + channel + Selected Channel + The selected channel index + + + 1 + + + ParameterNumber + ram + Available RAM (Mb) + Available memory for processing (in MB) + + + 128 + + + ParameterSelection + structype + Structuring Element Type + Choice of the structuring element type + + + ball + + + 0 + + + ParameterNumber + structype.ball.xradius + The Structuring Element Radius + The Structuring Element Radius + + + 5 + + + ParameterSelection + filter + Morphological Operation + Choice of the morphological operation + + + closing + + + 0 + + diff --git a/python/plugins/processing/otb/description/BinaryMorphologicalOperation-dilate.xml b/python/plugins/processing/otb/description/BinaryMorphologicalOperation-dilate.xml new file mode 100644 index 000000000000..1e608f06251f --- /dev/null +++ b/python/plugins/processing/otb/description/BinaryMorphologicalOperation-dilate.xml @@ -0,0 +1,90 @@ + + BinaryMorphologicalOperation-dilate + otbcli_BinaryMorphologicalOperation + BinaryMorphologicalOperation (dilate) + Feature Extraction + Performs morphological operations on an input image channel + + ParameterRaster + in + Input Image + The input image to be filtered. + False + + + OutputRaster + out + Feature Output Image + Output image containing the filtered output image. + + + + ParameterNumber + channel + Selected Channel + The selected channel index + + + 1 + + + ParameterNumber + ram + Available RAM (Mb) + Available memory for processing (in MB) + + + 128 + + + ParameterSelection + structype + Structuring Element Type + Choice of the structuring element type + + + ball + + + 0 + + + ParameterNumber + structype.ball.xradius + The Structuring Element Radius + The Structuring Element Radius + + + 5 + + + ParameterSelection + filter + Morphological Operation + Choice of the morphological operation + + + dilate + + + 0 + + + ParameterNumber + filter.dilate.foreval + Foreground Value + The Foreground Value + + + 1 + + + ParameterNumber + filter.dilate.backval + Background Value + The Background Value + + + 0 + + diff --git a/python/plugins/processing/otb/description/BinaryMorphologicalOperation-erode.xml b/python/plugins/processing/otb/description/BinaryMorphologicalOperation-erode.xml new file mode 100644 index 000000000000..e7ef87a93fcb --- /dev/null +++ b/python/plugins/processing/otb/description/BinaryMorphologicalOperation-erode.xml @@ -0,0 +1,72 @@ + + BinaryMorphologicalOperation-erode + otbcli_BinaryMorphologicalOperation + BinaryMorphologicalOperation (erode) + Feature Extraction + Performs morphological operations on an input image channel + + ParameterRaster + in + Input Image + The input image to be filtered. + False + + + OutputRaster + out + Feature Output Image + Output image containing the filtered output image. + + + + ParameterNumber + channel + Selected Channel + The selected channel index + + + 1 + + + ParameterNumber + ram + Available RAM (Mb) + Available memory for processing (in MB) + + + 128 + + + ParameterSelection + structype + Structuring Element Type + Choice of the structuring element type + + + ball + + + 0 + + + ParameterNumber + structype.ball.xradius + The Structuring Element Radius + The Structuring Element Radius + + + 5 + + + ParameterSelection + filter + Morphological Operation + Choice of the morphological operation + + + erode + + + 0 + + diff --git a/python/plugins/processing/otb/description/BinaryMorphologicalOperation-opening.xml b/python/plugins/processing/otb/description/BinaryMorphologicalOperation-opening.xml new file mode 100644 index 000000000000..92d8668cdb51 --- /dev/null +++ b/python/plugins/processing/otb/description/BinaryMorphologicalOperation-opening.xml @@ -0,0 +1,72 @@ + + BinaryMorphologicalOperation-opening + otbcli_BinaryMorphologicalOperation + BinaryMorphologicalOperation (opening) + Feature Extraction + Performs morphological operations on an input image channel + + ParameterRaster + in + Input Image + The input image to be filtered. + False + + + OutputRaster + out + Feature Output Image + Output image containing the filtered output image. + + + + ParameterNumber + channel + Selected Channel + The selected channel index + + + 1 + + + ParameterNumber + ram + Available RAM (Mb) + Available memory for processing (in MB) + + + 128 + + + ParameterSelection + structype + Structuring Element Type + Choice of the structuring element type + + + ball + + + 0 + + + ParameterNumber + structype.ball.xradius + The Structuring Element Radius + The Structuring Element Radius + + + 5 + + + ParameterSelection + filter + Morphological Operation + Choice of the morphological operation + + + opening + + + 0 + + diff --git a/python/plugins/processing/otb/description/BinaryMorphologicalOperation.txt b/python/plugins/processing/otb/description/BinaryMorphologicalOperation.txt deleted file mode 100644 index 4460123e52fe..000000000000 --- a/python/plugins/processing/otb/description/BinaryMorphologicalOperation.txt +++ /dev/null @@ -1,19 +0,0 @@ -Binary Morphological Operation -otbcli_BinaryMorphologicalOperation -Binary Morphological Operation -Image Filtering -ParameterRaster|-in|Input Image|False -OutputRaster|-out|Output Image -ParameterNumber|-ram|Available RAM (Mb)|None|None|128 -ParameterNumber|-channel|Selected Channel|None|None|1 -ParameterSelection|-structype|Structuring Element Type|ball;cross|0 -ParameterNumber|-structype.ball.xradius|The Structuring Element X Radius|None|None|5 -ParameterNumber|-structype.ball.yradius|The Structuring Element Y Radius|None|None|5 -ParameterSelection|-filter|Morphological Operation|dilate;erode;opening;closing|0 -ParameterNumber|-filter.dilate.foreval|Dilate Foreground Value|None|None|1 -ParameterNumber|-filter.dilate.backval|Dilate Background Value Value|None|None|0 -ParameterNumber|-filter.erode.foreval|Erode Foreground Value|None|None|1 -ParameterNumber|-filter.erode.backval|Erode Background Value|None|None|0 -ParameterNumber|-filter.opening.foreval|Opening Foreground Value|None|None|1 -ParameterNumber|-filter.opening.backval|Opening Background Value|None|None|0 -ParameterNumber|-filter.closing.foreval|Closing Foreground Value|None|None|1 \ No newline at end of file diff --git a/python/plugins/processing/otb/description/BlockMatching.txt b/python/plugins/processing/otb/description/BlockMatching.txt deleted file mode 100644 index fd76675c32e2..000000000000 --- a/python/plugins/processing/otb/description/BlockMatching.txt +++ /dev/null @@ -1,33 +0,0 @@ -BlockMatching -otbcli_BlockMatching - Pixel-wise Block-Matching -Stereo -ParameterRaster|-io.inleft|Left input image|False -ParameterRaster|-io.inright|Right input image|False -OutputRaster|-io.out|The output disparity map -OutputRaster|-io.outmask|The output mask corresponding to all criterions -ParameterBoolean|-io.outmetric|Output optimal metric values as well| -ParameterRaster|-mask.inleft|Discard left pixels from mask image|True -ParameterRaster|-mask.inright|Discard right pixels from mask image|True -ParameterNumber|-mask.nodata|Discard pixels with no-data value|None|None|0.0 -ParameterNumber|-mask.variancet|Discard pixels with low local variance|None|None|100.0 -ParameterSelection|-bm.metric|Block-matching metric|ssd;ncc;lp|0 -ParameterNumber|-bm.metric.lp.p|p value|None|None|1.0 -ParameterNumber|-bm.radius|Radius of blocks|None|None|3 -ParameterNumber|-bm.minhd|Minimum horizontal disparity|None|None|0 -ParameterNumber|-bm.maxhd|Maximum horizontal disparity|None|None|0 -ParameterNumber|-bm.minvd|Minimum vertical disparity|None|None|0 -ParameterNumber|-bm.maxvd|Maximum vertical disparity|None|None|0 -ParameterSelection|-bm.subpixel|Sub-pixel interpolation|none;parabolic;triangular;dichotomy|0 -ParameterNumber|-bm.medianfilter.radius|Radius|None|None|0 -ParameterNumber|-bm.medianfilter.incoherence|Incoherence threshold|None|None|0.0 -ParameterSelection|-bm.initdisp|Initial disparities|none;uniform;maps|0 -ParameterNumber|-bm.initdisp.uniform.hdisp|Horizontal initial disparity|None|None|0 -ParameterNumber|-bm.initdisp.uniform.vdisp|Vertical initial disparity|None|None|0 -ParameterNumber|-bm.initdisp.uniform.hrad|Horizontal exploration radius|None|None|0 -ParameterNumber|-bm.initdisp.uniform.vrad|Vertical exploration radius|None|None|0 -ParameterRaster|-bm.initdisp.maps.hmap|Horizontal initial disparity map|False -ParameterRaster|-bm.initdisp.maps.vmap|Vertical initial disparity map|False -ParameterNumber|-bm.initdisp.maps.hrad|Horizontal exploration radius|None|None|0 -ParameterNumber|-bm.initdisp.maps.vrad|Vertical exploration radius|None|None|0 -ParameterNumber|-ram|Available RAM (Mb)|None|None|128 diff --git a/python/plugins/processing/otb/description/BundleToPerfectSensor.txt b/python/plugins/processing/otb/description/BundleToPerfectSensor.txt deleted file mode 100644 index c1ee11fe9a9a..000000000000 --- a/python/plugins/processing/otb/description/BundleToPerfectSensor.txt +++ /dev/null @@ -1,13 +0,0 @@ -BundleToPerfectSensor -otbcli_BundleToPerfectSensor -Bundle to perfect sensor -Geometry -ParameterRaster|-inp|Input PAN Image|False -ParameterRaster|-inxs|Input XS Image|False -ParameterSelection|-elev|Elevation management|dem;average|1 -ParameterFile|-elev.dem.path|DEM directory| -ParameterFile|-elev.dem.geoid|Geoid File|| -ParameterNumber|-elev.average.value|Average Elevation|None|None|0.0 -ParameterNumber|-lms|Spacing of the deformation field|None|None|0.0 -OutputRaster|-out|Output image -ParameterNumber|-ram|Available RAM (Mb)|None|None|128 diff --git a/python/plugins/processing/otb/description/ClassificationMapRegularization.xml b/python/plugins/processing/otb/description/ClassificationMapRegularization.xml new file mode 100644 index 000000000000..cc586e3a27a5 --- /dev/null +++ b/python/plugins/processing/otb/description/ClassificationMapRegularization.xml @@ -0,0 +1,64 @@ + + ClassificationMapRegularization + otbcli_ClassificationMapRegularization + Classification Map Regularization + Learning + Filters the input labeled image using Majority Voting in a ball shaped neighbordhood. + + ParameterRaster + io.in + Input classification image + The input labeled image to regularize. + False + + + OutputRaster + io.out + Output regularized image + The output regularized labeled image. + + + + ParameterNumber + ip.radius + Structuring element radius (in pixels) + The radius of the ball shaped structuring element (expressed in pixels). By default, 'ip.radius = 1 pixel'. + + + 1 + + + ParameterBoolean + ip.suvbool + Multiple majority: Undecided(X)/Original + Pixels with more than 1 majority class are marked as Undecided if this parameter is checked (true), or keep their Original labels otherwise (false). Please note that the Undecided value must be different from existing labels in the input labeled image. By default, 'ip.suvbool = false'. + True + + + ParameterNumber + ip.nodatalabel + Label for the NoData class + Label for the NoData class. Such input pixels keep their NoData label in the output image. By default, 'ip.nodatalabel = 0'. + + + 0 + + + ParameterNumber + ip.undecidedlabel + Label for the Undecided class + Label for the Undecided class. By default, 'ip.undecidedlabel = 0'. + + + 0 + + + ParameterNumber + ram + Available RAM (Mb) + Available memory for processing (in MB) + + + 128 + + diff --git a/python/plugins/processing/otb/description/ClassificationRegularization.txt b/python/plugins/processing/otb/description/ClassificationRegularization.txt deleted file mode 100644 index c57ede531431..000000000000 --- a/python/plugins/processing/otb/description/ClassificationRegularization.txt +++ /dev/null @@ -1,11 +0,0 @@ -Classification Regularization -otbcli_ClassificationMapRegularization -Classification Regularization -Learning -ParameterRaster|-io.in|Input Image|False -OutputRaster|-io.out|Output Image -ParameterNumber|-ram|Available RAM (Mb)|None|None|128 -ParameterNumber|-ip.radius|Structuring Element Radius|None|None|1 -ParameterBoolean|-ip.suvbool|Multiple majority|False -ParameterNumber|-ip.nodatalabel|Label for the NoData class|None|None|0 -ParameterNumber|-ip.undecidedlabel|Label for the Undecided class|None|None|0 diff --git a/python/plugins/processing/otb/description/ColorMapping-continuous.xml b/python/plugins/processing/otb/description/ColorMapping-continuous.xml new file mode 100644 index 000000000000..acf6d0e55b28 --- /dev/null +++ b/python/plugins/processing/otb/description/ColorMapping-continuous.xml @@ -0,0 +1,98 @@ + + ColorMapping-continuous + otbcli_ColorMapping + ColorMapping (continuous) + Image Manipulation + Maps an input label image to 8-bits RGB using look-up tables. + + ParameterRaster + in + Input Image + Input image filename + False + + + OutputRaster + out + Output Image + Output image filename + + + + ParameterNumber + ram + Available RAM (Mb) + Available memory for processing (in MB) + + + 128 + + + ParameterSelection + op + Operation + Selection of the operation to execute (default is : label to color). + + + labeltocolor + + + 0 + + + ParameterSelection + method + Color mapping method + Selection of color mapping methods and their parameters. + + + continuous + + + 0 + + + ParameterSelection + method.continuous.lut + Look-up tables + Available look-up tables. + + + red + green + blue + grey + hot + cool + spring + summer + autumn + winter + copper + jet + hsv + overunder + relief + + + 0 + + + ParameterNumber + method.continuous.min + Mapping range lower value + Set the lower input value of the mapping range. + + + 0 + + + ParameterNumber + method.continuous.max + Mapping range higher value + Set the higher input value of the mapping range. + + + 255 + + diff --git a/python/plugins/processing/otb/description/ColorMapping-custom.xml b/python/plugins/processing/otb/description/ColorMapping-custom.xml new file mode 100644 index 000000000000..6257536c0886 --- /dev/null +++ b/python/plugins/processing/otb/description/ColorMapping-custom.xml @@ -0,0 +1,65 @@ + + ColorMapping-custom + otbcli_ColorMapping + ColorMapping (custom) + Image Manipulation + Maps an input label image to 8-bits RGB using look-up tables. + + ParameterRaster + in + Input Image + Input image filename + False + + + OutputRaster + out + Output Image + Output image filename + + + + ParameterNumber + ram + Available RAM (Mb) + Available memory for processing (in MB) + + + 128 + + + ParameterSelection + op + Operation + Selection of the operation to execute (default is : label to color). + + + labeltocolor + + + 0 + + + ParameterSelection + method + Color mapping method + Selection of color mapping methods and their parameters. + + + custom + + + 0 + + + ParameterFile + method.custom.lut + Look-up table file + An ASCII file containing the look-up table +with one color per line +(for instance the line '1 255 0 0' means that all pixels with label 1 will be replaced by RGB color 255 0 0) +Lines beginning with a # are ignored + + False + + diff --git a/python/plugins/processing/otb/description/ColorMapping-image.xml b/python/plugins/processing/otb/description/ColorMapping-image.xml new file mode 100644 index 000000000000..60ef8c5ae9ad --- /dev/null +++ b/python/plugins/processing/otb/description/ColorMapping-image.xml @@ -0,0 +1,88 @@ + + ColorMapping-image + otbcli_ColorMapping + ColorMapping (image) + Image Manipulation + Maps an input label image to 8-bits RGB using look-up tables. + + ParameterRaster + in + Input Image + Input image filename + False + + + OutputRaster + out + Output Image + Output image filename + + + + ParameterNumber + ram + Available RAM (Mb) + Available memory for processing (in MB) + + + 128 + + + ParameterSelection + op + Operation + Selection of the operation to execute (default is : label to color). + + + labeltocolor + + + 0 + + + ParameterSelection + method + Color mapping method + Selection of color mapping methods and their parameters. + + + image + + + 0 + + + ParameterRaster + method.image.in + Support Image + Support image filename. For each label, the LUT is calculated from the mean pixel value in the support image, over the corresponding labeled areas. First of all, the support image is normalized with extrema rejection + False + + + ParameterNumber + method.image.nodatavalue + NoData value + NoData value for each channel of the support image, which will not be handled in the LUT estimation. If NOT checked, ALL the pixel values of the support image will be handled in the LUT estimation. + + + 0 + + + ParameterNumber + method.image.low + lower quantile + lower quantile for image normalization + + + 2 + + + ParameterNumber + method.image.up + upper quantile + upper quantile for image normalization + + + 2 + + diff --git a/python/plugins/processing/otb/description/ColorMapping-optimal.xml b/python/plugins/processing/otb/description/ColorMapping-optimal.xml new file mode 100644 index 000000000000..d1a2922fcdcc --- /dev/null +++ b/python/plugins/processing/otb/description/ColorMapping-optimal.xml @@ -0,0 +1,63 @@ + + ColorMapping-optimal + otbcli_ColorMapping + ColorMapping (optimal) + Image Manipulation + Maps an input label image to 8-bits RGB using look-up tables. + + ParameterRaster + in + Input Image + Input image filename + False + + + OutputRaster + out + Output Image + Output image filename + + + + ParameterNumber + ram + Available RAM (Mb) + Available memory for processing (in MB) + + + 128 + + + ParameterSelection + op + Operation + Selection of the operation to execute (default is : label to color). + + + labeltocolor + + + 0 + + + ParameterSelection + method + Color mapping method + Selection of color mapping methods and their parameters. + + + optimal + + + 0 + + + ParameterNumber + method.optimal.background + Background label + Value of the background label + + + 0 + + diff --git a/python/plugins/processing/otb/description/ColorMapping.txt b/python/plugins/processing/otb/description/ColorMapping.txt deleted file mode 100644 index 60294b950f6a..000000000000 --- a/python/plugins/processing/otb/description/ColorMapping.txt +++ /dev/null @@ -1,18 +0,0 @@ -ColorMapping -otbcli_ColorMapping -Color Mapping -Image Manipulation -ParameterRaster|-in|Input Image|False -OutputRaster|-out|Output Image -ParameterNumber|-ram|Available RAM (Mb)|None|None|128 -ParameterSelection|-op|Operation|labeltocolor;colortolabel|0 -ParameterNumber|-op.colortolabel.notfound|Not Found Label|None|None|404 -ParameterSelection|-method|Color mapping method|custom;continuous;optimal;image|0 -ParameterFile|-method.custom.lut|Look-up table file|| -ParameterSelection|-method.continuous.lut|Look-up tables|red;green;blue;grey;hot;cool;spring;summer;autumn;winter;copper;jet;hsv;overunder;relief|0 -ParameterNumber|-method.continuous.min|Mapping range lower value|None|None|0.0 -ParameterNumber|-method.continuous.max|Mapping range higher value|None|None|255.0 -ParameterNumber|-method.optimal.background|Background label|None|None|0 -ParameterRaster|-method.image.in|Support Image|False -ParameterNumber|-method.image.low|lower quantile|None|None|2 -ParameterNumber|-method.image.up|upper quantile|None|None|2 diff --git a/python/plugins/processing/otb/description/CompareImages.txt b/python/plugins/processing/otb/description/CompareImages.txt deleted file mode 100644 index 4bfde76f7cf0..000000000000 --- a/python/plugins/processing/otb/description/CompareImages.txt +++ /dev/null @@ -1,15 +0,0 @@ -CompareImages -otbcli_CompareImages -Images comparaison -Miscellaneous -ParameterRaster|-ref.in|Reference image|False -ParameterNumber|-ref.channel|Reference image channel|None|None|1 -ParameterRaster|-meas.in|Measured image|False -ParameterNumber|-meas.channel|Measured image channel|None|None|1 -ParameterNumber|-roi.startx|Start X|None|None|0 -ParameterNumber|-roi.starty|Start Y|None|None|0 -ParameterNumber|-roi.sizex|Size X|None|None|0 -ParameterNumber|-roi.sizey|Size Y|None|None|0 -ParameterNumber|-mse|MSE|None|None|0.0 -ParameterNumber|-mae|MAE|None|None|0.0 -ParameterNumber|-psnr|PSNR|None|None|0.0 diff --git a/python/plugins/processing/otb/description/CompareImages.xml b/python/plugins/processing/otb/description/CompareImages.xml new file mode 100644 index 000000000000..7e23f83650ab --- /dev/null +++ b/python/plugins/processing/otb/description/CompareImages.xml @@ -0,0 +1,75 @@ + + CompareImages + otbcli_CompareImages + Images comparaison + Miscellaneous + Estimator between 2 images. + + ParameterRaster + ref.in + Reference image + Image used as reference in the comparison + False + + + ParameterNumber + ref.channel + Reference image channel + Used channel for the reference image + + + 1 + + + ParameterRaster + meas.in + Measured image + Image used as measured in the comparison + False + + + ParameterNumber + meas.channel + Measured image channel + Used channel for the measured image + + + 1 + + + ParameterNumber + roi.startx + Start X + ROI start x position. + + + 0 + + + ParameterNumber + roi.starty + Start Y + ROI start y position. + + + 0 + + + ParameterNumber + roi.sizex + Size X + Size along x in pixels. + + + 0 + + + ParameterNumber + roi.sizey + Size Y + Size along y in pixels. + + + 0 + + diff --git a/python/plugins/processing/otb/description/ComputeConfusionMatrix-raster.xml b/python/plugins/processing/otb/description/ComputeConfusionMatrix-raster.xml new file mode 100644 index 000000000000..d42f3fd620e0 --- /dev/null +++ b/python/plugins/processing/otb/description/ComputeConfusionMatrix-raster.xml @@ -0,0 +1,58 @@ + + ComputeConfusionMatrix-raster + otbcli_ComputeConfusionMatrix + ComputeConfusionMatrix (raster) + Learning + Computes the confusion matrix of a classification + + ParameterRaster + in + Input Image + The input classification image. + False + + + OutputFile + out + Matrix output + Filename to store the output matrix (csv format) + + + + ParameterSelection + ref + Ground truth + Choice of ground truth format + + + raster + + + 0 + + + ParameterRaster + ref.raster.in + Input reference image + Input image containing the ground truth labels + False + + + ParameterNumber + nodatalabel + Value for nodata pixels + Label for the NoData class. Such input pixels will be discarded from the ground truth and from the input classification map. By default, 'nodatalabel = 0'. + + + 0 + + + ParameterNumber + ram + Available RAM (Mb) + Available memory for processing (in MB) + + + 128 + + diff --git a/python/plugins/processing/otb/description/ComputeConfusionMatrix-vector.xml b/python/plugins/processing/otb/description/ComputeConfusionMatrix-vector.xml new file mode 100644 index 000000000000..42b830ccafcc --- /dev/null +++ b/python/plugins/processing/otb/description/ComputeConfusionMatrix-vector.xml @@ -0,0 +1,68 @@ + + ComputeConfusionMatrix-vector + otbcli_ComputeConfusionMatrix + ComputeConfusionMatrix (vector) + Learning + Computes the confusion matrix of a classification + + ParameterRaster + in + Input Image + The input classification image. + False + + + OutputFile + out + Matrix output + Filename to store the output matrix (csv format) + + + + ParameterSelection + ref + Ground truth + Choice of ground truth format + + + vector + + + 0 + + + ParameterFile + ref.vector.in + Input reference vector data + Input vector data of the ground truth + + False + + + ParameterString + ref.vector.field + Field name + Field name containing the label values + Class + + True + + + ParameterNumber + nodatalabel + Value for nodata pixels + Label for the NoData class. Such input pixels will be discarded from the ground truth and from the input classification map. By default, 'nodatalabel = 0'. + + + 0 + + + ParameterNumber + ram + Available RAM (Mb) + Available memory for processing (in MB) + + + 128 + + diff --git a/python/plugins/processing/otb/description/ComputeConfusionMatrix.txt b/python/plugins/processing/otb/description/ComputeConfusionMatrix.txt deleted file mode 100644 index 75a073ef6505..000000000000 --- a/python/plugins/processing/otb/description/ComputeConfusionMatrix.txt +++ /dev/null @@ -1,14 +0,0 @@ -Compute Confusion Matrix -otbcli_ComputeConfusionMatrix -Compute Confusion Matrix -Learning -ParameterRaster|-in|Input Image|False -OutputFile|-out|Matrix Output -ParameterSelection|-ref|Ground Truth|raster;vector|1 -ParameterRaster|-ref.raster.in|Input Reference Image|False -ParameterFile|-ref.vector.in|Input Vector Data|False -ParameterString|-ref.vector.field|Field name|None|None|dn -ParameterNumber|-labels|Number of labels|None|None|2 -ParameterNumber|-nodata|Value for nodata pixels|None|None|0 -ParameterNumber|-ram|Available RAM (Mb)|None|None|128 - diff --git a/python/plugins/processing/otb/description/ComputeImagesStatistics.txt b/python/plugins/processing/otb/description/ComputeImagesStatistics.txt deleted file mode 100644 index c5991623ef6e..000000000000 --- a/python/plugins/processing/otb/description/ComputeImagesStatistics.txt +++ /dev/null @@ -1,6 +0,0 @@ -ComputeImagesStatistics -otbcli_ComputeImagesStatistics -Compute Images second order statistics -Learning -ParameterMultipleInput|-il|Input images|3|False -OutputFile|-out|Output XML file diff --git a/python/plugins/processing/otb/description/ComputeImagesStatistics.xml b/python/plugins/processing/otb/description/ComputeImagesStatistics.xml new file mode 100644 index 000000000000..43c742d6796a --- /dev/null +++ b/python/plugins/processing/otb/description/ComputeImagesStatistics.xml @@ -0,0 +1,31 @@ + + ComputeImagesStatistics + otbcli_ComputeImagesStatistics + Compute Images second order statistics + Learning + Computes global mean and standard deviation for each band from a set of images and optionally saves the results in an XML file. + + ParameterMultipleInput + il + Input images + List of input images filenames. + + False + + + ParameterNumber + bv + Background Value + Background value to ignore in statistics computation. + + + 0.0 + + + OutputFile + out + Output XML file + XML filename where the statistics are saved for future reuse. + + + diff --git a/python/plugins/processing/otb/description/ComputeModulusAndPhase-OneEntry.xml b/python/plugins/processing/otb/description/ComputeModulusAndPhase-OneEntry.xml new file mode 100644 index 000000000000..bdc2f5229eff --- /dev/null +++ b/python/plugins/processing/otb/description/ComputeModulusAndPhase-OneEntry.xml @@ -0,0 +1,49 @@ + + ComputeModulusAndPhase-one-OneEntry + otbcli_ComputeModulusAndPhase + ComputeModulusAndPhase-one (OneEntry) + Miscellaneous + This application computes the modulus and the phase of a complex SAR data. + + ParameterSelection + nbinput + Number Of inputs + Choice about the number of input files used to store the real and imaginary part of the SAR image + + + one + + + 0 + + + ParameterRaster + nbinput.one.in + Input image + Image file with SAR data. + False + + + OutputRaster + mod + Modulus + Modulus of the input: sqrt(real*real + imag*imag). + + + + OutputRaster + pha + Phase + Phase of the input: atan2(imag, real). + + + + ParameterNumber + ram + Available RAM (Mb) + Available memory for processing (in MB) + + + 128 + + diff --git a/python/plugins/processing/otb/description/ComputeModulusAndPhase-TwoEntries.xml b/python/plugins/processing/otb/description/ComputeModulusAndPhase-TwoEntries.xml new file mode 100644 index 000000000000..336924e5605d --- /dev/null +++ b/python/plugins/processing/otb/description/ComputeModulusAndPhase-TwoEntries.xml @@ -0,0 +1,56 @@ + + ComputeModulusAndPhase-two-TwoEntries + otbcli_ComputeModulusAndPhase + ComputeModulusAndPhase-two (TwoEntries) + Miscellaneous + This application computes the modulus and the phase of a complex SAR data. + + ParameterSelection + nbinput + Number Of inputs + Choice about the number of input files used to store the real and imaginary part of the SAR image + + + two + + + 0 + + + ParameterRaster + nbinput.two.re + Real part input + Image file with real part of the SAR data. + False + + + ParameterRaster + nbinput.two.im + Imaginary part input + Image file with imaginary part of the SAR data. + False + + + OutputRaster + mod + Modulus + Modulus of the input: sqrt(real*real + imag*imag). + + + + OutputRaster + pha + Phase + Phase of the input: atan2(imag, real). + + + + ParameterNumber + ram + Available RAM (Mb) + Available memory for processing (in MB) + + + 128 + + diff --git a/python/plugins/processing/otb/description/ComputePolylineFeatureFromImage.txt b/python/plugins/processing/otb/description/ComputePolylineFeatureFromImage.txt deleted file mode 100644 index f0fafbaa2113..000000000000 --- a/python/plugins/processing/otb/description/ComputePolylineFeatureFromImage.txt +++ /dev/null @@ -1,13 +0,0 @@ -ComputePolylineFeatureFromImage -otbcli_ComputePolylineFeatureFromImage -Compute Polyline Feature From Image -Feature Extraction -ParameterRaster|-in|Input Image|False -ParameterVector|-vd|Vector Data|-1|False -ParameterSelection|-elev|Elevation management|dem;average|1 -ParameterFile|-elev.dem.path|DEM directory| -ParameterFile|-elev.dem.geoid|Geoid File|| -ParameterNumber|-elev.average.value|Average Elevation|None|None|0.0 -ParameterString|-expr|Feature expression| -ParameterString|-field|Feature name| -OutputVector|-out|Output Vector Data diff --git a/python/plugins/processing/otb/description/ConcatenateImages.txt b/python/plugins/processing/otb/description/ConcatenateImages.txt deleted file mode 100644 index 1f4173ed8059..000000000000 --- a/python/plugins/processing/otb/description/ConcatenateImages.txt +++ /dev/null @@ -1,7 +0,0 @@ -ConcatenateImages -otbcli_ConcatenateImages -Images Concatenation -Image Manipulation -ParameterMultipleInput|-il|Input images list|3|False -OutputRaster|-out|Output Image -ParameterNumber|-ram|Available RAM (Mb)|None|None|128 diff --git a/python/plugins/processing/otb/description/ConcatenateImages.xml b/python/plugins/processing/otb/description/ConcatenateImages.xml new file mode 100644 index 000000000000..eea11d897702 --- /dev/null +++ b/python/plugins/processing/otb/description/ConcatenateImages.xml @@ -0,0 +1,31 @@ + + ConcatenateImages + otbcli_ConcatenateImages + Images Concatenation + Image Manipulation + Concatenate a list of images of the same size into a single multi-channel one. + + ParameterMultipleInput + il + Input images list + The list of images to concatenate + + False + + + OutputRaster + out + Output Image + The concatenated output image + + + + ParameterNumber + ram + Available RAM (Mb) + Available memory for processing (in MB) + + + 128 + + diff --git a/python/plugins/processing/otb/description/ConcatenateVectorData.txt b/python/plugins/processing/otb/description/ConcatenateVectorData.txt deleted file mode 100644 index a7c76ec45d34..000000000000 --- a/python/plugins/processing/otb/description/ConcatenateVectorData.txt +++ /dev/null @@ -1,6 +0,0 @@ -ConcatenateVectorData -otbcli_ConcatenateVectorData -Concatenate -Vector Data Manipulation -ParameterMultipleInput|-vd|Input VectorDatas to concatenate|-1|False -OutputVector|-out|Concatenated VectorData diff --git a/python/plugins/processing/otb/description/ConcatenateVectorData.xml b/python/plugins/processing/otb/description/ConcatenateVectorData.xml new file mode 100644 index 000000000000..9b95a36fee95 --- /dev/null +++ b/python/plugins/processing/otb/description/ConcatenateVectorData.xml @@ -0,0 +1,22 @@ + + ConcatenateVectorData + otbcli_ConcatenateVectorData + Concatenate + Vector Data Manipulation + Concatenate VectorDatas + + ParameterMultipleInput + vd + Input VectorDatas to concatenate + VectorData files to be concatenated in an unique VectorData + + False + + + OutputVector + out + Concatenated VectorData + Output conctenated VectorData + + + diff --git a/python/plugins/processing/otb/description/ConnectedComponentSegmentation.txt b/python/plugins/processing/otb/description/ConnectedComponentSegmentation.txt deleted file mode 100644 index 26d18616f378..000000000000 --- a/python/plugins/processing/otb/description/ConnectedComponentSegmentation.txt +++ /dev/null @@ -1,13 +0,0 @@ -ConnectedComponentSegmentation -otbcli_ConnectedComponentSegmentation -Connected Component Segmentation -Segmentation -ParameterRaster|-in|Input Image|False -OutputVector|-out|Output Shape -ParameterString|-mask|Mask expression| -ParameterString|-expr|Connected Component Expression| -ParameterNumber|-minsize|Minimum Object Size|None|None|2 -ParameterString|-obia|OBIA Expression| -ParameterFile|-elev.dem|DEM directory|True -ParameterFile|-elev.geoid|Geoid File||True -ParameterNumber|-elev.default|Average Elevation|None|None|0.0 diff --git a/python/plugins/processing/otb/description/ConnectedComponentSegmentation.xml b/python/plugins/processing/otb/description/ConnectedComponentSegmentation.xml new file mode 100644 index 000000000000..8fad26e1b547 --- /dev/null +++ b/python/plugins/processing/otb/description/ConnectedComponentSegmentation.xml @@ -0,0 +1,66 @@ + + ConnectedComponentSegmentation + otbcli_ConnectedComponentSegmentation + Connected Component Segmentation + Segmentation + Connected component segmentation and object based image filtering of the input image according to user-defined criterions. + + ParameterRaster + in + Input Image + The image to segment. + False + + + OutputVector + out + Output Shape + The segmentation shape. + + + + ParameterString + mask + Mask expression + Mask mathematical expression (only if support image is given) + + + True + + + ParameterString + expr + Connected Component Expression + Formula used for connected component segmentation + + + False + + + ParameterNumber + minsize + Minimum Object Size + Min object size (area in pixel) + + + 2 + + + ParameterString + obia + OBIA Expression + OBIA mathematical expression + + + True + + + ParameterNumber + elev.default + Default elevation + This parameter allows to set the default height above ellipsoid when there is no DEM available, no coverage for some points or pixels with no_data in the DEM tiles, and no geoid file has been set. This is also used by some application as an average elevation value. + + + 0 + + diff --git a/python/plugins/processing/otb/description/Convert.txt b/python/plugins/processing/otb/description/Convert.txt deleted file mode 100644 index b7208bc008b2..000000000000 --- a/python/plugins/processing/otb/description/Convert.txt +++ /dev/null @@ -1,8 +0,0 @@ -Convert -otbcli_Convert -Image Conversion -Image Manipulation -ParameterRaster|-in|Input image|False -ParameterSelection|-type|Rescale type|none;linear;log2|0 -OutputRaster|-out|Output Image -ParameterNumber|-ram|Available RAM (Mb)|None|None|128 diff --git a/python/plugins/processing/otb/description/ConvertCartoToGeoPoint.txt b/python/plugins/processing/otb/description/ConvertCartoToGeoPoint.txt deleted file mode 100644 index db57628e80ba..000000000000 --- a/python/plugins/processing/otb/description/ConvertCartoToGeoPoint.txt +++ /dev/null @@ -1,12 +0,0 @@ -ConvertCartoToGeoPoint -otbcli_ConvertCartoToGeoPoint -Cartographic to geographic coordinates conversion -Geometry -ParameterNumber|-carto.x|X cartographic coordinates|None|None|0.0 -ParameterNumber|-carto.y|Y cartographic coordinates|None|None|0.0 -ParameterSelection|-mapproj|Output Cartographic Map Projection|utm;lambert2;lambert93;wgs;epsg|4 -ParameterNumber|-mapproj.utm.zone|Zone number|None|None|31 -ParameterBoolean|-mapproj.utm.northhem|Northern Hemisphere| -ParameterNumber|-mapproj.epsg.code|EPSG Code|None|None|32631 -ParameterNumber|-long|Output long|None|None|0.0 -ParameterNumber|-lat|Output lat|None|None|0.0 diff --git a/python/plugins/processing/otb/description/ConvertSensorToGeoPoint.txt b/python/plugins/processing/otb/description/ConvertSensorToGeoPoint.txt deleted file mode 100644 index 460155c241fe..000000000000 --- a/python/plugins/processing/otb/description/ConvertSensorToGeoPoint.txt +++ /dev/null @@ -1,11 +0,0 @@ -ConvertSensorToGeoPoint -otbcli_ConvertSensorToGeoPoint -Convert Sensor Point To Geographic Point -Geometry -ParameterRaster|-in|Sensor image|False -ParameterNumber|-input.idx|X value of desired point|None|None|0.0 -ParameterNumber|-input.idy|Y value of desired point|None|None|0.0 -ParameterNumber|-output.idx|Output Point Longitude|None|None|0.0 -ParameterNumber|-output.idy|Output Point Latitude|None|None|0.0 -ParameterString|-output.town|Main town near the coordinates computed| -ParameterString|-output.country|Country of the image| diff --git a/python/plugins/processing/otb/description/DSFuzzyModelEstimation.txt b/python/plugins/processing/otb/description/DSFuzzyModelEstimation.txt deleted file mode 100644 index 9ba7a4dd04a2..000000000000 --- a/python/plugins/processing/otb/description/DSFuzzyModelEstimation.txt +++ /dev/null @@ -1,12 +0,0 @@ -DSFuzzyModelEstimation -otbcli_DSFuzzyModelEstimation -Fuzzy Model estimation -Feature Extraction -ParameterVector|-psin|Input Positive Vector Data|-1|False -ParameterVector|-nsin|Input Negative Vector Data|-1|False -ParameterString|-cri|Criterion|((Belief + Plausibility)/2.) -ParameterNumber|-wgt|Weighting|None|None|0.5 -ParameterFile|-initmod|initialization model|| -ParameterNumber|-maxnbit|Maximum number of iterations|None|None|200 -ParameterBoolean|-optobs|Optimizer Observer| -OutputFile|-out|Output filename diff --git a/python/plugins/processing/otb/description/DimensionalityReduction-ica.xml b/python/plugins/processing/otb/description/DimensionalityReduction-ica.xml new file mode 100644 index 000000000000..4123cfec5f38 --- /dev/null +++ b/python/plugins/processing/otb/description/DimensionalityReduction-ica.xml @@ -0,0 +1,81 @@ + + DimensionalityReduction-ica + otbcli_DimensionalityReduction + DimensionalityReduction (ica) + Image Filtering + Perform Dimension reduction of the input image. + + ParameterRaster + in + Input Image + The input image to apply dimensionality reduction. + False + + + OutputRaster + out + Output Image + output image. Components are ordered by decreasing eigenvalues. + + + + OutputRaster + outinv + Inverse Output Image + reconstruct output image. + + + + ParameterSelection + method + Algorithm + Selection of the reduction dimension method. + + + ica + + + 0 + + + ParameterNumber + method.ica.iter + number of iterations + + + + 20 + + + ParameterNumber + method.ica.mu + Give the increment weight of W in [0, 1] + + + + 1 + + + ParameterNumber + nbcomp + Number of Components. + Number of relevant components kept. By default all components are kept. + + + 0 + + + ParameterBoolean + normalize + Normalize. + center AND reduce data before Dimensionality reduction. + True + + + OutputFile + outmatrix + Transformation matrix output + Filename to store the transformation matrix (csv format) + + + diff --git a/python/plugins/processing/otb/description/DimensionalityReduction-maf.xml b/python/plugins/processing/otb/description/DimensionalityReduction-maf.xml new file mode 100644 index 000000000000..99936940c9e4 --- /dev/null +++ b/python/plugins/processing/otb/description/DimensionalityReduction-maf.xml @@ -0,0 +1,56 @@ + + DimensionalityReduction-maf + otbcli_DimensionalityReduction + DimensionalityReduction (maf) + Image Filtering + Perform Dimension reduction of the input image. + + ParameterRaster + in + Input Image + The input image to apply dimensionality reduction. + False + + + OutputRaster + out + Output Image + output image. Components are ordered by decreasing eigenvalues. + + + + ParameterSelection + method + Algorithm + Selection of the reduction dimension method. + + + maf + + + 0 + + + ParameterNumber + nbcomp + Number of Components. + Number of relevant components kept. By default all components are kept. + + + 0 + + + ParameterBoolean + normalize + Normalize. + center AND reduce data before Dimensionality reduction. + True + + + OutputFile + outmatrix + Transformation matrix output + Filename to store the transformation matrix (csv format) + + + diff --git a/python/plugins/processing/otb/description/DimensionalityReduction-napca.xml b/python/plugins/processing/otb/description/DimensionalityReduction-napca.xml new file mode 100644 index 000000000000..752c0fe15416 --- /dev/null +++ b/python/plugins/processing/otb/description/DimensionalityReduction-napca.xml @@ -0,0 +1,81 @@ + + DimensionalityReduction-napca + otbcli_DimensionalityReduction + DimensionalityReduction (napca) + Image Filtering + Perform Dimension reduction of the input image. + + ParameterRaster + in + Input Image + The input image to apply dimensionality reduction. + False + + + OutputRaster + out + Output Image + output image. Components are ordered by decreasing eigenvalues. + + + + OutputRaster + outinv + Inverse Output Image + reconstruct output image. + + + + ParameterSelection + method + Algorithm + Selection of the reduction dimension method. + + + napca + + + 0 + + + ParameterNumber + method.napca.radiusx + Set the x radius of the sliding window. + + + + 1 + + + ParameterNumber + method.napca.radiusy + Set the y radius of the sliding window. + + + + 1 + + + ParameterNumber + nbcomp + Number of Components. + Number of relevant components kept. By default all components are kept. + + + 0 + + + ParameterBoolean + normalize + Normalize. + center AND reduce data before Dimensionality reduction. + True + + + OutputFile + outmatrix + Transformation matrix output + Filename to store the transformation matrix (csv format) + + + diff --git a/python/plugins/processing/otb/description/DimensionalityReduction-pca.xml b/python/plugins/processing/otb/description/DimensionalityReduction-pca.xml new file mode 100644 index 000000000000..2a6e83af65e4 --- /dev/null +++ b/python/plugins/processing/otb/description/DimensionalityReduction-pca.xml @@ -0,0 +1,63 @@ + + DimensionalityReduction-pca + otbcli_DimensionalityReduction + DimensionalityReduction (pca) + Image Filtering + Perform Dimension reduction of the input image. + + ParameterRaster + in + Input Image + The input image to apply dimensionality reduction. + False + + + OutputRaster + out + Output Image + output image. Components are ordered by decreasing eigenvalues. + + + + OutputRaster + outinv + Inverse Output Image + reconstruct output image. + + + + ParameterSelection + method + Algorithm + Selection of the reduction dimension method. + + + pca + + + 0 + + + ParameterNumber + nbcomp + Number of Components. + Number of relevant components kept. By default all components are kept. + + + 0 + + + ParameterBoolean + normalize + Normalize. + center AND reduce data before Dimensionality reduction. + True + + + OutputFile + outmatrix + Transformation matrix output + Filename to store the transformation matrix (csv format) + + + diff --git a/python/plugins/processing/otb/description/DimensionalityReduction.txt b/python/plugins/processing/otb/description/DimensionalityReduction.txt deleted file mode 100644 index f629a4590776..000000000000 --- a/python/plugins/processing/otb/description/DimensionalityReduction.txt +++ /dev/null @@ -1,16 +0,0 @@ -DimensionalityReduction -otbcli_DimensionalityReduction -Dimensionality reduction application -Image Filtering -ParameterRaster|-in|Input Image|False -OutputRaster|-out|Output Image -ParameterNumber|-rescale.outmin|Output min value|None|None|0.0 -ParameterNumber|-rescale.outmax|Output max value|None|None|255.0 -OutputRaster|-outinv| Inverse Output Image -ParameterSelection|-method|Algorithm|pca;napca;maf;ica|0 -ParameterNumber|-method.napca.radiusx|Set the x radius of the sliding window.|None|None|1 -ParameterNumber|-method.napca.radiusy|Set the y radius of the sliding window.|None|None|1 -ParameterNumber|-method.ica.iter|number of iterations |None|None|20 -ParameterNumber|-method.ica.mu|Give the increment weight of W in [0, 1]|None|None|1.0 -ParameterNumber|-nbcomp|Number of Components.|None|None|0 -ParameterBoolean|-normalize|Normalize.| diff --git a/python/plugins/processing/otb/description/DisparityMapToElevationMap.txt b/python/plugins/processing/otb/description/DisparityMapToElevationMap.txt deleted file mode 100644 index d2de6103203d..000000000000 --- a/python/plugins/processing/otb/description/DisparityMapToElevationMap.txt +++ /dev/null @@ -1,19 +0,0 @@ -DisparityMapToElevationMap -otbcli_DisparityMapToElevationMap -Disparity map to elevation map -Stereo -ParameterRaster|-io.in|Input disparity map|False -ParameterRaster|-io.left|Left sensor image|False -ParameterRaster|-io.right|Right sensor image|False -ParameterRaster|-io.lgrid|Left Grid|False -ParameterRaster|-io.rgrid|Right Grid|False -OutputRaster|-io.out|Output elevation map -ParameterRaster|-io.mask|Disparity mask|True -ParameterNumber|-step|DEM step|None|None|5.0 -ParameterNumber|-hmin|Minimum elevation expected|None|None|0.0 -ParameterNumber|-hmax|Maximum elevation expected|None|None|100.0 -ParameterSelection|-elev|Elevation management|dem;average|1 -ParameterFile|-elev.dem.path|DEM directory| -ParameterFile|-elev.dem.geoid|Geoid File|| -ParameterNumber|-elev.average.value|Average Elevation|None|None|0.0 -ParameterNumber|-ram|Available RAM (Mb)|None|None|128 diff --git a/python/plugins/processing/otb/description/EdgeExtraction-gradient.xml b/python/plugins/processing/otb/description/EdgeExtraction-gradient.xml new file mode 100644 index 000000000000..4c367d9593e2 --- /dev/null +++ b/python/plugins/processing/otb/description/EdgeExtraction-gradient.xml @@ -0,0 +1,51 @@ + + EdgeExtraction-gradient + otbcli_EdgeExtraction + EdgeExtraction (gradient) + Feature Extraction + Computes edge features on every pixel of the input image selected channel + + ParameterRaster + in + Input Image + The input image to compute the features on. + False + + + ParameterNumber + channel + Selected Channel + The selected channel index + + + 1 + + + ParameterNumber + ram + Available RAM (Mb) + Available memory for processing (in MB) + + + 128 + + + ParameterSelection + filter + Edge feature + Choice of edge feature + + + gradient + + + 0 + + + OutputRaster + out + Feature Output Image + Output image containing the edge features. + + + diff --git a/python/plugins/processing/otb/description/EdgeExtraction-sobel.xml b/python/plugins/processing/otb/description/EdgeExtraction-sobel.xml new file mode 100644 index 000000000000..80d9e1158b86 --- /dev/null +++ b/python/plugins/processing/otb/description/EdgeExtraction-sobel.xml @@ -0,0 +1,51 @@ + + EdgeExtraction-sobel + otbcli_EdgeExtraction + EdgeExtraction (sobel) + Feature Extraction + Computes edge features on every pixel of the input image selected channel + + ParameterRaster + in + Input Image + The input image to compute the features on. + False + + + ParameterNumber + channel + Selected Channel + The selected channel index + + + 1 + + + ParameterNumber + ram + Available RAM (Mb) + Available memory for processing (in MB) + + + 128 + + + ParameterSelection + filter + Edge feature + Choice of edge feature + + + sobel + + + 0 + + + OutputRaster + out + Feature Output Image + Output image containing the edge features. + + + diff --git a/python/plugins/processing/otb/description/EdgeExtraction-touzi.xml b/python/plugins/processing/otb/description/EdgeExtraction-touzi.xml new file mode 100644 index 000000000000..4238d64bbf3a --- /dev/null +++ b/python/plugins/processing/otb/description/EdgeExtraction-touzi.xml @@ -0,0 +1,60 @@ + + EdgeExtraction-touzi + otbcli_EdgeExtraction + EdgeExtraction (touzi) + Feature Extraction + Computes edge features on every pixel of the input image selected channel + + ParameterRaster + in + Input Image + The input image to compute the features on. + False + + + ParameterNumber + channel + Selected Channel + The selected channel index + + + 1 + + + ParameterNumber + ram + Available RAM (Mb) + Available memory for processing (in MB) + + + 128 + + + ParameterSelection + filter + Edge feature + Choice of edge feature + + + touzi + + + 0 + + + ParameterNumber + filter.touzi.xradius + The Radius + The Radius + + + 1 + + + OutputRaster + out + Feature Output Image + Output image containing the edge features. + + + diff --git a/python/plugins/processing/otb/description/EdgeExtraction.txt b/python/plugins/processing/otb/description/EdgeExtraction.txt deleted file mode 100644 index 73d54ee7819b..000000000000 --- a/python/plugins/processing/otb/description/EdgeExtraction.txt +++ /dev/null @@ -1,12 +0,0 @@ -Edge Extraction -otbcli_EdgeExtraction -Edge Extraction -Feature Extraction -ParameterRaster|-in|Input Image|False -OutputRaster|-out|Output Image -ParameterNumber|-channel|Selected Channel|None|None|1 -ParameterNumber|-ram|Available RAM (Mb)|None|None|128 -ParameterSelection|-filter|Edge feature|gradient;sobel;touzi|0 -ParameterNumber|-filter.touzi.xradius|The X Radius|None|None|1 -ParameterNumber|-filter.touzi.yradius|The Y Radius|None|None|1 - diff --git a/python/plugins/processing/otb/description/EdisonMeanShiftSegmentation.txt b/python/plugins/processing/otb/description/EdisonMeanShiftSegmentation.txt deleted file mode 100644 index fc6d1696a095..000000000000 --- a/python/plugins/processing/otb/description/EdisonMeanShiftSegmentation.txt +++ /dev/null @@ -1,11 +0,0 @@ -EdisonMeanShiftSegmentation -otbcli_Segmentation -Edison Mean Shift segmentation (labeled raster output) -Segmentation -ParameterRaster|-filter edison -in|Input Image|False -ParameterNumber|-filter.edison.spatialr|Spatial radius|None|None|5 -ParameterNumber|-filter.edison.ranger|Range radius|None|None|15.0 -ParameterNumber|-filter.edison.minsize|Min region size|0|None|100 -ParameterNumber|-filter.edison.scale|Scale Factor|0|None|1.0 -OutputRaster|-mode raster -mode.raster.out|Output labeled image - diff --git a/python/plugins/processing/otb/description/EdisonMeanShiftSegmentation_vector.txt b/python/plugins/processing/otb/description/EdisonMeanShiftSegmentation_vector.txt deleted file mode 100644 index c27d490c60f5..000000000000 --- a/python/plugins/processing/otb/description/EdisonMeanShiftSegmentation_vector.txt +++ /dev/null @@ -1,20 +0,0 @@ -EdisonMeanShiftSegmentationVector -otbcli_Segmentation -Edison Mean Shift segmentation (large-scale, vector output) -Segmentation -ParameterRaster|-filter edison -in|Input Image|False -ParameterNumber|-filter.edison.spatialr|Spatial radius|None|None|5 -ParameterNumber|-filter.edison.ranger|Range radius|None|None|15.0 -ParameterNumber|-filter.edison.minsize|Min region size|0|None|100 -ParameterNumber|-filter.edison.scale|Scale Factor|0|None|1.0 -OutputVector|-mode vector -mode.vector.out|Output vector file -ParameterVector|-mode.vector.inmask|Mask Image|-1|True -ParameterBoolean|-mode.vector.neighbor|8-neighbor connectivity|False -ParameterBoolean|-mode.vector.stitch|Stitch polygons|True -ParameterNumber|-mode.vector.minsize|Minimum object size|1|None|1 -ParameterNumber|-mode.vector.simplify|Simplify polygons|None|None|0.0 -ParameterString|-mode.vector.layername|Layer name |layer -ParemeterString|-mode.vector.fieldname|Geometry index field name|DN -ParameterNumber|-mode.vector.tilesize|Tile size|0|None|1024 -ParameterNumber|-mode.vector.startlabel|Starting geometry index|1|None|1 -ParameterSelection|-mode.vector.outmode|Writing mode (update file/overwrite file/overwrite layer/update layer)|ulco;ovw;ulovw;ulu|0 diff --git a/python/plugins/processing/otb/description/ExtractROI-fit.xml b/python/plugins/processing/otb/description/ExtractROI-fit.xml new file mode 100644 index 000000000000..968cbd8f2775 --- /dev/null +++ b/python/plugins/processing/otb/description/ExtractROI-fit.xml @@ -0,0 +1,58 @@ + + ExtractROI-fit + otbcli_ExtractROI + ExtractROI (fit) + Image Manipulation + Extract a ROI defined by the user. + + ParameterRaster + in + Input Image + Input image. + False + + + OutputRaster + out + Output Image + Output image. + + + + ParameterNumber + ram + Available RAM (Mb) + Available memory for processing (in MB) + + + 128 + + + ParameterSelection + mode + Extraction mode + + + + fit + + + 0 + + + ParameterRaster + mode.fit.ref + Reference image + Reference image to define the ROI + False + + + ParameterNumber + mode.fit.elev.default + Default elevation + This parameter allows to set the default height above ellipsoid when there is no DEM available, no coverage for some points or pixels with no_data in the DEM tiles, and no geoid file has been set. This is also used by some application as an average elevation value. + + + 0 + + diff --git a/python/plugins/processing/otb/description/ExtractROI-standard.xml b/python/plugins/processing/otb/description/ExtractROI-standard.xml new file mode 100644 index 000000000000..4eb65f3044fc --- /dev/null +++ b/python/plugins/processing/otb/description/ExtractROI-standard.xml @@ -0,0 +1,78 @@ + + ExtractROI-standard + otbcli_ExtractROI + ExtractROI (standard) + Image Manipulation + Extract a ROI defined by the user. + + ParameterRaster + in + Input Image + Input image. + False + + + OutputRaster + out + Output Image + Output image. + + + + ParameterNumber + ram + Available RAM (Mb) + Available memory for processing (in MB) + + + 128 + + + ParameterSelection + mode + Extraction mode + + + + standard + + + 0 + + + ParameterNumber + startx + Start X + ROI start x position. + + + 0 + + + ParameterNumber + starty + Start Y + ROI start y position. + + + 0 + + + ParameterNumber + sizex + Size X + size along x in pixels. + + + 0 + + + ParameterNumber + sizey + Size Y + size along y in pixels. + + + 0 + + diff --git a/python/plugins/processing/otb/description/ExtractROI.txt b/python/plugins/processing/otb/description/ExtractROI.txt deleted file mode 100644 index 411e7b4bdba7..000000000000 --- a/python/plugins/processing/otb/description/ExtractROI.txt +++ /dev/null @@ -1,11 +0,0 @@ -ExtractROI -otbcli_ExtractROI -Extract ROI -Image Manipulation -ParameterRaster|-in|Input Image|False -OutputRaster|-out|Output Image -ParameterNumber|-ram|Available RAM (Mb)|None|None|128 -ParameterNumber|-startx|Start X|None|None|0 -ParameterNumber|-starty|Start Y|None|None|0 -ParameterNumber|-sizex|Size X|None|None|0 -ParameterNumber|-sizey|Size Y|None|None|0 diff --git a/python/plugins/processing/otb/description/FineRegistration.txt b/python/plugins/processing/otb/description/FineRegistration.txt deleted file mode 100644 index 83554534dbf2..000000000000 --- a/python/plugins/processing/otb/description/FineRegistration.txt +++ /dev/null @@ -1,26 +0,0 @@ -FineRegistration -otbcli_FineRegistration -Fine Registration -Stereo -ParameterRaster|-ref|Reference Image|False -ParameterRaster|-sec|Secondary Image|False -OutputRaster|-out|Output Image -ParameterNumber|-erx|Exploration Radius X|None|None|0 -ParameterNumber|-ery|Exploration Radius Y|None|None|0 -ParameterNumber|-mrx|Metric Radius X|None|None|0 -ParameterNumber|-mry|Metric Radius Y|None|None|0 -ParameterRaster|-w|Image To Warp|True -OutputRaster|-wo|Output Warped Image -ParameterNumber|-cox|Coarse Offset X|None|None|0.0 -ParameterNumber|-coy|Coarse Offset Y|None|None|0.0 -ParameterNumber|-ssrx|Sub-Sampling Rate X|None|None|1.0 -ParameterNumber|-ssry|Sub-Sampling Rate Y|None|None|1.0 -ParameterNumber|-rgsx|Reference Gaussian Smoothing X|None|None|0.0 -ParameterNumber|-rgsy|Reference Gaussian Smoothing Y|None|None|0.0 -ParameterNumber|-sgsx|Secondary Gaussian Smoothing X|None|None|0.0 -ParameterNumber|-sgsy|Secondary Gaussian Smoothing Y|None|None|0.0 -ParameterString|-m|Metric| -ParameterNumber|-spa|SubPixelAccuracy|None|None|0.00999999977648 -ParameterNumber|-vmlt|Validity Mask Lower Threshold|None|None|0.0 -ParameterNumber|-vmut|Validity Mask Upper Threshold|None|None|0.0 -ParameterNumber|-ram|Available RAM (Mb)|None|None|128 diff --git a/python/plugins/processing/otb/description/FusionOfClassifications-dempstershafer.xml b/python/plugins/processing/otb/description/FusionOfClassifications-dempstershafer.xml new file mode 100644 index 000000000000..47f9d023cf8a --- /dev/null +++ b/python/plugins/processing/otb/description/FusionOfClassifications-dempstershafer.xml @@ -0,0 +1,74 @@ + + FusionOfClassifications-dempstershafer + otbcli_FusionOfClassifications + FusionOfClassifications (dempstershafer) + Learning + Fuses several classifications maps of the same image on the basis of class labels. + + ParameterMultipleInput + il + Input classifications + List of input classification maps to fuse. Labels in each classification image must represent the same class. + + False + + + ParameterSelection + method + Fusion method + Selection of the fusion method and its parameters. + + + dempstershafer + + + 0 + + + ParameterMultipleExternalInput + method.dempstershafer.cmfl + Confusion Matrices + A list of confusion matrix files (*.CSV format) to define the masses of belief and the class labels. Each file should be formatted the following way: the first line, beginning with a '#' symbol, should be a list of the class labels present in the corresponding input classification image, organized in the same order as the confusion matrix rows/columns. + False + + + ParameterSelection + method.dempstershafer.mob + Mass of belief measurement + Type of confusion matrix measurement used to compute the masses of belief of each classifier. + + + precision + recall + accuracy + kappa + + + 0 + + + ParameterNumber + nodatalabel + Label for the NoData class + Label for the NoData class. Such input pixels keep their NoData label in the output image and are not handled in the fusion process. By default, 'nodatalabel = 0'. + + + 0 + + + ParameterNumber + undecidedlabel + Label for the Undecided class + Label for the Undecided class. Pixels with more than 1 fused class are marked as Undecided. Please note that the Undecided value must be different from existing labels in the input classifications. By default, 'undecidedlabel = 0'. + + + 0 + + + OutputRaster + out + The output classification image + The output classification image resulting from the fusion of the input classification images. + + + diff --git a/python/plugins/processing/otb/description/FusionOfClassifications-majorityvoting.xml b/python/plugins/processing/otb/description/FusionOfClassifications-majorityvoting.xml new file mode 100644 index 000000000000..22a743bdd711 --- /dev/null +++ b/python/plugins/processing/otb/description/FusionOfClassifications-majorityvoting.xml @@ -0,0 +1,52 @@ + + FusionOfClassifications-majorityvoting + otbcli_FusionOfClassifications + FusionOfClassifications (majorityvoting) + Learning + Fuses several classifications maps of the same image on the basis of class labels. + + ParameterMultipleInput + il + Input classifications + List of input classification maps to fuse. Labels in each classification image must represent the same class. + + False + + + ParameterSelection + method + Fusion method + Selection of the fusion method and its parameters. + + + majorityvoting + + + 0 + + + ParameterNumber + nodatalabel + Label for the NoData class + Label for the NoData class. Such input pixels keep their NoData label in the output image and are not handled in the fusion process. By default, 'nodatalabel = 0'. + + + 0 + + + ParameterNumber + undecidedlabel + Label for the Undecided class + Label for the Undecided class. Pixels with more than 1 fused class are marked as Undecided. Please note that the Undecided value must be different from existing labels in the input classifications. By default, 'undecidedlabel = 0'. + + + 0 + + + OutputRaster + out + The output classification image + The output classification image resulting from the fusion of the input classification images. + + + diff --git a/python/plugins/processing/otb/description/FusionOfClassifications.txt b/python/plugins/processing/otb/description/FusionOfClassifications.txt deleted file mode 100644 index f40519c13014..000000000000 --- a/python/plugins/processing/otb/description/FusionOfClassifications.txt +++ /dev/null @@ -1,7 +0,0 @@ -Fusion of Classifications -otbcli_FusionOfClassifications -Fusion of Classifications -Learning -ParameterMultipleInput|-il|Input classifications|-1|False -ParameterNumber|-undecided|Label for the undecided class|None|None|0 -OutputRaster|-out|Output Image diff --git a/python/plugins/processing/otb/description/GrayScaleMorphologicalOperation-closing.xml b/python/plugins/processing/otb/description/GrayScaleMorphologicalOperation-closing.xml new file mode 100644 index 000000000000..00e204da52b0 --- /dev/null +++ b/python/plugins/processing/otb/description/GrayScaleMorphologicalOperation-closing.xml @@ -0,0 +1,72 @@ + + GrayScaleMorphologicalOperation-closing + otbcli_GrayScaleMorphologicalOperation + GrayScaleMorphologicalOperation (closing) + Feature Extraction + Performs morphological operations on a grayscale input image + + ParameterRaster + in + Input Image + The input image to be filtered. + False + + + OutputRaster + out + Feature Output Image + Output image containing the filtered output image. + + + + ParameterNumber + channel + Selected Channel + The selected channel index + + + 1 + + + ParameterNumber + ram + Available RAM (Mb) + Available memory for processing (in MB) + + + 128 + + + ParameterSelection + structype + Structuring Element Type + Choice of the structuring element type + + + ball + + + 0 + + + ParameterNumber + structype.ball.xradius + The Structuring Element Radius + The Structuring Element Radius + + + 5 + + + ParameterSelection + filter + Morphological Operation + Choice of the morphological operation + + + closing + + + 0 + + diff --git a/python/plugins/processing/otb/description/GrayScaleMorphologicalOperation-dilate.xml b/python/plugins/processing/otb/description/GrayScaleMorphologicalOperation-dilate.xml new file mode 100644 index 000000000000..c811ad2b1191 --- /dev/null +++ b/python/plugins/processing/otb/description/GrayScaleMorphologicalOperation-dilate.xml @@ -0,0 +1,72 @@ + + GrayScaleMorphologicalOperation-dilate + otbcli_GrayScaleMorphologicalOperation + GrayScaleMorphologicalOperation (dilate) + Feature Extraction + Performs morphological operations on a grayscale input image + + ParameterRaster + in + Input Image + The input image to be filtered. + False + + + OutputRaster + out + Feature Output Image + Output image containing the filtered output image. + + + + ParameterNumber + channel + Selected Channel + The selected channel index + + + 1 + + + ParameterNumber + ram + Available RAM (Mb) + Available memory for processing (in MB) + + + 128 + + + ParameterSelection + structype + Structuring Element Type + Choice of the structuring element type + + + ball + + + 0 + + + ParameterNumber + structype.ball.xradius + The Structuring Element Radius + The Structuring Element Radius + + + 5 + + + ParameterSelection + filter + Morphological Operation + Choice of the morphological operation + + + dilate + + + 0 + + diff --git a/python/plugins/processing/otb/description/GrayScaleMorphologicalOperation-erode.xml b/python/plugins/processing/otb/description/GrayScaleMorphologicalOperation-erode.xml new file mode 100644 index 000000000000..8e3602090f16 --- /dev/null +++ b/python/plugins/processing/otb/description/GrayScaleMorphologicalOperation-erode.xml @@ -0,0 +1,72 @@ + + GrayScaleMorphologicalOperation-erode + otbcli_GrayScaleMorphologicalOperation + GrayScaleMorphologicalOperation (erode) + Feature Extraction + Performs morphological operations on a grayscale input image + + ParameterRaster + in + Input Image + The input image to be filtered. + False + + + OutputRaster + out + Feature Output Image + Output image containing the filtered output image. + + + + ParameterNumber + channel + Selected Channel + The selected channel index + + + 1 + + + ParameterNumber + ram + Available RAM (Mb) + Available memory for processing (in MB) + + + 128 + + + ParameterSelection + structype + Structuring Element Type + Choice of the structuring element type + + + ball + + + 0 + + + ParameterNumber + structype.ball.xradius + The Structuring Element Radius + The Structuring Element Radius + + + 5 + + + ParameterSelection + filter + Morphological Operation + Choice of the morphological operation + + + erode + + + 0 + + diff --git a/python/plugins/processing/otb/description/GrayScaleMorphologicalOperation-opening.xml b/python/plugins/processing/otb/description/GrayScaleMorphologicalOperation-opening.xml new file mode 100644 index 000000000000..8e50230edd52 --- /dev/null +++ b/python/plugins/processing/otb/description/GrayScaleMorphologicalOperation-opening.xml @@ -0,0 +1,72 @@ + + GrayScaleMorphologicalOperation-opening + otbcli_GrayScaleMorphologicalOperation + GrayScaleMorphologicalOperation (opening) + Feature Extraction + Performs morphological operations on a grayscale input image + + ParameterRaster + in + Input Image + The input image to be filtered. + False + + + OutputRaster + out + Feature Output Image + Output image containing the filtered output image. + + + + ParameterNumber + channel + Selected Channel + The selected channel index + + + 1 + + + ParameterNumber + ram + Available RAM (Mb) + Available memory for processing (in MB) + + + 128 + + + ParameterSelection + structype + Structuring Element Type + Choice of the structuring element type + + + ball + + + 0 + + + ParameterNumber + structype.ball.xradius + The Structuring Element Radius + The Structuring Element Radius + + + 5 + + + ParameterSelection + filter + Morphological Operation + Choice of the morphological operation + + + opening + + + 0 + + diff --git a/python/plugins/processing/otb/description/GrayScaleMorphologicalOperation.txt b/python/plugins/processing/otb/description/GrayScaleMorphologicalOperation.txt deleted file mode 100644 index 15778b40fb85..000000000000 --- a/python/plugins/processing/otb/description/GrayScaleMorphologicalOperation.txt +++ /dev/null @@ -1,11 +0,0 @@ -Gray Scale Morphological Operation -otbcli_GrayScaleMorphologicalOperation -Gray Scale Morphological Operation -Image Filtering -ParameterRaster|-in|Input Image|False -OutputRaster|-out|Output Image -ParameterNumber|-channel|Selected Channel|None|None|1 -ParameterSelection|-structype|Structuring Element Type|ball;cross|0 -ParameterNumber|-structype.ball.xradius|The Structuring Element X Radius|None|None|5 -ParameterNumber|-structype.ball.yradius|The Structuring Element Y Radius|None|None|5 -ParameterSelection|-filter|Morphological Operation|dilate;erode;opening;closing|0 diff --git a/python/plugins/processing/otb/description/GridBasedImageResampling.txt b/python/plugins/processing/otb/description/GridBasedImageResampling.txt deleted file mode 100644 index 34ce865460af..000000000000 --- a/python/plugins/processing/otb/description/GridBasedImageResampling.txt +++ /dev/null @@ -1,18 +0,0 @@ -GridBasedImageResampling -otbcli_GridBasedImageResampling -Grid Based Image Resampling -Geometry -ParameterRaster|-io.in|Input image|False -OutputRaster|-io.out|Output Image -ParameterRaster|-grid.in|Input resampling grid|False -ParameterSelection|-grid.type|Grid Type|def;loc|0 -ParameterNumber|-out.ulx|Upper Left X|None|None|0.0 -ParameterNumber|-out.uly|Upper Left Y|None|None|0.0 -ParameterNumber|-out.sizex|Size X|None|None|0 -ParameterNumber|-out.sizey|Size Y|None|None|0 -ParameterNumber|-out.spacingx|Pixel Size X|None|None|1.0 -ParameterNumber|-out.spacingy|Pixel Size Y|None|None|1.0 -ParameterNumber|-out.default|Default value|None|None|0.0 -ParameterSelection|-interpolator|Interpolation|nn;linear;bco|2 -ParameterNumber|-interpolator.bco.radius|Radius for bicubic interpolation|None|None|2 -ParameterNumber|-ram|Available RAM (Mb)|None|None|128 diff --git a/python/plugins/processing/otb/description/HaralickTextureExtraction.txt b/python/plugins/processing/otb/description/HaralickTextureExtraction.txt deleted file mode 100644 index a1909c622f81..000000000000 --- a/python/plugins/processing/otb/description/HaralickTextureExtraction.txt +++ /dev/null @@ -1,16 +0,0 @@ -Haralick Texture Extraction -otbcli_HaralickTextureExtraction -Haralick Texture Extraction -Feature Extraction -ParameterRaster|-in|Input Image|False -OutputRaster|-out|Output Image -ParameterNumber|-ram|Available RAM (Mb)|None|None|128 -ParameterNumber|-channel|Raster Band|None|None|1 -ParameterNumber|-parameters.xrad|X Radius|None|None|1 -ParameterNumber|-parameters.yrad|Y Radius|None|None|1 -ParameterNumber|-parameters.xoff|X Offset|None|None|1 -ParameterNumber|-parameters.yoff|Y Offset|None|None|1 -ParameterNumber|-parameters.min|Image Minimum|None|None|1 -ParameterNumber|-parameters.max|Image Maximum|None|None|255 -ParameterNumber|-parameters.nbbin|Histogram number of bin|None|None|8 -ParameterSelection|-texture|Texture Set Selection|simple;advanced;higher|0 \ No newline at end of file diff --git a/python/plugins/processing/otb/description/HaralickTextureExtraction.xml b/python/plugins/processing/otb/description/HaralickTextureExtraction.xml new file mode 100644 index 000000000000..9ce1ceac932b --- /dev/null +++ b/python/plugins/processing/otb/description/HaralickTextureExtraction.xml @@ -0,0 +1,116 @@ + + HaralickTextureExtraction + otbcli_HaralickTextureExtraction + Haralick Texture Extraction + Feature Extraction + Computes textures on every pixel of the input image selected channel + + ParameterRaster + in + Input Image + The input image to compute the features on. + False + + + ParameterNumber + channel + Selected Channel + The selected channel index + + + 1 + + + ParameterNumber + ram + Available RAM (Mb) + Available memory for processing (in MB) + + + 128 + + + ParameterNumber + parameters.xrad + X Radius + X Radius + + + 2 + + + ParameterNumber + parameters.yrad + Y Radius + Y Radius + + + 2 + + + ParameterNumber + parameters.xoff + X Offset + X Offset + + + 1 + + + ParameterNumber + parameters.yoff + Y Offset + Y Offset + + + 1 + + + ParameterNumber + parameters.min + Image Minimum + Image Minimum + + + 0 + + + ParameterNumber + parameters.max + Image Maximum + Image Maximum + + + 255 + + + ParameterNumber + parameters.nbbin + Histogram number of bin + Histogram number of bin + + + 8 + + + ParameterSelection + texture + Texture Set Selection + Choice of The Texture Set + + + simple + advanced + higher + + + 0 + + + OutputRaster + out + Output Image + Output image containing the selected texture features. + + + diff --git a/python/plugins/processing/otb/description/HooverCompareSegmentation.txt b/python/plugins/processing/otb/description/HooverCompareSegmentation.txt deleted file mode 100644 index af1d02f8bea5..000000000000 --- a/python/plugins/processing/otb/description/HooverCompareSegmentation.txt +++ /dev/null @@ -1,14 +0,0 @@ -HooverCompareSegmentation -otbcli_HooverCompareSegmentation -Hoover compare segmentation -Segmentation -ParameterRaster|-ingt|Input ground truth|False -ParameterRaster|-inms|Input machine segmentation|False -ParameterNumber|-bg|Background label|None|None|0 -ParameterNumber|-th|Overlapping threshold|None|None|0.75 -OutputRaster|-outgt|Colored ground truth output -OutputRaster|-outms|Colored machine segmentation output -ParameterNumber|-rc|Correct detection score|None|None|0.0 -ParameterNumber|-rf|Over-segmentation score|None|None|0.0 -ParameterNumber|-ra|Under-segmentation score|None|None|0.0 -ParameterNumber|-rm|Missed detection score|None|None|0.0 diff --git a/python/plugins/processing/otb/description/HooverCompareSegmentation.xml b/python/plugins/processing/otb/description/HooverCompareSegmentation.xml new file mode 100644 index 000000000000..7c772ecbc39f --- /dev/null +++ b/python/plugins/processing/otb/description/HooverCompareSegmentation.xml @@ -0,0 +1,89 @@ + + HooverCompareSegmentation + otbcli_HooverCompareSegmentation + Hoover compare segmentation + Segmentation + Compare two segmentations with Hoover metrics + + ParameterRaster + ingt + Input ground truth + A partial ground truth segmentation image. + False + + + ParameterRaster + inms + Input machine segmentation + A machine segmentation image. + False + + + ParameterNumber + bg + Background label + Label value of the background in the input segmentations + + + 0 + + + ParameterNumber + th + Overlapping threshold + Overlapping threshold used to find Hoover instances. + + + 0.75 + + + OutputRaster + outgt + Colored ground truth output + The colored ground truth output image. + + + + OutputRaster + outms + Colored machine segmentation output + The colored machine segmentation output image. + + + + ParameterNumber + rc + Correct detection score + Overall score for correct detection (RC) + + + 0.0 + + + ParameterNumber + rf + Over-segmentation score + Overall score for over segmentation (RF) + + + 0.0 + + + ParameterNumber + ra + Under-segmentation score + Overall score for under segmentation (RA) + + + 0.0 + + + ParameterNumber + rm + Missed detection score + Overall score for missed detection (RM) + + + 0.0 + + diff --git a/python/plugins/processing/otb/description/HyperspectralUnmixing.txt b/python/plugins/processing/otb/description/HyperspectralUnmixing.txt deleted file mode 100644 index dd9fd59a877f..000000000000 --- a/python/plugins/processing/otb/description/HyperspectralUnmixing.txt +++ /dev/null @@ -1,8 +0,0 @@ -HyperspectralUnmixing -otbcli_HyperspectralUnmixing -Hyperspectral data unmixing -Miscellaneous -ParameterRaster|-in|Input Image Filename|False -OutputRaster|-out|Output Image -ParameterRaster|-ie|Input endmembers|False -ParameterSelection|-ua|Unmixing algorithm|ucls;ncls;isra;mdmdnmf|0 diff --git a/python/plugins/processing/otb/description/ImageClassifier.xml b/python/plugins/processing/otb/description/ImageClassifier.xml new file mode 100644 index 000000000000..4f799e5e299a --- /dev/null +++ b/python/plugins/processing/otb/description/ImageClassifier.xml @@ -0,0 +1,53 @@ + + ImageClassifier + otbcli_ImageClassifier + Image Classification + Learning + Performs a classification of the input image according to a model file. + + ParameterRaster + in + Input Image + The input image to classify. + False + + + ParameterRaster + mask + Input Mask + The mask allows to restrict classification of the input image to the area where mask pixel values are greater than 0. + True + + + ParameterFile + model + Model file + A model file (produced by TrainImagesClassifier application, maximal class label = 65535). + + False + + + ParameterFile + imstat + Statistics file + A XML file containing mean and standard deviation to center and reduce samples before classification (produced by ComputeImagesStatistics application). + + True + + + OutputRaster + out + Output Image + Output image containing class labels + + + + ParameterNumber + ram + Available RAM (Mb) + Available memory for processing (in MB) + + + 128 + + diff --git a/python/plugins/processing/otb/description/ImageEnvelope.txt b/python/plugins/processing/otb/description/ImageEnvelope.txt deleted file mode 100644 index a4b1ada7079b..000000000000 --- a/python/plugins/processing/otb/description/ImageEnvelope.txt +++ /dev/null @@ -1,12 +0,0 @@ -ImageEnvelope -otbcli_ImageEnvelope -Image Envelope -Geometry -ParameterRaster|-in|Input Image|False -OutputVector|-out|Output Vector Data -ParameterNumber|-sr|Sampling Rate|None|None|0 -ParameterSelection|-elev|Elevation management|dem;average|1 -ParameterFile|-elev.dem.path|DEM directory| -ParameterFile|-elev.dem.geoid|Geoid File|| -ParameterNumber|-elev.average.value|Average Elevation|None|None|0.0 -ParameterString|-proj|Projection| diff --git a/python/plugins/processing/otb/description/ImageEnvelope.xml b/python/plugins/processing/otb/description/ImageEnvelope.xml new file mode 100644 index 000000000000..66d4e3ecc61c --- /dev/null +++ b/python/plugins/processing/otb/description/ImageEnvelope.xml @@ -0,0 +1,39 @@ + + ImageEnvelope + otbcli_ImageEnvelope + Image Envelope + Geometry + Extracts an image envelope. + + ParameterRaster + in + Input Image + Input image. + False + + + OutputVector + out + Output Vector Data + Vector data file containing the envelope + + + + ParameterNumber + sr + Sampling Rate + Sampling rate for image edges (in pixel) + + + 0 + + + ParameterString + proj + Projection + Projection to be used to compute the envelope (default is WGS84) + + + True + + diff --git a/python/plugins/processing/otb/description/ImageSVMClassifier.txt b/python/plugins/processing/otb/description/ImageSVMClassifier.txt deleted file mode 100644 index 186ca2647025..000000000000 --- a/python/plugins/processing/otb/description/ImageSVMClassifier.txt +++ /dev/null @@ -1,10 +0,0 @@ -ImageSVMClassifier -otbcli_ImageSVMClassifier -Image SVM Classification -Learning -ParameterRaster|-in|Input Image|False -ParameterRaster|-mask|Input Mask|True -ParameterFile|-svm|SVM Model file|| -ParameterFile|-imstat|Statistics file| -OutputRaster|-out|Output Image -ParameterNumber|-ram|Available RAM (Mb)|None|None|128 diff --git a/python/plugins/processing/otb/description/KMeansClassification.txt b/python/plugins/processing/otb/description/KMeansClassification.txt deleted file mode 100644 index b44cea5d5744..000000000000 --- a/python/plugins/processing/otb/description/KMeansClassification.txt +++ /dev/null @@ -1,14 +0,0 @@ -KMeansClassification -otbcli_KMeansClassification -Unsupervised KMeans image classification -Learning -ParameterRaster|-in|Input Image|False -OutputRaster|-out|Output Image -ParameterNumber|-ram|Available RAM (Mb)|None|None|128 -ParameterRaster|-vm|Validity Mask|True -ParameterNumber|-ts|Training set size|None|None|100 -ParameterNumber|-nc|Number of classes|None|None|5 -ParameterNumber|-maxit|Maximum number of iterations|None|None|1000 -ParameterNumber|-ct|Convergence threshold|None|None|9.99999974738e-05 -OutputFile|-outmeans|Centroid filename -ParameterNumber|-rand|set user defined seed|None|None|0 diff --git a/python/plugins/processing/otb/description/KMeansClassification.xml b/python/plugins/processing/otb/description/KMeansClassification.xml new file mode 100644 index 000000000000..7c2d15b71388 --- /dev/null +++ b/python/plugins/processing/otb/description/KMeansClassification.xml @@ -0,0 +1,80 @@ + + KMeansClassification + otbcli_KMeansClassification + Unsupervised KMeans image classification + Learning + Unsupervised KMeans image classification + + ParameterRaster + in + Input Image + Input image to classify. + False + + + OutputRaster + out + Output Image + Output image containing the class indexes. + + + + ParameterNumber + ram + Available RAM (Mb) + Available memory for processing (in MB) + + + 128 + + + ParameterRaster + vm + Validity Mask + Validity mask. Only non-zero pixels will be used to estimate KMeans modes. + True + + + ParameterNumber + ts + Training set size + Size of the training set (in pixels). + + + 100 + + + ParameterNumber + nc + Number of classes + Number of modes, which will be used to generate class membership. + + + 5 + + + ParameterNumber + maxit + Maximum number of iterations + Maximum number of iterations for the learning step. + + + 1000 + + + ParameterNumber + ct + Convergence threshold + Convergence threshold for class centroid (L2 distance, by default 0.0001). + + + 0.0001 + + + OutputFile + outmeans + Centroid filename + Output text file containing centroid positions + + + diff --git a/python/plugins/processing/otb/description/KmzExport.txt b/python/plugins/processing/otb/description/KmzExport.txt deleted file mode 100644 index f081a440a6dc..000000000000 --- a/python/plugins/processing/otb/description/KmzExport.txt +++ /dev/null @@ -1,13 +0,0 @@ -KmzExport -otbcli_KmzExport -Image to KMZ Export -Miscellaneous -ParameterRaster|-in|Input image|False -OutputFile|-out|Output .kmz product -ParameterNumber|-tilesize|Tile Size|None|None|256 -ParameterRaster|-logo|Image logo|True -ParameterRaster|-legend|Image legend|True -ParameterSelection|-elev|Elevation management|dem;average|1 -ParameterString|-elev.dem|DEM directory|True -ParameterFile|-elev.geoid|Geoid File| -ParameterNumber|-elev.default|Average Elevation|None|None|0.0 \ No newline at end of file diff --git a/python/plugins/processing/otb/description/KmzExport.xml b/python/plugins/processing/otb/description/KmzExport.xml new file mode 100644 index 000000000000..9eef07197da9 --- /dev/null +++ b/python/plugins/processing/otb/description/KmzExport.xml @@ -0,0 +1,53 @@ + + KmzExport + otbcli_KmzExport + Image to KMZ Export + Miscellaneous + Export the input image in a KMZ product. + + ParameterRaster + in + Input image + Input image + False + + + OutputFile + out + Output .kmz product + Output Kmz product directory (with .kmz extension) + + + + ParameterNumber + tilesize + Tile Size + Size of the tiles in the kmz product, in number of pixels (default = 512). + + + 512 + + + ParameterRaster + logo + Image logo + Path to the image logo to add to the KMZ product. + True + + + ParameterRaster + legend + Image legend + Path to the image legend to add to the KMZ product. + True + + + ParameterNumber + elev.default + Default elevation + This parameter allows to set the default height above ellipsoid when there is no DEM available, no coverage for some points or pixels with no_data in the DEM tiles, and no geoid file has been set. This is also used by some application as an average elevation value. + + + 0 + + diff --git a/python/plugins/processing/otb/description/LSMSSegmentation.xml b/python/plugins/processing/otb/description/LSMSSegmentation.xml new file mode 100644 index 000000000000..14449f66bb82 --- /dev/null +++ b/python/plugins/processing/otb/description/LSMSSegmentation.xml @@ -0,0 +1,88 @@ + + LSMSSegmentation + otbcli_LSMSSegmentation + Exact Large-Scale Mean-Shift segmentation, step 2 + Segmentation + Second step of the exact Large-Scale Mean-Shift segmentation workflow. + + ParameterRaster + in + Filtered image + The filtered image (cf. Adaptive MeanShift Smoothing application). + False + + + ParameterRaster + inpos + Spatial image + The spatial image. Spatial input is the displacement map (output of the Adaptive MeanShift Smoothing application). + True + + + OutputRaster + out + Output Image + The output image. The output image is the segmentation of the filtered image. It is recommended to set the pixel type to uint32. + + + + ParameterNumber + ranger + Range radius + Range radius defining the radius (expressed in radiometry unit) in the multi-spectral space. + + + 15 + + + ParameterNumber + spatialr + Spatial radius + Spatial radius of the neighborhood. + + + 5 + + + ParameterNumber + minsize + Minimum Region Size + Minimum Region Size. If, after the segmentation, a region is of size lower than this criterion, the region is deleted. + + + 0 + + + ParameterNumber + tilesizex + Size of tiles in pixel (X-axis) + Size of tiles along the X-axis. + + + 500 + + + ParameterNumber + tilesizey + Size of tiles in pixel (Y-axis) + Size of tiles along the Y-axis. + + + 500 + + + ParameterFile + tmpdir + Directory where to write temporary files + This applications need to write temporary files for each tile. This parameter allows choosing the path where to write those files. If disabled, the current path will be used. + + True + + + ParameterBoolean + cleanup + Temporary files cleaning + If activated, the application will try to clean all temporary files it created + True + + diff --git a/python/plugins/processing/otb/description/LSMSSmallRegionsMerging.xml b/python/plugins/processing/otb/description/LSMSSmallRegionsMerging.xml new file mode 100644 index 000000000000..9cb0621e80c3 --- /dev/null +++ b/python/plugins/processing/otb/description/LSMSSmallRegionsMerging.xml @@ -0,0 +1,55 @@ + + LSMSSmallRegionsMerging + otbcli_LSMSSmallRegionsMerging + Exact Large-Scale Mean-Shift segmentation, step 3 (optional) + Segmentation + Third (optional) step of the exact Large-Scale Mean-Shift segmentation workflow. + + ParameterRaster + in + Input image + The input image. + False + + + ParameterRaster + inseg + Segmented image + The segmented image input. Segmented image input is the segmentation of the input image. + False + + + OutputRaster + out + Output Image + The output image. The output image is the input image where the minimal regions have been merged. + + + + ParameterNumber + minsize + Minimum Region Size + Minimum Region Size. If, after the segmentation, a region is of size lower than this criterion, the region is merged with the "nearest" region (radiometrically). + + + 50 + + + ParameterNumber + tilesizex + Size of tiles in pixel (X-axis) + Size of tiles along the X-axis. + + + 500 + + + ParameterNumber + tilesizey + Size of tiles in pixel (Y-axis) + Size of tiles along the Y-axis. + + + 500 + + diff --git a/python/plugins/processing/otb/description/LSMSVectorization.xml b/python/plugins/processing/otb/description/LSMSVectorization.xml new file mode 100644 index 000000000000..2d908bddb4d4 --- /dev/null +++ b/python/plugins/processing/otb/description/LSMSVectorization.xml @@ -0,0 +1,46 @@ + + LSMSVectorization + otbcli_LSMSVectorization + Exact Large-Scale Mean-Shift segmentation, step 4 + Segmentation + Fourth step of the exact Large-Scale Mean-Shift segmentation workflow. + + ParameterRaster + in + Input Image + The input image. + False + + + ParameterRaster + inseg + Segmented image + The segmented image input. Segmented image input is the segmentation of the input image. + False + + + OutputVector + out + Output GIS vector file + The output GIS vector file, representing the vectorized version of the segmented image where the features of the polygons are the radiometric means and variances. + + + + ParameterNumber + tilesizex + Size of tiles in pixel (X-axis) + Size of tiles along the X-axis. + + + 500 + + + ParameterNumber + tilesizey + Size of tiles in pixel (Y-axis) + Size of tiles along the Y-axis. + + + 500 + + diff --git a/python/plugins/processing/otb/description/LineSegmentDetection.txt b/python/plugins/processing/otb/description/LineSegmentDetection.txt deleted file mode 100644 index 1354eba52d2d..000000000000 --- a/python/plugins/processing/otb/description/LineSegmentDetection.txt +++ /dev/null @@ -1,11 +0,0 @@ -LineSegmentDetection -otbcli_LineSegmentDetection -Line segment detection -Feature Extraction -ParameterRaster|-in|Input Image|False -OutputVector|-out|Output Detected lines -ParameterSelection|-elev|Elevation management|dem;average|1 -ParameterFile|-elev.dem.path|DEM directory| -ParameterFile|-elev.dem.geoid|Geoid File|| -ParameterNumber|-elev.average.value|Average Elevation|None|None|0.0 -ParameterBoolean|-norescale|No rescaling in [0, 255]| diff --git a/python/plugins/processing/otb/description/LineSegmentDetection.xml b/python/plugins/processing/otb/description/LineSegmentDetection.xml new file mode 100644 index 000000000000..20822d5dc351 --- /dev/null +++ b/python/plugins/processing/otb/description/LineSegmentDetection.xml @@ -0,0 +1,28 @@ + + LineSegmentDetection + otbcli_LineSegmentDetection + Line segment detection + Feature Extraction + Detect line segments in raster + + ParameterRaster + in + Input Image + Input image on which lines will be detected. + False + + + OutputVector + out + Output Detected lines + Output detected line segments (vector data). + + + + ParameterBoolean + norescale + No rescaling in [0, 255] + By default, the input image amplitude is rescaled between [0,255]. Turn on this parameter to skip rescaling + True + + diff --git a/python/plugins/processing/otb/description/LocalStatisticExtraction.txt b/python/plugins/processing/otb/description/LocalStatisticExtraction.txt deleted file mode 100644 index eeb039cfd4bd..000000000000 --- a/python/plugins/processing/otb/description/LocalStatisticExtraction.txt +++ /dev/null @@ -1,9 +0,0 @@ -Local Statistic Extraction -otbcli_LocalStatisticExtraction -Local Statistic Extraction -Feature Extraction -ParameterRaster|-in|Input Image|False -OutputRaster|-out|Output Image -ParameterNumber|-channel|Selected Channel|None|None|1 -ParameterNumber|-ram|Available RAM (Mb)|None|None|128 -ParameterNumber|-radius|Neighborhood radius|None|None|3 diff --git a/python/plugins/processing/otb/description/LocalStatisticExtraction.xml b/python/plugins/processing/otb/description/LocalStatisticExtraction.xml new file mode 100644 index 000000000000..f94caa6580fc --- /dev/null +++ b/python/plugins/processing/otb/description/LocalStatisticExtraction.xml @@ -0,0 +1,48 @@ + + LocalStatisticExtraction + otbcli_LocalStatisticExtraction + Local Statistic Extraction + Feature Extraction + Computes local statistical moments on every pixel in the selected channel of the input image + + ParameterRaster + in + Input Image + The input image to compute the features on. + False + + + ParameterNumber + channel + Selected Channel + The selected channel index + + + 1 + + + ParameterNumber + ram + Available RAM (Mb) + Available memory for processing (in MB) + + + 128 + + + ParameterNumber + radius + Neighborhood radius + The computational window radius. + + + 3 + + + OutputRaster + out + Feature Output Image + Output image containing the local statistical moments. + + + diff --git a/python/plugins/processing/otb/description/MaximumAutocorrelationFactor.txt b/python/plugins/processing/otb/description/MaximumAutocorrelationFactor.txt deleted file mode 100644 index 32b047e6a66e..000000000000 --- a/python/plugins/processing/otb/description/MaximumAutocorrelationFactor.txt +++ /dev/null @@ -1,6 +0,0 @@ -MaximumAutocorrelationFactor -otbcli_MaximumAutocorrelationFactor -Maximum Auto-correlation Factor Decomposition -Image Filtering -ParameterRaster|-in|Input Image|False -OutputRaster|-out|MAF output diff --git a/python/plugins/processing/otb/description/MeanShiftSegmentation.txt b/python/plugins/processing/otb/description/MeanShiftSegmentation.txt deleted file mode 100644 index a8ad1cdcc95d..000000000000 --- a/python/plugins/processing/otb/description/MeanShiftSegmentation.txt +++ /dev/null @@ -1,12 +0,0 @@ -MeanShiftSegmentation -otbcli_Segmentation -Mean Shift segmentation (labeled raster output) -Segmentation -ParameterRaster|-filter meanshift -in|Input Image|False -ParameterNumber|-filter.meanshift.spatialr|Spatial radius|None|None|5 -ParameterNumber|-filter.meanshift.thres|Mode convergence threshold|None|None|0.1 -ParameterNumber|-filter.meanshift.ranger|Range radius|None|None|15.0 -ParameterNumber|-filter.meanshift.minsize|Min region size|0|None|100 -ParameterNumber|-filter.meanshift.maxiter|Maximum number of iterations|0|None|100 -OutputRaster|-mode raster -mode.raster.out|Output labeled image - diff --git a/python/plugins/processing/otb/description/MeanShiftSegmentation_vector.txt b/python/plugins/processing/otb/description/MeanShiftSegmentation_vector.txt deleted file mode 100644 index 575c74741518..000000000000 --- a/python/plugins/processing/otb/description/MeanShiftSegmentation_vector.txt +++ /dev/null @@ -1,22 +0,0 @@ -MeanShiftSegmentationVector -otbcli_Segmentation -Mean Shift segmentation (large-scale, vector output) -Segmentation -ParameterRaster|-filter meanshift -in|Input Image|False -ParameterNumber|-filter.meanshift.spatialr|Spatial radius|None|None|5 -ParameterNumber|-filter.meanshift.thres|Mode convergence threshold|None|None|0.1 -ParameterNumber|-filter.meanshift.ranger|Range radius|None|None|15.0 -ParameterNumber|-filter.meanshift.minsize|Min region size|0|None|100 -ParameterNumber|-filter.meanshift.maxiter|Maximum number of iterations|0|None|100 -OutputVector|-mode vector -mode.vector.out|Output vector file -ParameterVector|-mode.vector.inmask|Mask Image|-1|True -ParameterBoolean|-mode.vector.neighbor|8-neighbor connectivity|False -ParameterBoolean|-mode.vector.stitch|Stitch polygons|True -ParameterNumber|-mode.vector.minsize|Minimum object size|1|None|1 -ParameterNumber|-mode.vector.simplify|Simplify polygons|None|None|0.0 -ParameterString|-mode.vector.layername|Layer name |layer -ParemeterString|-mode.vector.fieldname|Geometry index field name|DN -ParameterNumber|-mode.vector.tilesize|Tile size|0|None|1024 -ParameterNumber|-mode.vector.startlabel|Starting geometry index|1|None|1 -ParameterSelection|-mode.vector.outmode|Writing mode (update file/overwrite file/overwrite layer/update layer)|ulco;ovw;ulovw;ulu|0 -ParameterString|-mode.vector.ogroptions|OGR options for layer creation| diff --git a/python/plugins/processing/otb/description/MeanShiftSmoothing.txt b/python/plugins/processing/otb/description/MeanShiftSmoothing.txt deleted file mode 100644 index dce783d133e4..000000000000 --- a/python/plugins/processing/otb/description/MeanShiftSmoothing.txt +++ /dev/null @@ -1,11 +0,0 @@ -MeanShiftSmoothing -otbcli_MeanShiftSmoothing -Mean Shift filtering -Image Filtering -ParameterRaster|-in|Input Image|False -OutputRaster|-fout|Filtered output -ParameterNumber|-spatialr|Spatial radius|None|None|5 -ParameterNumber|-ranger|Range radius|None|None|15.0 -ParameterNumber|-thres|Mode convergence threshold|None|None|0.10000000149 -ParameterNumber|-maxiter|Maximum number of iterations|None|None|100 -ParameterBoolean|-modesearch|Mode search.|True diff --git a/python/plugins/processing/otb/description/MeanShiftSmoothing.xml b/python/plugins/processing/otb/description/MeanShiftSmoothing.xml new file mode 100644 index 000000000000..d0253d84d00f --- /dev/null +++ b/python/plugins/processing/otb/description/MeanShiftSmoothing.xml @@ -0,0 +1,80 @@ + + MeanShiftSmoothing + otbcli_MeanShiftSmoothing + Mean Shift filtering (can be used as Exact Large-Scale Mean-Shift segmentation, step 1) + Image Filtering + Perform mean shift filtering + + ParameterRaster + in + Input Image + The input image. + False + + + OutputRaster + fout + Filtered output + The filtered output image. + + + + OutputRaster + foutpos + Spatial image + The spatial image output. Spatial image output is a displacement map (pixel position after convergence). + + + + ParameterNumber + spatialr + Spatial radius + Spatial radius of the neighborhood. + + + 5 + + + ParameterNumber + ranger + Range radius + Range radius defining the radius (expressed in radiometry unit) in the multi-spectral space. + + + 15 + + + ParameterNumber + thres + Mode convergence threshold + Algorithm iterative scheme will stop if mean-shift vector is below this threshold or if iteration number reached maximum number of iterations. + + + 0.1 + + + ParameterNumber + maxiter + Maximum number of iterations + Algorithm iterative scheme will stop if convergence hasn't been reached after the maximum number of iterations. + + + 100 + + + ParameterNumber + rangeramp + Range radius coefficient + This coefficient makes dependent the ranger of the colorimetry of the filtered pixel : y = rangeramp*x+ranger. + + + 0 + + + ParameterBoolean + modesearch + Mode search. + If activated pixel iterative convergence is stopped if the path . Be careful, with this option, the result will slightly depend on thread number + True + + diff --git a/python/plugins/processing/otb/description/MorphologicalProfilesSegmentation_raster.txt b/python/plugins/processing/otb/description/MorphologicalProfilesSegmentation_raster.txt deleted file mode 100644 index 9ca8a9be4eb8..000000000000 --- a/python/plugins/processing/otb/description/MorphologicalProfilesSegmentation_raster.txt +++ /dev/null @@ -1,10 +0,0 @@ -MorphologicalProfilesSegmentationRaster -otbcli_Segmentation -Morphological Profiles Based Segmentation (labeled raster output) -Segmentation -ParameterRaster|-filter mprofiles -in|Input Image|False -ParameterNumber|-filter.mprofiles.size|Profile Size|None|None|5 -ParameterNumber|-filter.mprofiles.start|Initial Radius|None|None|1 -ParameterNumber|-filter.mprofiles.step|Radius Step|None|None|1 -ParameterNumber|-filter.mprofiles.sigma|Threshold of final decision rule|0|None|1 -OutputRaster|-mode raster -mode.raster.out|Output labeled image \ No newline at end of file diff --git a/python/plugins/processing/otb/description/MorphologicalProfilesSegmentation_vector.txt b/python/plugins/processing/otb/description/MorphologicalProfilesSegmentation_vector.txt deleted file mode 100644 index 555b4d778a80..000000000000 --- a/python/plugins/processing/otb/description/MorphologicalProfilesSegmentation_vector.txt +++ /dev/null @@ -1,21 +0,0 @@ -MorphologicalProfilesSegmentationVector -otbcli_Segmentation -Morphological Profiles Based Segmentation (large-scale, vector output) -Segmentation -ParameterRaster|-filter mprofiles -in|Input Image|False -ParameterNumber|-filter.mprofiles.size|Profile Size|None|None|5 -ParameterNumber|-filter.mprofiles.start|Initial Radius|None|None|1 -ParameterNumber|-filter.mprofiles.step|Radius Step|None|None|1 -ParameterNumber|-filter.mprofiles.sigma|Threshold of final decision rule|0|None|1 -ParameterBoolean|-mode.vector.neighbor|8-neighbor connectivity|False -ParameterBoolean|-mode.vector.stitch|Stitch polygons|True -ParameterNumber|-mode.vector.minsize|Minimum object size|1|None|1 -ParameterNumber|-mode.vector.simplify|Simplify polygons|None|None|0.0 -ParameterString|-mode.vector.layername|Layer name|layer -ParemeterString|-mode.vector.fieldname|Geometry index field name|DN -ParameterNumber|-mode.vector.tilesize|Tile size|0|None|1024 -ParameterNumber|-mode.vector.startlabel|Starting geometry index|1|None|1 -ParameterSelection|-mode.vector.outmode|Writing mode (update file/overwrite file/overwrite layer/update layer)|ulco;ovw;ulovw;ulu|0 -ParameterString|-mode.vector.ogroptions|OGR options for layer creation| -ParameterVector|-mode.vector.inmask|Mask Image|-1|True -OutputVector|-mode vector -mode.vector.out|Output vector file \ No newline at end of file diff --git a/python/plugins/processing/otb/description/MultiResolutionPyramid.txt b/python/plugins/processing/otb/description/MultiResolutionPyramid.txt deleted file mode 100644 index de7bb3322e60..000000000000 --- a/python/plugins/processing/otb/description/MultiResolutionPyramid.txt +++ /dev/null @@ -1,11 +0,0 @@ -MultiResolutionPyramid -otbcli_MultiResolutionPyramid -Multi Resolution Pyramid -Image Manipulation -ParameterRaster|-in|Input Image|False -OutputFile|-out|Output Image -ParameterNumber|-ram|Available RAM (Mb)|None|None|128 -ParameterNumber|-level|Number Of Levels|None|None|1 -ParameterNumber|-sfactor|Subsampling factor|None|None|2 -ParameterNumber|-vfactor|Variance factor|None|None|0.600000023842 -ParameterBoolean|-fast|Use Fast Scheme| diff --git a/python/plugins/processing/otb/description/MultivariateAlterationDetector.txt b/python/plugins/processing/otb/description/MultivariateAlterationDetector.txt deleted file mode 100644 index 026015877dd9..000000000000 --- a/python/plugins/processing/otb/description/MultivariateAlterationDetector.txt +++ /dev/null @@ -1,8 +0,0 @@ -MultivariateAlterationDetector -otbcli_MultivariateAlterationDetector -Multivariate alteration detector -Feature Extraction -ParameterRaster|-in1|Input Image 1|False -ParameterRaster|-in2|Input Image 2|False -OutputRaster|-out|Change Map -ParameterNumber|-ram|Available RAM (Mb)|None|None|128 diff --git a/python/plugins/processing/otb/description/MultivariateAlterationDetector.xml b/python/plugins/processing/otb/description/MultivariateAlterationDetector.xml new file mode 100644 index 000000000000..ec433281f34b --- /dev/null +++ b/python/plugins/processing/otb/description/MultivariateAlterationDetector.xml @@ -0,0 +1,37 @@ + + MultivariateAlterationDetector + otbcli_MultivariateAlterationDetector + Multivariate alteration detector + Feature Extraction + Multivariate Alteration Detector + + ParameterRaster + in1 + Input Image 1 + Image which describe initial state of the scene. + False + + + ParameterRaster + in2 + Input Image 2 + Image which describe scene after perturbations. + False + + + OutputRaster + out + Change Map + Image of detected changes. + + + + ParameterNumber + ram + Available RAM (Mb) + Available memory for processing (in MB) + + + 128 + + diff --git a/python/plugins/processing/otb/description/OSMDownloader.txt b/python/plugins/processing/otb/description/OSMDownloader.txt deleted file mode 100644 index 9aa25e109875..000000000000 --- a/python/plugins/processing/otb/description/OSMDownloader.txt +++ /dev/null @@ -1,13 +0,0 @@ -OSMDownloader -otbcli_OSMDownloader -Open Street Map layers importations applications -Miscellaneous -OutputVector|-out|Output vector data -ParameterRaster|-support|Support image|False -ParameterString|-key|OSM tag key| -ParameterString|-value|OSM tag value| -ParameterSelection|-elev|Elevation management|dem;average|1 -ParameterFile|-elev.dem.path|DEM directory| -ParameterFile|-elev.dem.geoid|Geoid File|| -ParameterNumber|-elev.average.value|Average Elevation|None|None|0.0 -ParameterBoolean|-printclasses|option to display available key/value classes| diff --git a/python/plugins/processing/otb/description/ObtainUTMZoneFromGeoPoint.txt b/python/plugins/processing/otb/description/ObtainUTMZoneFromGeoPoint.txt deleted file mode 100644 index e5aab204c02b..000000000000 --- a/python/plugins/processing/otb/description/ObtainUTMZoneFromGeoPoint.txt +++ /dev/null @@ -1,7 +0,0 @@ -ObtainUTMZoneFromGeoPoint -otbcli_ObtainUTMZoneFromGeoPoint -Obtain UTM Zone From Geo Point -Miscellaneous -ParameterNumber|-lat|Latitude|None|None|0.0 -ParameterNumber|-lon|Longitude|None|None|0.0 -ParameterNumber|-utm|UTMZone|None|None|0 diff --git a/python/plugins/processing/otb/description/OpticalCalibration.txt b/python/plugins/processing/otb/description/OpticalCalibration.txt deleted file mode 100644 index 809fdf14656a..000000000000 --- a/python/plugins/processing/otb/description/OpticalCalibration.txt +++ /dev/null @@ -1,17 +0,0 @@ -OpticalCalibration -otbcli_OpticalCalibration -Optical calibration -Calibration -ParameterRaster|-in|Input|False -OutputRaster|-out|Output -ParameterNumber|-ram|Available RAM (Mb)|None|None|128 -ParameterSelection|-level|Calibration Level|toa;toc|0 -ParameterBoolean|-milli|Convert to milli reflectance| -ParameterFile|-rsr|Relative Spectral Response File|| -ParameterSelection|-atmo.aerosol|Aerosol Model|noaersol;continental;maritime;urban;desertic|0 -ParameterNumber|-atmo.oz|Ozone Amount|None|None|0.0 -ParameterNumber|-atmo.wa|Water Vapor Amount|None|None|2.5 -ParameterNumber|-atmo.pressure|Atmospheric Pressure|None|None|1030.0 -ParameterNumber|-atmo.opt|Aerosol Optical Thickness|None|None|0.20000000298 -ParameterFile|-atmo.aeronet|Aeronet File|| -ParameterNumber|-radius|Window radius|None|None|2 diff --git a/python/plugins/processing/otb/description/OpticalCalibration.xml b/python/plugins/processing/otb/description/OpticalCalibration.xml new file mode 100644 index 000000000000..0d26f45ae140 --- /dev/null +++ b/python/plugins/processing/otb/description/OpticalCalibration.xml @@ -0,0 +1,66 @@ + + OpticalCalibration + otbcli_OpticalCalibration + Optical calibration + Calibration + Perform optical calibration TOA/TOC (Top Of Atmosphere/Top Of Canopy). Supported sensors: QuickBird, Ikonos, WorldView2, Formosat, Spot5, Pleiades + + ParameterRaster + in + Input + Input image filename (values in DN) + False + + + OutputRaster + out + Output + Output calibrated image filename + + + + ParameterNumber + ram + Available RAM (Mb) + Available memory for processing (in MB) + + + 128 + + + ParameterSelection + level + Calibration Level + + + + toa + + + 0 + + + ParameterBoolean + milli + Convert to milli reflectance + Flag to use milli-reflectance instead of reflectance. +This allows to save the image with integer pixel type (in the range [0, 1000] instead of floating point in the range [0, 1]. In order to do that, use this option and set the output pixel type (-out filename uint16 for example) + True + + + ParameterBoolean + clamp + Clamp of reflectivity values between [0, 100] + Clamping in the range [0, 100]. It can be useful to preserve area with specular reflectance. + True + + + ParameterFile + rsr + Relative Spectral Response File + Sensor relative spectral response file +By default the application gets these informations in the metadata + + True + + diff --git a/python/plugins/processing/otb/description/OrthoRectification-epsg.xml b/python/plugins/processing/otb/description/OrthoRectification-epsg.xml new file mode 100644 index 000000000000..15b225cb376e --- /dev/null +++ b/python/plugins/processing/otb/description/OrthoRectification-epsg.xml @@ -0,0 +1,115 @@ + + OrthoRectification-epsg + otbcli_OrthoRectification + OrthoRectification (epsg) + Geometry + This application allows to ortho-rectify optical images from supported sensors. + + + ParameterRaster + io.in + Input Image + The input image to ortho-rectify + False + + + OutputRaster + io.out + Output Image + The ortho-rectified output image + + + + ParameterSelection + map + Output Cartographic Map Projection + Parameters of the output map projection to be used. + + + epsg + + + 0 + + + ParameterNumber + map.epsg.code + EPSG Code + See www.spatialreference.org to find which EPSG code is associated to your projection + + + 4326 + + + ParameterSelection + outputs.mode + Parameters estimation modes + + + + autosize + autospacing + + + 0 + + + ParameterNumber + outputs.default + Default pixel value + Default value to write when outside of input image. + + + 0 + + + ParameterNumber + elev.default + Default elevation + This parameter allows to set the default height above ellipsoid when there is no DEM available, no coverage for some points or pixels with no_data in the DEM tiles, and no geoid file has been set. This is also used by some application as an average elevation value. + + + 0 + + + ParameterSelection + interpolator + Interpolation + This group of parameters allows to define how the input image will be interpolated during resampling. + + + bco + nn + linear + + + 0 + + + ParameterNumber + interpolator.bco.radius + Radius for bicubic interpolation + This parameter allows to control the size of the bicubic interpolation filter. If the target pixel size is higher than the input pixel size, increasing this parameter will reduce aliasing artefacts. + + + 2 + + + ParameterNumber + opt.ram + Available RAM (Mb) + This allows to set the maximum amount of RAM available for processing. As the writing task is time consuming, it is better to write large pieces of data, which can be achieved by increasing this parameter (pay attention to your system capabilities) + + + 128 + + + ParameterNumber + opt.gridspacing + Resampling grid spacing + Resampling is done according to a coordinate mapping deformation grid, whose pixel size is set by this parameter, and expressed in the coordinate system of the output image The closer to the output spacing this parameter is, the more precise will be the ortho-rectified image,but increasing this parameter will reduce processing time. + + + 4 + + diff --git a/python/plugins/processing/otb/description/OrthoRectification-fit-to-ortho.xml b/python/plugins/processing/otb/description/OrthoRectification-fit-to-ortho.xml new file mode 100644 index 000000000000..4c9cc1ed71a2 --- /dev/null +++ b/python/plugins/processing/otb/description/OrthoRectification-fit-to-ortho.xml @@ -0,0 +1,100 @@ + + OrthoRectification-fit-to-ortho + otbcli_OrthoRectification + OrthoRectification (fit-to-ortho) + Geometry + This application allows to ortho-rectify optical images from supported sensors. + + + ParameterRaster + io.in + Input Image + The input image to ortho-rectify + False + + + OutputRaster + io.out + Output Image + The ortho-rectified output image + + + + ParameterSelection + outputs.mode + Parameters estimation modes + + + + orthofit + + + 0 + + + ParameterRaster + outputs.ortho + Model ortho-image + A model ortho-image that can be used to compute size, origin and spacing of the output + True + + + ParameterNumber + outputs.default + Default pixel value + Default value to write when outside of input image. + + + 0 + + + ParameterNumber + elev.default + Default elevation + This parameter allows to set the default height above ellipsoid when there is no DEM available, no coverage for some points or pixels with no_data in the DEM tiles, and no geoid file has been set. This is also used by some application as an average elevation value. + + + 0 + + + ParameterSelection + interpolator + Interpolation + This group of parameters allows to define how the input image will be interpolated during resampling. + + + bco + nn + linear + + + 0 + + + ParameterNumber + interpolator.bco.radius + Radius for bicubic interpolation + This parameter allows to control the size of the bicubic interpolation filter. If the target pixel size is higher than the input pixel size, increasing this parameter will reduce aliasing artefacts. + + + 2 + + + ParameterNumber + opt.ram + Available RAM (Mb) + This allows to set the maximum amount of RAM available for processing. As the writing task is time consuming, it is better to write large pieces of data, which can be achieved by increasing this parameter (pay attention to your system capabilities) + + + 128 + + + ParameterNumber + opt.gridspacing + Resampling grid spacing + Resampling is done according to a coordinate mapping deformation grid, whose pixel size is set by this parameter, and expressed in the coordinate system of the output image The closer to the output spacing this parameter is, the more precise will be the ortho-rectified image,but increasing this parameter will reduce processing time. + + + 4 + + diff --git a/python/plugins/processing/otb/description/OrthoRectification-lambert-WGS84.xml b/python/plugins/processing/otb/description/OrthoRectification-lambert-WGS84.xml new file mode 100644 index 000000000000..8282aeeae08b --- /dev/null +++ b/python/plugins/processing/otb/description/OrthoRectification-lambert-WGS84.xml @@ -0,0 +1,108 @@ + + OrthoRectification-lambert-WGS84 + otbcli_OrthoRectification + OrthoRectification (lambert-WGS84) + Geometry + This application allows to ortho-rectify optical images from supported sensors. + + + ParameterRaster + io.in + Input Image + The input image to ortho-rectify + False + + + OutputRaster + io.out + Output Image + The ortho-rectified output image + + + + ParameterSelection + map + Output Cartographic Map Projection + Parameters of the output map projection to be used. + + + lambert2 + lambert93 + wgs + + + 0 + + + ParameterSelection + outputs.mode + Parameters estimation modes + + + + autosize + autospacing + + + 0 + + + ParameterNumber + outputs.default + Default pixel value + Default value to write when outside of input image. + + + 0 + + + ParameterNumber + elev.default + Default elevation + This parameter allows to set the default height above ellipsoid when there is no DEM available, no coverage for some points or pixels with no_data in the DEM tiles, and no geoid file has been set. This is also used by some application as an average elevation value. + + + 0 + + + ParameterSelection + interpolator + Interpolation + This group of parameters allows to define how the input image will be interpolated during resampling. + + + bco + nn + linear + + + 0 + + + ParameterNumber + interpolator.bco.radius + Radius for bicubic interpolation + This parameter allows to control the size of the bicubic interpolation filter. If the target pixel size is higher than the input pixel size, increasing this parameter will reduce aliasing artefacts. + + + 2 + + + ParameterNumber + opt.ram + Available RAM (Mb) + This allows to set the maximum amount of RAM available for processing. As the writing task is time consuming, it is better to write large pieces of data, which can be achieved by increasing this parameter (pay attention to your system capabilities) + + + 128 + + + ParameterNumber + opt.gridspacing + Resampling grid spacing + Resampling is done according to a coordinate mapping deformation grid, whose pixel size is set by this parameter, and expressed in the coordinate system of the output image The closer to the output spacing this parameter is, the more precise will be the ortho-rectified image,but increasing this parameter will reduce processing time. + + + 4 + + diff --git a/python/plugins/processing/otb/description/OrthoRectification-utm.xml b/python/plugins/processing/otb/description/OrthoRectification-utm.xml new file mode 100644 index 000000000000..f0dafe09515e --- /dev/null +++ b/python/plugins/processing/otb/description/OrthoRectification-utm.xml @@ -0,0 +1,122 @@ + + OrthoRectification-utm + otbcli_OrthoRectification + OrthoRectification (utm) + Geometry + This application allows to ortho-rectify optical images from supported sensors. + + + ParameterRaster + io.in + Input Image + The input image to ortho-rectify + False + + + OutputRaster + io.out + Output Image + The ortho-rectified output image + + + + ParameterSelection + map + Output Cartographic Map Projection + Parameters of the output map projection to be used. + + + utm + + + 0 + + + ParameterNumber + map.utm.zone + Zone number + The zone number ranges from 1 to 60 and allows to define the transverse mercator projection (along with the hemisphere) + + + 31 + + + ParameterBoolean + map.utm.northhem + Northern Hemisphere + The transverse mercator projections are defined by their zone number as well as the hemisphere. Activate this parameter if your image is in the northern hemisphere. + True + + + ParameterSelection + outputs.mode + Parameters estimation modes + + + + autosize + autospacing + + + 0 + + + ParameterNumber + outputs.default + Default pixel value + Default value to write when outside of input image. + + + 0 + + + ParameterNumber + elev.default + Default elevation + This parameter allows to set the default height above ellipsoid when there is no DEM available, no coverage for some points or pixels with no_data in the DEM tiles, and no geoid file has been set. This is also used by some application as an average elevation value. + + + 0 + + + ParameterSelection + interpolator + Interpolation + This group of parameters allows to define how the input image will be interpolated during resampling. + + + bco + nn + linear + + + 0 + + + ParameterNumber + interpolator.bco.radius + Radius for bicubic interpolation + This parameter allows to control the size of the bicubic interpolation filter. If the target pixel size is higher than the input pixel size, increasing this parameter will reduce aliasing artefacts. + + + 2 + + + ParameterNumber + opt.ram + Available RAM (Mb) + This allows to set the maximum amount of RAM available for processing. As the writing task is time consuming, it is better to write large pieces of data, which can be achieved by increasing this parameter (pay attention to your system capabilities) + + + 128 + + + ParameterNumber + opt.gridspacing + Resampling grid spacing + Resampling is done according to a coordinate mapping deformation grid, whose pixel size is set by this parameter, and expressed in the coordinate system of the output image The closer to the output spacing this parameter is, the more precise will be the ortho-rectified image,but increasing this parameter will reduce processing time. + + + 4 + + diff --git a/python/plugins/processing/otb/description/OrthoRectification.txt b/python/plugins/processing/otb/description/OrthoRectification.txt deleted file mode 100644 index 81c40ecb6cb1..000000000000 --- a/python/plugins/processing/otb/description/OrthoRectification.txt +++ /dev/null @@ -1,28 +0,0 @@ -OrthoRectification -otbcli_OrthoRectification -Ortho-rectification -Geometry -ParameterRaster|-io.in|Input Image|False -OutputRaster|-io.out|Output Image -ParameterSelection|-map|Output Cartographic Map Projection|utm;lambert2;lambert93;wgs;epsg|4 -ParameterNumber|-map.utm.zone|Zone number|None|None|31 -ParameterBoolean|-map.utm.northhem|Northern Hemisphere| -ParameterNumber|-map.epsg.code|EPSG Code|None|None|32631 -ParameterSelection|-outputs.mode|Parameters estimation modes|auto;autosize;autospacing|0 -ParameterNumber|-outputs.ulx|Upper Left X|None|None|0.0 -ParameterNumber|-outputs.uly|Upper Left Y|None|None|0.0 -ParameterNumber|-outputs.sizex|Size X|None|None|0 -ParameterNumber|-outputs.sizey|Size Y|None|None|0 -ParameterNumber|-outputs.spacingx|Pixel Size X|None|None|0.0 -ParameterNumber|-outputs.spacingy|Pixel Size Y|None|None|0.0 -ParameterBoolean|-outputs.isotropic|Force isotropic spacing by default|True -ParameterNumber|-outputs.default|Default pixel value|None|None|0.0 -ParameterSelection|-elev|Elevation management|dem;average|1 -ParameterString|-elev.dem|DEM directory| -ParameterFile|-elev.geoid|Geoid File| -ParameterNumber|-elev.default|Average Elevation|None|None|0.0 -ParameterSelection|-interpolator|Interpolation|nn;linear;bco|0 -ParameterNumber|-interpolator.bco.radius|Radius for bicubic interpolation|None|None|2 -ParameterNumber|-opt.rpc|RPC modeling (points per axis)|None|None|10 -ParameterNumber|-opt.ram|Available RAM (Mb)|None|None|128 -ParameterNumber|-opt.gridspacing|Resampling grid spacing|None|None|4.0 \ No newline at end of file diff --git a/python/plugins/processing/otb/description/Pansharpening-bayes.xml b/python/plugins/processing/otb/description/Pansharpening-bayes.xml new file mode 100644 index 000000000000..50c390f607bc --- /dev/null +++ b/python/plugins/processing/otb/description/Pansharpening-bayes.xml @@ -0,0 +1,67 @@ + + Pansharpening-bayes + otbcli_Pansharpening + Pansharpening (bayes) + Geometry + Perform P+XS pansharpening + + ParameterRaster + inp + Input PAN Image + Input panchromatic image. + False + + + ParameterRaster + inxs + Input XS Image + Input XS image. + False + + + OutputRaster + out + Output image + Output image. + + + + ParameterSelection + method + Algorithm + Selection of the pan-sharpening method. + + + bayes + + + 0 + + + ParameterNumber + method.bayes.lambda + Weight + Set the weighting value. + + + 0.9999 + + + ParameterNumber + method.bayes.s + S coefficient + Set the S coefficient. + + + 1 + + + ParameterNumber + ram + Available RAM (Mb) + Available memory for processing (in MB) + + + 128 + + diff --git a/python/plugins/processing/otb/description/Pansharpening-lmvm.xml b/python/plugins/processing/otb/description/Pansharpening-lmvm.xml new file mode 100644 index 000000000000..821e2928a183 --- /dev/null +++ b/python/plugins/processing/otb/description/Pansharpening-lmvm.xml @@ -0,0 +1,67 @@ + + Pansharpening-lmvm + otbcli_Pansharpening + Pansharpening (lmvm) + Geometry + Perform P+XS pansharpening + + ParameterRaster + inp + Input PAN Image + Input panchromatic image. + False + + + ParameterRaster + inxs + Input XS Image + Input XS image. + False + + + OutputRaster + out + Output image + Output image. + + + + ParameterSelection + method + Algorithm + Selection of the pan-sharpening method. + + + lmvm + + + 0 + + + ParameterNumber + method.lmvm.radiusx + X radius + Set the x radius of the sliding window. + + + 3 + + + ParameterNumber + method.lmvm.radiusy + Y radius + Set the y radius of the sliding window. + + + 3 + + + ParameterNumber + ram + Available RAM (Mb) + Available memory for processing (in MB) + + + 128 + + diff --git a/python/plugins/processing/otb/description/Pansharpening-rcs.xml b/python/plugins/processing/otb/description/Pansharpening-rcs.xml new file mode 100644 index 000000000000..c37f6f900ff8 --- /dev/null +++ b/python/plugins/processing/otb/description/Pansharpening-rcs.xml @@ -0,0 +1,49 @@ + + Pansharpening-rcs + otbcli_Pansharpening + Pansharpening (rcs) + Geometry + Perform P+XS pansharpening + + ParameterRaster + inp + Input PAN Image + Input panchromatic image. + False + + + ParameterRaster + inxs + Input XS Image + Input XS image. + False + + + OutputRaster + out + Output image + Output image. + + + + ParameterSelection + method + Algorithm + Selection of the pan-sharpening method. + + + rcs + + + 0 + + + ParameterNumber + ram + Available RAM (Mb) + Available memory for processing (in MB) + + + 128 + + diff --git a/python/plugins/processing/otb/description/Pansharpening.txt b/python/plugins/processing/otb/description/Pansharpening.txt deleted file mode 100644 index 64adffa00ce7..000000000000 --- a/python/plugins/processing/otb/description/Pansharpening.txt +++ /dev/null @@ -1,12 +0,0 @@ -Pansharpening -otbcli_Pansharpening -Pansharpening -Image Manipulation -ParameterRaster|-inp|Input PAN Image|False -ParameterRaster|-inxs|Input XS Image|False -OutputRaster|-out|Output Image -ParameterSelection|-method|Algorithm|rcs;lmvm;bayes|0 -ParameterNumber|-method.lmvm.radiusx|X radius|None|None|3 -ParameterNumber|-method.lmvm.radiusy|Y radius|None|None|3 -ParameterNumber|-method.bayes.s|S coefficient|None|None|1 -ParameterNumber|-ram|Available RAM (Mb)|None|None|128 diff --git a/python/plugins/processing/otb/description/PixelValue.txt b/python/plugins/processing/otb/description/PixelValue.txt deleted file mode 100644 index d37d7069bc4a..000000000000 --- a/python/plugins/processing/otb/description/PixelValue.txt +++ /dev/null @@ -1,8 +0,0 @@ -PixelValue -otbcli_PixelValue -Pixel Value -Miscellaneous -ParameterRaster|-in|Input Image|False -ParameterNumber|-coordx|Col index|None|None|0 -ParameterNumber|-coordy|Line index|None|None|0 -ParameterString|-value|Pixel Value| diff --git a/python/plugins/processing/otb/description/PixelWiseBlockMatching.txt b/python/plugins/processing/otb/description/PixelWiseBlockMatching.txt deleted file mode 100644 index 220eebbbac1d..000000000000 --- a/python/plugins/processing/otb/description/PixelWiseBlockMatching.txt +++ /dev/null @@ -1,34 +0,0 @@ -PixelWiseBlockMatching -otbcli_PixelWiseBlockMatching - Pixel-wise Block-Matching -Stereo -ParameterRaster|-io.inleft|Left input image|False -ParameterRaster|-io.inright|Right input image|False -OutputRaster|-io.out|The output disparity map -OutputRaster|-io.outmaskleft|The left output mask corresponding to all criterions -OutputRaster|-io.outmaskright|The right output mask corresponding to all criterions -ParameterBoolean|-io.outmetric|Output optimal metric values as well| -ParameterRaster|-mask.inleft|Discard left pixels from mask image|True -ParameterRaster|-mask.inright|Discard right pixels from mask image|True -ParameterNumber|-mask.nodata|Discard pixels with no-data value|None|None|0.0 -ParameterNumber|-mask.variancet|Discard pixels with low local variance|None|None|100.0 -ParameterSelection|-bm.metric|Block-matching metric|ssd;ncc;lp|0 -ParameterNumber|-bm.metric.lp.p|p value|None|None|1.0 -ParameterNumber|-bm.radius|Radius of blocks|None|None|3 -ParameterNumber|-bm.minhd|Minimum horizontal disparity|None|None|0 -ParameterNumber|-bm.maxhd|Maximum horizontal disparity|None|None|0 -ParameterNumber|-bm.minvd|Minimum vertical disparity|None|None|0 -ParameterNumber|-bm.maxvd|Maximum vertical disparity|None|None|0 -ParameterSelection|-bm.subpixel|Sub-pixel interpolation|none;parabolic;triangular;dichotomy|0 -ParameterNumber|-bm.medianfilter.radius|Radius|None|None|0 -ParameterNumber|-bm.medianfilter.incoherence|Incoherence threshold|None|None|0.0 -ParameterSelection|-bm.initdisp|Initial disparities|none;uniform;maps|0 -ParameterNumber|-bm.initdisp.uniform.hdisp|Horizontal initial disparity|None|None|0 -ParameterNumber|-bm.initdisp.uniform.vdisp|Vertical initial disparity|None|None|0 -ParameterNumber|-bm.initdisp.uniform.hrad|Horizontal exploration radius|None|None|0 -ParameterNumber|-bm.initdisp.uniform.vrad|Vertical exploration radius|None|None|0 -ParameterRaster|-bm.initdisp.maps.hmap|Horizontal initial disparity map|False -ParameterRaster|-bm.initdisp.maps.vmap|Vertical initial disparity map|False -ParameterNumber|-bm.initdisp.maps.hrad|Horizontal exploration radius|None|None|0 -ParameterNumber|-bm.initdisp.maps.vrad|Vertical exploration radius|None|None|0 -ParameterNumber|-ram|Available RAM (Mb)|None|None|128 diff --git a/python/plugins/processing/otb/description/Quicklook.txt b/python/plugins/processing/otb/description/Quicklook.txt deleted file mode 100644 index 4416b0adbfd9..000000000000 --- a/python/plugins/processing/otb/description/Quicklook.txt +++ /dev/null @@ -1,13 +0,0 @@ -Quicklook -otbcli_Quicklook -Quick Look -Image Manipulation -ParameterRaster|-in|Input Image|False -OutputRaster|-out|Output Image -ParameterNumber|-rox|ROI Origin X|None|None|0 -ParameterNumber|-roy|ROI Origin Y|None|None|0 -ParameterNumber|-rsx|ROI Size X|None|None|0 -ParameterNumber|-rsy|ROI Size Y|None|None|0 -ParameterNumber|-sr|Sampling ratio|None|None|2 -ParameterNumber|-sx|Size X|None|None|0 -ParameterNumber|-sy|Size Y|None|None|0 diff --git a/python/plugins/processing/otb/description/RadiometricIndices.txt b/python/plugins/processing/otb/description/RadiometricIndices.txt deleted file mode 100644 index d2d588b4d193..000000000000 --- a/python/plugins/processing/otb/description/RadiometricIndices.txt +++ /dev/null @@ -1,13 +0,0 @@ -Radiometric Indices -otbcli_RadiometricIndices -Radiometric Indices -Feature Extraction -ParameterRaster|-in|Input Image|False -OutputRaster|-out|Output Image -ParameterNumber|-ram|Available RAM (Mb)|None|None|128 -ParameterNumber|-channels.blue|Blue Channel|None|None|1 -ParameterNumber|-channels.green|Green Channel|None|None|2 -ParameterNumber|-channels.red|Red Channel|None|None|3 -ParameterNumber|-channels.nir|NIR Channel|None|None|4 -ParameterNumber|-channels.mir|Mir Channel|None|None|5 -ParameterSelection|-list|Available Radiometric Indices|Vegetation:NDVI;Vegetation:TNDVI;Vegetation:RVI;Vegetation:SAVI;Vegetation:TSAVI;Vegetation:MSAVI;Vegetation:MSAVI2;Vegetation:GEMI;Vegetation:IPVI;Vegetation:LAIFromNDVILog;Vegetation:LAIFromReflLinear;Vegetation:LAIFromNDVIFormo;Water:NDWI;Water:NDWI2;Water:MNDWI;Water:NDPI;Water:NDTI;Soil:RI;Soil:CI;Soil:BI;Soil:BI2 diff --git a/python/plugins/processing/otb/description/RadiometricIndices.xml b/python/plugins/processing/otb/description/RadiometricIndices.xml new file mode 100644 index 000000000000..504495fac13c --- /dev/null +++ b/python/plugins/processing/otb/description/RadiometricIndices.xml @@ -0,0 +1,124 @@ + + RadiometricIndices + otbcli_RadiometricIndices + Radiometric Indices + Feature Extraction + Compute radiometric indices. + + ParameterRaster + in + Input Image + Input image + False + + + OutputRaster + out + Output Image + Radiometric indices output image + + + + ParameterNumber + ram + Available RAM (Mb) + Available memory for processing (in MB) + + + 128 + + + ParameterNumber + channels.blue + Blue Channel + Blue channel index + + + 1 + + + ParameterNumber + channels.green + Green Channel + Green channel index + + + 1 + + + ParameterNumber + channels.red + Red Channel + Red channel index + + + 1 + + + ParameterNumber + channels.nir + NIR Channel + NIR channel index + + + 1 + + + ParameterNumber + channels.mir + Mir Channel + Mir channel index + + + 1 + + + ParameterSelection + list + Available Radiometric Indices + List of available radiometric indices with their relevant channels in brackets: + Vegetation:NDVI - Normalized difference vegetation index (Red, NIR) + Vegetation:TNDVI - Transformed normalized difference vegetation index (Red, NIR) + Vegetation:RVI - Ratio vegetation index (Red, NIR) + Vegetation:SAVI - Soil adjusted vegetation index (Red, NIR) + Vegetation:TSAVI - Transformed soil adjusted vegetation index (Red, NIR) + Vegetation:MSAVI - Modified soil adjusted vegetation index (Red, NIR) + Vegetation:MSAVI2 - Modified soil adjusted vegetation index 2 (Red, NIR) + Vegetation:GEMI - Global environment monitoring index (Red, NIR) + Vegetation:IPVI - Infrared percentage vegetation index (Red, NIR) + + Water:NDWI - Normalized difference water index (Gao 1996) (NIR, MIR) + Water:NDWI2 - Normalized difference water index (Mc Feeters 1996) (Green, NIR) + Water:MNDWI - Modified normalized difference water index (Xu 2006) (Green, MIR) + Water:NDPI - Normalized difference pond index (Lacaux et al.) (MIR, Green) + Water:NDTI - Normalized difference turbidity index (Lacaux et al.) (Red, Green) + + Soil:RI - Redness index (Red, Green) + Soil:CI - Color index (Red, Green) + Soil:BI - Brightness index (Red, Green) + Soil:BI2 - Brightness index 2 (NIR, Red, Green) + + + ndvi + tndvi + rvi + savi + tsavi + msavi + msavi2 + gemi + ipvi + ndwi + ndwi2 + mndwi + ndpi + ndti + ri + ci + bi + bi2 + + + 0 + + diff --git a/python/plugins/processing/otb/description/Rasterization.txt b/python/plugins/processing/otb/description/Rasterization.txt deleted file mode 100644 index 8404dde39404..000000000000 --- a/python/plugins/processing/otb/description/Rasterization.txt +++ /dev/null @@ -1,19 +0,0 @@ -Rasterization -otbcli_Rasterization -Rasterization -Vector Data Manipulation -ParameterFile|-in|Input vector dataset|| -OutputRaster|-out|Ouptut image -ParameterRaster|-im|Input reference image|True -ParameterNumber|-szx|Output size x|None|None|0 -ParameterNumber|-szy|Output size y|None|None|0 -ParameterNumber|-epsg|Output EPSG code|None|None|0 -ParameterNumber|-orx|Output Upper-left x|None|None|0.0 -ParameterNumber|-ory|Output Upper-left y|None|None|0.0 -ParameterNumber|-spx|Spacing (GSD) x|None|None|0.0 -ParameterNumber|-spy|Spacing (GSD) y|None|None|0.0 -ParameterNumber|-background|Background value|None|None|0.0 -ParameterSelection|-mode|Rasterization mode|binary;attribute|0 -ParameterNumber|-mode.binary.foreground|Foreground value|None|None|255.0 -ParameterString|-mode.attribute.field|The attribute field to burn|DN -ParameterNumber|-ram|Available RAM (Mb)|None|None|128 diff --git a/python/plugins/processing/otb/description/ReadImageInfo.txt b/python/plugins/processing/otb/description/ReadImageInfo.txt deleted file mode 100644 index 7d5e2aa43f0f..000000000000 --- a/python/plugins/processing/otb/description/ReadImageInfo.txt +++ /dev/null @@ -1,35 +0,0 @@ -ReadImageInfo -otbcli_ReadImageInfo -Read image information -Image Manipulation -ParameterRaster|-in|Input Image|False -ParameterBoolean|-keywordlist|Display the OSSIM keywordlist| -ParameterNumber|-sizex|Size X|None|None|0 -ParameterNumber|-sizey|Size Y|None|None|0 -ParameterNumber|-spacingx|Pixel Size X|None|None|0.0 -ParameterNumber|-spacingy|Pixel Size Y|None|None|0.0 -ParameterNumber|-originx|Image Origin X|None|None|0.0 -ParameterNumber|-originy|Image Origin Y|None|None|0.0 -ParameterNumber|-estimatedgroundspacingx|Estimated ground spacing X|None|None|0.0 -ParameterNumber|-estimatedgroundspacingy|Estimated ground spacing Y|None|None|0.0 -ParameterNumber|-numberbands|Number Of Bands|None|None|0 -ParameterString|-sensor|Sensor id| -ParameterString|-id|Image id| -ParameterString|-time|Acquisition time| -ParameterNumber|-ullat|Upper left lattitude|None|None|0.0 -ParameterNumber|-ullon|Upper left longitude|None|None|0.0 -ParameterNumber|-urlat|Upper right lattitude|None|None|0.0 -ParameterNumber|-urlon|Upper right longitude|None|None|0.0 -ParameterNumber|-lrlat|Lower right lattitude|None|None|0.0 -ParameterNumber|-lrlon|Lower right longitude|None|None|0.0 -ParameterNumber|-lllat|Lower left lattitude|None|None|0.0 -ParameterNumber|-lllon|Lower left longitude|None|None|0.0 -ParameterString|-town|Nearest town| -ParameterString|-country|Country| -ParameterNumber|-rgb.r|Red Band|None|None|1 -ParameterNumber|-rgb.g|Green Band|None|None|2 -ParameterNumber|-rgb.b|Blue Band|None|None|3 -ParameterString|-projectionref|Projection| -ParameterString|-keyword|Keywordlist| -ParameterNumber|-gcp.count|GCPs Number|None|None|0 -ParameterString|-gcp.proj|GCP Projection| diff --git a/python/plugins/processing/otb/description/ReadImageInfo.xml b/python/plugins/processing/otb/description/ReadImageInfo.xml new file mode 100644 index 000000000000..0e96948f43bc --- /dev/null +++ b/python/plugins/processing/otb/description/ReadImageInfo.xml @@ -0,0 +1,57 @@ + + ReadImageInfo + otbcli_ReadImageInfo + Read image information + Image Manipulation + Get information about the image + + ParameterRaster + in + Input Image + Input image to analyse + False + + + ParameterBoolean + keywordlist + Display the OSSIM keywordlist + Output the OSSIM keyword list. It contains metadata information (sensor model, geometry ). Informations are stored in keyword list (pairs of key/value) + True + + + ParameterString + gcp.ids + GCPs Id + GCPs identifier + + + False + + + ParameterString + gcp.info + GCPs Info + GCPs Information + + + False + + + ParameterString + gcp.imcoord + GCPs Image Coordinates + GCPs Image coordinates + + + False + + + ParameterString + gcp.geocoord + GCPs Geographic Coordinates + GCPs Geographic Coordinates + + + False + + diff --git a/python/plugins/processing/otb/description/Rescale.txt b/python/plugins/processing/otb/description/Rescale.txt deleted file mode 100644 index dcdefdfaade4..000000000000 --- a/python/plugins/processing/otb/description/Rescale.txt +++ /dev/null @@ -1,9 +0,0 @@ -Rescale -otbcli_Rescale -Rescale Image -Image Manipulation -ParameterRaster|-in|Input Image|False -OutputRaster|-out|Output Image -ParameterNumber|-ram|Available RAM (Mb)|None|None|128 -ParameterNumber|-outmin|Output min value|None|None|0.0 -ParameterNumber|-outmax|Output max value|None|None|255.0 diff --git a/python/plugins/processing/otb/description/Rescale.xml b/python/plugins/processing/otb/description/Rescale.xml new file mode 100644 index 000000000000..af6d67ffbf6f --- /dev/null +++ b/python/plugins/processing/otb/description/Rescale.xml @@ -0,0 +1,48 @@ + + Rescale + otbcli_Rescale + Rescale Image + Image Manipulation + Rescale the image between two given values. + + ParameterRaster + in + Input Image + The image to scale. + False + + + OutputRaster + out + Output Image + The rescaled image filename. + + + + ParameterNumber + ram + Available RAM (Mb) + Available memory for processing (in MB) + + + 128 + + + ParameterNumber + outmin + Output min value + Minimum value of the output image. + + + 0 + + + ParameterNumber + outmax + Output max value + Maximum value of the output image. + + + 255 + + diff --git a/python/plugins/processing/otb/description/RigidTransformResample-id.xml b/python/plugins/processing/otb/description/RigidTransformResample-id.xml new file mode 100644 index 000000000000..8ff7125e59f1 --- /dev/null +++ b/python/plugins/processing/otb/description/RigidTransformResample-id.xml @@ -0,0 +1,83 @@ + + RigidTransformResample-id + otbcli_RigidTransformResample + RigidTransformResample (id) + Geometry + Resample an image with a rigid transform + + ParameterRaster + in + Input image + The input image to translate. + False + + + OutputRaster + out + Output image + The transformed output image. + + + + ParameterSelection + transform.type + Type of transformation + Type of transformation. Available transformations are spatial scaling, translation and rotation with scaling factor + + + id + + + 0 + + + ParameterNumber + transform.type.id.scalex + X scaling + Scaling factor between the output X spacing and the input X spacing + + + 1 + + + ParameterNumber + transform.type.id.scaley + Y scaling + Scaling factor between the output Y spacing and the input Y spacing + + + 1 + + + ParameterSelection + interpolator + Interpolation + This group of parameters allows to define how the input image will be interpolated during resampling. + + + nn + linear + bco + + + 2 + + + ParameterNumber + interpolator.bco.radius + Radius for bicubic interpolation + This parameter allows to control the size of the bicubic interpolation filter. If the target pixel size is higher than the input pixel size, increasing this parameter will reduce aliasing artefacts. + + + 2 + + + ParameterNumber + ram + Available RAM (Mb) + This allows to set the maximum amount of RAM available for processing. As the writing task is time consuming, it is better to write large pieces of data, which can be achieved by increasing this parameter (pay attention to your system capabilities) + + + 128 + + diff --git a/python/plugins/processing/otb/description/RigidTransformResample-rotation.xml b/python/plugins/processing/otb/description/RigidTransformResample-rotation.xml new file mode 100644 index 000000000000..80d7333fc4ff --- /dev/null +++ b/python/plugins/processing/otb/description/RigidTransformResample-rotation.xml @@ -0,0 +1,92 @@ + + RigidTransformResample-rotation + otbcli_RigidTransformResample + RigidTransformResample (rotation) + Geometry + Resample an image with a rigid transform + + ParameterRaster + in + Input image + The input image to translate. + False + + + OutputRaster + out + Output image + The transformed output image. + + + + ParameterSelection + transform.type + Type of transformation + Type of transformation. Available transformations are spatial scaling, translation and rotation with scaling factor + + + rotation + + + 0 + + + ParameterNumber + transform.type.rotation.angle + Rotation angle + The rotation angle in degree (values between -180 and 180) + + + 0 + + + ParameterNumber + transform.type.rotation.scalex + X scaling + Scale factor between the X spacing of the rotated output image and the X spacing of the unrotated image + + + 1 + + + ParameterNumber + transform.type.rotation.scaley + Y scaling + Scale factor between the Y spacing of the rotated output image and the Y spacing of the unrotated image + + + 1 + + + ParameterSelection + interpolator + Interpolation + This group of parameters allows to define how the input image will be interpolated during resampling. + + + nn + linear + bco + + + 2 + + + ParameterNumber + interpolator.bco.radius + Radius for bicubic interpolation + This parameter allows to control the size of the bicubic interpolation filter. If the target pixel size is higher than the input pixel size, increasing this parameter will reduce aliasing artefacts. + + + 2 + + + ParameterNumber + ram + Available RAM (Mb) + This allows to set the maximum amount of RAM available for processing. As the writing task is time consuming, it is better to write large pieces of data, which can be achieved by increasing this parameter (pay attention to your system capabilities) + + + 128 + + diff --git a/python/plugins/processing/otb/description/RigidTransformResample-translation.xml b/python/plugins/processing/otb/description/RigidTransformResample-translation.xml new file mode 100644 index 000000000000..031ef35889a3 --- /dev/null +++ b/python/plugins/processing/otb/description/RigidTransformResample-translation.xml @@ -0,0 +1,101 @@ + + RigidTransformResample-translation + otbcli_RigidTransformResample + RigidTransformResample (translation) + Geometry + Resample an image with a rigid transform + + ParameterRaster + in + Input image + The input image to translate. + False + + + OutputRaster + out + Output image + The transformed output image. + + + + ParameterSelection + transform.type + Type of transformation + Type of transformation. Available transformations are spatial scaling, translation and rotation with scaling factor + + + translation + + + 0 + + + ParameterNumber + transform.type.translation.tx + The X translation (in physical units) + The translation value along X axis (in physical units). + + + 0 + + + ParameterNumber + transform.type.translation.ty + The Y translation (in physical units) + The translation value along Y axis (in physical units) + + + 0 + + + ParameterNumber + transform.type.translation.scalex + X scaling + Scaling factor between the output X spacing and the input X spacing + + + 1 + + + ParameterNumber + transform.type.translation.scaley + Y scaling + Scaling factor between the output Y spacing and the input Y spacing + + + 1 + + + ParameterSelection + interpolator + Interpolation + This group of parameters allows to define how the input image will be interpolated during resampling. + + + nn + linear + bco + + + 2 + + + ParameterNumber + interpolator.bco.radius + Radius for bicubic interpolation + This parameter allows to control the size of the bicubic interpolation filter. If the target pixel size is higher than the input pixel size, increasing this parameter will reduce aliasing artefacts. + + + 2 + + + ParameterNumber + ram + Available RAM (Mb) + This allows to set the maximum amount of RAM available for processing. As the writing task is time consuming, it is better to write large pieces of data, which can be achieved by increasing this parameter (pay attention to your system capabilities) + + + 128 + + diff --git a/python/plugins/processing/otb/description/RigidTransformResample.txt b/python/plugins/processing/otb/description/RigidTransformResample.txt deleted file mode 100644 index 9bc8a6fa5ea9..000000000000 --- a/python/plugins/processing/otb/description/RigidTransformResample.txt +++ /dev/null @@ -1,17 +0,0 @@ -RigidTransformResample -otbcli_RigidTransformResample -Image resampling with a rigid transform -Geometry -ParameterRaster|-in|Input image|False -OutputRaster|-out|Output image -ParameterSelection|-transform.type|Type of transformation|id;translation;rotation|0 -ParameterNumber|-transform.type.id.scalex|X scaling|None|None|1.0 -ParameterNumber|-transform.type.id.scaley|Y scaling|None|None|1.0 -ParameterNumber|-transform.type.translation.tx|The X translation (in physical units)|None|None|0.0 -ParameterNumber|-transform.type.translation.ty|The Y translation (in physical units)|None|None|0.0 -ParameterNumber|-transform.type.rotation.angle|Rotation angle|None|None|0.0 -ParameterNumber|-transform.type.rotation.scalex|X scaling|None|None|1.0 -ParameterNumber|-transform.type.rotation.scaley|Y scaling|None|None|1.0 -ParameterSelection|-interpolator|Interpolation|nn;linear;bco|2 -ParameterNumber|-interpolator.bco.radius|Radius for bicubic interpolation|None|None|2 -ParameterNumber|-ram|Available RAM (Mb)|None|None|128 diff --git a/python/plugins/processing/otb/description/SFSTextureExtraction.txt b/python/plugins/processing/otb/description/SFSTextureExtraction.txt deleted file mode 100644 index 96f905644dc6..000000000000 --- a/python/plugins/processing/otb/description/SFSTextureExtraction.txt +++ /dev/null @@ -1,14 +0,0 @@ -SFS Texture Extraction -otbcli_SFSTextureExtraction -SFS Texture Extraction -Feature Extraction -ParameterRaster|-in|Input Image|False -OutputRaster|-out|Output Image -ParameterNumber|-channel|Selected Channel|None|None|1 -ParameterNumber|-ram|Available RAM (Mb)|None|None|128 -ParameterNumber|-parameters.spethre|Spectral Threshold|None|None|50 -ParameterNumber|-parameters.spathre|Spatial Threshold|None|None|100 -ParameterNumber|-parameters.nbdir|Number of Direction|None|None|20 -ParameterNumber|-parameters.alpha|Alpha|None|None|1 -ParameterNumber|-parameters.maxcons|Ratio Maximum Consideration Number |None|None|5 - diff --git a/python/plugins/processing/otb/description/SOMClassification.txt b/python/plugins/processing/otb/description/SOMClassification.txt deleted file mode 100644 index 4c00844ec04b..000000000000 --- a/python/plugins/processing/otb/description/SOMClassification.txt +++ /dev/null @@ -1,21 +0,0 @@ -SOMClassification -otbcli_SOMClassification -SOM Classification -Learning -ParameterRaster|-in|InputImage|False -OutputRaster|-out|OutputImage -ParameterRaster|-vm|ValidityMask|True -ParameterNumber|-tp|TrainingProbability|None|None|1.0 -ParameterNumber|-ts|TrainingSetSize|None|None|0 -ParameterNumber|-sl|StreamingLines|None|None|0 -OutputRaster|-som|SOM Map -ParameterNumber|-sx|SizeX|None|None|32 -ParameterNumber|-sy|SizeY|None|None|32 -ParameterNumber|-nx|NeighborhoodX|None|None|10 -ParameterNumber|-ny|NeighborhoodY|None|None|10 -ParameterNumber|-ni|NumberIteration|None|None|5 -ParameterNumber|-bi|BetaInit|None|None|1.0 -ParameterNumber|-bf|BetaFinal|None|None|0.10000000149 -ParameterNumber|-iv|InitialValue|None|None|0.0 -ParameterNumber|-ram|Available RAM (Mb)|None|None|128 -ParameterNumber|-rand|set user defined seed|None|None|0 diff --git a/python/plugins/processing/otb/description/SOMClassification.xml b/python/plugins/processing/otb/description/SOMClassification.xml new file mode 100644 index 000000000000..fd13d30e4363 --- /dev/null +++ b/python/plugins/processing/otb/description/SOMClassification.xml @@ -0,0 +1,152 @@ + + SOMClassification + otbcli_SOMClassification + SOM Classification + Learning + SOM image classification. + + ParameterRaster + in + InputImage + Input image to classify. + False + + + OutputRaster + out + OutputImage + Output classified image (each pixel contains the index of its corresponding vector in the SOM). + + + + ParameterRaster + vm + ValidityMask + Validity mask (only pixels corresponding to a mask value greater than 0 will be used for learning) + True + + + ParameterNumber + tp + TrainingProbability + Probability for a sample to be selected in the training set + + + 1 + + + ParameterNumber + ts + TrainingSetSize + Maximum training set size (in pixels) + + + 0 + + + ParameterNumber + sl + StreamingLines + Number of lines in each streaming block (used during data sampling) + + + 0 + + + OutputRaster + som + SOM Map + Output image containing the Self-Organizing Map + + + + ParameterNumber + sx + SizeX + X size of the SOM map + + + 32 + + + ParameterNumber + sy + SizeY + Y size of the SOM map + + + 32 + + + ParameterNumber + nx + NeighborhoodX + X size of the initial neighborhood in the SOM map + + + 10 + + + ParameterNumber + ny + NeighborhoodY + Y size of the initial neighborhood in the SOM map + + + 10 + + + ParameterNumber + ni + NumberIteration + Number of iterations for SOM learning + + + 5 + + + ParameterNumber + bi + BetaInit + Initial learning coefficient + + + 1 + + + ParameterNumber + bf + BetaFinal + Final learning coefficient + + + 0.1 + + + ParameterNumber + iv + InitialValue + Maximum initial neuron weight + + + 0 + + + ParameterNumber + ram + Available RAM (Mb) + Available memory for processing (in MB) + + + 128 + + + ParameterNumber + rand + set user defined seed + Set specific seed. with integer value. + + + 0 + + diff --git a/python/plugins/processing/otb/description/SarRadiometricCalibration.txt b/python/plugins/processing/otb/description/SarRadiometricCalibration.txt deleted file mode 100644 index d059f06228d4..000000000000 --- a/python/plugins/processing/otb/description/SarRadiometricCalibration.txt +++ /dev/null @@ -1,8 +0,0 @@ -SarRadiometricCalibration -otbcli_SarRadiometricCalibration -SAR Radiometric calibration -Calibration -ParameterRaster|-in|Input Complex Image|False -OutputRaster|-out|Output Image -ParameterNumber|-ram|Available RAM (Mb)|None|None|128 -ParameterBoolean|-noise|Disable Noise| diff --git a/python/plugins/processing/otb/description/Segmentation-cc.xml b/python/plugins/processing/otb/description/Segmentation-cc.xml new file mode 100644 index 000000000000..8fc792fabcc8 --- /dev/null +++ b/python/plugins/processing/otb/description/Segmentation-cc.xml @@ -0,0 +1,153 @@ + + Segmentation-cc + otbcli_Segmentation + Segmentation (cc) + Segmentation + Performs segmentation of an image, and output either a raster or a vector file. In vector mode, large input datasets are supported. + + ParameterRaster + in + Input Image + The input image to segment + False + + + ParameterSelection + filter + Segmentation algorithm + Choice of segmentation algorithm (mean-shift by default) + + + cc + + + 0 + + + ParameterString + filter.cc.expr + Condition + User defined connection condition, written as a mathematical expression. Available variables are p(i)b(i), intensity_p(i) and distance (example of expression : distance < 10 ) + + + False + + + ParameterSelection + mode + Processing mode + Choice of processing mode, either raster or large-scale. + + + vector + + + 0 + + + OutputVector + mode.vector.out + Output vector file + The output vector file or database (name can be anything understood by OGR) + + + + ParameterSelection + mode.vector.outmode + Writing mode for the output vector file + This allows to set the writing behaviour for the output vector file. Please note that the actual behaviour depends on the file format. + + + ulco + ovw + ulovw + ulu + + + 0 + + + ParameterRaster + mode.vector.inmask + Mask Image + Only pixels whose mask value is strictly positive will be segmented. + True + + + ParameterBoolean + mode.vector.neighbor + 8-neighbor connectivity + Activate 8-Neighborhood connectivity (default is 4). + True + + + ParameterBoolean + mode.vector.stitch + Stitch polygons + Scan polygons on each side of tiles and stitch polygons which connect by more than one pixel. + True + + + ParameterNumber + mode.vector.minsize + Minimum object size + Objects whose size is below the minimum object size (area in pixels) will be ignored during vectorization. + + + 1 + + + ParameterNumber + mode.vector.simplify + Simplify polygons + Simplify polygons according to a given tolerance (in pixel). This option allows to reduce the size of the output file or database. + + + 0.1 + + + ParameterString + mode.vector.layername + Layer name + Name of the layer in the vector file or database (default is Layer). + layer + + False + + + ParameterString + mode.vector.fieldname + Geometry index field name + Name of the field holding the geometry index in the output vector file or database. + DN + + False + + + ParameterNumber + mode.vector.tilesize + Tiles size + User defined tiles size for tile-based segmentation. Optimal tile size is selected according to available RAM if null. + + + 1024 + + + ParameterNumber + mode.vector.startlabel + Starting geometry index + Starting value of the geometry index field + + + 1 + + + ParameterString + mode.vector.ogroptions + OGR options for layer creation + A list of layer creation options in the form KEY=VALUE that will be passed directly to OGR without any validity checking. Options may depend on the file format, and can be found in OGR documentation. + + + True + + diff --git a/python/plugins/processing/otb/description/Segmentation-edison.xml b/python/plugins/processing/otb/description/Segmentation-edison.xml new file mode 100644 index 000000000000..e02eac849bf6 --- /dev/null +++ b/python/plugins/processing/otb/description/Segmentation-edison.xml @@ -0,0 +1,180 @@ + + Segmentation-edison + otbcli_Segmentation + Segmentation (edison) + Segmentation + Performs segmentation of an image, and output either a raster or a vector file. In vector mode, large input datasets are supported. + + ParameterRaster + in + Input Image + The input image to segment + False + + + ParameterSelection + filter + Segmentation algorithm + Choice of segmentation algorithm (mean-shift by default) + + + edison + + + 0 + + + ParameterNumber + filter.edison.spatialr + Spatial radius + Spatial radius defining neighborhood. + + + 5 + + + ParameterNumber + filter.edison.ranger + Range radius + Range radius defining the radius (expressed in radiometry unit) in the multi-spectral space. + + + 15 + + + ParameterNumber + filter.edison.minsize + Minimum region size + Minimum size of a region in segmentation. Smaller clusters will be merged to the neighboring cluster with the closest radiometry. + + + 100 + + + ParameterNumber + filter.edison.scale + Scale factor + Scaling of the image before processing. This is useful for images with narrow decimal ranges (like [0,1] for instance). + + + 1 + + + ParameterSelection + mode + Processing mode + Choice of processing mode, either raster or large-scale. + + + vector + + + 0 + + + OutputVector + mode.vector.out + Output vector file + The output vector file or database (name can be anything understood by OGR) + + + + ParameterSelection + mode.vector.outmode + Writing mode for the output vector file + This allows to set the writing behaviour for the output vector file. Please note that the actual behaviour depends on the file format. + + + ulco + ovw + ulovw + ulu + + + 0 + + + ParameterRaster + mode.vector.inmask + Mask Image + Only pixels whose mask value is strictly positive will be segmented. + True + + + ParameterBoolean + mode.vector.neighbor + 8-neighbor connectivity + Activate 8-Neighborhood connectivity (default is 4). + True + + + ParameterBoolean + mode.vector.stitch + Stitch polygons + Scan polygons on each side of tiles and stitch polygons which connect by more than one pixel. + True + + + ParameterNumber + mode.vector.minsize + Minimum object size + Objects whose size is below the minimum object size (area in pixels) will be ignored during vectorization. + + + 1 + + + ParameterNumber + mode.vector.simplify + Simplify polygons + Simplify polygons according to a given tolerance (in pixel). This option allows to reduce the size of the output file or database. + + + 0.1 + + + ParameterString + mode.vector.layername + Layer name + Name of the layer in the vector file or database (default is Layer). + layer + + False + + + ParameterString + mode.vector.fieldname + Geometry index field name + Name of the field holding the geometry index in the output vector file or database. + DN + + False + + + ParameterNumber + mode.vector.tilesize + Tiles size + User defined tiles size for tile-based segmentation. Optimal tile size is selected according to available RAM if null. + + + 1024 + + + ParameterNumber + mode.vector.startlabel + Starting geometry index + Starting value of the geometry index field + + + 1 + + + ParameterString + mode.vector.ogroptions + OGR options for layer creation + A list of layer creation options in the form KEY=VALUE that will be passed directly to OGR without any validity checking. Options may depend on the file format, and can be found in OGR documentation. + + + True + + diff --git a/python/plugins/processing/otb/description/Segmentation-meanshift.xml b/python/plugins/processing/otb/description/Segmentation-meanshift.xml new file mode 100644 index 000000000000..7f067343c9e4 --- /dev/null +++ b/python/plugins/processing/otb/description/Segmentation-meanshift.xml @@ -0,0 +1,189 @@ + + Segmentation-meanshift + otbcli_Segmentation + Segmentation (meanshift) + Segmentation + Performs segmentation of an image, and output either a raster or a vector file. In vector mode, large input datasets are supported. + + ParameterRaster + in + Input Image + The input image to segment + False + + + ParameterSelection + filter + Segmentation algorithm + Choice of segmentation algorithm (mean-shift by default) + + + meanshift + + + 0 + + + ParameterNumber + filter.meanshift.spatialr + Spatial radius + Spatial radius of the neighborhood. + + + 5 + + + ParameterNumber + filter.meanshift.ranger + Range radius + Range radius defining the radius (expressed in radiometry unit) in the multispectral space. + + + 15 + + + ParameterNumber + filter.meanshift.thres + Mode convergence threshold + Algorithm iterative scheme will stop if mean-shift vector is below this threshold or if iteration number reached maximum number of iterations. + + + 0.1 + + + ParameterNumber + filter.meanshift.maxiter + Maximum number of iterations + Algorithm iterative scheme will stop if convergence hasn't been reached after the maximum number of iterations. + + + 100 + + + ParameterNumber + filter.meanshift.minsize + Minimum region size + Minimum size of a region (in pixel unit) in segmentation. Smaller clusters will be merged to the neighboring cluster with the closest radiometry. If set to 0 no pruning is done. + + + 100 + + + ParameterSelection + mode + Processing mode + Choice of processing mode, either raster or large-scale. + + + vector + + + 0 + + + OutputVector + mode.vector.out + Output vector file + The output vector file or database (name can be anything understood by OGR) + + + + ParameterSelection + mode.vector.outmode + Writing mode for the output vector file + This allows to set the writing behaviour for the output vector file. Please note that the actual behaviour depends on the file format. + + + ulco + ovw + ulovw + ulu + + + 0 + + + ParameterRaster + mode.vector.inmask + Mask Image + Only pixels whose mask value is strictly positive will be segmented. + True + + + ParameterBoolean + mode.vector.neighbor + 8-neighbor connectivity + Activate 8-Neighborhood connectivity (default is 4). + True + + + ParameterBoolean + mode.vector.stitch + Stitch polygons + Scan polygons on each side of tiles and stitch polygons which connect by more than one pixel. + True + + + ParameterNumber + mode.vector.minsize + Minimum object size + Objects whose size is below the minimum object size (area in pixels) will be ignored during vectorization. + + + 1 + + + ParameterNumber + mode.vector.simplify + Simplify polygons + Simplify polygons according to a given tolerance (in pixel). This option allows to reduce the size of the output file or database. + + + 0.1 + + + ParameterString + mode.vector.layername + Layer name + Name of the layer in the vector file or database (default is Layer). + layer + + False + + + ParameterString + mode.vector.fieldname + Geometry index field name + Name of the field holding the geometry index in the output vector file or database. + DN + + False + + + ParameterNumber + mode.vector.tilesize + Tiles size + User defined tiles size for tile-based segmentation. Optimal tile size is selected according to available RAM if null. + + + 1024 + + + ParameterNumber + mode.vector.startlabel + Starting geometry index + Starting value of the geometry index field + + + 1 + + + ParameterString + mode.vector.ogroptions + OGR options for layer creation + A list of layer creation options in the form KEY=VALUE that will be passed directly to OGR without any validity checking. Options may depend on the file format, and can be found in OGR documentation. + + + True + + diff --git a/python/plugins/processing/otb/description/Segmentation-mprofiles.xml b/python/plugins/processing/otb/description/Segmentation-mprofiles.xml new file mode 100644 index 000000000000..6fc14a7c3858 --- /dev/null +++ b/python/plugins/processing/otb/description/Segmentation-mprofiles.xml @@ -0,0 +1,180 @@ + + Segmentation-mprofiles + otbcli_Segmentation + Segmentation (mprofiles) + Segmentation + Performs segmentation of an image, and output either a raster or a vector file. In vector mode, large input datasets are supported. + + ParameterRaster + in + Input Image + The input image to segment + False + + + ParameterSelection + filter + Segmentation algorithm + Choice of segmentation algorithm (mean-shift by default) + + + mprofiles + + + 0 + + + ParameterNumber + filter.mprofiles.size + Profile Size + Size of the profiles + + + 5 + + + ParameterNumber + filter.mprofiles.start + Initial radius + Initial radius of the structuring element (in pixels) + + + 1 + + + ParameterNumber + filter.mprofiles.step + Radius step. + Radius step along the profile (in pixels) + + + 1 + + + ParameterNumber + filter.mprofiles.sigma + Threshold of the final decision rule + Profiles values under the threshold will be ignored. + + + 1 + + + ParameterSelection + mode + Processing mode + Choice of processing mode, either raster or large-scale. + + + vector + + + 0 + + + OutputVector + mode.vector.out + Output vector file + The output vector file or database (name can be anything understood by OGR) + + + + ParameterSelection + mode.vector.outmode + Writing mode for the output vector file + This allows to set the writing behaviour for the output vector file. Please note that the actual behaviour depends on the file format. + + + ulco + ovw + ulovw + ulu + + + 0 + + + ParameterRaster + mode.vector.inmask + Mask Image + Only pixels whose mask value is strictly positive will be segmented. + True + + + ParameterBoolean + mode.vector.neighbor + 8-neighbor connectivity + Activate 8-Neighborhood connectivity (default is 4). + True + + + ParameterBoolean + mode.vector.stitch + Stitch polygons + Scan polygons on each side of tiles and stitch polygons which connect by more than one pixel. + True + + + ParameterNumber + mode.vector.minsize + Minimum object size + Objects whose size is below the minimum object size (area in pixels) will be ignored during vectorization. + + + 1 + + + ParameterNumber + mode.vector.simplify + Simplify polygons + Simplify polygons according to a given tolerance (in pixel). This option allows to reduce the size of the output file or database. + + + 0.1 + + + ParameterString + mode.vector.layername + Layer name + Name of the layer in the vector file or database (default is Layer). + layer + + False + + + ParameterString + mode.vector.fieldname + Geometry index field name + Name of the field holding the geometry index in the output vector file or database. + DN + + False + + + ParameterNumber + mode.vector.tilesize + Tiles size + User defined tiles size for tile-based segmentation. Optimal tile size is selected according to available RAM if null. + + + 1024 + + + ParameterNumber + mode.vector.startlabel + Starting geometry index + Starting value of the geometry index field + + + 1 + + + ParameterString + mode.vector.ogroptions + OGR options for layer creation + A list of layer creation options in the form KEY=VALUE that will be passed directly to OGR without any validity checking. Options may depend on the file format, and can be found in OGR documentation. + + + True + + diff --git a/python/plugins/processing/otb/description/Segmentation-watershed.xml b/python/plugins/processing/otb/description/Segmentation-watershed.xml new file mode 100644 index 000000000000..7ef004e4f4fc --- /dev/null +++ b/python/plugins/processing/otb/description/Segmentation-watershed.xml @@ -0,0 +1,162 @@ + + Segmentation-watershed + otbcli_Segmentation + Segmentation (watershed) + Segmentation + Performs segmentation of an image, and output either a raster or a vector file. In vector mode, large input datasets are supported. + + ParameterRaster + in + Input Image + The input image to segment + False + + + ParameterSelection + filter + Segmentation algorithm + Choice of segmentation algorithm (mean-shift by default) + + + watershed + + + 0 + + + ParameterNumber + filter.watershed.threshold + Depth Threshold + Depth threshold Units in percentage of the maximum depth in the image. + + + 0.01 + + + ParameterNumber + filter.watershed.level + Flood Level + flood level for generating the merge tree from the initial segmentation (between 0 and 1) + + + 0.1 + + + ParameterSelection + mode + Processing mode + Choice of processing mode, either raster or large-scale. + + + vector + + + 0 + + + OutputVector + mode.vector.out + Output vector file + The output vector file or database (name can be anything understood by OGR) + + + + ParameterSelection + mode.vector.outmode + Writing mode for the output vector file + This allows to set the writing behaviour for the output vector file. Please note that the actual behaviour depends on the file format. + + + ulco + ovw + ulovw + ulu + + + 0 + + + ParameterRaster + mode.vector.inmask + Mask Image + Only pixels whose mask value is strictly positive will be segmented. + True + + + ParameterBoolean + mode.vector.neighbor + 8-neighbor connectivity + Activate 8-Neighborhood connectivity (default is 4). + True + + + ParameterBoolean + mode.vector.stitch + Stitch polygons + Scan polygons on each side of tiles and stitch polygons which connect by more than one pixel. + True + + + ParameterNumber + mode.vector.minsize + Minimum object size + Objects whose size is below the minimum object size (area in pixels) will be ignored during vectorization. + + + 1 + + + ParameterNumber + mode.vector.simplify + Simplify polygons + Simplify polygons according to a given tolerance (in pixel). This option allows to reduce the size of the output file or database. + + + 0.1 + + + ParameterString + mode.vector.layername + Layer name + Name of the layer in the vector file or database (default is Layer). + layer + + False + + + ParameterString + mode.vector.fieldname + Geometry index field name + Name of the field holding the geometry index in the output vector file or database. + DN + + False + + + ParameterNumber + mode.vector.tilesize + Tiles size + User defined tiles size for tile-based segmentation. Optimal tile size is selected according to available RAM if null. + + + 1024 + + + ParameterNumber + mode.vector.startlabel + Starting geometry index + Starting value of the geometry index field + + + 1 + + + ParameterString + mode.vector.ogroptions + OGR options for layer creation + A list of layer creation options in the form KEY=VALUE that will be passed directly to OGR without any validity checking. Options may depend on the file format, and can be found in OGR documentation. + + + True + + diff --git a/python/plugins/processing/otb/description/SimpleConnectedComponentsSegmentation.txt b/python/plugins/processing/otb/description/SimpleConnectedComponentsSegmentation.txt deleted file mode 100644 index 63f40c8137ce..000000000000 --- a/python/plugins/processing/otb/description/SimpleConnectedComponentsSegmentation.txt +++ /dev/null @@ -1,8 +0,0 @@ -SimpleConnectedComponentsSegmentation -otbcli_Segmentation -Simple Connected Components segmentation (labeled raster output) -Segmentation -ParameterRaster|-filter cc -in|Input Image|False -ParameterString|-filter.cc.expr|Condition| -OutputRaster|-mode raster -mode.raster.out|Output labeled image - diff --git a/python/plugins/processing/otb/description/SimpleConnectedComponentsSegmentation_vector.txt b/python/plugins/processing/otb/description/SimpleConnectedComponentsSegmentation_vector.txt deleted file mode 100644 index 658d2efba648..000000000000 --- a/python/plugins/processing/otb/description/SimpleConnectedComponentsSegmentation_vector.txt +++ /dev/null @@ -1,18 +0,0 @@ -SimpleConnectedComponentsSegmentationVector -otbcli_Segmentation -Simple Connected Components segmentation (large-scale, vector output) -Segmentation -ParameterRaster|-filter cc -in|Input Image|False -ParameterString|-filter.cc.expr|Condition| -OutputVector|-mode vector -mode.vector.out|Output vector file -ParameterVector|-mode.vector.inmask|Mask Image|-1|True -ParameterBoolean|-mode.vector.neighbor|8-neighbor connectivity|False -ParameterBoolean|-mode.vector.stitch|Stitch polygons|True -ParameterNumber|-mode.vector.minsize|Minimum object size|1|None|1 -ParameterNumber|-mode.vector.simplify|Simplify polygons|None|None|0.0 -ParameterString|-mode.vector.layername|Layer name |layer -ParemeterString|-mode.vector.fieldname|Geometry index field name|DN -ParameterNumber|-mode.vector.tilesize|Tile size|0|None|1024 -ParameterNumber|-mode.vector.startlabel|Starting geometry index|1|None|1 -ParameterSelection|-mode.vector.outmode|Writing mode (update file/overwrite file/overwrite layer/update layer)|ulco;ovw;ulovw;ulu|0 -ParameterString|-mode.vector.ogroptions|OGR options for layer creation| diff --git a/python/plugins/processing/otb/description/Smoothing-anidif.xml b/python/plugins/processing/otb/description/Smoothing-anidif.xml new file mode 100644 index 000000000000..565747cda838 --- /dev/null +++ b/python/plugins/processing/otb/description/Smoothing-anidif.xml @@ -0,0 +1,60 @@ + + Smoothing-anidif + otbcli_Smoothing + Smoothing (anidif) + Image Filtering + Apply a smoothing filter to an image + + ParameterRaster + in + Input Image + Input image to smooth. + False + + + OutputRaster + out + Output Image + Output smoothed image. + + + + ParameterNumber + ram + Available RAM (Mb) + Available memory for processing (in MB) + + + 128 + + + ParameterSelection + type + Smoothing Type + Smoothing kernel to apply + + + anidif + + + 2 + + + ParameterNumber + type.anidif.timestep + Time Step + Diffusion equation time step + + + 0.125 + + + ParameterNumber + type.anidif.nbiter + Nb Iterations + Number of iterations + + + 10 + + diff --git a/python/plugins/processing/otb/description/Smoothing-gaussian.xml b/python/plugins/processing/otb/description/Smoothing-gaussian.xml new file mode 100644 index 000000000000..a07675ba03e5 --- /dev/null +++ b/python/plugins/processing/otb/description/Smoothing-gaussian.xml @@ -0,0 +1,51 @@ + + Smoothing-gaussian + otbcli_Smoothing + Smoothing (gaussian) + Image Filtering + Apply a smoothing filter to an image + + ParameterRaster + in + Input Image + Input image to smooth. + False + + + OutputRaster + out + Output Image + Output smoothed image. + + + + ParameterNumber + ram + Available RAM (Mb) + Available memory for processing (in MB) + + + 128 + + + ParameterSelection + type + Smoothing Type + Smoothing kernel to apply + + + gaussian + + + 2 + + + ParameterNumber + type.gaussian.radius + Radius + Gaussian radius (in pixels) + + + 2 + + diff --git a/python/plugins/processing/otb/description/Smoothing-mean.xml b/python/plugins/processing/otb/description/Smoothing-mean.xml new file mode 100644 index 000000000000..d093be754662 --- /dev/null +++ b/python/plugins/processing/otb/description/Smoothing-mean.xml @@ -0,0 +1,51 @@ + + Smoothing-mean + otbcli_Smoothing + Smoothing (mean) + Image Filtering + Apply a smoothing filter to an image + + ParameterRaster + in + Input Image + Input image to smooth. + False + + + OutputRaster + out + Output Image + Output smoothed image. + + + + ParameterNumber + ram + Available RAM (Mb) + Available memory for processing (in MB) + + + 128 + + + ParameterSelection + type + Smoothing Type + Smoothing kernel to apply + + + mean + + + 2 + + + ParameterNumber + type.mean.radius + Radius + Mean radius (in pixels) + + + 2 + + diff --git a/python/plugins/processing/otb/description/Smoothing.txt b/python/plugins/processing/otb/description/Smoothing.txt deleted file mode 100644 index 417be6429745..000000000000 --- a/python/plugins/processing/otb/description/Smoothing.txt +++ /dev/null @@ -1,12 +0,0 @@ -Smoothing -otbcli_Smoothing -Smoothing -Image Filtering -ParameterRaster|-in|Input Image|False -OutputRaster|-out|Output Image -ParameterNumber|-ram|Available RAM (Mb)|None|None|128 -ParameterSelection|-type|Smoothing Type|mean;gaussian;anidif|2 -ParameterNumber|-type.mean.radius|Radius|None|None|2 -ParameterNumber|-type.gaussian.radius|Radius|None|None|2 -ParameterNumber|-type.anidif.timestep|Time Step|None|None|0.125 -ParameterNumber|-type.anidif.nbiter|Nb Iterations|None|None|10 diff --git a/python/plugins/processing/otb/description/SplitImage.txt b/python/plugins/processing/otb/description/SplitImage.txt deleted file mode 100644 index be27aa391306..000000000000 --- a/python/plugins/processing/otb/description/SplitImage.txt +++ /dev/null @@ -1,7 +0,0 @@ -SplitImage -otbcli_SplitImage -Split Image -Image Manipulation -ParameterRaster|-in|Input Image|False -OutputFile|-out|Output Image -ParameterNumber|-ram|Available RAM (Mb)|None|None|128 diff --git a/python/plugins/processing/otb/description/SplitImage.xml b/python/plugins/processing/otb/description/SplitImage.xml new file mode 100644 index 000000000000..298a935096ae --- /dev/null +++ b/python/plugins/processing/otb/description/SplitImage.xml @@ -0,0 +1,30 @@ + + SplitImage + otbcli_SplitImage + Split Image + Image Manipulation + Split a N multiband image into N images + + ParameterRaster + in + Input Image + Input multiband image filename. + False + + + OutputFile + out + Output Image + Output filename that will be used to get the prefix and the extension of the output images to write + + + + ParameterNumber + ram + Available RAM (Mb) + Available memory for processing (in MB) + + + 128 + + diff --git a/python/plugins/processing/otb/description/StereoFramework.xml b/python/plugins/processing/otb/description/StereoFramework.xml new file mode 100644 index 000000000000..f85f2400655c --- /dev/null +++ b/python/plugins/processing/otb/description/StereoFramework.xml @@ -0,0 +1,315 @@ + + StereoFramework + otbcli_StereoFramework + Stereo Framework + Stereo + Compute the ground elevation based on one or multiple stereo pair(s) + + ParameterMultipleInput + input.il + Input images list + The list of images. + + False + + + ParameterString + input.co + Couples list + List of index of couples im image list. Couples must be separated by a comma. (index start at 0). for example : 0 1,1 2 will process a first couple composed of the first and the second image in image list, then the first and the third image +. note that images are handled by pairs. if left empty couples are created from input index i.e. a first couple will be composed of the first and second image, a second couple with third and fourth image etc. (in this case image list must be even). + + + True + + + ParameterNumber + input.channel + Image channel used for the block matching + Used channel for block matching (used for all images) + + + 1 + + + ParameterNumber + elev.default + Default elevation + This parameter allows to set the default height above ellipsoid when there is no DEM available, no coverage for some points or pixels with no_data in the DEM tiles, and no geoid file has been set. This is also used by some application as an average elevation value. + + + 0 + + + ParameterNumber + output.res + Output resolution + Spatial sampling distance of the output elevation : the cell size (in m) + + + 1 + + + ParameterNumber + output.nodata + NoData value + DSM empty cells are filled with this value (optional -32768 by default) + + + -32768 + + + ParameterSelection + output.fusionmethod + Method to fuse measures in each DSM cell + This parameter allows to choose the method used to fuse elevation measurements in each output DSM cell + + + max + min + mean + acc + + + 0 + + + OutputRaster + output.out + Output DSM + Output elevation image + + + + ParameterSelection + output.mode + Parameters estimation modes + + + + fit + user + + + 0 + + + ParameterNumber + output.mode.user.ulx + Upper Left X + Cartographic X coordinate of upper-left corner (meters for cartographic projections, degrees for geographic ones) + + + 0.0 + + + ParameterNumber + output.mode.user.uly + Upper Left Y + Cartographic Y coordinate of the upper-left corner (meters for cartographic projections, degrees for geographic ones) + + + 0.0 + + + ParameterNumber + output.mode.user.sizex + Size X + Size of projected image along X (in pixels) + + + 0 + + + ParameterNumber + output.mode.user.sizey + Size Y + Size of projected image along Y (in pixels) + + + 0 + + + ParameterNumber + output.mode.user.spacingx + Pixel Size X + Size of each pixel along X axis (meters for cartographic projections, degrees for geographic ones) + + + 0.0 + + + ParameterNumber + output.mode.user.spacingy + Pixel Size Y + Size of each pixel along Y axis (meters for cartographic projections, degrees for geographic ones) + + + 0.0 + + + ParameterSelection + map + Output Cartographic Map Projection + Parameters of the output map projection to be used. + + + utm + lambert2 + lambert93 + wgs + epsg + + + 3 + + + ParameterNumber + map.utm.zone + Zone number + The zone number ranges from 1 to 60 and allows to define the transverse mercator projection (along with the hemisphere) + + + 31 + + + ParameterBoolean + map.utm.northhem + Northern Hemisphere + The transverse mercator projections are defined by their zone number as well as the hemisphere. Activate this parameter if your image is in the northern hemisphere. + True + + + ParameterNumber + map.epsg.code + EPSG Code + See www.spatialreference.org to find which EPSG code is associated to your projection + + + 4326 + + + ParameterNumber + stereorect.fwdgridstep + Step of the deformation grid (in pixels) + Stereo-rectification deformation grid only varies slowly. Therefore, it is recommended to use a coarser grid (higher step value) in case of large images + + + 16 + + + ParameterNumber + stereorect.invgridssrate + Sub-sampling rate for epipolar grid inversion + Grid inversion is an heavy process that implies spline regression on control points. To avoid eating to much memory, this parameter allows to first sub-sample the field to invert. + + + 10 + + + ParameterSelection + bm.metric + Block-matching metric + + + + ssdmean + ssd + ncc + lp + + + 0 + + + ParameterNumber + bm.metric.lp.p + p value + Value of the p parameter in Lp pseudo-norm (must be positive) + + + 1 + + + ParameterNumber + bm.radius + Radius of blocks for matching filter (in pixels) + The radius of blocks in Block-Matching (in pixels) + + + 2 + + + ParameterNumber + bm.minhoffset + Minimum altitude offset (in meters) + Minimum altitude below the selected elevation source (in meters) + + + -20 + + + ParameterNumber + bm.maxhoffset + Maximum altitude offset (in meters) + Maximum altitude above the selected elevation source (in meters) + + + 20 + + + ParameterBoolean + postproc.bij + Use bijection consistency in block matching strategy + use bijection consistency. Right to Left correlation is computed to validate Left to Right disparities. If bijection is not found pixel is rejected. + True + + + ParameterBoolean + postproc.med + Use median disparities filtering + disparities output can be filtered using median post filtering (disabled by default). + True + + + ParameterNumber + postproc.metrict + Correlation metric threshold + Use block matching metric output to discard pixels with low correlation value (disabled by default, float value) + + + 0.6 + + + ParameterRaster + mask.left + Input left mask + Mask for left input image + True + + + ParameterRaster + mask.right + Input right mask + Mask for right input image + True + + + ParameterNumber + mask.variancet + Discard pixels with low local variance + This parameter allows to discard pixels whose local variance is too small (the size of the neighborhood is given by the radius parameter) + + + 50 + + + ParameterNumber + ram + Available RAM (Mb) + Available memory for processing (in MB) + + + 128 + + diff --git a/python/plugins/processing/otb/description/StereoRectificationGridGenerator.txt b/python/plugins/processing/otb/description/StereoRectificationGridGenerator.txt deleted file mode 100644 index 0da27dc1f4f7..000000000000 --- a/python/plugins/processing/otb/description/StereoRectificationGridGenerator.txt +++ /dev/null @@ -1,26 +0,0 @@ -StereoRectificationGridGenerator -otbcli_StereoRectificationGridGenerator -Stereo-rectification deformation grid generator -Geometry -ParameterRaster|-io.inleft|Left input image|False -ParameterRaster|-io.inright|Right input image|False -OutputRaster|-io.outleft|Left output deformation grid -OutputRaster|-io.outright|Right output deformation grid -ParameterSelection|-epi.elevation|Elevation management|avg;avgdem;dem|0 -ParameterNumber|-epi.elevation.avg.value|Average elevation value|None|None|0.0 -ParameterFile|-epi.elevation.avgdem.path|DEM directory| -ParameterFile|-epi.elevation.avgdem.geoid|Geoid file|| -ParameterNumber|-epi.elevation.avgdem.step|Sub-sampling step|None|None|1 -ParameterNumber|-epi.elevation.avgdem.value|Average elevation value|None|None|0.0 -ParameterNumber|-epi.elevation.avgdem.mindisp|Minimum disparity from DEM|None|None|0.0 -ParameterNumber|-epi.elevation.avgdem.maxdisp|Maximum disparity from DEM|None|None|0.0 -ParameterFile|-epi.elevation.dem.path|DEM directory| -ParameterFile|-epi.elevation.dem.geoid|Geoid file|| -ParameterNumber|-epi.scale|Scale of epipolar images|None|None|1.0 -ParameterNumber|-epi.step|Step of the deformation grid (in nb. of pixels)|None|None|1 -ParameterNumber|-epi.rectsizex|Rectified image size X|None|None|0 -ParameterNumber|-epi.rectsizey|Rectified image size Y|None|None|0 -ParameterNumber|-epi.baseline|Mean baseline ratio|None|None|0.0 -OutputRaster|-inverse.outleft|Left inverse deformation grid -OutputRaster|-inverse.outright|Right inverse deformation grid -ParameterNumber|-inverse.ssrate|Sub-sampling rate for inversion|None|None|16 diff --git a/python/plugins/processing/otb/description/StereoSensorModelToElevationMap.txt b/python/plugins/processing/otb/description/StereoSensorModelToElevationMap.txt deleted file mode 100644 index 8ae0950dcab0..000000000000 --- a/python/plugins/processing/otb/description/StereoSensorModelToElevationMap.txt +++ /dev/null @@ -1,22 +0,0 @@ -StereoSensorModelToElevationMap -otbcli_StereoSensorModelToElevationMap -Stereo sensor model to elevation map -Stereo -ParameterRaster|-ref|Reference|False -ParameterRaster|-sec|Secondary|False -OutputRaster|-out|Output Image -ParameterNumber|-ram|Available RAM (Mb)|None|None|128 -ParameterNumber|-r|Radius|None|None|3 -ParameterNumber|-ct|Correlation Threshold|None|None|0.699999988079 -ParameterNumber|-vt|Variance Threshold|None|None|4.0 -ParameterNumber|-minh|MinHeightOffset|None|None|-20.0 -ParameterNumber|-maxh|MaxHeightOffset|None|None|20.0 -ParameterNumber|-step|HeightStep|None|None|1.0 -ParameterNumber|-ae|AverageElevation|None|None|0.0 -ParameterSelection|-elev|Elevation management|dem;average|1 -ParameterFile|-elev.dem.path|DEM directory| -ParameterFile|-elev.dem.geoid|Geoid File|| -ParameterNumber|-elev.average.value|Average Elevation|None|None|0.0 -ParameterNumber|-rgs|ReferenceGaussianSmoothing|None|None|1.0 -ParameterNumber|-sgs|SecondaryGaussianSmoothing|None|None|1.0 -ParameterBoolean|-s|SubtractInitialHeight| diff --git a/python/plugins/processing/otb/description/Superimpose.txt b/python/plugins/processing/otb/description/Superimpose.txt deleted file mode 100644 index 98da6734b597..000000000000 --- a/python/plugins/processing/otb/description/Superimpose.txt +++ /dev/null @@ -1,13 +0,0 @@ -Superimpose -otbcli_Superimpose -Superimpose sensor -Geometry -ParameterRaster|-inr|Reference input|False -ParameterRaster|-inm|The image to reproject|False -ParameterSelection|-elev|Elevation management|dem;average|1 -ParameterFile|-elev.dem.path|DEM directory| -ParameterFile|-elev.dem.geoid|Geoid File|| -ParameterNumber|-elev.average.value|Average Elevation|None|None|0.0 -ParameterNumber|-lms|Spacing of the deformation field|None|None|4.0 -OutputRaster|-out|Output image -ParameterNumber|-ram|Available RAM (Mb)|None|None|128 diff --git a/python/plugins/processing/otb/description/Superimpose.xml b/python/plugins/processing/otb/description/Superimpose.xml new file mode 100644 index 000000000000..d9c4aa3faba9 --- /dev/null +++ b/python/plugins/processing/otb/description/Superimpose.xml @@ -0,0 +1,78 @@ + + Superimpose + otbcli_Superimpose + Superimpose sensor + Geometry + Using available image metadata, project one image onto another one + + ParameterRaster + inr + Reference input + The input reference image. + False + + + ParameterRaster + inm + The image to reproject + The image to reproject into the geometry of the reference input. + False + + + ParameterNumber + elev.default + Default elevation + This parameter allows to set the default height above ellipsoid when there is no DEM available, no coverage for some points or pixels with no_data in the DEM tiles, and no geoid file has been set. This is also used by some application as an average elevation value. + + + 0 + + + ParameterNumber + lms + Spacing of the deformation field + Generate a coarser deformation field with the given spacing + + + 4 + + + OutputRaster + out + Output image + Output reprojected image. + + + + ParameterSelection + interpolator + Interpolation + This group of parameters allows to define how the input image will be interpolated during resampling. + + + bco + nn + linear + + + 0 + + + ParameterNumber + interpolator.bco.radius + Radius for bicubic interpolation + This parameter allows to control the size of the bicubic interpolation filter. If the target pixel size is higher than the input pixel size, increasing this parameter will reduce aliasing artefacts. + + + 2 + + + ParameterNumber + ram + Available RAM (Mb) + Available memory for processing (in MB) + + + 128 + + diff --git a/python/plugins/processing/otb/description/TileFusion.xml b/python/plugins/processing/otb/description/TileFusion.xml new file mode 100644 index 000000000000..1a9ca2292207 --- /dev/null +++ b/python/plugins/processing/otb/description/TileFusion.xml @@ -0,0 +1,40 @@ + + TileFusion + otbcli_TileFusion + Image Tile Fusion + Image Manipulation + Fusion of an image made of several tile files. + + ParameterMultipleInput + il + Input Tile Images + Input tiles to concatenate (in lexicographic order : (0,0) (1,0) (0,1) (1,1)). + + False + + + ParameterNumber + cols + Number of tile columns + Number of columns in the tile array + + + 0 + + + ParameterNumber + rows + Number of tile rows + Number of rows in the tile array + + + 0 + + + OutputRaster + out + Output Image + Output entire image + + + diff --git a/python/plugins/processing/otb/description/TrainImagesClassifier-ann.xml b/python/plugins/processing/otb/description/TrainImagesClassifier-ann.xml new file mode 100644 index 000000000000..42a82ed6f59e --- /dev/null +++ b/python/plugins/processing/otb/description/TrainImagesClassifier-ann.xml @@ -0,0 +1,240 @@ + + TrainImagesClassifier-ann + otbcli_TrainImagesClassifier + TrainImagesClassifier (ann) + Learning + Train a classifier from multiple pairs of images and training vector data. + + ParameterMultipleInput + io.il + Input Image List + A list of input images. + + False + + + ParameterMultipleInput + io.vd + Input Vector Data List + A list of vector data to select the training samples. + + False + + + ParameterFile + io.imstat + Input XML image statistics file + Input XML file containing the mean and the standard deviation of the input images. + + True + + + OutputFile + io.confmatout + Output confusion matrix + Output file containing the confusion matrix (.csv format). + + + + OutputFile + io.out + Output model + Output file containing the model estimated (.txt format). + + + + ParameterNumber + elev.default + Default elevation + This parameter allows to set the default height above ellipsoid when there is no DEM available, no coverage for some points or pixels with no_data in the DEM tiles, and no geoid file has been set. This is also used by some application as an average elevation value. + + + 0 + + + ParameterNumber + sample.mt + Maximum training sample size per class + Maximum size per class (in pixels) of the training sample list (default = 1000) (no limit = -1). If equal to -1, then the maximal size of the available training sample list per class will be equal to the surface area of the smallest class multiplied by the training sample ratio. + + + 1000 + + + ParameterNumber + sample.mv + Maximum validation sample size per class + Maximum size per class (in pixels) of the validation sample list (default = 1000) (no limit = -1). If equal to -1, then the maximal size of the available validation sample list per class will be equal to the surface area of the smallest class multiplied by the validation sample ratio. + + + 1000 + + + ParameterBoolean + sample.edg + On edge pixel inclusion + Takes pixels on polygon edge into consideration when building training and validation samples. + True + + + ParameterNumber + sample.vtr + Training and validation sample ratio + Ratio between training and validation samples (0.0 = all training, 1.0 = all validation) (default = 0.5). + + + 0.5 + + + ParameterString + sample.vfn + Name of the discrimination field + Name of the field used to discriminate class labels in the input vector data files. + Class + + False + + + ParameterSelection + classifier + Classifier to use for the training + Choice of the classifier to use for the training. + + + ann + + + 0 + + + ParameterSelection + classifier.ann.t + Train Method Type + Type of training method for the multilayer perceptron (MLP) neural network. + + + reg + back + + + 0 + + + ParameterString + classifier.ann.sizes + Number of neurons in each intermediate layer + The number of neurons in each intermediate layer (excluding input and output layers). + + + False + + + ParameterSelection + classifier.ann.f + Neuron activation function type + Neuron activation function. + + + ident + sig + gau + + + 1 + + + ParameterNumber + classifier.ann.a + Alpha parameter of the activation function + Alpha parameter of the activation function (used only with sigmoid and gaussian functions). + + + 1 + + + ParameterNumber + classifier.ann.b + Beta parameter of the activation function + Beta parameter of the activation function (used only with sigmoid and gaussian functions). + + + 1 + + + ParameterNumber + classifier.ann.bpdw + Strength of the weight gradient term in the BACKPROP method + Strength of the weight gradient term in the BACKPROP method. The recommended value is about 0.1. + + + 0.1 + + + ParameterNumber + classifier.ann.bpms + Strength of the momentum term (the difference between weights on the 2 previous iterations) + Strength of the momentum term (the difference between weights on the 2 previous iterations). This parameter provides some inertia to smooth the random fluctuations of the weights. It can vary from 0 (the feature is disabled) to 1 and beyond. The value 0.1 or so is good enough. + + + 0.1 + + + ParameterNumber + classifier.ann.rdw + Initial value Delta_0 of update-values Delta_{ij} in RPROP method + Initial value Delta_0 of update-values Delta_{ij} in RPROP method (default = 0.1). + + + 0.1 + + + ParameterNumber + classifier.ann.rdwm + Update-values lower limit Delta_{min} in RPROP method + Update-values lower limit Delta_{min} in RPROP method. It must be positive (default = 1e-7). + + + 1e-07 + + + ParameterSelection + classifier.ann.term + Termination criteria + Termination criteria. + + + iter + eps + all + + + 2 + + + ParameterNumber + classifier.ann.eps + Epsilon value used in the Termination criteria + Epsilon value used in the Termination criteria. + + + 0.01 + + + ParameterNumber + classifier.ann.iter + Maximum number of iterations used in the Termination criteria + Maximum number of iterations used in the Termination criteria. + + + 1000 + + + ParameterNumber + rand + set user defined seed + Set specific seed. with integer value. + + + 0 + + diff --git a/python/plugins/processing/otb/description/TrainImagesClassifier-bayes.xml b/python/plugins/processing/otb/description/TrainImagesClassifier-bayes.xml new file mode 100644 index 000000000000..3366123704be --- /dev/null +++ b/python/plugins/processing/otb/description/TrainImagesClassifier-bayes.xml @@ -0,0 +1,118 @@ + + TrainImagesClassifier-bayes + otbcli_TrainImagesClassifier + TrainImagesClassifier (bayes) + Learning + Train a classifier from multiple pairs of images and training vector data. + + ParameterMultipleInput + io.il + Input Image List + A list of input images. + + False + + + ParameterMultipleInput + io.vd + Input Vector Data List + A list of vector data to select the training samples. + + False + + + ParameterFile + io.imstat + Input XML image statistics file + Input XML file containing the mean and the standard deviation of the input images. + + True + + + OutputFile + io.confmatout + Output confusion matrix + Output file containing the confusion matrix (.csv format). + + + + OutputFile + io.out + Output model + Output file containing the model estimated (.txt format). + + + + ParameterNumber + elev.default + Default elevation + This parameter allows to set the default height above ellipsoid when there is no DEM available, no coverage for some points or pixels with no_data in the DEM tiles, and no geoid file has been set. This is also used by some application as an average elevation value. + + + 0 + + + ParameterNumber + sample.mt + Maximum training sample size per class + Maximum size per class (in pixels) of the training sample list (default = 1000) (no limit = -1). If equal to -1, then the maximal size of the available training sample list per class will be equal to the surface area of the smallest class multiplied by the training sample ratio. + + + 1000 + + + ParameterNumber + sample.mv + Maximum validation sample size per class + Maximum size per class (in pixels) of the validation sample list (default = 1000) (no limit = -1). If equal to -1, then the maximal size of the available validation sample list per class will be equal to the surface area of the smallest class multiplied by the validation sample ratio. + + + 1000 + + + ParameterBoolean + sample.edg + On edge pixel inclusion + Takes pixels on polygon edge into consideration when building training and validation samples. + True + + + ParameterNumber + sample.vtr + Training and validation sample ratio + Ratio between training and validation samples (0.0 = all training, 1.0 = all validation) (default = 0.5). + + + 0.5 + + + ParameterString + sample.vfn + Name of the discrimination field + Name of the field used to discriminate class labels in the input vector data files. + Class + + False + + + ParameterSelection + classifier + Classifier to use for the training + Choice of the classifier to use for the training. + + + bayes + + + 0 + + + ParameterNumber + rand + set user defined seed + Set specific seed. with integer value. + + + 0 + + diff --git a/python/plugins/processing/otb/description/TrainImagesClassifier-boost.xml b/python/plugins/processing/otb/description/TrainImagesClassifier-boost.xml new file mode 100644 index 000000000000..29a85340f5e8 --- /dev/null +++ b/python/plugins/processing/otb/description/TrainImagesClassifier-boost.xml @@ -0,0 +1,160 @@ + + TrainImagesClassifier-boost + otbcli_TrainImagesClassifier + TrainImagesClassifier (boost) + Learning + Train a classifier from multiple pairs of images and training vector data. + + ParameterMultipleInput + io.il + Input Image List + A list of input images. + + False + + + ParameterMultipleInput + io.vd + Input Vector Data List + A list of vector data to select the training samples. + + False + + + ParameterFile + io.imstat + Input XML image statistics file + Input XML file containing the mean and the standard deviation of the input images. + + True + + + OutputFile + io.confmatout + Output confusion matrix + Output file containing the confusion matrix (.csv format). + + + + OutputFile + io.out + Output model + Output file containing the model estimated (.txt format). + + + + ParameterNumber + elev.default + Default elevation + This parameter allows to set the default height above ellipsoid when there is no DEM available, no coverage for some points or pixels with no_data in the DEM tiles, and no geoid file has been set. This is also used by some application as an average elevation value. + + + 0 + + + ParameterNumber + sample.mt + Maximum training sample size per class + Maximum size per class (in pixels) of the training sample list (default = 1000) (no limit = -1). If equal to -1, then the maximal size of the available training sample list per class will be equal to the surface area of the smallest class multiplied by the training sample ratio. + + + 1000 + + + ParameterNumber + sample.mv + Maximum validation sample size per class + Maximum size per class (in pixels) of the validation sample list (default = 1000) (no limit = -1). If equal to -1, then the maximal size of the available validation sample list per class will be equal to the surface area of the smallest class multiplied by the validation sample ratio. + + + 1000 + + + ParameterBoolean + sample.edg + On edge pixel inclusion + Takes pixels on polygon edge into consideration when building training and validation samples. + True + + + ParameterNumber + sample.vtr + Training and validation sample ratio + Ratio between training and validation samples (0.0 = all training, 1.0 = all validation) (default = 0.5). + + + 0.5 + + + ParameterString + sample.vfn + Name of the discrimination field + Name of the field used to discriminate class labels in the input vector data files. + Class + + False + + + ParameterSelection + classifier + Classifier to use for the training + Choice of the classifier to use for the training. + + + boost + + + 0 + + + ParameterSelection + classifier.boost.t + Boost Type + Type of Boosting algorithm. + + + discrete + real + logit + gentle + + + 1 + + + ParameterNumber + classifier.boost.w + Weak count + The number of weak classifiers. + + + 100 + + + ParameterNumber + classifier.boost.r + Weight Trim Rate + A threshold between 0 and 1 used to save computational time. Samples with summary weight <= (1 - weight_trim_rate) do not participate in the next iteration of training. Set this parameter to 0 to turn off this functionality. + + + 0.95 + + + ParameterNumber + classifier.boost.m + Maximum depth of the tree + Maximum depth of the tree. + + + 1 + + + ParameterNumber + rand + set user defined seed + Set specific seed. with integer value. + + + 0 + + diff --git a/python/plugins/processing/otb/description/TrainImagesClassifier-dt.xml b/python/plugins/processing/otb/description/TrainImagesClassifier-dt.xml new file mode 100644 index 000000000000..447971850a98 --- /dev/null +++ b/python/plugins/processing/otb/description/TrainImagesClassifier-dt.xml @@ -0,0 +1,177 @@ + + TrainImagesClassifier-dt + otbcli_TrainImagesClassifier + TrainImagesClassifier (dt) + Learning + Train a classifier from multiple pairs of images and training vector data. + + ParameterMultipleInput + io.il + Input Image List + A list of input images. + + False + + + ParameterMultipleInput + io.vd + Input Vector Data List + A list of vector data to select the training samples. + + False + + + ParameterFile + io.imstat + Input XML image statistics file + Input XML file containing the mean and the standard deviation of the input images. + + True + + + OutputFile + io.confmatout + Output confusion matrix + Output file containing the confusion matrix (.csv format). + + + + OutputFile + io.out + Output model + Output file containing the model estimated (.txt format). + + + + ParameterNumber + elev.default + Default elevation + This parameter allows to set the default height above ellipsoid when there is no DEM available, no coverage for some points or pixels with no_data in the DEM tiles, and no geoid file has been set. This is also used by some application as an average elevation value. + + + 0 + + + ParameterNumber + sample.mt + Maximum training sample size per class + Maximum size per class (in pixels) of the training sample list (default = 1000) (no limit = -1). If equal to -1, then the maximal size of the available training sample list per class will be equal to the surface area of the smallest class multiplied by the training sample ratio. + + + 1000 + + + ParameterNumber + sample.mv + Maximum validation sample size per class + Maximum size per class (in pixels) of the validation sample list (default = 1000) (no limit = -1). If equal to -1, then the maximal size of the available validation sample list per class will be equal to the surface area of the smallest class multiplied by the validation sample ratio. + + + 1000 + + + ParameterBoolean + sample.edg + On edge pixel inclusion + Takes pixels on polygon edge into consideration when building training and validation samples. + True + + + ParameterNumber + sample.vtr + Training and validation sample ratio + Ratio between training and validation samples (0.0 = all training, 1.0 = all validation) (default = 0.5). + + + 0.5 + + + ParameterString + sample.vfn + Name of the discrimination field + Name of the field used to discriminate class labels in the input vector data files. + Class + + False + + + ParameterSelection + classifier + Classifier to use for the training + Choice of the classifier to use for the training. + + + dt + + + 0 + + + ParameterNumber + classifier.dt.max + Maximum depth of the tree + The training algorithm attempts to split each node while its depth is smaller than the maximum possible depth of the tree. The actual depth may be smaller if the other termination criteria are met, and/or if the tree is pruned. + + + 65535 + + + ParameterNumber + classifier.dt.min + Minimum number of samples in each node + If all absolute differences between an estimated value in a node and the values of the train samples in this node are smaller than this regression accuracy parameter, then the node will not be split. + + + 10 + + + ParameterNumber + classifier.dt.ra + Termination criteria for regression tree + + + + 0.01 + + + ParameterNumber + classifier.dt.cat + Cluster possible values of a categorical variable into K <= cat clusters to find a suboptimal split + Cluster possible values of a categorical variable into K <= cat clusters to find a suboptimal split. + + + 10 + + + ParameterNumber + classifier.dt.f + K-fold cross-validations + If cv_folds > 1, then it prunes a tree with K-fold cross-validation where K is equal to cv_folds. + + + 10 + + + ParameterBoolean + classifier.dt.r + Set Use1seRule flag to false + If true, then a pruning will be harsher. This will make a tree more compact and more resistant to the training data noise but a bit less accurate. + True + + + ParameterBoolean + classifier.dt.t + Set TruncatePrunedTree flag to false + If true, then pruned branches are physically removed from the tree. + True + + + ParameterNumber + rand + set user defined seed + Set specific seed. with integer value. + + + 0 + + diff --git a/python/plugins/processing/otb/description/TrainImagesClassifier-gbt.xml b/python/plugins/processing/otb/description/TrainImagesClassifier-gbt.xml new file mode 100644 index 000000000000..33483a0cf10c --- /dev/null +++ b/python/plugins/processing/otb/description/TrainImagesClassifier-gbt.xml @@ -0,0 +1,154 @@ + + TrainImagesClassifier-gbt + otbcli_TrainImagesClassifier + TrainImagesClassifier (gbt) + Learning + Train a classifier from multiple pairs of images and training vector data. + + ParameterMultipleInput + io.il + Input Image List + A list of input images. + + False + + + ParameterMultipleInput + io.vd + Input Vector Data List + A list of vector data to select the training samples. + + False + + + ParameterFile + io.imstat + Input XML image statistics file + Input XML file containing the mean and the standard deviation of the input images. + + True + + + OutputFile + io.confmatout + Output confusion matrix + Output file containing the confusion matrix (.csv format). + + + + OutputFile + io.out + Output model + Output file containing the model estimated (.txt format). + + + + ParameterNumber + elev.default + Default elevation + This parameter allows to set the default height above ellipsoid when there is no DEM available, no coverage for some points or pixels with no_data in the DEM tiles, and no geoid file has been set. This is also used by some application as an average elevation value. + + + 0 + + + ParameterNumber + sample.mt + Maximum training sample size per class + Maximum size per class (in pixels) of the training sample list (default = 1000) (no limit = -1). If equal to -1, then the maximal size of the available training sample list per class will be equal to the surface area of the smallest class multiplied by the training sample ratio. + + + 1000 + + + ParameterNumber + sample.mv + Maximum validation sample size per class + Maximum size per class (in pixels) of the validation sample list (default = 1000) (no limit = -1). If equal to -1, then the maximal size of the available validation sample list per class will be equal to the surface area of the smallest class multiplied by the validation sample ratio. + + + 1000 + + + ParameterBoolean + sample.edg + On edge pixel inclusion + Takes pixels on polygon edge into consideration when building training and validation samples. + True + + + ParameterNumber + sample.vtr + Training and validation sample ratio + Ratio between training and validation samples (0.0 = all training, 1.0 = all validation) (default = 0.5). + + + 0.5 + + + ParameterString + sample.vfn + Name of the discrimination field + Name of the field used to discriminate class labels in the input vector data files. + Class + + False + + + ParameterSelection + classifier + Classifier to use for the training + Choice of the classifier to use for the training. + + + gbt + + + 0 + + + ParameterNumber + classifier.gbt.w + Number of boosting algorithm iterations + Number "w" of boosting algorithm iterations, with w*K being the total number of trees in the GBT model, where K is the output number of classes. + + + 200 + + + ParameterNumber + classifier.gbt.s + Regularization parameter + Regularization parameter. + + + 0.01 + + + ParameterNumber + classifier.gbt.p + Portion of the whole training set used for each algorithm iteration + Portion of the whole training set used for each algorithm iteration. The subset is generated randomly. + + + 0.8 + + + ParameterNumber + classifier.gbt.max + Maximum depth of the tree + The training algorithm attempts to split each node while its depth is smaller than the maximum possible depth of the tree. The actual depth may be smaller if the other termination criteria are met, and/or if the tree is pruned. + + + 3 + + + ParameterNumber + rand + set user defined seed + Set specific seed. with integer value. + + + 0 + + diff --git a/python/plugins/processing/otb/description/TrainImagesClassifier-knn.xml b/python/plugins/processing/otb/description/TrainImagesClassifier-knn.xml new file mode 100644 index 000000000000..fed27c0d5248 --- /dev/null +++ b/python/plugins/processing/otb/description/TrainImagesClassifier-knn.xml @@ -0,0 +1,127 @@ + + TrainImagesClassifier-knn + otbcli_TrainImagesClassifier + TrainImagesClassifier (knn) + Learning + Train a classifier from multiple pairs of images and training vector data. + + ParameterMultipleInput + io.il + Input Image List + A list of input images. + + False + + + ParameterMultipleInput + io.vd + Input Vector Data List + A list of vector data to select the training samples. + + False + + + ParameterFile + io.imstat + Input XML image statistics file + Input XML file containing the mean and the standard deviation of the input images. + + True + + + OutputFile + io.confmatout + Output confusion matrix + Output file containing the confusion matrix (.csv format). + + + + OutputFile + io.out + Output model + Output file containing the model estimated (.txt format). + + + + ParameterNumber + elev.default + Default elevation + This parameter allows to set the default height above ellipsoid when there is no DEM available, no coverage for some points or pixels with no_data in the DEM tiles, and no geoid file has been set. This is also used by some application as an average elevation value. + + + 0 + + + ParameterNumber + sample.mt + Maximum training sample size per class + Maximum size per class (in pixels) of the training sample list (default = 1000) (no limit = -1). If equal to -1, then the maximal size of the available training sample list per class will be equal to the surface area of the smallest class multiplied by the training sample ratio. + + + 1000 + + + ParameterNumber + sample.mv + Maximum validation sample size per class + Maximum size per class (in pixels) of the validation sample list (default = 1000) (no limit = -1). If equal to -1, then the maximal size of the available validation sample list per class will be equal to the surface area of the smallest class multiplied by the validation sample ratio. + + + 1000 + + + ParameterBoolean + sample.edg + On edge pixel inclusion + Takes pixels on polygon edge into consideration when building training and validation samples. + True + + + ParameterNumber + sample.vtr + Training and validation sample ratio + Ratio between training and validation samples (0.0 = all training, 1.0 = all validation) (default = 0.5). + + + 0.5 + + + ParameterString + sample.vfn + Name of the discrimination field + Name of the field used to discriminate class labels in the input vector data files. + Class + + False + + + ParameterSelection + classifier + Classifier to use for the training + Choice of the classifier to use for the training. + + + knn + + + 0 + + + ParameterNumber + classifier.knn.k + Number of Neighbors + The number of neighbors to use. + + + 32 + + + ParameterNumber + rand + set user defined seed + Set specific seed. with integer value. + + + 0 + + diff --git a/python/plugins/processing/otb/description/TrainImagesClassifier-libsvm.xml b/python/plugins/processing/otb/description/TrainImagesClassifier-libsvm.xml new file mode 100644 index 000000000000..37352811ce97 --- /dev/null +++ b/python/plugins/processing/otb/description/TrainImagesClassifier-libsvm.xml @@ -0,0 +1,149 @@ + + TrainImagesClassifier-libsvm + otbcli_TrainImagesClassifier + TrainImagesClassifier (libsvm) + Learning + Train a classifier from multiple pairs of images and training vector data. + + ParameterMultipleInput + io.il + Input Image List + A list of input images. + + False + + + ParameterMultipleInput + io.vd + Input Vector Data List + A list of vector data to select the training samples. + + False + + + ParameterFile + io.imstat + Input XML image statistics file + Input XML file containing the mean and the standard deviation of the input images. + + True + + + OutputFile + io.confmatout + Output confusion matrix + Output file containing the confusion matrix (.csv format). + + + + OutputFile + io.out + Output model + Output file containing the model estimated (.txt format). + + + + ParameterNumber + elev.default + Default elevation + This parameter allows to set the default height above ellipsoid when there is no DEM available, no coverage for some points or pixels with no_data in the DEM tiles, and no geoid file has been set. This is also used by some application as an average elevation value. + + + 0 + + + ParameterNumber + sample.mt + Maximum training sample size per class + Maximum size per class (in pixels) of the training sample list (default = 1000) (no limit = -1). If equal to -1, then the maximal size of the available training sample list per class will be equal to the surface area of the smallest class multiplied by the training sample ratio. + + + 1000 + + + ParameterNumber + sample.mv + Maximum validation sample size per class + Maximum size per class (in pixels) of the validation sample list (default = 1000) (no limit = -1). If equal to -1, then the maximal size of the available validation sample list per class will be equal to the surface area of the smallest class multiplied by the validation sample ratio. + + + 1000 + + + ParameterBoolean + sample.edg + On edge pixel inclusion + Takes pixels on polygon edge into consideration when building training and validation samples. + True + + + ParameterNumber + sample.vtr + Training and validation sample ratio + Ratio between training and validation samples (0.0 = all training, 1.0 = all validation) (default = 0.5). + + + 0.5 + + + ParameterString + sample.vfn + Name of the discrimination field + Name of the field used to discriminate class labels in the input vector data files. + Class + + False + + + ParameterSelection + classifier + Classifier to use for the training + Choice of the classifier to use for the training. + + + libsvm + + + 0 + + + ParameterSelection + classifier.libsvm.k + SVM Kernel Type + SVM Kernel Type. + + + linear + rbf + poly + sigmoid + + + 0 + + + ParameterNumber + classifier.libsvm.c + Cost parameter C + SVM models have a cost parameter C (1 by default) to control the trade-off between training errors and forcing rigid margins. + + + 1 + + + ParameterBoolean + classifier.libsvm.opt + Parameters optimization + SVM parameters optimization flag. + True + + + ParameterNumber + rand + set user defined seed + Set specific seed. with integer value. + + + 0 + + diff --git a/python/plugins/processing/otb/description/TrainImagesClassifier-rf.xml b/python/plugins/processing/otb/description/TrainImagesClassifier-rf.xml new file mode 100644 index 000000000000..457197ebe615 --- /dev/null +++ b/python/plugins/processing/otb/description/TrainImagesClassifier-rf.xml @@ -0,0 +1,181 @@ + + TrainImagesClassifier-rf + otbcli_TrainImagesClassifier + TrainImagesClassifier (rf) + Learning + Train a classifier from multiple pairs of images and training vector data. + + ParameterMultipleInput + io.il + Input Image List + A list of input images. + + False + + + ParameterMultipleInput + io.vd + Input Vector Data List + A list of vector data to select the training samples. + + False + + + ParameterFile + io.imstat + Input XML image statistics file + Input XML file containing the mean and the standard deviation of the input images. + + True + + + OutputFile + io.confmatout + Output confusion matrix + Output file containing the confusion matrix (.csv format). + + + + OutputFile + io.out + Output model + Output file containing the model estimated (.txt format). + + + + ParameterNumber + elev.default + Default elevation + This parameter allows to set the default height above ellipsoid when there is no DEM available, no coverage for some points or pixels with no_data in the DEM tiles, and no geoid file has been set. This is also used by some application as an average elevation value. + + + 0 + + + ParameterNumber + sample.mt + Maximum training sample size per class + Maximum size per class (in pixels) of the training sample list (default = 1000) (no limit = -1). If equal to -1, then the maximal size of the available training sample list per class will be equal to the surface area of the smallest class multiplied by the training sample ratio. + + + 1000 + + + ParameterNumber + sample.mv + Maximum validation sample size per class + Maximum size per class (in pixels) of the validation sample list (default = 1000) (no limit = -1). If equal to -1, then the maximal size of the available validation sample list per class will be equal to the surface area of the smallest class multiplied by the validation sample ratio. + + + 1000 + + + ParameterBoolean + sample.edg + On edge pixel inclusion + Takes pixels on polygon edge into consideration when building training and validation samples. + True + + + ParameterNumber + sample.vtr + Training and validation sample ratio + Ratio between training and validation samples (0.0 = all training, 1.0 = all validation) (default = 0.5). + + + 0.5 + + + ParameterString + sample.vfn + Name of the discrimination field + Name of the field used to discriminate class labels in the input vector data files. + Class + + False + + + ParameterSelection + classifier + Classifier to use for the training + Choice of the classifier to use for the training. + + + rf + + + 0 + + + ParameterNumber + classifier.rf.max + Maximum depth of the tree + The depth of the tree. A low value will likely underfit and conversely a high value will likely overfit. The optimal value can be obtained using cross validation or other suitable methods. + + + 5 + + + ParameterNumber + classifier.rf.min + Minimum number of samples in each node + If the number of samples in a node is smaller than this parameter, then the node will not be split. A reasonable value is a small percentage of the total data e.g. 1 percent. + + + 10 + + + ParameterNumber + classifier.rf.ra + Termination Criteria for regression tree + If all absolute differences between an estimated value in a node and the values of the train samples in this node are smaller than this regression accuracy parameter, then the node will not be split. + + + 0 + + + ParameterNumber + classifier.rf.cat + Cluster possible values of a categorical variable into K <= cat clusters to find a suboptimal split + Cluster possible values of a categorical variable into K <= cat clusters to find a suboptimal split. + + + 10 + + + ParameterNumber + classifier.rf.var + Size of the randomly selected subset of features at each tree node + The size of the subset of features, randomly selected at each tree node, that are used to find the best split(s). If you set it to 0, then the size will be set to the square root of the total number of features. + + + 0 + + + ParameterNumber + classifier.rf.nbtrees + Maximum number of trees in the forest + The maximum number of trees in the forest. Typically, the more trees you have, the better the accuracy. However, the improvement in accuracy generally diminishes and reaches an asymptote for a certain number of trees. Also to keep in mind, increasing the number of trees increases the prediction time linearly. + + + 100 + + + ParameterNumber + classifier.rf.acc + Sufficient accuracy (OOB error) + Sufficient accuracy (OOB error). + + + 0.01 + + + ParameterNumber + rand + set user defined seed + Set specific seed. with integer value. + + + 0 + + diff --git a/python/plugins/processing/otb/description/TrainImagesClassifier-svm.xml b/python/plugins/processing/otb/description/TrainImagesClassifier-svm.xml new file mode 100644 index 000000000000..c135e851b771 --- /dev/null +++ b/python/plugins/processing/otb/description/TrainImagesClassifier-svm.xml @@ -0,0 +1,202 @@ + + TrainImagesClassifier-svm + otbcli_TrainImagesClassifier + TrainImagesClassifier (svm) + Learning + Train a classifier from multiple pairs of images and training vector data. + + ParameterMultipleInput + io.il + Input Image List + A list of input images. + + False + + + ParameterMultipleInput + io.vd + Input Vector Data List + A list of vector data to select the training samples. + + False + + + ParameterFile + io.imstat + Input XML image statistics file + Input XML file containing the mean and the standard deviation of the input images. + + True + + + OutputFile + io.confmatout + Output confusion matrix + Output file containing the confusion matrix (.csv format). + + + + OutputFile + io.out + Output model + Output file containing the model estimated (.txt format). + + + + ParameterNumber + elev.default + Default elevation + This parameter allows to set the default height above ellipsoid when there is no DEM available, no coverage for some points or pixels with no_data in the DEM tiles, and no geoid file has been set. This is also used by some application as an average elevation value. + + + 0 + + + ParameterNumber + sample.mt + Maximum training sample size per class + Maximum size per class (in pixels) of the training sample list (default = 1000) (no limit = -1). If equal to -1, then the maximal size of the available training sample list per class will be equal to the surface area of the smallest class multiplied by the training sample ratio. + + + 1000 + + + ParameterNumber + sample.mv + Maximum validation sample size per class + Maximum size per class (in pixels) of the validation sample list (default = 1000) (no limit = -1). If equal to -1, then the maximal size of the available validation sample list per class will be equal to the surface area of the smallest class multiplied by the validation sample ratio. + + + 1000 + + + ParameterBoolean + sample.edg + On edge pixel inclusion + Takes pixels on polygon edge into consideration when building training and validation samples. + True + + + ParameterNumber + sample.vtr + Training and validation sample ratio + Ratio between training and validation samples (0.0 = all training, 1.0 = all validation) (default = 0.5). + + + 0.5 + + + ParameterString + sample.vfn + Name of the discrimination field + Name of the field used to discriminate class labels in the input vector data files. + Class + + False + + + ParameterSelection + classifier + Classifier to use for the training + Choice of the classifier to use for the training. + + + svm + + + 0 + + + ParameterSelection + classifier.svm.m + SVM Model Type + Type of SVM formulation. + + + csvc + nusvc + oneclass + + + 0 + + + ParameterSelection + classifier.svm.k + SVM Kernel Type + SVM Kernel Type. + + + linear + rbf + poly + sigmoid + + + 0 + + + ParameterNumber + classifier.svm.c + Cost parameter C + SVM models have a cost parameter C (1 by default) to control the trade-off between training errors and forcing rigid margins. + + + 1 + + + ParameterNumber + classifier.svm.nu + Parameter nu of a SVM optimization problem (NU_SVC / ONE_CLASS) + Parameter nu of a SVM optimization problem. + + + 0 + + + ParameterNumber + classifier.svm.coef0 + Parameter coef0 of a kernel function (POLY / SIGMOID) + Parameter coef0 of a kernel function (POLY / SIGMOID). + + + 0 + + + ParameterNumber + classifier.svm.gamma + Parameter gamma of a kernel function (POLY / RBF / SIGMOID) + Parameter gamma of a kernel function (POLY / RBF / SIGMOID). + + + 1 + + + ParameterNumber + classifier.svm.degree + Parameter degree of a kernel function (POLY) + Parameter degree of a kernel function (POLY). + + + 1 + + + ParameterBoolean + classifier.svm.opt + Parameters optimization + SVM parameters optimization flag. +-If set to True, then the optimal SVM parameters will be estimated. Parameters are considered optimal by OpenCV when the cross-validation estimate of the test set error is minimal. Finally, the SVM training process is computed 10 times with these optimal parameters over subsets corresponding to 1/10th of the training samples using the k-fold cross-validation (with k = 10). +-If set to False, the SVM classification process will be computed once with the currently set input SVM parameters over the training samples. +-Thus, even with identical input SVM parameters and a similar random seed, the output SVM models will be different according to the method used (optimized or not) because the samples are not identically processed within OpenCV. + True + + + ParameterNumber + rand + set user defined seed + Set specific seed. with integer value. + + + 0 + + diff --git a/python/plugins/processing/otb/description/TrainSVMImagesClassifier.txt b/python/plugins/processing/otb/description/TrainSVMImagesClassifier.txt deleted file mode 100644 index 72a36ea1efe7..000000000000 --- a/python/plugins/processing/otb/description/TrainSVMImagesClassifier.txt +++ /dev/null @@ -1,21 +0,0 @@ -TrainSVMImagesClassifier -otbcli_TrainSVMImagesClassifier -Train SVM classifier from multiple images -Learning -ParameterMultipleInput|-io.il|Input Image List|3|False -ParameterMultipleInput|-io.vd|Vector Data List|-1|False -ParameterFile|-io.imstat|XML image statistics file| -OutputFile|-io.out|Output SVM model -*ParameterSelection|-elev|Elevation management|dem;average|1 -*ParameterFile|-elev.dem|DEM directory| -*ParameterFile|-elev.geoid|Geoid File| -*ParameterNumber|-elev.default|Average Elevation|None|None|0.0 -*ParameterNumber|-sample.mt|Maximum training sample size|None|None|-1 -*ParameterNumber|-sample.mv|Maximum validation sample size|None|None|-1 -*ParameterBoolean|-sample.edg|On edge pixel inclusion| -ParameterNumber|-sample.vtr|training and validation sample ratio|None|None|0.5 -ParameterString|-sample.vfn|Name of the discrimination field|Class -ParameterSelection|-svm.k|SVM Kernel Type|linear;rbf;poly;sigmoid|0 -ParameterNumber|-svm.c|Cost parameter C.|None|None|1.0 -ParameterBoolean|-svm.opt|parameters optimization| -ParameterNumber|-rand|set user defined seed|None|None|0 diff --git a/python/plugins/processing/otb/description/ValidateSVMImagesClassifier.txt b/python/plugins/processing/otb/description/ValidateSVMImagesClassifier.txt deleted file mode 100644 index b29ac04fd4de..000000000000 --- a/python/plugins/processing/otb/description/ValidateSVMImagesClassifier.txt +++ /dev/null @@ -1,14 +0,0 @@ -ValidateSVMImagesClassifier -otbcli_ValidateSVMImagesClassifier -Validate SVM Images Classifier -Learning -ParameterMultipleInput|-il|Input Image List|3|False -ParameterMultipleInput|-vd|Vector Data List|-1|False -ParameterFile|-imstat|XML image statistics file|| -ParameterSelection|-elev|Elevation management|dem;average|1 -ParameterFile|-elev.dem.path|DEM directory| -ParameterFile|-elev.dem.geoid|Geoid File|| -ParameterNumber|-elev.average.value|Average Elevation|None|None|0.0 -OutputFile|-out|Output filename -ParameterFile|-svm|SVM validation filename|| -ParameterNumber|-rand|set user defined seed|None|None|0 diff --git a/python/plugins/processing/otb/description/VectorDataDSValidation.txt b/python/plugins/processing/otb/description/VectorDataDSValidation.txt deleted file mode 100644 index 64478cb3a9a8..000000000000 --- a/python/plugins/processing/otb/description/VectorDataDSValidation.txt +++ /dev/null @@ -1,9 +0,0 @@ -VectorDataDSValidation -otbcli_VectorDataDSValidation -Vector Data validation -Feature Extraction -ParameterVector|-in|Input Vector Data|-1|False -ParameterFile|-descmod|Descriptors model filename|| -ParameterString|-cri|Criterion|((Belief + Plausibility)/2.) -ParameterNumber|-thd|Criterion threshold|None|None|0.5 -OutputVector|-out|Output Vector Data diff --git a/python/plugins/processing/otb/description/VectorDataExtractROIApplication.txt b/python/plugins/processing/otb/description/VectorDataExtractROIApplication.txt deleted file mode 100644 index 34cc96e55786..000000000000 --- a/python/plugins/processing/otb/description/VectorDataExtractROIApplication.txt +++ /dev/null @@ -1,11 +0,0 @@ -VectorDataExtractROIApplication -otbcli_VectorDataExtractROIApplication -VectorData Extract ROI -Vector Data Manipulation -ParameterVector|-io.vd|Input Vector data|-1|False -ParameterRaster|-io.in|Support image|False -OutputVector|-io.out|Output Vector data -ParameterSelection|-elev|Elevation management|dem;average|1 -ParameterFile|-elev.dem.path|DEM directory| -ParameterFile|-elev.dem.geoid|Geoid File|| -ParameterNumber|-elev.average.value|Average Elevation|None|None|0.0 diff --git a/python/plugins/processing/otb/description/VectorDataReprojection.txt b/python/plugins/processing/otb/description/VectorDataReprojection.txt deleted file mode 100644 index ed7e343e50f6..000000000000 --- a/python/plugins/processing/otb/description/VectorDataReprojection.txt +++ /dev/null @@ -1,13 +0,0 @@ -VectorDataReprojection -otbcli_VectorDataReprojection -Vector Data reprojection -Vector Data Manipulation -ParameterFile|-in.vd|Input vector data|| -ParameterRaster|-in.kwl|Use image keywords list|True -OutputFile|-out.vd|Output vector data -ParameterSelection|-out.proj|Output Projection choice|image;user|0 -ParameterRaster|-out.proj.image.in|Image used to get projection map|False -ParameterSelection|-out.proj.user.map|Output Cartographic Map Projection|utm;lambert2;lambert93;wgs;epsg|4 -ParameterNumber|-out.proj.user.map.utm.zone|Zone number|None|None|31 -ParameterBoolean|-out.proj.user.map.utm.northhem|Northern Hemisphere| -ParameterNumber|-out.proj.user.map.epsg.code|EPSG Code|None|None|32631 diff --git a/python/plugins/processing/otb/description/VectorDataSetField.txt b/python/plugins/processing/otb/description/VectorDataSetField.txt deleted file mode 100644 index a51262b79294..000000000000 --- a/python/plugins/processing/otb/description/VectorDataSetField.txt +++ /dev/null @@ -1,8 +0,0 @@ -VectorDataSetField -otbcli_VectorDataSetField -Vector data set field -Vector Data Manipulation -ParameterVector|-in|Input|-1|False -OutputVector|-out|Output -ParameterString|-fn|Field| -ParameterString|-fv|Value| diff --git a/python/plugins/processing/otb/description/VectorDataTransform.txt b/python/plugins/processing/otb/description/VectorDataTransform.txt deleted file mode 100644 index 57fdb56fd741..000000000000 --- a/python/plugins/processing/otb/description/VectorDataTransform.txt +++ /dev/null @@ -1,13 +0,0 @@ -VectorDataTransform -otbcli_VectorDataTransform -Vector Data Transformation -Vector Data Manipulation -ParameterVector|-vd|Input Vector data|-1|False -OutputVector|-out|Output Vector data -ParameterRaster|-in|Support image|False -ParameterNumber|-transform.tx|Translation X|None|None|0.0 -ParameterNumber|-transform.ty|Translation Y|None|None|0.0 -ParameterNumber|-transform.ro|Rotation Angle|None|None|0.0 -ParameterNumber|-transform.centerx|Center X|None|None|0.0 -ParameterNumber|-transform.centery|Center Y|None|None|0.0 -ParameterNumber|-transform.scale|Scale|None|None|1.0 diff --git a/python/plugins/processing/otb/description/VertexComponentAnalysis.txt b/python/plugins/processing/otb/description/VertexComponentAnalysis.txt deleted file mode 100644 index 4b86196ce374..000000000000 --- a/python/plugins/processing/otb/description/VertexComponentAnalysis.txt +++ /dev/null @@ -1,8 +0,0 @@ -VertexComponentAnalysis -otbcli_VertexComponentAnalysis -Vertex Component Analysis -Miscellaneous -ParameterRaster|-in|Input Image|False -ParameterNumber|-ne|Number of endmembers|None|None|1 -OutputRaster|-outendm|Output Endmembers -ParameterNumber|-rand|set user defined seed|None|None|0 diff --git a/python/plugins/processing/otb/description/WatershedSegmentation.txt b/python/plugins/processing/otb/description/WatershedSegmentation.txt deleted file mode 100644 index 2f3279fbfa40..000000000000 --- a/python/plugins/processing/otb/description/WatershedSegmentation.txt +++ /dev/null @@ -1,9 +0,0 @@ -WatershedSegmentation -otbcli_Segmentation -Watershed segmentation (labeled raster output) -Segmentation -ParameterRaster|-filter watershed -in|Input Image|False -ParameterNumber|-filter.watershed.threshold|Depth Threshold|0|None|0.01 -ParameterNumber|-filter.watershed.level|Flood level|0|None|0.1 -OutputRaster|-mode raster -mode.raster.out|Output labeled image - diff --git a/python/plugins/processing/otb/description/WatershedSegmentation_vector.txt b/python/plugins/processing/otb/description/WatershedSegmentation_vector.txt deleted file mode 100644 index 7445e63839a8..000000000000 --- a/python/plugins/processing/otb/description/WatershedSegmentation_vector.txt +++ /dev/null @@ -1,19 +0,0 @@ -WatershedSegmentationVector -otbcli_Segmentation -Watershed segmentation (large-scale, vector output) -Segmentation -ParameterRaster|-filter watershed -in|Input Image|False -ParameterNumber|-filter.watershed.threshold|Depth Threshold|0|None|0.01 -ParameterNumber|-filter.watershed.level|Flood level|0|None|0.1 -OutputVector|-mode vector -mode.vector.out|Output vector file -ParameterVector|-mode.vector.inmask|Mask Image|-1|True -ParameterBoolean|-mode.vector.neighbor|8-neighbor connectivity|False -ParameterBoolean|-mode.vector.stitch|Stitch polygons|True -ParameterNumber|-mode.vector.minsize|Minimum object size|1|None|1 -ParameterNumber|-mode.vector.simplify|Simplify polygons|None|None|0.0 -ParameterString|-mode.vector.layername|Layer name |layer -ParemeterString|-mode.vector.fieldname|Geometry index field name|DN -ParameterNumber|-mode.vector.tilesize|Tile size|0|None|1024 -ParameterNumber|-mode.vector.startlabel|Starting geometry index|1|None|1 -ParameterSelection|-mode.vector.outmode|Writing mode (update file/overwrite file/overwrite layer/update layer)|ulco;ovw;ulovw;ulu|0 -ParameterString|-mode.vector.ogroptions|OGR options for layer creation| diff --git a/python/plugins/processing/otb/description/doc/BandMath.html b/python/plugins/processing/otb/description/doc/BandMath.html index 824ea0921f1d..d51a52a29817 100644 --- a/python/plugins/processing/otb/description/doc/BandMath.html +++ b/python/plugins/processing/otb/description/doc/BandMath.html @@ -1,2 +1,6 @@ -

Band Math Application

Brief Description

Perform a mathematical operation on monoband images

Tags

Util

Long Description

This application performs a mathematical operation on monoband images. Mathematical formula interpretation is done via MuPasrer libraries http://muparser.sourceforge.net/

Parameters

Limitations

None

Authors

OTB-Team

See also

Example of use

\ No newline at end of file + + +

BandMath

Brief Description

Perform a mathematical operation on monoband images

Tags

Util

Long Description

This application performs a mathematical operation on monoband images. Mathematical formula interpretation is done via MuParser libraries http://muparser.sourceforge.net/

Parameters

Limitations

None

Authors

OTB-Team

See Also

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/BinaryMorphologicalOperation-closing.html b/python/plugins/processing/otb/description/doc/BinaryMorphologicalOperation-closing.html new file mode 100644 index 000000000000..f0147996c389 --- /dev/null +++ b/python/plugins/processing/otb/description/doc/BinaryMorphologicalOperation-closing.html @@ -0,0 +1,5 @@ + + +

BinaryMorphologicalOperation

Brief Description

Performs morphological operations on an input image channel

Tags

MorphologicalOperations,Feature Extraction

Long Description

This application performs binary morphological operations on a mono band image

Parameters

Limitations

None

Authors

OTB-Team

See Also

itkBinaryDilateImageFilter, itkBinaryErodeImageFilter, itkBinaryMorphologicalOpeningImageFilter and itkBinaryMorphologicalClosingImageFilter classes

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/BinaryMorphologicalOperation-dilate.html b/python/plugins/processing/otb/description/doc/BinaryMorphologicalOperation-dilate.html new file mode 100644 index 000000000000..f0147996c389 --- /dev/null +++ b/python/plugins/processing/otb/description/doc/BinaryMorphologicalOperation-dilate.html @@ -0,0 +1,5 @@ + + +

BinaryMorphologicalOperation

Brief Description

Performs morphological operations on an input image channel

Tags

MorphologicalOperations,Feature Extraction

Long Description

This application performs binary morphological operations on a mono band image

Parameters

Limitations

None

Authors

OTB-Team

See Also

itkBinaryDilateImageFilter, itkBinaryErodeImageFilter, itkBinaryMorphologicalOpeningImageFilter and itkBinaryMorphologicalClosingImageFilter classes

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/BinaryMorphologicalOperation-erode.html b/python/plugins/processing/otb/description/doc/BinaryMorphologicalOperation-erode.html new file mode 100644 index 000000000000..f0147996c389 --- /dev/null +++ b/python/plugins/processing/otb/description/doc/BinaryMorphologicalOperation-erode.html @@ -0,0 +1,5 @@ + + +

BinaryMorphologicalOperation

Brief Description

Performs morphological operations on an input image channel

Tags

MorphologicalOperations,Feature Extraction

Long Description

This application performs binary morphological operations on a mono band image

Parameters

Limitations

None

Authors

OTB-Team

See Also

itkBinaryDilateImageFilter, itkBinaryErodeImageFilter, itkBinaryMorphologicalOpeningImageFilter and itkBinaryMorphologicalClosingImageFilter classes

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/BinaryMorphologicalOperation-opening.html b/python/plugins/processing/otb/description/doc/BinaryMorphologicalOperation-opening.html new file mode 100644 index 000000000000..f0147996c389 --- /dev/null +++ b/python/plugins/processing/otb/description/doc/BinaryMorphologicalOperation-opening.html @@ -0,0 +1,5 @@ + + +

BinaryMorphologicalOperation

Brief Description

Performs morphological operations on an input image channel

Tags

MorphologicalOperations,Feature Extraction

Long Description

This application performs binary morphological operations on a mono band image

Parameters

Limitations

None

Authors

OTB-Team

See Also

itkBinaryDilateImageFilter, itkBinaryErodeImageFilter, itkBinaryMorphologicalOpeningImageFilter and itkBinaryMorphologicalClosingImageFilter classes

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/BinaryMorphologicalOperation.html b/python/plugins/processing/otb/description/doc/BinaryMorphologicalOperation.html new file mode 100644 index 000000000000..f0147996c389 --- /dev/null +++ b/python/plugins/processing/otb/description/doc/BinaryMorphologicalOperation.html @@ -0,0 +1,5 @@ + + +

BinaryMorphologicalOperation

Brief Description

Performs morphological operations on an input image channel

Tags

MorphologicalOperations,Feature Extraction

Long Description

This application performs binary morphological operations on a mono band image

Parameters

Limitations

None

Authors

OTB-Team

See Also

itkBinaryDilateImageFilter, itkBinaryErodeImageFilter, itkBinaryMorphologicalOpeningImageFilter and itkBinaryMorphologicalClosingImageFilter classes

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/BlockMatching.html b/python/plugins/processing/otb/description/doc/BlockMatching.html index 8bcf5bbaa770..44edb2a7280d 100644 --- a/python/plugins/processing/otb/description/doc/BlockMatching.html +++ b/python/plugins/processing/otb/description/doc/BlockMatching.html @@ -1,901 +1,5 @@ - - - Pixel-wise Block-Matching - - - - - - - - -

[next] [tail] [up]

-

4.7.1 Pixel-wise Block-Matching

-

Performs block-matching to estimate pixel-wise disparities between two images -

Detailed description
-

This application allows to performs block-matching to estimate pixel-wise disparities between two images. -The application allows to choose the block-matching method to use. It also allows to input masks (related to -the left and right input image) of pixels for which the disparity should be investigated. Additionally, -two criteria can be optionally used to disable disparity investigation for some pixel: a no-data - - -value, and a threshold on the local variance. This allows to speed-up computation by avoiding to -investigate disparities that will not be reliable anyway. For efficiency reasons, if the optimal metric -values image is desired, it will be concatenated to the output image (which will then have three -bands : horizontal disparity, vertical disparity and metric value). One can split these images -afterward. -

Parameters
-

This section describes in details the parameters available for this application. Table 4.38, page 447 -presents a summary of these parameters and the parameters keys to be used in command-line and -programming languages. Application key is BlockMatching.

- - -

- - -
-

-

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

Parameter key

Parameter type

Parameter description

io

Group

Input and output data

io.inleft

Input image

Left input image

io.inright

Input image

Right input image

io.out

Output image

The output disparity map

io.outmask

Output image

The output mask corresponding to all -criterions

io.outmetric

Boolean

Output optimal metric values as well

mask

Group

Image masking parameters

mask.inleft

Input image

Discard left pixels from mask image

mask.inright

Input image

Discard right pixels from mask image

mask.nodata

Float

Discard pixels with no-data value

mask.variancet

Float

Discard pixels with low local variance

bm

Group

Block matching parameters

bm.metric

Choices

Block-matching metric

bm.metric ssd

Choice

Sum of Squared Distances

bm.metric ncc

Choice

Normalized Cross-Correlation

bm.metric lp

Choice

Lp pseudo-norm

bm.metric.lp.p

Float

p value

bm.radius

Int

Radius of blocks

bm.minhd

Int

Minimum horizontal disparity

bm.maxhd

Int

Maximum horizontal disparity

bm.minvd

Int

Minimum vertical disparity

bm.maxvd

Int

Maximum vertical disparity

bm.subpixel

Choices

Sub-pixel interpolation

bm.subpixel none

Choice

None

bm.subpixel parabolic

Choice

Parabolic

bm.subpixel triangular

Choice

Triangular

bm.subpixel dichotomy

Choice

Dichotomy

bm.medianfilter

Group

Median filtering

bm.medianfilter.radius

Int

Radius

bm.medianfilter.incoherence

Float

Incoherence threshold

bm.initdisp

Choices

Initial disparities

bm.initdisp none

Choice

None

bm.initdisp uniform

Choice

Uniform initial disparity

bm.initdisp maps

Choice

Initial disparity maps

bm.initdisp.uniform.hdisp

Int

Horizontal initial disparity

bm.initdisp.uniform.vdisp

Int

Vertical initial disparity

bm.initdisp.uniform.hrad

Int

Horizontal exploration radius

bm.initdisp.uniform.vrad

Int

Vertical exploration radius

bm.initdisp.maps.hmap

Input image

Horizontal initial disparity map

bm.initdisp.maps.vmap

Input image

Vertical initial disparity map

bm.initdisp.maps.hrad

Int

Horizontal exploration radius

bm.initdisp.maps.vrad

Int

Vertical exploration radius

ram

Int

Available RAM (Mb)

-
-
Table 4.38: Parameters table for Pixel-wise Block-Matching.
- - -
-
-

Input and output data -This group of parameters allows to set the input and output images. -

-

Image masking parameters -This group of parameters allows to determine the masking parameters to prevent disparities estimation for -some pixels of the left image -

-

Block matching parameters -This group of parameters allow to tune the block-matching behaviour -

-

Available RAM (Mb) -Available memory for processing (in MB) -

-

Example
-

To run this example in command-line, use the following: -

otbcli_BlockMatching -io.inleft StereoFixed.png -io.inright StereoMoving.png -bm.minhd -10 -bm.maxhd 10 -mask.variancet 10 -io.out MyDisparity.tif -
-

To run this example from Python, use the following code snippet: -

#!/usr/bin/python 
 
# Import the otb applications package 
import otbApplication 
 
# The following line creates an instance of the BlockMatching application 
BlockMatching = otbApplication.Registry.CreateApplication("BlockMatching") 
 
# The following lines set all the application parameters: 
BlockMatching.SetParameterString("io.inleft", "StereoFixed.png") 
 
BlockMatching.SetParameterString("io.inright", "StereoMoving.png") 
 
BlockMatching.SetParameterInt("bm.minhd", -10) 
 
BlockMatching.SetParameterInt("bm.maxhd", 10) 
 
BlockMatching.SetParameterFloat("mask.variancet", 10) 
 
BlockMatching.SetParameterString("io.out", "MyDisparity.tif") 
 
# The following line execute the application 
BlockMatching.ExecuteAndWriteOutput() -
-

-

Limitations
-

None -

Authors
-

This application has been written by OTB-Team. - - -

See also
-

These additional ressources can be useful for further information: -

-

[next] [front] [up]

-

- + + +

BlockMatching

Brief Description

Performs block-matching to estimate pixel-wise disparities between two images

Tags

Stereo

Long Description

This application allows to performs block-matching to estimate pixel-wise disparities between two images. The application allows to choose the block-matching method to use. It also allows to input masks (related to the left and right input image) of pixels for which the disparity should be investigated. Additionally, two criteria can be optionally used to disable disparity investigation for some pixel: a no-data value, and a threshold on the local variance. This allows to speed-up computation by avoiding to investigate disparities that will not be reliable anyway. For efficiency reasons, if the optimal metric values image is desired, it will be concatenated to the output image (which will then have three bands : horizontal disparity, vertical disparity and metric value). One can split these images afterward.

Parameters

Limitations

None

Authors

OTB-Team

See Also

otbStereoRectificationGridGenerator

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/BundleToPerfectSensor.html b/python/plugins/processing/otb/description/doc/BundleToPerfectSensor.html index 688c065511d6..2a2e4404838a 100644 --- a/python/plugins/processing/otb/description/doc/BundleToPerfectSensor.html +++ b/python/plugins/processing/otb/description/doc/BundleToPerfectSensor.html @@ -1 +1,5 @@ -

Bundle to perfect sensor application

Brief Description

Perform P+XS pansharpening

Tags

Geometry, Image Manipulation, Pansharpening

Long Description

This application performs P+XS pansharpening.

Parameters

Limitations

None

Authors

OTB-Team

See also

Example of use

\ No newline at end of file + + +

BundleToPerfectSensor

Brief Description

Perform P+XS pansharpening

Tags

Geometry,Pansharpening

Long Description

This application performs P+XS pansharpening.

Parameters

Limitations

None

Authors

OTB-Team

See Also

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/ClassificationMapRegularization.html b/python/plugins/processing/otb/description/doc/ClassificationMapRegularization.html new file mode 100644 index 000000000000..95a7491bc525 --- /dev/null +++ b/python/plugins/processing/otb/description/doc/ClassificationMapRegularization.html @@ -0,0 +1,7 @@ + + +

ClassificationMapRegularization

Brief Description

Filters the input labeled image using Majority Voting in a ball shaped neighbordhood.

Tags

Learning,Image Analysis

Long Description

This application filters the input labeled image using Majority Voting in a ball shaped neighbordhood. Majority Voting takes the more representative value of all the pixels identified by the ball shaped structuring element and then sets the center pixel to this majority label value. + -NoData is the label of the NOT classified pixels in the input image. These input pixels keep their NoData label in the output image. + -Pixels with more than 1 majority class are marked as Undecided if the parameter 'ip.suvbool == true', or keep their Original labels otherwise.

Parameters

Limitations

The input image must be a single band labeled image. The structuring element radius must have a minimum value equal to 1 pixel. Please note that the Undecided value must be different from existing labels in the input labeled image.

Authors

OTB-Team

See Also

Documentation of the ClassificationMapRegularization application.

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/ColorMapping-continuous.html b/python/plugins/processing/otb/description/doc/ColorMapping-continuous.html new file mode 100644 index 000000000000..a57cae59fbe2 --- /dev/null +++ b/python/plugins/processing/otb/description/doc/ColorMapping-continuous.html @@ -0,0 +1,13 @@ + + +

ColorMapping

Brief Description

Maps an input label image to 8-bits RGB using look-up tables.

Tags

Utilities,Image Manipulation,Image MetaData,Learning

Long Description

This application allows to map a label image to a 8-bits RGB image (in both ways) using different methods. + -The custom method allows to use a custom look-up table. The look-up table is loaded from a text file where each line describes an entry. The typical use of this method is to colorise a classification map. + -The continuous method allows to map a range of values in a scalar input image to a colored image using continuous look-up table, in order to enhance image interpretation. Several look-up tables can been chosen with different color ranges. +-The optimal method computes an optimal look-up table. When processing a segmentation label image (label to color), the color difference between adjacent segmented regions is maximized. When processing an unknown color image (color to label), all the present colors are mapped to a continuous label list. + - The support image method uses a color support image to associate an average color to each region.

Parameters

Limitations

The segmentation optimal method does not support streaming, and thus large images. The operation color to label is not implemented for the methods continuous LUT and support image LUT. + ColorMapping using support image is not threaded.

Authors

OTB-Team

See Also

ImageSVMClassifier

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/ColorMapping-custom.html b/python/plugins/processing/otb/description/doc/ColorMapping-custom.html new file mode 100644 index 000000000000..a57cae59fbe2 --- /dev/null +++ b/python/plugins/processing/otb/description/doc/ColorMapping-custom.html @@ -0,0 +1,13 @@ + + +

ColorMapping

Brief Description

Maps an input label image to 8-bits RGB using look-up tables.

Tags

Utilities,Image Manipulation,Image MetaData,Learning

Long Description

This application allows to map a label image to a 8-bits RGB image (in both ways) using different methods. + -The custom method allows to use a custom look-up table. The look-up table is loaded from a text file where each line describes an entry. The typical use of this method is to colorise a classification map. + -The continuous method allows to map a range of values in a scalar input image to a colored image using continuous look-up table, in order to enhance image interpretation. Several look-up tables can been chosen with different color ranges. +-The optimal method computes an optimal look-up table. When processing a segmentation label image (label to color), the color difference between adjacent segmented regions is maximized. When processing an unknown color image (color to label), all the present colors are mapped to a continuous label list. + - The support image method uses a color support image to associate an average color to each region.

Parameters

Limitations

The segmentation optimal method does not support streaming, and thus large images. The operation color to label is not implemented for the methods continuous LUT and support image LUT. + ColorMapping using support image is not threaded.

Authors

OTB-Team

See Also

ImageSVMClassifier

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/ColorMapping-image.html b/python/plugins/processing/otb/description/doc/ColorMapping-image.html new file mode 100644 index 000000000000..a57cae59fbe2 --- /dev/null +++ b/python/plugins/processing/otb/description/doc/ColorMapping-image.html @@ -0,0 +1,13 @@ + + +

ColorMapping

Brief Description

Maps an input label image to 8-bits RGB using look-up tables.

Tags

Utilities,Image Manipulation,Image MetaData,Learning

Long Description

This application allows to map a label image to a 8-bits RGB image (in both ways) using different methods. + -The custom method allows to use a custom look-up table. The look-up table is loaded from a text file where each line describes an entry. The typical use of this method is to colorise a classification map. + -The continuous method allows to map a range of values in a scalar input image to a colored image using continuous look-up table, in order to enhance image interpretation. Several look-up tables can been chosen with different color ranges. +-The optimal method computes an optimal look-up table. When processing a segmentation label image (label to color), the color difference between adjacent segmented regions is maximized. When processing an unknown color image (color to label), all the present colors are mapped to a continuous label list. + - The support image method uses a color support image to associate an average color to each region.

Parameters

Limitations

The segmentation optimal method does not support streaming, and thus large images. The operation color to label is not implemented for the methods continuous LUT and support image LUT. + ColorMapping using support image is not threaded.

Authors

OTB-Team

See Also

ImageSVMClassifier

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/ColorMapping-optimal.html b/python/plugins/processing/otb/description/doc/ColorMapping-optimal.html new file mode 100644 index 000000000000..a57cae59fbe2 --- /dev/null +++ b/python/plugins/processing/otb/description/doc/ColorMapping-optimal.html @@ -0,0 +1,13 @@ + + +

ColorMapping

Brief Description

Maps an input label image to 8-bits RGB using look-up tables.

Tags

Utilities,Image Manipulation,Image MetaData,Learning

Long Description

This application allows to map a label image to a 8-bits RGB image (in both ways) using different methods. + -The custom method allows to use a custom look-up table. The look-up table is loaded from a text file where each line describes an entry. The typical use of this method is to colorise a classification map. + -The continuous method allows to map a range of values in a scalar input image to a colored image using continuous look-up table, in order to enhance image interpretation. Several look-up tables can been chosen with different color ranges. +-The optimal method computes an optimal look-up table. When processing a segmentation label image (label to color), the color difference between adjacent segmented regions is maximized. When processing an unknown color image (color to label), all the present colors are mapped to a continuous label list. + - The support image method uses a color support image to associate an average color to each region.

Parameters

Limitations

The segmentation optimal method does not support streaming, and thus large images. The operation color to label is not implemented for the methods continuous LUT and support image LUT. + ColorMapping using support image is not threaded.

Authors

OTB-Team

See Also

ImageSVMClassifier

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/ColorMapping.html b/python/plugins/processing/otb/description/doc/ColorMapping.html index b7b31ec421b2..a57cae59fbe2 100644 --- a/python/plugins/processing/otb/description/doc/ColorMapping.html +++ b/python/plugins/processing/otb/description/doc/ColorMapping.html @@ -1,7 +1,13 @@ -

Color Mapping

Brief Description

Maps an input grayscale image into 8-bits RGB using look-up tables.

Tags

Learning

Long Description

This application allows to map an input grayscale into a 8-bits RGB image using three different methods. --The custom method allows to apply a custom look-up table to a labeled image. The look-up table is loaded from a text file where each line describes an entry. The typical use of this method is to colorise a classification map. --The continuous method allows to map a range of values in a scalar input image into a colored image using continuous look-up table, in order to enhance image interpretation. Several look-up tables can ben chosen with different color ranges. --The segmentation method is dedicated to segmentation labeled outputs where each segment correspond to a unique labeled. It computes an optimal look-up table such that color difference between adjacent segmented regions is maximised.

Parameters

Limitations

The segmentation optimal method does not support streaming, and thus large images. The operation color to label is not implemented for the methods continuous LUT and support image LUT. + ColorMapping using support image is not threaded.

Authors

OTB-Team

See Also

ImageSVMClassifier

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/CompareImages.html b/python/plugins/processing/otb/description/doc/CompareImages.html index 68a07db3a7fb..ce92b570b672 100644 --- a/python/plugins/processing/otb/description/doc/CompareImages.html +++ b/python/plugins/processing/otb/description/doc/CompareImages.html @@ -1 +1,5 @@ -

Images comparaison

Brief Description

Estimator between 2 images.

Tags

Statistics

Long Description

This application computes MSE (Mean Squared Error), MAE (Mean Absolute Error) and PSNR(Peak Signal to Noise Ratio) between the channel of two images (reference and measurement). The user has to set the used channel and can specified an ROI.

Parameters

Limitations

None

Authors

OTB-Team

See also

BandMath application, ImageStatistics application

Example of use

\ No newline at end of file + + +

CompareImages

Brief Description

Estimator between 2 images.

Tags

Statistics

Long Description

This application computes MSE (Mean Squared Error), MAE (Mean Absolute Error) and PSNR (Peak Signal to Noise Ratio) between the channel of two images (reference and measurement). The user has to set the used channel and can specify a ROI.

Parameters

Limitations

None

Authors

OTB-Team

See Also

BandMath application, ImageStatistics

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/ComputeConfusionMatrix-raster.html b/python/plugins/processing/otb/description/doc/ComputeConfusionMatrix-raster.html new file mode 100644 index 000000000000..d8299fe437d4 --- /dev/null +++ b/python/plugins/processing/otb/description/doc/ComputeConfusionMatrix-raster.html @@ -0,0 +1,5 @@ + + +

ComputeConfusionMatrix

Brief Description

Computes the confusion matrix of a classification

Tags

Learning

Long Description

This application computes the confusion matrix of a classification map relatively to a ground truth. This ground truth can be given as a raster or a vector data. Only reference and produced pixels with values different from NoData are handled in the calculation of the confusion matrix. The confusion matrix is organized the following way: rows = reference labels, columns = produced labels. In the header of the output file, the reference and produced class labels are ordered according to the rows/columns of the confusion matrix.

Parameters

Limitations

None

Authors

OTB-Team

See Also

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/ComputeConfusionMatrix-vector.html b/python/plugins/processing/otb/description/doc/ComputeConfusionMatrix-vector.html new file mode 100644 index 000000000000..d8299fe437d4 --- /dev/null +++ b/python/plugins/processing/otb/description/doc/ComputeConfusionMatrix-vector.html @@ -0,0 +1,5 @@ + + +

ComputeConfusionMatrix

Brief Description

Computes the confusion matrix of a classification

Tags

Learning

Long Description

This application computes the confusion matrix of a classification map relatively to a ground truth. This ground truth can be given as a raster or a vector data. Only reference and produced pixels with values different from NoData are handled in the calculation of the confusion matrix. The confusion matrix is organized the following way: rows = reference labels, columns = produced labels. In the header of the output file, the reference and produced class labels are ordered according to the rows/columns of the confusion matrix.

Parameters

Limitations

None

Authors

OTB-Team

See Also

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/ComputeConfusionMatrix.html b/python/plugins/processing/otb/description/doc/ComputeConfusionMatrix.html new file mode 100644 index 000000000000..d8299fe437d4 --- /dev/null +++ b/python/plugins/processing/otb/description/doc/ComputeConfusionMatrix.html @@ -0,0 +1,5 @@ + + +

ComputeConfusionMatrix

Brief Description

Computes the confusion matrix of a classification

Tags

Learning

Long Description

This application computes the confusion matrix of a classification map relatively to a ground truth. This ground truth can be given as a raster or a vector data. Only reference and produced pixels with values different from NoData are handled in the calculation of the confusion matrix. The confusion matrix is organized the following way: rows = reference labels, columns = produced labels. In the header of the output file, the reference and produced class labels are ordered according to the rows/columns of the confusion matrix.

Parameters

Limitations

None

Authors

OTB-Team

See Also

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/ComputeImagesStatistics.html b/python/plugins/processing/otb/description/doc/ComputeImagesStatistics.html index 34e957f0a31a..4cc40bfc5a71 100644 --- a/python/plugins/processing/otb/description/doc/ComputeImagesStatistics.html +++ b/python/plugins/processing/otb/description/doc/ComputeImagesStatistics.html @@ -1 +1,5 @@ -

Compute Images second order statistics

Brief Description

Computes global mean and standard deviation for each band from a set of images and optionally saves the results in an XML file.

Tags

Learning, Image Analysis

Long Description

This application computes a global mean and standard deviation for each band of a set of images and optionally saves the results in an XML file. The output XML is intended to be used an input for the TrainImagesSVMClassifier application to normalize samples before learning.

Parameters

Limitations

The set of input images must have the same number of bands. Input images must be of the same number, type and order of bands.

Authors

OTB-Team

See also

Documentation of the TrainImagesSVMClassifier application.

Example of use

\ No newline at end of file + + +

ComputeImagesStatistics

Brief Description

Computes global mean and standard deviation for each band from a set of images and optionally saves the results in an XML file.

Tags

Learning,Image Analysis

Long Description

This application computes a global mean and standard deviation for each band of a set of images and optionally saves the results in an XML file. The output XML is intended to be used an input for the TrainImagesClassifier application to normalize samples before learning.

Parameters

Limitations

Each image of the set must contain the same bands as the others (i.e. same types, in the same order).

Authors

OTB-Team

See Also

Documentation of the TrainImagesClassifier application.

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/ComputeModulusAndPhase-OneEntry.html b/python/plugins/processing/otb/description/doc/ComputeModulusAndPhase-OneEntry.html new file mode 100644 index 000000000000..bb861bd888a5 --- /dev/null +++ b/python/plugins/processing/otb/description/doc/ComputeModulusAndPhase-OneEntry.html @@ -0,0 +1,5 @@ + + +

ComputeModulusAndPhase

Brief Description

Read one or two files and compute the module and the phase

Tags

SAR

Long Description

This application computes the modulus and the phase of a complex SAR data. This complex SAR data could be provided as a monoband complex pixel type image or a 2 bands real pixel type image or two monobands (first one real part and second one imaginary part) real pixel type images.

Parameters

Limitations

None

Authors

Alexia Mondot (alexia.mondot@c-s.fr) and Mickael Savinaud (mickael.savinaud@c-s.fr)

See Also

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/ComputeModulusAndPhase-TwoEntries.html b/python/plugins/processing/otb/description/doc/ComputeModulusAndPhase-TwoEntries.html new file mode 100644 index 000000000000..bb861bd888a5 --- /dev/null +++ b/python/plugins/processing/otb/description/doc/ComputeModulusAndPhase-TwoEntries.html @@ -0,0 +1,5 @@ + + +

ComputeModulusAndPhase

Brief Description

Read one or two files and compute the module and the phase

Tags

SAR

Long Description

This application computes the modulus and the phase of a complex SAR data. This complex SAR data could be provided as a monoband complex pixel type image or a 2 bands real pixel type image or two monobands (first one real part and second one imaginary part) real pixel type images.

Parameters

Limitations

None

Authors

Alexia Mondot (alexia.mondot@c-s.fr) and Mickael Savinaud (mickael.savinaud@c-s.fr)

See Also

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/ComputeModulusAndPhase.html b/python/plugins/processing/otb/description/doc/ComputeModulusAndPhase.html new file mode 100644 index 000000000000..bb861bd888a5 --- /dev/null +++ b/python/plugins/processing/otb/description/doc/ComputeModulusAndPhase.html @@ -0,0 +1,5 @@ + + +

ComputeModulusAndPhase

Brief Description

Read one or two files and compute the module and the phase

Tags

SAR

Long Description

This application computes the modulus and the phase of a complex SAR data. This complex SAR data could be provided as a monoband complex pixel type image or a 2 bands real pixel type image or two monobands (first one real part and second one imaginary part) real pixel type images.

Parameters

Limitations

None

Authors

Alexia Mondot (alexia.mondot@c-s.fr) and Mickael Savinaud (mickael.savinaud@c-s.fr)

See Also

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/ComputePolylineFeatureFromImage.html b/python/plugins/processing/otb/description/doc/ComputePolylineFeatureFromImage.html index 5ad92c630264..e256c147602d 100644 --- a/python/plugins/processing/otb/description/doc/ComputePolylineFeatureFromImage.html +++ b/python/plugins/processing/otb/description/doc/ComputePolylineFeatureFromImage.html @@ -1 +1,5 @@ -

Compute Polyline Feature From Image Application

Brief Description

Compute a polyline feature descriptors from an input image which are part of the polyline pixels that verify the FeatureExpression

Tags

Feature Extraction

Long Description

This application computes a polyline feature descriptors from an input image which are part of the polyline pixels that verify the FeatureExpression.

Parameters

Limitations

Since it do not rely on streaming process, take care of the size of input image before launching application.

Authors

OTB-Team

See also

Example of use

\ No newline at end of file + + +

ComputePolylineFeatureFromImage

Brief Description

This application compute for each studied polyline, contained in the input VectorData, the choosen descriptors.

Tags

Feature Extraction

Long Description

The first step in the classifier fusion based validation is to compute, for each studied polyline, the choosen descriptors.

Parameters

Limitations

Since it does not rely on streaming process, take care of the size of input image before launching application.

Authors

OTB-Team

See Also

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/ConcatenateImages.html b/python/plugins/processing/otb/description/doc/ConcatenateImages.html index e7341f47f0dc..76caf5d7e76d 100644 --- a/python/plugins/processing/otb/description/doc/ConcatenateImages.html +++ b/python/plugins/processing/otb/description/doc/ConcatenateImages.html @@ -1 +1,5 @@ -

Images Concatenation Application

Brief Description

Concatenate a list of images into a single multi channel one.

Tags

Image Manipulation, Concatenation, Multi channel

Long Description

This application performs images concatenation. It will take the input image list (mono or multi channel) and generate a single multi channel image. The channel order is the one of the list.

Parameters

Limitations

None

Authors

OTB-Team

See also

Rescale application, Convert application

Example of use

\ No newline at end of file + + +

ConcatenateImages

Brief Description

Concatenate a list of images of the same size into a single multi-channel one.

Tags

Image Manipulation,Concatenation,Multi-channel

Long Description

This application performs images channels concatenation. It will walk the input image list (single or multi-channel) and generates a single multi-channel image. The channel order is the one of the list.

Parameters

Limitations

All input images must have the same size.

Authors

OTB-Team

See Also

Rescale application, Convert

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/ConcatenateVectorData.html b/python/plugins/processing/otb/description/doc/ConcatenateVectorData.html index 5acbac5451ea..8ff5e5632c0c 100644 --- a/python/plugins/processing/otb/description/doc/ConcatenateVectorData.html +++ b/python/plugins/processing/otb/description/doc/ConcatenateVectorData.html @@ -1 +1,5 @@ -

Concatenate Application

Brief Description

Concatenate VectorDatas

Tags

Vector data Manipulation

Long Description

This application concatenate a list of VectorData to produce a unique VectorData as outputNote that the VectorDatas must be of the same type (Storing polygons only, lines only, or points only)

Parameters

Limitations

None

Authors

OTB-Team

See also

Example of use

\ No newline at end of file + + +

ConcatenateVectorData

Brief Description

Concatenate VectorDatas

Tags

Vector Data Manipulation

Long Description

This application concatenates a list of VectorData to produce a unique VectorData as output.Note that the VectorDatas must be of the same type (Storing polygons only, lines only, or points only)

Parameters

Limitations

None

Authors

OTB-Team

See Also

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/ConnectedComponentSegmentation.html b/python/plugins/processing/otb/description/doc/ConnectedComponentSegmentation.html index c992f81aa89a..de09bcd75865 100644 --- a/python/plugins/processing/otb/description/doc/ConnectedComponentSegmentation.html +++ b/python/plugins/processing/otb/description/doc/ConnectedComponentSegmentation.html @@ -1 +1,5 @@ -

Connected Component Segmentation Application

Brief Description

Compute a connected component segmentation.

Tags

Image Analysis, Segmentation

Long Description

Compute a connected component segmentation, which takes mathematical formula as a neighborhood thresholding criteria.

Parameters

Limitations

None

Authors

OTB-Team

See also

Example of use

\ No newline at end of file + + +

ConnectedComponentSegmentation

Brief Description

Connected component segmentation and object based image filtering of the input image according to user-defined criterions.

Tags

Image Analysis,Segmentation

Long Description

This application allows to perform a masking, connected components segmentation and object based image filtering. First and optionally, a mask can be built based on user-defined criterions to select pixels of the image which will be segmented. Then a connected component segmentation is performed with a user defined criterion to decide whether two neighbouring pixels belong to the same segment or not. After this segmentation step, an object based image filtering is applied using another user-defined criterion reasoning on segment properties, like shape or radiometric attributes. Criterions are mathematical expressions analysed by the MuParser library (http://muparser.sourceforge.net/). For instance, expression "((b1>80) and intensity>95)" will merge two neighbouring pixel in a single segment if their intensity is more than 95 and their value in the first image band is more than 80. See parameters documentation for a list of available attributes. The output of the object based image filtering is vectorized and can be written in shapefile or KML format. If the input image is in raw geometry, resulting polygons will be transformed to WGS84 using sensor modelling before writing, to ensure consistency with GIS softwares. For this purpose, a Digital Elevation Model can be provided to the application. The whole processing is done on a per-tile basis for large images, so this application can handle images of arbitrary size.

Parameters

Limitations

Due to the tiling scheme in case of large images, some segments can be arbitrarily split across multiple tiles.

Authors

OTB-Team

See Also

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/Convert.html b/python/plugins/processing/otb/description/doc/Convert.html index c584afd15e1a..cab60f0c3f7c 100644 --- a/python/plugins/processing/otb/description/doc/Convert.html +++ b/python/plugins/processing/otb/description/doc/Convert.html @@ -1,2 +1,6 @@ -

Image Conversion Application

Brief Description

Convert an image to a different format, eventually rescaling the data and/or changing the pixel type.

Tags

Conversion, Image Dynamic

Long Description

This application performs an image pixel type conversion (short, ushort, char, uchar, int, uint, float and double types are handled). The output image is written in the specified format (ie. that corresponds to the given extension). - The convertion can include a rescale usiong the image 2% minimum and maximum values. The rescale can be linear or log2.

Parameters

Limitations

None

Authors

OTB-Team

See also

Rescale application

Example of use

\ No newline at end of file + + +

Convert

Brief Description

Convert an image to a different format, eventually rescaling the data and/or changing the pixel type.

Tags

Conversion,Image Dynamic,Image Manipulation

Long Description

This application performs an image pixel type conversion (short, ushort, uchar, int, uint, float and double types are handled). The output image is written in the specified format (ie. that corresponds to the given extension). + The convertion can include a rescale using the image 2 percent minimum and maximum values. The rescale can be linear or log2.

Parameters

Limitations

None

Authors

OTB-Team

See Also

Rescale

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/ConvertCartoToGeoPoint.html b/python/plugins/processing/otb/description/doc/ConvertCartoToGeoPoint.html index a6f7223058ff..a677627d74e1 100644 --- a/python/plugins/processing/otb/description/doc/ConvertCartoToGeoPoint.html +++ b/python/plugins/processing/otb/description/doc/ConvertCartoToGeoPoint.html @@ -1 +1,5 @@ -

Cartographic to geographic coordinates conversion

Brief Description

Convert cartographic coordinates to geographic one.

Tags

Coordinates, Geometry

Long Description

This application computes the geographic coordinates from a cartographic one. user has to give the X and Y coordinate and the cartographic projection (UTM/LAMBERT/LAMBERT2/LAMBERT93/SINUS/ECKERT4/TRANSMERCATOR/MOLLWEID/SVY21).

Parameters

Limitations

None

Authors

OTB-Team

See also

Example of use

\ No newline at end of file + + +

ConvertCartoToGeoPoint

Brief Description

Convert cartographic coordinates to geographic one.

Tags

Coordinates,Geometry

Long Description

This application computes the geographic coordinates from a cartographic one. User has to give the X and Y coordinate and the cartographic projection (UTM/LAMBERT/LAMBERT2/LAMBERT93/SINUS/ECKERT4/TRANSMERCATOR/MOLLWEID/SVY21).

Parameters

Limitations

None

Authors

OTB-Team

See Also

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/ConvertSensorToGeoPoint.html b/python/plugins/processing/otb/description/doc/ConvertSensorToGeoPoint.html new file mode 100644 index 000000000000..f80ec6b3e0b3 --- /dev/null +++ b/python/plugins/processing/otb/description/doc/ConvertSensorToGeoPoint.html @@ -0,0 +1,5 @@ + + +

ConvertSensorToGeoPoint

Brief Description

Sensor to geographic coordinates conversion.

Tags

Geometry

Long Description

This Application converts a sensor point of an input image to a geographic point using the Forward Sensor Model of the input image.

Parameters

Limitations

None

Authors

OTB-Team

See Also

ConvertCartoToGeoPoint application, otbObtainUTMZoneFromGeoPoint

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/DSFuzzyModelEstimation.html b/python/plugins/processing/otb/description/doc/DSFuzzyModelEstimation.html index ed997ac4b972..2f4790730f12 100644 --- a/python/plugins/processing/otb/description/doc/DSFuzzyModelEstimation.html +++ b/python/plugins/processing/otb/description/doc/DSFuzzyModelEstimation.html @@ -1 +1,5 @@ -

Fuzzy Model estimation Application

Brief Description

Estimate feature fuzzy model parameters using 2 vector data (ground truth samples and wrong samples).

Tags

Feature Extraction

Long Description

Estimate feature fuzzy model parameters using 2 vector data (ground truth samples and wrong samples).

Parameters

Limitations

None.

Authors

OTB-Team

See also

Example of use

\ No newline at end of file + + +

DSFuzzyModelEstimation

Brief Description

Estimate feature fuzzy model parameters using 2 vector data (ground truth samples and wrong samples).

Tags

Feature Extraction

Long Description

Estimate feature fuzzy model parameters using 2 vector data (ground truth samples and wrong samples).

Parameters

Limitations

None.

Authors

OTB-Team

See Also

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/DimensionalityReduction-ica.html b/python/plugins/processing/otb/description/doc/DimensionalityReduction-ica.html new file mode 100644 index 000000000000..1a624e336723 --- /dev/null +++ b/python/plugins/processing/otb/description/doc/DimensionalityReduction-ica.html @@ -0,0 +1,5 @@ + + +

DimensionalityReduction

Brief Description

Perform Dimension reduction of the input image.

Tags

Dimensionality Reduction,Image Filtering

Long Description

Performs dimensionality reduction on input image. PCA,NA-PCA,MAF,ICA methods are available.

Parameters

Limitations

Though the inverse transform can be computed, this application only provides the forward transform for now.

Authors

OTB-Team

See Also

"Kernel maximum autocorrelation factor and minimum noise fraction transformations," IEEE Transactions on Image Processing, vol. 20, no. 3, pp. 612-624, (2011)

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/DimensionalityReduction-maf.html b/python/plugins/processing/otb/description/doc/DimensionalityReduction-maf.html new file mode 100644 index 000000000000..1a624e336723 --- /dev/null +++ b/python/plugins/processing/otb/description/doc/DimensionalityReduction-maf.html @@ -0,0 +1,5 @@ + + +

DimensionalityReduction

Brief Description

Perform Dimension reduction of the input image.

Tags

Dimensionality Reduction,Image Filtering

Long Description

Performs dimensionality reduction on input image. PCA,NA-PCA,MAF,ICA methods are available.

Parameters

Limitations

Though the inverse transform can be computed, this application only provides the forward transform for now.

Authors

OTB-Team

See Also

"Kernel maximum autocorrelation factor and minimum noise fraction transformations," IEEE Transactions on Image Processing, vol. 20, no. 3, pp. 612-624, (2011)

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/DimensionalityReduction-napca.html b/python/plugins/processing/otb/description/doc/DimensionalityReduction-napca.html new file mode 100644 index 000000000000..1a624e336723 --- /dev/null +++ b/python/plugins/processing/otb/description/doc/DimensionalityReduction-napca.html @@ -0,0 +1,5 @@ + + +

DimensionalityReduction

Brief Description

Perform Dimension reduction of the input image.

Tags

Dimensionality Reduction,Image Filtering

Long Description

Performs dimensionality reduction on input image. PCA,NA-PCA,MAF,ICA methods are available.

Parameters

Limitations

Though the inverse transform can be computed, this application only provides the forward transform for now.

Authors

OTB-Team

See Also

"Kernel maximum autocorrelation factor and minimum noise fraction transformations," IEEE Transactions on Image Processing, vol. 20, no. 3, pp. 612-624, (2011)

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/DimensionalityReduction-pca.html b/python/plugins/processing/otb/description/doc/DimensionalityReduction-pca.html new file mode 100644 index 000000000000..1a624e336723 --- /dev/null +++ b/python/plugins/processing/otb/description/doc/DimensionalityReduction-pca.html @@ -0,0 +1,5 @@ + + +

DimensionalityReduction

Brief Description

Perform Dimension reduction of the input image.

Tags

Dimensionality Reduction,Image Filtering

Long Description

Performs dimensionality reduction on input image. PCA,NA-PCA,MAF,ICA methods are available.

Parameters

Limitations

Though the inverse transform can be computed, this application only provides the forward transform for now.

Authors

OTB-Team

See Also

"Kernel maximum autocorrelation factor and minimum noise fraction transformations," IEEE Transactions on Image Processing, vol. 20, no. 3, pp. 612-624, (2011)

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/DimensionalityReduction.html b/python/plugins/processing/otb/description/doc/DimensionalityReduction.html index 5d850572691b..1a624e336723 100644 --- a/python/plugins/processing/otb/description/doc/DimensionalityReduction.html +++ b/python/plugins/processing/otb/description/doc/DimensionalityReduction.html @@ -1,488 +1,5 @@ - - -Dimensionality reduction application - - - - - - - - -

[next] [tail] [up]

-

4.5.1 Dimensionality reduction application

-

Perform Dimension reduction of the input image. -

Detailed description
-

Performs dimensionality reduction on input image. PCA,NA-PCA,MAF,ICA methods are available. -

Parameters
-

This section describes in details the parameters available for this application. Table 4.27, page 387 -presents a summary of these parameters and the parameters keys to be used in command-line and -programming languages. Application key is DimensionalityReduction.

- - -

- - -
-

-

- - - - - - - - - - - - - - - - - -

Parameter key

Parameter type

Parameter description

in

Input image

Input Image

out

Output image

Output Image

rescale

Group

Rescale Output.

rescale.outmin

Float

Output min value

rescale.outmax

Float

Output max value

outinv

Output image

Inverse Output Image

method

Choices

Algorithm

method pca

Choice

PCA

method napca

Choice

NA-PCA

method maf

Choice

MAF

method ica

Choice

ICA

method.napca.radiusx

Int

Set the x radius of the sliding window.

method.napca.radiusy

Int

Set the y radius of the sliding window.

method.ica.iter

Int

number of iterations

method.ica.mu

Float

Give the increment weight of W in [0, 1]

nbcomp

Int

Number of Components.

normalize

Boolean

Normalize.

-
-
Table 4.27: Parameters table for Dimensionality reduction application.
- - -
-
-

Input Image -The input image to apply dimensionality reduction. -

Output Image -output image. Components are ordered by decreasing eigenvalues. -

Rescale Output. -

-

Inverse Output Image -reconstruct output image. -

Algorithm -Selection of the reduction dimension method. Available choices are: -

-

Number of Components. -Number of relevant components kept. By default all components are kept. -

Normalize. -center AND reduce data before Dimensionality reduction. -

-

Example
-

To run this example in command-line, use the following: -

otbcli_DimensionalityReduction -in cupriteSubHsi.tif -out FilterOutput.tif -method pca -
-

To run this example from Python, use the following code snippet: -

#!/usr/bin/python 
 
# Import the otb applications package 
import otbApplication 
 
# The following line creates an instance of the DimensionalityReduction application 
DimensionalityReduction = otbApplication.Registry.CreateApplication("DimensionalityReduction") 
 
# The following lines set all the application parameters: 
DimensionalityReduction.SetParameterString("in", "cupriteSubHsi.tif") 
 
DimensionalityReduction.SetParameterString("out", "FilterOutput.tif") 
 
DimensionalityReduction.SetParameterString("method","pca") 
 
# The following line execute the application 
DimensionalityReduction.ExecuteAndWriteOutput() -
-

-

Limitations
-

Though the inverse transform can be computed, this application only provides the forward transform for -now. - - -

Authors
-

This application has been written by OTB-Team. -

See also
-

These additional ressources can be useful for further information: -

-

[next] [front] [up]

-

- + + +

DimensionalityReduction

Brief Description

Perform Dimension reduction of the input image.

Tags

Dimensionality Reduction,Image Filtering

Long Description

Performs dimensionality reduction on input image. PCA,NA-PCA,MAF,ICA methods are available.

Parameters

Limitations

Though the inverse transform can be computed, this application only provides the forward transform for now.

Authors

OTB-Team

See Also

"Kernel maximum autocorrelation factor and minimum noise fraction transformations," IEEE Transactions on Image Processing, vol. 20, no. 3, pp. 612-624, (2011)

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/DisparityMapToElevationMap.html b/python/plugins/processing/otb/description/doc/DisparityMapToElevationMap.html index 9f662f74e780..08737aea17de 100644 --- a/python/plugins/processing/otb/description/doc/DisparityMapToElevationMap.html +++ b/python/plugins/processing/otb/description/doc/DisparityMapToElevationMap.html @@ -1,613 +1,5 @@ - - -Disparity map to elevation map - - - - - - - - -

[next] [prev] [prev-tail] [tail] [up]

-

4.7.2 Disparity map to elevation map

-

Projects a disparity map into a regular elevation map -

Detailed description
-

This application uses a disparity map computed from a stereo image pair to produce an elevation map on the -ground area covered by the stereo pair. The needed inputs are : the disparity map, the stereo pair (in original -geometry) and the epipolar deformation grids. These grids have to link the original geometry (stereo pair) -and the epipolar geometry (disparity map). -

Parameters
-

This section describes in details the parameters available for this application. Table 4.39, page 454 -presents a summary of these parameters and the parameters keys to be used in command-line and -programming languages. Application key is DisparityMapToElevationMap.

- - -

- - -
-

-

- - - - - - - - - - - - - - - - - - -

Parameter key

Parameter type

Parameter description

io

Group

Input and output data

io.in

Input image

Input disparity map

io.left

Input image

Left sensor image

io.right

Input image

Right sensor image

io.lgrid

Input image

Left Grid

io.rgrid

Input image

Right Grid

io.out

Output image

Output elevation map

io.mask

Input image

Disparity mask

step

Float

DEM step

hmin

Float

Minimum elevation expected

hmax

Float

Maximum elevation expected

elev

Choices

Elevation management

elev dem

Choice

DEM directory

elev average

Choice

Average Elevation

elev.dem.path

Directory

DEM directory

elev.dem.geoid

Input File name

Geoid File

elev.average.value

Float

Average Elevation

ram

Int

Available RAM (Mb)

-
-
Table 4.39: Parameters table for Disparity map to elevation map.
- - -
-
-

Input and output data -This group of parameters allows to set the input and output images and grids. -

-

DEM step -Spacing of the output elevation map (in meters) -

Minimum elevation expected -Minimum elevation expected (in meters) -

Maximum elevation expected -Maximum elevation expected (in meters) - - -

Elevation management -This group of parameters allows to manage elevation values. Supported formats are SRTM, DTED or any -geotiff processed by the DEM import application Available choices are: -

-

Available RAM (Mb) -Available memory for processing (in MB) -

-

Example
-

To run this example in command-line, use the following: -

otbcli_DisparityMapToElevationMap -io.in disparity.tif -io.left sensor_left.tif -io.right sensor_right.tif -io.lgrid grid_epi_left.tif -io.rgrid grid_epi_right.tif -io.out dem.tif -
-

To run this example from Python, use the following code snippet: -

#!/usr/bin/python 
 
# Import the otb applications package 
import otbApplication 
 
# The following line creates an instance of the DisparityMapToElevationMap application 
DisparityMapToElevationMap = otbApplication.Registry.CreateApplication("DisparityMapToElevationMap") 
 
# The following lines set all the application parameters: 
DisparityMapToElevationMap.SetParameterString("io.in", "disparity.tif") 
 
DisparityMapToElevationMap.SetParameterString("io.left", "sensor_left.tif") 
 
DisparityMapToElevationMap.SetParameterString("io.right", "sensor_right.tif") 
 
DisparityMapToElevationMap.SetParameterString("io.lgrid", "grid_epi_left.tif") 
 
DisparityMapToElevationMap.SetParameterString("io.rgrid", "grid_epi_right.tif") 
 
DisparityMapToElevationMap.SetParameterString("io.out", "dem.tif") 
 
# The following line execute the application 
DisparityMapToElevationMap.ExecuteAndWriteOutput() -
- - -

-

Limitations
-

None -

Authors
-

This application has been written by OTB-Team. -

See also
-

These additional ressources can be useful for further information: -

-

[next] [prev] [prev-tail] [front] [up]

-

- + + +

DisparityMapToElevationMap

Brief Description

Projects a disparity map into a regular elevation map

Tags

Stereo

Long Description

This application uses a disparity map computed from a stereo image pair to produce an elevation map on the ground area covered by the stereo pair. The needed inputs are : the disparity map, the stereo pair (in original geometry) and the epipolar deformation grids. These grids have to link the original geometry (stereo pair) and the epipolar geometry (disparity map).

Parameters

Limitations

None

Authors

OTB-Team

See Also

otbStereoRectificationGridGenerator otbBlockMatching

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/DownloadSRTMTiles.html b/python/plugins/processing/otb/description/doc/DownloadSRTMTiles.html new file mode 100644 index 000000000000..f3982026371a --- /dev/null +++ b/python/plugins/processing/otb/description/doc/DownloadSRTMTiles.html @@ -0,0 +1,5 @@ + + +

DownloadSRTMTiles

Brief Description

Download or list SRTM tiles related to a set of images

Tags

Utilities,Image Manipulation

Long Description

This application allows to select the appropriate SRTM tiles that covers a list of images. It builds a list of the required tiles. Two modes are available: the first one download those tiles from the USGS SRTM3 website (http://dds.cr.usgs.gov/srtm/version2_1/SRTM3/), the second one list those tiles in a local directory. In both cases, you need to indicate the directory in which directory tiles will be download or the location of local SRTM files.

Parameters

Limitations

None

Authors

OTB-Team

See Also

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/EdgeExtraction-gradient.html b/python/plugins/processing/otb/description/doc/EdgeExtraction-gradient.html new file mode 100644 index 000000000000..db327d661980 --- /dev/null +++ b/python/plugins/processing/otb/description/doc/EdgeExtraction-gradient.html @@ -0,0 +1,5 @@ + + +

EdgeExtraction

Brief Description

Computes edge features on every pixel of the input image selected channel

Tags

Edge,Feature Extraction

Long Description

This application computes edge features on a mono band image

Parameters

Limitations

None

Authors

OTB-Team

See Also

otb class

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/EdgeExtraction-sobel.html b/python/plugins/processing/otb/description/doc/EdgeExtraction-sobel.html new file mode 100644 index 000000000000..db327d661980 --- /dev/null +++ b/python/plugins/processing/otb/description/doc/EdgeExtraction-sobel.html @@ -0,0 +1,5 @@ + + +

EdgeExtraction

Brief Description

Computes edge features on every pixel of the input image selected channel

Tags

Edge,Feature Extraction

Long Description

This application computes edge features on a mono band image

Parameters

Limitations

None

Authors

OTB-Team

See Also

otb class

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/EdgeExtraction-touzi.html b/python/plugins/processing/otb/description/doc/EdgeExtraction-touzi.html new file mode 100644 index 000000000000..db327d661980 --- /dev/null +++ b/python/plugins/processing/otb/description/doc/EdgeExtraction-touzi.html @@ -0,0 +1,5 @@ + + +

EdgeExtraction

Brief Description

Computes edge features on every pixel of the input image selected channel

Tags

Edge,Feature Extraction

Long Description

This application computes edge features on a mono band image

Parameters

Limitations

None

Authors

OTB-Team

See Also

otb class

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/EdgeExtraction.html b/python/plugins/processing/otb/description/doc/EdgeExtraction.html new file mode 100644 index 000000000000..db327d661980 --- /dev/null +++ b/python/plugins/processing/otb/description/doc/EdgeExtraction.html @@ -0,0 +1,5 @@ + + +

EdgeExtraction

Brief Description

Computes edge features on every pixel of the input image selected channel

Tags

Edge,Feature Extraction

Long Description

This application computes edge features on a mono band image

Parameters

Limitations

None

Authors

OTB-Team

See Also

otb class

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/ExtractROI-fit.html b/python/plugins/processing/otb/description/doc/ExtractROI-fit.html new file mode 100644 index 000000000000..d41e6ff33c1d --- /dev/null +++ b/python/plugins/processing/otb/description/doc/ExtractROI-fit.html @@ -0,0 +1,5 @@ + + +

ExtractROI

Brief Description

Extract a ROI defined by the user.

Tags

Image Manipulation

Long Description

This application extracts a Region Of Interest with user defined size, or reference image.

Parameters

Limitations

None

Authors

OTB-Team

See Also

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/ExtractROI-standard.html b/python/plugins/processing/otb/description/doc/ExtractROI-standard.html new file mode 100644 index 000000000000..d41e6ff33c1d --- /dev/null +++ b/python/plugins/processing/otb/description/doc/ExtractROI-standard.html @@ -0,0 +1,5 @@ + + +

ExtractROI

Brief Description

Extract a ROI defined by the user.

Tags

Image Manipulation

Long Description

This application extracts a Region Of Interest with user defined size, or reference image.

Parameters

Limitations

None

Authors

OTB-Team

See Also

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/ExtractROI.html b/python/plugins/processing/otb/description/doc/ExtractROI.html index dfd3a846a8da..d41e6ff33c1d 100644 --- a/python/plugins/processing/otb/description/doc/ExtractROI.html +++ b/python/plugins/processing/otb/description/doc/ExtractROI.html @@ -1 +1,5 @@ -

Extract ROI Application

Brief Description

Extract a ROI defined by the user.

Tags

Image Manipulation

Long Description

This application extracts a Region Of Interest with user defined size.

Parameters

Limitations

None

Authors

OTB-Team

See also

Example of use

\ No newline at end of file + + +

ExtractROI

Brief Description

Extract a ROI defined by the user.

Tags

Image Manipulation

Long Description

This application extracts a Region Of Interest with user defined size, or reference image.

Parameters

Limitations

None

Authors

OTB-Team

See Also

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/FineRegistration.html b/python/plugins/processing/otb/description/doc/FineRegistration.html index 211f92dc47f9..253696c8b3f6 100644 --- a/python/plugins/processing/otb/description/doc/FineRegistration.html +++ b/python/plugins/processing/otb/description/doc/FineRegistration.html @@ -1 +1,5 @@ -

Fine Registration Application

Brief Description

Estimate disparity map between two images.

Tags

Stereo

Long Description

Estimate disparity map between two images. Output image contain x offset, y offset and metric value.

Parameters

Limitations

None

Authors

OTB-Team

See also

Example of use

\ No newline at end of file + + +

FineRegistration

Brief Description

Estimate disparity map between two images.

Tags

Stereo

Long Description

Estimate disparity map between two images. Output image contain x offset, y offset and metric value.

Parameters

Limitations

None

Authors

OTB-Team

See Also

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/FusionOfClassifications-dempstershafer.html b/python/plugins/processing/otb/description/doc/FusionOfClassifications-dempstershafer.html new file mode 100644 index 000000000000..5f91e9e9ef87 --- /dev/null +++ b/python/plugins/processing/otb/description/doc/FusionOfClassifications-dempstershafer.html @@ -0,0 +1,9 @@ + + +

FusionOfClassifications

Brief Description

Fuses several classifications maps of the same image on the basis of class labels.

Tags

Learning,Image Analysis

Long Description

This application allows to fuse several classification maps and produces a single more robust classification map. Fusion is done either by mean of Majority Voting, or with the Dempster Shafer combination method on class labels. + -MAJORITY VOTING: for each pixel, the class with the highest number of votes is selected. + -DEMPSTER SHAFER: for each pixel, the class label for which the Belief Function is maximal is selected. This Belief Function is calculated by mean of the Dempster Shafer combination of Masses of Belief, and indicates the belief that each input classification map presents for each label value. Moreover, the Masses of Belief are based on the input confusion matrices of each classification map, either by using the PRECISION or RECALL rates, or the OVERALL ACCURACY, or the KAPPA coefficient. Thus, each input classification map needs to be associated with its corresponding input confusion matrix file for the Dempster Shafer fusion. +-Input pixels with the NODATA label are not handled in the fusion of classification maps. Moreover, pixels for which all the input classifiers are set to NODATA keep this value in the output fused image. +-In case of number of votes equality, the UNDECIDED label is attributed to the pixel.

Parameters

Limitations

None

Authors

OTB-Team

See Also

ImageClassifier application

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/FusionOfClassifications-majorityvoting.html b/python/plugins/processing/otb/description/doc/FusionOfClassifications-majorityvoting.html new file mode 100644 index 000000000000..5f91e9e9ef87 --- /dev/null +++ b/python/plugins/processing/otb/description/doc/FusionOfClassifications-majorityvoting.html @@ -0,0 +1,9 @@ + + +

FusionOfClassifications

Brief Description

Fuses several classifications maps of the same image on the basis of class labels.

Tags

Learning,Image Analysis

Long Description

This application allows to fuse several classification maps and produces a single more robust classification map. Fusion is done either by mean of Majority Voting, or with the Dempster Shafer combination method on class labels. + -MAJORITY VOTING: for each pixel, the class with the highest number of votes is selected. + -DEMPSTER SHAFER: for each pixel, the class label for which the Belief Function is maximal is selected. This Belief Function is calculated by mean of the Dempster Shafer combination of Masses of Belief, and indicates the belief that each input classification map presents for each label value. Moreover, the Masses of Belief are based on the input confusion matrices of each classification map, either by using the PRECISION or RECALL rates, or the OVERALL ACCURACY, or the KAPPA coefficient. Thus, each input classification map needs to be associated with its corresponding input confusion matrix file for the Dempster Shafer fusion. +-Input pixels with the NODATA label are not handled in the fusion of classification maps. Moreover, pixels for which all the input classifiers are set to NODATA keep this value in the output fused image. +-In case of number of votes equality, the UNDECIDED label is attributed to the pixel.

Parameters

Limitations

None

Authors

OTB-Team

See Also

ImageClassifier application

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/FusionOfClassifications.html b/python/plugins/processing/otb/description/doc/FusionOfClassifications.html new file mode 100644 index 000000000000..5f91e9e9ef87 --- /dev/null +++ b/python/plugins/processing/otb/description/doc/FusionOfClassifications.html @@ -0,0 +1,9 @@ + + +

FusionOfClassifications

Brief Description

Fuses several classifications maps of the same image on the basis of class labels.

Tags

Learning,Image Analysis

Long Description

This application allows to fuse several classification maps and produces a single more robust classification map. Fusion is done either by mean of Majority Voting, or with the Dempster Shafer combination method on class labels. + -MAJORITY VOTING: for each pixel, the class with the highest number of votes is selected. + -DEMPSTER SHAFER: for each pixel, the class label for which the Belief Function is maximal is selected. This Belief Function is calculated by mean of the Dempster Shafer combination of Masses of Belief, and indicates the belief that each input classification map presents for each label value. Moreover, the Masses of Belief are based on the input confusion matrices of each classification map, either by using the PRECISION or RECALL rates, or the OVERALL ACCURACY, or the KAPPA coefficient. Thus, each input classification map needs to be associated with its corresponding input confusion matrix file for the Dempster Shafer fusion. +-Input pixels with the NODATA label are not handled in the fusion of classification maps. Moreover, pixels for which all the input classifiers are set to NODATA keep this value in the output fused image. +-In case of number of votes equality, the UNDECIDED label is attributed to the pixel.

Parameters

Limitations

None

Authors

OTB-Team

See Also

ImageClassifier application

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/GeneratePlyFile.html b/python/plugins/processing/otb/description/doc/GeneratePlyFile.html new file mode 100644 index 000000000000..0af728358bcc --- /dev/null +++ b/python/plugins/processing/otb/description/doc/GeneratePlyFile.html @@ -0,0 +1,5 @@ + + +

GeneratePlyFile

Brief Description

Generate a 3D Ply file from a DEM and a color image.

Tags

Geometry

Long Description

Generate a 3D Ply file from a DEM and a color image.

Parameters

Limitations

Authors

OTB-Team

See Also

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/GenerateRPCSensorModel.html b/python/plugins/processing/otb/description/doc/GenerateRPCSensorModel.html new file mode 100644 index 000000000000..9ee7268ebd68 --- /dev/null +++ b/python/plugins/processing/otb/description/doc/GenerateRPCSensorModel.html @@ -0,0 +1,5 @@ + + +

GenerateRPCSensorModel

Brief Description

Generate a RPC sensor model from a list of Ground Control Points.

Tags

Geometry

Long Description

This application generates a RPC sensor model from a list of Ground Control Points. At least 20 points are required for estimation wihtout elevation support, and 40 points for estimation with elevation support. Elevation support will be automatically deactivated if an insufficient amount of points is provided. The application can optionnaly output a file containing accuracy statistics for each point, and a vector file containing segments represening points residues. The map projection parameter allows to define a map projection in which the accuracy is evaluated.

Parameters

Limitations

None

Authors

OTB-Team

See Also

OrthoRectication,HomologousPointsExtraction,RefineSensorModel

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/GrayScaleMorphologicalOperation-closing.html b/python/plugins/processing/otb/description/doc/GrayScaleMorphologicalOperation-closing.html new file mode 100644 index 000000000000..18563e259c30 --- /dev/null +++ b/python/plugins/processing/otb/description/doc/GrayScaleMorphologicalOperation-closing.html @@ -0,0 +1,5 @@ + + +

GrayScaleMorphologicalOperation

Brief Description

Performs morphological operations on a grayscale input image

Tags

MorphologicalOperations,Feature Extraction

Long Description

This application performs grayscale morphological operations on a mono band image

Parameters

Limitations

None

Authors

OTB-Team

See Also

itkGrayscaleDilateImageFilter, itkGrayscaleErodeImageFilter, itkGrayscaleMorphologicalOpeningImageFilter and itkGrayscaleMorphologicalClosingImageFilter classes

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/GrayScaleMorphologicalOperation-dilate.html b/python/plugins/processing/otb/description/doc/GrayScaleMorphologicalOperation-dilate.html new file mode 100644 index 000000000000..18563e259c30 --- /dev/null +++ b/python/plugins/processing/otb/description/doc/GrayScaleMorphologicalOperation-dilate.html @@ -0,0 +1,5 @@ + + +

GrayScaleMorphologicalOperation

Brief Description

Performs morphological operations on a grayscale input image

Tags

MorphologicalOperations,Feature Extraction

Long Description

This application performs grayscale morphological operations on a mono band image

Parameters

Limitations

None

Authors

OTB-Team

See Also

itkGrayscaleDilateImageFilter, itkGrayscaleErodeImageFilter, itkGrayscaleMorphologicalOpeningImageFilter and itkGrayscaleMorphologicalClosingImageFilter classes

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/GrayScaleMorphologicalOperation-erode.html b/python/plugins/processing/otb/description/doc/GrayScaleMorphologicalOperation-erode.html new file mode 100644 index 000000000000..18563e259c30 --- /dev/null +++ b/python/plugins/processing/otb/description/doc/GrayScaleMorphologicalOperation-erode.html @@ -0,0 +1,5 @@ + + +

GrayScaleMorphologicalOperation

Brief Description

Performs morphological operations on a grayscale input image

Tags

MorphologicalOperations,Feature Extraction

Long Description

This application performs grayscale morphological operations on a mono band image

Parameters

Limitations

None

Authors

OTB-Team

See Also

itkGrayscaleDilateImageFilter, itkGrayscaleErodeImageFilter, itkGrayscaleMorphologicalOpeningImageFilter and itkGrayscaleMorphologicalClosingImageFilter classes

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/GrayScaleMorphologicalOperation-opening.html b/python/plugins/processing/otb/description/doc/GrayScaleMorphologicalOperation-opening.html new file mode 100644 index 000000000000..18563e259c30 --- /dev/null +++ b/python/plugins/processing/otb/description/doc/GrayScaleMorphologicalOperation-opening.html @@ -0,0 +1,5 @@ + + +

GrayScaleMorphologicalOperation

Brief Description

Performs morphological operations on a grayscale input image

Tags

MorphologicalOperations,Feature Extraction

Long Description

This application performs grayscale morphological operations on a mono band image

Parameters

Limitations

None

Authors

OTB-Team

See Also

itkGrayscaleDilateImageFilter, itkGrayscaleErodeImageFilter, itkGrayscaleMorphologicalOpeningImageFilter and itkGrayscaleMorphologicalClosingImageFilter classes

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/GrayScaleMorphologicalOperation.html b/python/plugins/processing/otb/description/doc/GrayScaleMorphologicalOperation.html new file mode 100644 index 000000000000..18563e259c30 --- /dev/null +++ b/python/plugins/processing/otb/description/doc/GrayScaleMorphologicalOperation.html @@ -0,0 +1,5 @@ + + +

GrayScaleMorphologicalOperation

Brief Description

Performs morphological operations on a grayscale input image

Tags

MorphologicalOperations,Feature Extraction

Long Description

This application performs grayscale morphological operations on a mono band image

Parameters

Limitations

None

Authors

OTB-Team

See Also

itkGrayscaleDilateImageFilter, itkGrayscaleErodeImageFilter, itkGrayscaleMorphologicalOpeningImageFilter and itkGrayscaleMorphologicalClosingImageFilter classes

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/GridBasedImageResampling.html b/python/plugins/processing/otb/description/doc/GridBasedImageResampling.html new file mode 100644 index 000000000000..cc6f32cee3e5 --- /dev/null +++ b/python/plugins/processing/otb/description/doc/GridBasedImageResampling.html @@ -0,0 +1,5 @@ + + +

GridBasedImageResampling

Brief Description

Resamples an image according to a resampling grid

Tags

Geometry

Long Description

This application allows to perform image resampling from an input resampling grid.

Parameters

Limitations

None

Authors

OTB-Team

See Also

otbStereorecificationGridGeneration

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/HaralickTextureExtraction.html b/python/plugins/processing/otb/description/doc/HaralickTextureExtraction.html new file mode 100644 index 000000000000..a1d7246471ec --- /dev/null +++ b/python/plugins/processing/otb/description/doc/HaralickTextureExtraction.html @@ -0,0 +1,5 @@ + + +

HaralickTextureExtraction

Brief Description

Computes textures on every pixel of the input image selected channel

Tags

Textures,Feature Extraction

Long Description

This application computes Haralick, advanced and higher order textures on a mono band image

Parameters

Limitations

None

Authors

OTB-Team

See Also

otbScalarImageToTexturesFilter, otbScalarImageToAdvancedTexturesFilter and otbScalarImageToHigherOrderTexturesFilter classes

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/HomologousPointsExtraction.html b/python/plugins/processing/otb/description/doc/HomologousPointsExtraction.html new file mode 100644 index 000000000000..715e7865806a --- /dev/null +++ b/python/plugins/processing/otb/description/doc/HomologousPointsExtraction.html @@ -0,0 +1,5 @@ + + +

HomologousPointsExtraction

Brief Description

Allows to compute homologous points between images using keypoints

Tags

Feature Extraction

Long Description

This application allows to compute homologous points between images using keypoints. SIFT or SURF keypoints can be used and the band on which keypoints are computed can be set independantly for both images. The application offers two modes : the first is the full mode where keypoints are extracted from the full extent of both images (please note that in this mode large image file are not supported). The second mode, called geobins, allows to set-up spatial binning so as to get fewer points spread accross the entire image. In this mode, the corresponding spatial bin in the second image is estimated using geographical transform or sensor modelling, and is padded according to the user defined precision. Last, in both modes the application can filter matches whose colocalisation in first image exceed this precision. The elevation parameters are to deal more precisely with sensor modelling in case of sensor geometry data. The outvector option allows to create a vector file with segments corresponding to the localisation error between the matches. It can be useful to assess the precision of a registration for instance.

Parameters

Limitations

Full mode does not handle large images.

Authors

OTB-Team

See Also

RefineSensorModel

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/HooverCompareSegmentation.html b/python/plugins/processing/otb/description/doc/HooverCompareSegmentation.html new file mode 100644 index 000000000000..c77e2f782b5f --- /dev/null +++ b/python/plugins/processing/otb/description/doc/HooverCompareSegmentation.html @@ -0,0 +1,7 @@ + + +

HooverCompareSegmentation

Brief Description

Compare two segmentations with Hoover metrics

Tags

Segmentation

Long Description

This application compares a machine segmentation (MS) with a partial ground truth segmentation (GT). The Hoover metrics are used to estimate scores for correct detection, over-segmentation, under-segmentation and missed detection. + The application can output the overall Hoover scores along with coloredimages of the MS and GT segmentation showing the state of each region (correct detection, over-segmentation, under-segmentation, missed) + The Hoover metrics are described in : Hoover et al., "An experimental comparison of range image segmentation algorithms", IEEE PAMI vol. 18, no. 7, July 1996.

Parameters

Limitations

None

Authors

OTB-Team

See Also

otbHooverMatrixFilter, otbHooverInstanceFilter, otbLabelMapToAttributeImageFilter

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/HyperspectralUnmixing.html b/python/plugins/processing/otb/description/doc/HyperspectralUnmixing.html index 1a18144439a8..9488cfe65887 100644 --- a/python/plugins/processing/otb/description/doc/HyperspectralUnmixing.html +++ b/python/plugins/processing/otb/description/doc/HyperspectralUnmixing.html @@ -1,4 +1,8 @@ -

Hyperspectral data unmixing

Brief Description

Estimate abundance maps from an hyperspectral image and a set of endmembers.

Tags

Hyperspectral

Long Description

The application applies a linear unmixing algorithm to an hyperspectral data cube. This method supposes that the mixture between materials in the scene is macroscopic and simulate a linear mixing model of spectra. -The Linear Mixing Model (LMM) acknowledges that reflectance spectrum associated with each pixel is a linear combination of pure materials in the recovery area, commonly known as endmembers.Endmembers can be estimated using the VertexComponentAnalysis application. -The application allows to estimate the abundance maps with several algorithms : Unconstrained Least Square (ucls), Fully Constrained Least Square (fcls),Image Space Reconstruction Algorithm (isra) and Non-negative constrained Least Square (ncls) and Minimum Dispersion Constrained Non Negative Matrix Factorization (MDMDNMF). -

Parameters

Limitations

None

Authors

OTB-Team

See also

VertexComponentAnalysis

Example of use

+ + +

HyperspectralUnmixing

Brief Description

Estimate abundance maps from an hyperspectral image and a set of endmembers.

Tags

Hyperspectral

Long Description

The application applies a linear unmixing algorithm to an hyperspectral data cube. This method supposes that the mixture between materials in the scene is macroscopic and simulates a linear mixing model of spectra. +The Linear Mixing Model (LMM) acknowledges that reflectance spectrum associated with each pixel is a linear combination of pure materials in the recovery area, commonly known as endmembers. Endmembers can be estimated using the VertexComponentAnalysis application. +The application allows to estimate the abundance maps with several algorithms : Unconstrained Least Square (ucls), Fully Constrained Least Square (fcls), Image Space Reconstruction Algorithm (isra) and Non-negative constrained Least Square (ncls) and Minimum Dispertion Constrained Non Negative Matrix Factorization (MDMDNMF). +

Parameters

Limitations

None

Authors

OTB-Team

See Also

VertexComponentAnalysis

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/ImageClassifier.html b/python/plugins/processing/otb/description/doc/ImageClassifier.html new file mode 100644 index 000000000000..52d60c4e9026 --- /dev/null +++ b/python/plugins/processing/otb/description/doc/ImageClassifier.html @@ -0,0 +1,5 @@ + + +

ImageClassifier

Brief Description

Performs a classification of the input image according to a model file.

Tags

Learning

Long Description

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.

Parameters

Limitations

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.

Authors

OTB-Team

See Also

TrainImagesClassifier, ValidateImagesClassifier, ComputeImagesStatistics

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/ImageEnvelope.html b/python/plugins/processing/otb/description/doc/ImageEnvelope.html index 7e16d0ca211a..a60cb53ef65a 100644 --- a/python/plugins/processing/otb/description/doc/ImageEnvelope.html +++ b/python/plugins/processing/otb/description/doc/ImageEnvelope.html @@ -1 +1,5 @@ -

Image Envelope Application

Brief Description

Extracts an image envelope.

Tags

Geometry

Long Description

Build a vector data containing the polygon of the image envelope.

Parameters

Limitations

None

Authors

OTB-Team

See also

Example of use

\ No newline at end of file + + +

ImageEnvelope

Brief Description

Extracts an image envelope.

Tags

Geometry

Long Description

Build a vector data containing the polygon of the image envelope.

Parameters

Limitations

None

Authors

OTB-Team

See Also

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/KMeansClassification.html b/python/plugins/processing/otb/description/doc/KMeansClassification.html index c72198818eca..182c1a17836b 100644 --- a/python/plugins/processing/otb/description/doc/KMeansClassification.html +++ b/python/plugins/processing/otb/description/doc/KMeansClassification.html @@ -1 +1,5 @@ -

Unsupervised KMeans image classification Application

Brief Description

Unsupervised KMeans image classification

Tags

Segmentation, Learning

Long Description

Performs Unsupervised KMeans image classification.

Parameters

Limitations

None

Authors

OTB-Team

See also

Example of use

\ No newline at end of file + + +

KMeansClassification

Brief Description

Unsupervised KMeans image classification

Tags

Segmentation,Learning

Long Description

Performs unsupervised KMeans image classification.

Parameters

Limitations

None

Authors

OTB-Team

See Also

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/KmzExport.html b/python/plugins/processing/otb/description/doc/KmzExport.html index 04d38658d45f..6f7701b64e05 100644 --- a/python/plugins/processing/otb/description/doc/KmzExport.html +++ b/python/plugins/processing/otb/description/doc/KmzExport.html @@ -1 +1,5 @@ -

Image to KMZ Export Application

Brief Description

Export the input image in a KMZ product.

Tags

KMZ, Export

Long Description

This application exports the input image in a kmz product that can be display in the Google Earth software. The user can set the size of the product size, a logo and a legend to the product. Furthemore, to obtain a product that fits the relief, a DEM can be used.

Parameters

Limitations

None

Authors

OTB-Team

See also

Conversion

Example of use

\ No newline at end of file + + +

KmzExport

Brief Description

Export the input image in a KMZ product.

Tags

KMZ,Export

Long Description

This application exports the input image in a kmz product that can be display in the Google Earth software. The user can set the size of the product size, a logo and a legend to the product. Furthemore, to obtain a product that fits the relief, a DEM can be used.

Parameters

Limitations

None

Authors

OTB-Team

See Also

Conversion

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/LSMSSegmentation.html b/python/plugins/processing/otb/description/doc/LSMSSegmentation.html new file mode 100644 index 000000000000..03151c9dd5f8 --- /dev/null +++ b/python/plugins/processing/otb/description/doc/LSMSSegmentation.html @@ -0,0 +1,5 @@ + + +

LSMSSegmentation

Brief Description

Second step of the exact Large-Scale Mean-Shift segmentation workflow.

Tags

Segmentation,LSMS

Long Description

This application performs the second step of the exact Large-Scale Mean-Shift segmentation workflow (LSMS). Filtered range image and spatial image should be created with the MeanShiftSmoothing application, with modesearch parameter disabled. If spatial image is not set, the application will only process the range image and spatial radius parameter will not be taken into account. This application will produce a labeled image where neighbor pixels whose range distance is below range radius (and optionally spatial distance below spatial radius) will be grouped together into the same cluster. For large images one can use the nbtilesx and nbtilesy parameters for tile-wise processing, with the guarantees of identical results. Please note that this application will generate a lot of temporary files (as many as the number of tiles), and will therefore require twice the size of the final result in term of disk space. The cleanup option (activated by default) allows to remove all temporary file as soon as they are not needed anymore (if cleanup is activated, tmpdir set and tmpdir does not exists before running the application, it will be removed as well during cleanup). The tmpdir option allows to define a directory where to write the temporary files. Please also note that the output image type should be set to uint32 to ensure that there are enough labels available.

Parameters

Limitations

This application is part of the Large-Scale Mean-Shift segmentation workflow (LSMS) and may not be suited for any other purpose.

Authors

David Youssefi

See Also

MeanShiftSmoothing, LSMSSmallRegionsMerging, LSMSVectorization

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/LSMSSmallRegionsMerging.html b/python/plugins/processing/otb/description/doc/LSMSSmallRegionsMerging.html new file mode 100644 index 000000000000..b293794cb450 --- /dev/null +++ b/python/plugins/processing/otb/description/doc/LSMSSmallRegionsMerging.html @@ -0,0 +1,5 @@ + + +

LSMSSmallRegionsMerging

Brief Description

Third (optional) step of the exact Large-Scale Mean-Shift segmentation workflow.

Tags

Segmentation,LSMS

Long Description

This application performs the third step of the exact Large-Scale Mean-Shift segmentation workflow (LSMS). Given a segmentation result (label image) and the original image, it will merge regions whose size in pixels is lower than minsize parameter with the adjacent regions with the adjacent region with closest radiometry and acceptable size. Small regions will be processed by size: first all regions of area, which is equal to 1 pixel will be merged with adjacent region, then all regions of area equal to 2 pixels, until regions of area minsize. For large images one can use the nbtilesx and nbtilesy parameters for tile-wise processing, with the guarantees of identical results.

Parameters

Limitations

This application is part of the Large-Scale Mean-Shift segmentation workflow (LSMS) and may not be suited for any other purpose.

Authors

David Youssefi

See Also

LSMSSegmentation, LSMSVectorization, MeanShiftSmoothing

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/LSMSVectorization.html b/python/plugins/processing/otb/description/doc/LSMSVectorization.html new file mode 100644 index 000000000000..5414a039181e --- /dev/null +++ b/python/plugins/processing/otb/description/doc/LSMSVectorization.html @@ -0,0 +1,5 @@ + + +

LSMSVectorization

Brief Description

Fourth step of the exact Large-Scale Mean-Shift segmentation workflow.

Tags

Segmentation,LSMS

Long Description

This application performs the fourth step of the exact Large-Scale Mean-Shift segmentation workflow (LSMS). Given a segmentation result (label image), that may have been processed for small regions merging or not, it will convert it to a GIS vector file containing one polygon per segment. Each polygon contains additional fields: mean and variance of each channels from input image (in parameter), segmentation image label, number of pixels in the polygon. For large images one can use the nbtilesx and nbtilesy parameters for tile-wise processing, with the guarantees of identical results.

Parameters

Limitations

This application is part of the Large-Scale Mean-Shift segmentation workflow (LSMS) and may not be suited for any other purpose.

Authors

David Youssefi

See Also

MeanShiftSmoothing, LSMSSegmentation, LSMSSmallRegionsMerging

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/LineSegmentDetection.html b/python/plugins/processing/otb/description/doc/LineSegmentDetection.html index 0745d677fb2f..4e8939cb1dec 100644 --- a/python/plugins/processing/otb/description/doc/LineSegmentDetection.html +++ b/python/plugins/processing/otb/description/doc/LineSegmentDetection.html @@ -1,3 +1,7 @@ -

Line segment detection application

Brief Description

Detect line segments in raster

Tags

Feature Extraction

Long Description

This application detects locally straight contours in a image. It is based on Burns, Hanson, and Riseman method and use an a contrario validation approach (Desolneux, Moisan, and Morel). The algorithm was published by Rafael Gromponevon Gioi, Jérémie Jakubowicz, Jean-Michel Morel and Gregory Randall. - The given approach compute gradient and level lines of the image and detects aligned points in line support region. The application allows to export the detected lines in a vector data.

Parameters

Limitations

None

Authors

OTB-Team

See also

On Line demonstration of the LSD algorithm is available here: http://www.ipol.im/pub/algo/gjmr_line_segment_detector/ -

Example of use

\ No newline at end of file + + +

LineSegmentDetection

Brief Description

Detect line segments in raster

Tags

Feature Extraction

Long Description

This application detects locally straight contours in a image. It is based on Burns, Hanson, and Riseman method and use an a contrario validation approach (Desolneux, Moisan, and Morel). The algorithm was published by Rafael Gromponevon Gioi, Jérémie Jakubowicz, Jean-Michel Morel and Gregory Randall. + The given approach computes gradient and level lines of the image and detects aligned points in line support region. The application allows to export the detected lines in a vector data.

Parameters

Limitations

None

Authors

OTB-Team

See Also

On Line demonstration of the LSD algorithm is available here: http://www.ipol.im/pub/algo/gjmr_line_segment_detector/ +

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/LocalStatisticExtraction.html b/python/plugins/processing/otb/description/doc/LocalStatisticExtraction.html new file mode 100644 index 000000000000..390f34a9f127 --- /dev/null +++ b/python/plugins/processing/otb/description/doc/LocalStatisticExtraction.html @@ -0,0 +1,5 @@ + + +

LocalStatisticExtraction

Brief Description

Computes local statistical moments on every pixel in the selected channel of the input image

Tags

Statistics,Feature Extraction

Long Description

This application computes the 4 local statistical moments on every pixel in the selected channel of the input image, over a specified neighborhood. The output image is multi band with one statistical moment (feature) per band. Thus, the 4 output features are the Mean, the Variance, the Skewness and the Kurtosis. They are provided in this exact order in the output image.

Parameters

Limitations

None

Authors

OTB-Team

See Also

otbRadiometricMomentsImageFunction class

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/MeanShiftSmoothing.html b/python/plugins/processing/otb/description/doc/MeanShiftSmoothing.html index 5caea2449a37..c27e3649e34c 100644 --- a/python/plugins/processing/otb/description/doc/MeanShiftSmoothing.html +++ b/python/plugins/processing/otb/description/doc/MeanShiftSmoothing.html @@ -1,421 +1,5 @@ - - -Mean Shift filtering - - - - - - - - -

[next] [prev] [prev-tail] [tail] [up]

-

4.5.3 Mean Shift filtering

-

Perform mean shift filtering -

Detailed description
-

This application performs mean shift fitlering (multi-threaded). -

Parameters
-

This section describes in details the parameters available for this application. Table 4.29, page 396 -presents a summary of these parameters and the parameters keys to be used in command-line and -programming languages. Application key is MeanShiftSmoothing.

- - -

- - -
-

-

- - - - - - - -

Parameter key

Parameter type

Parameter description

in

Input image

Input Image

fout

Output image

Filtered output

spatialr

Int

Spatial radius

ranger

Float

Range radius

thres

Float

Mode convergence threshold

maxiter

Int

Maximum number of iterations

modesearch

Boolean

Mode search.

-
-
Table 4.29: Parameters table for Mean Shift filtering.
- - -
-
- -
Example
-

To run this example in command-line, use the following: -

otbcli_MeanShiftSmoothing -in maur_rgb.png -fout MeanShift_FilterOutput.tif -spatialr 16 -ranger 16 -thres 0.1 -maxiter 100 -
-

To run this example from Python, use the following code snippet: -

#!/usr/bin/python 
 
# Import the otb applications package 
import otbApplication 
 
# The following line creates an instance of the MeanShiftSmoothing application 
MeanShiftSmoothing = otbApplication.Registry.CreateApplication("MeanShiftSmoothing") 
 
# The following lines set all the application parameters: 
MeanShiftSmoothing.SetParameterString("in", "maur_rgb.png") 
 
MeanShiftSmoothing.SetParameterString("fout", "MeanShift_FilterOutput.tif") 
 
MeanShiftSmoothing.SetParameterInt("spatialr", 16) 
 
MeanShiftSmoothing.SetParameterFloat("ranger", 16) 
 
MeanShiftSmoothing.SetParameterFloat("thres", 0.1) 
 
MeanShiftSmoothing.SetParameterInt("maxiter", 100) 
 
# The following line execute the application 
MeanShiftSmoothing.ExecuteAndWriteOutput() -
- - -

-

Limitations
-

With mode search option, the result will slightly depend on thread number. -

Authors
-

This application has been written by OTB-Team. - - -

[next] [prev] [prev-tail] [front] [up]

-

- + + +

MeanShiftSmoothing

Brief Description

Perform mean shift filtering

Tags

Image Filtering

Long Description

This application performs mean shift fitlering (multi-threaded).

Parameters

Limitations

With mode search option, the result will slightly depend on thread number.

Authors

OTB-Team

See Also

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/MultiResolutionPyramid.html b/python/plugins/processing/otb/description/doc/MultiResolutionPyramid.html index 02f4fb384bc1..b704492f009d 100644 --- a/python/plugins/processing/otb/description/doc/MultiResolutionPyramid.html +++ b/python/plugins/processing/otb/description/doc/MultiResolutionPyramid.html @@ -1 +1,5 @@ -

Multi Resolution Pyramid Application

Brief Description

Build a multi-resolution pyramid of the image.

Tags

Conversion, Image Manipulation, Image MultiResolution, Util

Long Description

This application builds a multi-resolution pyramid of the input image.

Parameters

Limitations

None

Authors

OTB-Team

See also

Example of use

\ No newline at end of file + + +

MultiResolutionPyramid

Brief Description

Build a multi-resolution pyramid of the image.

Tags

Conversion,Image Manipulation,Image MultiResolution,Util

Long Description

This application builds a multi-resolution pyramid of the input image. User can specified the number of levels of the pyramid and the subsampling factor. To speed up the process, you can use the fast scheme option

Parameters

Limitations

None

Authors

OTB-Team

See Also

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/MultivariateAlterationDetector.html b/python/plugins/processing/otb/description/doc/MultivariateAlterationDetector.html index 19caa09b6a91..9c403a2b5d34 100644 --- a/python/plugins/processing/otb/description/doc/MultivariateAlterationDetector.html +++ b/python/plugins/processing/otb/description/doc/MultivariateAlterationDetector.html @@ -1 +1,21 @@ -

Multivariate alteration detector

Brief Description

Multivariate Alteration Detector

Tags

Feature Extraction

Long Description

This application detects change between two given images.

Parameters

Limitations

None

Authors

OTB-Team

See also

Example of use

\ No newline at end of file + + +

MultivariateAlterationDetector

Brief Description

Multivariate Alteration Detector

Tags

Feature Extraction

Long Description

This application detects change between two given images.

Parameters

Limitations

None

Authors

OTB-Team

See Also

This filter implements the Multivariate Alteration Detector, based on the following work: + A. A. Nielsen and K. Conradsen, Multivariate alteration detection (mad) in multispectral, bi-temporal image data: a new approach to change detection studies, Remote Sens. Environ., vol. 64, pp. 1-19, (1998) + + Multivariate Alteration Detector takes two images as inputs and produce a set of N change maps as a VectorImage (where N is the maximum of number of bands in first and second image) with the following properties: + - Change maps are differences of a pair of linear combinations of bands from image 1 and bands from image 2 chosen to maximize the correlation. + - Each change map is orthogonal to the others. + + This is a statistical method which can handle different modalities and even different bands and number of bands between images. + + If numbers of bands in image 1 and 2 are equal, then change maps are sorted by increasing correlation. If number of bands is different, the change maps are sorted by decreasing correlation. + + The GetV1() and GetV2() methods allow to retrieve the linear combinations used to generate the Mad change maps as a vnl_matrix of double, and the GetRho() method allows to retrieve the correlation associated to each Mad change maps as a vnl_vector. + + This filter has been implemented from the Matlab code kindly made available by the authors here: + http://www2.imm.dtu.dk/~aa/software.html + + Both cases (same and different number of bands) have been validated by comparing the output image to the output produced by the Matlab code, and the reference images for testing have been generated from the Matlab code using Octave.

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/OSMDownloader.html b/python/plugins/processing/otb/description/doc/OSMDownloader.html index c7699906778d..c8e91234efcd 100644 --- a/python/plugins/processing/otb/description/doc/OSMDownloader.html +++ b/python/plugins/processing/otb/description/doc/OSMDownloader.html @@ -1,2 +1,6 @@ -

Open Street Map layers importations applications

Brief Description

Generate a vector data from OSM on the input image extend

Tags

Image MetaData

Long Description

Generate a vector data from Open Street Map data. A DEM could be use. By default, the entire layer is downloaded, an image can be use as support for the OSM data. The application can provide also available classes in layers . This application required an Internet access. Informations about the OSM project : http://www.openstreetmap.fr/

Parameters

Limitations

None

Authors

OTB-Team

See also

Convertion

Example of use

\ No newline at end of file + + +

OSMDownloader

Brief Description

Generate a vector data from OSM on the input image extend

Tags

Image MetaData

Long Description

Generate a vector data from Open Street Map data. A DEM could be use. By default, the entire layer is downloaded, an image can be use as support for the OSM data. The application can provide also available classes in layers . This application required an Internet access. Informations about the OSM project : http://www.openstreetmap.fr/

Parameters

Limitations

None

Authors

OTB-Team

See Also

Convertion

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/ObtainUTMZoneFromGeoPoint.html b/python/plugins/processing/otb/description/doc/ObtainUTMZoneFromGeoPoint.html new file mode 100644 index 000000000000..fba3ce365548 --- /dev/null +++ b/python/plugins/processing/otb/description/doc/ObtainUTMZoneFromGeoPoint.html @@ -0,0 +1,5 @@ + + +

ObtainUTMZoneFromGeoPoint

Brief Description

UTM zone determination from a geographic point.

Tags

Coordinates

Long Description

This application returns the UTM zone of an input geographic point.

Parameters

Limitations

None

Authors

OTB-Team

See Also

Example of use

Obtain a UTM Zone \ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/OpticalCalibration.html b/python/plugins/processing/otb/description/doc/OpticalCalibration.html index bbd7a1575580..808dc9ce4465 100644 --- a/python/plugins/processing/otb/description/doc/OpticalCalibration.html +++ b/python/plugins/processing/otb/description/doc/OpticalCalibration.html @@ -1,6 +1,10 @@ -

Optical calibration application

Brief Description

Perform optical calibration TOA/TOC (Top Of Atmosphere/Top Of Canopy). Supported sensors: QuickBird, Ikonos, WorldView2, Formosat, Spot5

Tags

Calibration

Long Description

The application allows to convert pixel values from DN (for Digital Numbers) to physically interpretable and comparable values.Calibrated values are called surface reflectivity and its values lie in the range [0, 1]. + + +

OpticalCalibration

Brief Description

Perform optical calibration TOA/TOC (Top Of Atmosphere/Top Of Canopy). Supported sensors: QuickBird, Ikonos, WorldView2, Formosat, Spot5, Pleiades

Tags

Calibration

Long Description

The application allows to convert pixel values from DN (for Digital Numbers) to physically interpretable and comparable values. Calibrated values are called surface reflectivity and its values lie in the range [0, 1]. The first level is called Top Of Atmosphere (TOA) reflectivity. It takes into account the sensor gain, sensor spectral response and the solar illumination. The second level is called Top Of Canopy (TOC) reflectivity. In addition to sensor gain and solar illumination, it takes into account the optical thickness of the atmosphere, the atmospheric pressure, the water vapor amount, the ozone amount, as well as the composition and amount of aerosol gasses. -It is also possible to indicate an AERONET file which contains atmospheric parameters (version 1 and version 2 of Aeronet file are supported.

Parameters

Limitations

None

Authors

OTB-Team

See also

The OTB CookBook

Example of use

\ No newline at end of file +It is also possible to indicate an AERONET file which contains atmospheric parameters (version 1 and version 2 of Aeronet file are supported.

Parameters

Limitations

None

Authors

OTB-Team

See Also

The OTB CookBook

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/OrthoRectification-epsg.html b/python/plugins/processing/otb/description/doc/OrthoRectification-epsg.html new file mode 100644 index 000000000000..b9540dfdda96 --- /dev/null +++ b/python/plugins/processing/otb/description/doc/OrthoRectification-epsg.html @@ -0,0 +1,7 @@ + + +

OrthoRectification

Brief Description

This application allows to ortho-rectify optical images from supported sensors. +

Tags

Geometry

Long Description

An inverse sensor model is built from the input image metadata to convert geographical to raw geometry coordinates. This inverse sensor model is then combined with the chosen map projection to build a global coordinate mapping grid. Last, this grid is used to resample using the chosen interpolation algorithm. A Digital Elevation Model can be specified to account for terrain deformations. +In case of SPOT5 images, the sensor model can be approximated by an RPC model in order to speed-up computation.

Parameters

Limitations

Supported sensors are Pleiades, SPOT5 (TIF format), Ikonos, Quickbird, Worldview2, GeoEye.

Authors

OTB-Team

See Also

Ortho-rectification chapter from the OTB Software Guide

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/OrthoRectification-fit-to-ortho.html b/python/plugins/processing/otb/description/doc/OrthoRectification-fit-to-ortho.html new file mode 100644 index 000000000000..b9540dfdda96 --- /dev/null +++ b/python/plugins/processing/otb/description/doc/OrthoRectification-fit-to-ortho.html @@ -0,0 +1,7 @@ + + +

OrthoRectification

Brief Description

This application allows to ortho-rectify optical images from supported sensors. +

Tags

Geometry

Long Description

An inverse sensor model is built from the input image metadata to convert geographical to raw geometry coordinates. This inverse sensor model is then combined with the chosen map projection to build a global coordinate mapping grid. Last, this grid is used to resample using the chosen interpolation algorithm. A Digital Elevation Model can be specified to account for terrain deformations. +In case of SPOT5 images, the sensor model can be approximated by an RPC model in order to speed-up computation.

Parameters

Limitations

Supported sensors are Pleiades, SPOT5 (TIF format), Ikonos, Quickbird, Worldview2, GeoEye.

Authors

OTB-Team

See Also

Ortho-rectification chapter from the OTB Software Guide

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/OrthoRectification-lambert-WGS84.html b/python/plugins/processing/otb/description/doc/OrthoRectification-lambert-WGS84.html new file mode 100644 index 000000000000..b9540dfdda96 --- /dev/null +++ b/python/plugins/processing/otb/description/doc/OrthoRectification-lambert-WGS84.html @@ -0,0 +1,7 @@ + + +

OrthoRectification

Brief Description

This application allows to ortho-rectify optical images from supported sensors. +

Tags

Geometry

Long Description

An inverse sensor model is built from the input image metadata to convert geographical to raw geometry coordinates. This inverse sensor model is then combined with the chosen map projection to build a global coordinate mapping grid. Last, this grid is used to resample using the chosen interpolation algorithm. A Digital Elevation Model can be specified to account for terrain deformations. +In case of SPOT5 images, the sensor model can be approximated by an RPC model in order to speed-up computation.

Parameters

Limitations

Supported sensors are Pleiades, SPOT5 (TIF format), Ikonos, Quickbird, Worldview2, GeoEye.

Authors

OTB-Team

See Also

Ortho-rectification chapter from the OTB Software Guide

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/OrthoRectification-utm.html b/python/plugins/processing/otb/description/doc/OrthoRectification-utm.html new file mode 100644 index 000000000000..b9540dfdda96 --- /dev/null +++ b/python/plugins/processing/otb/description/doc/OrthoRectification-utm.html @@ -0,0 +1,7 @@ + + +

OrthoRectification

Brief Description

This application allows to ortho-rectify optical images from supported sensors. +

Tags

Geometry

Long Description

An inverse sensor model is built from the input image metadata to convert geographical to raw geometry coordinates. This inverse sensor model is then combined with the chosen map projection to build a global coordinate mapping grid. Last, this grid is used to resample using the chosen interpolation algorithm. A Digital Elevation Model can be specified to account for terrain deformations. +In case of SPOT5 images, the sensor model can be approximated by an RPC model in order to speed-up computation.

Parameters

Limitations

Supported sensors are Pleiades, SPOT5 (TIF format), Ikonos, Quickbird, Worldview2, GeoEye.

Authors

OTB-Team

See Also

Ortho-rectification chapter from the OTB Software Guide

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/OrthoRectification.html b/python/plugins/processing/otb/description/doc/OrthoRectification.html index 153ba595ac8c..b9540dfdda96 100644 --- a/python/plugins/processing/otb/description/doc/OrthoRectification.html +++ b/python/plugins/processing/otb/description/doc/OrthoRectification.html @@ -1,3 +1,7 @@ -

Ortho-rectification application

Brief Description

This application allows to ortho-rectify optical images from supported sensors. -

Tags

Image Manipulation, Geometry

Long Description

An inverse sensor model is built from the input image metadata to convert geographical to raw geometry coordinates. This inverse sensor model is then combined with the chosen map projection to build a global coordinate mapping grid. Last, this grid is used to resample using the chosen interpolation algorithm. A Digital Elevation Model can be specified to account for terrain deformations. -In case of SPOT5 images, the sensor model can be approximated by an RPC model in order to speed-up computation.

Parameters

Limitations

Supported sensors are SPOT5 (TIF format), Ikonos, Quickbird, Worldview2, GeoEye.

Authors

OTB-Team

See also

Ortho-rectification chapter from the OTB Software Guide

Example of use

\ No newline at end of file + + +

OrthoRectification

Brief Description

This application allows to ortho-rectify optical images from supported sensors. +

Tags

Geometry

Long Description

An inverse sensor model is built from the input image metadata to convert geographical to raw geometry coordinates. This inverse sensor model is then combined with the chosen map projection to build a global coordinate mapping grid. Last, this grid is used to resample using the chosen interpolation algorithm. A Digital Elevation Model can be specified to account for terrain deformations. +In case of SPOT5 images, the sensor model can be approximated by an RPC model in order to speed-up computation.

Parameters

Limitations

Supported sensors are Pleiades, SPOT5 (TIF format), Ikonos, Quickbird, Worldview2, GeoEye.

Authors

OTB-Team

See Also

Ortho-rectification chapter from the OTB Software Guide

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/Pansharpening-bayes.html b/python/plugins/processing/otb/description/doc/Pansharpening-bayes.html new file mode 100644 index 000000000000..414545c6e5bc --- /dev/null +++ b/python/plugins/processing/otb/description/doc/Pansharpening-bayes.html @@ -0,0 +1,5 @@ + + +

Pansharpening

Brief Description

Perform P+XS pansharpening

Tags

Geometry,Pansharpening

Long Description

This application performs P+XS pansharpening. Pansharpening is a process of merging high-resolution panchromatic and lower resolution multispectral imagery to create a single high-resolution color image. Algorithms available in the applications are: RCS, bayesian fusion and Local Mean and Variance Matching(LMVM).

Parameters

Limitations

None

Authors

OTB-Team

See Also

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/Pansharpening-lmvm.html b/python/plugins/processing/otb/description/doc/Pansharpening-lmvm.html new file mode 100644 index 000000000000..414545c6e5bc --- /dev/null +++ b/python/plugins/processing/otb/description/doc/Pansharpening-lmvm.html @@ -0,0 +1,5 @@ + + +

Pansharpening

Brief Description

Perform P+XS pansharpening

Tags

Geometry,Pansharpening

Long Description

This application performs P+XS pansharpening. Pansharpening is a process of merging high-resolution panchromatic and lower resolution multispectral imagery to create a single high-resolution color image. Algorithms available in the applications are: RCS, bayesian fusion and Local Mean and Variance Matching(LMVM).

Parameters

Limitations

None

Authors

OTB-Team

See Also

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/Pansharpening-rcs.html b/python/plugins/processing/otb/description/doc/Pansharpening-rcs.html new file mode 100644 index 000000000000..414545c6e5bc --- /dev/null +++ b/python/plugins/processing/otb/description/doc/Pansharpening-rcs.html @@ -0,0 +1,5 @@ + + +

Pansharpening

Brief Description

Perform P+XS pansharpening

Tags

Geometry,Pansharpening

Long Description

This application performs P+XS pansharpening. Pansharpening is a process of merging high-resolution panchromatic and lower resolution multispectral imagery to create a single high-resolution color image. Algorithms available in the applications are: RCS, bayesian fusion and Local Mean and Variance Matching(LMVM).

Parameters

Limitations

None

Authors

OTB-Team

See Also

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/Pansharpening.html b/python/plugins/processing/otb/description/doc/Pansharpening.html new file mode 100644 index 000000000000..414545c6e5bc --- /dev/null +++ b/python/plugins/processing/otb/description/doc/Pansharpening.html @@ -0,0 +1,5 @@ + + +

Pansharpening

Brief Description

Perform P+XS pansharpening

Tags

Geometry,Pansharpening

Long Description

This application performs P+XS pansharpening. Pansharpening is a process of merging high-resolution panchromatic and lower resolution multispectral imagery to create a single high-resolution color image. Algorithms available in the applications are: RCS, bayesian fusion and Local Mean and Variance Matching(LMVM).

Parameters

Limitations

None

Authors

OTB-Team

See Also

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/PixelValue.html b/python/plugins/processing/otb/description/doc/PixelValue.html new file mode 100644 index 000000000000..ada52dc12bd5 --- /dev/null +++ b/python/plugins/processing/otb/description/doc/PixelValue.html @@ -0,0 +1,6 @@ + + +

PixelValue

Brief Description

Get the value of a pixel.

Tags

Utilities,Coordinates,Raster

Long Description

Get the value of a pixel. +Pay attention, index starts at 0.

Parameters

Limitations

None

Authors

OTB-Team

See Also

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/Quicklook.html b/python/plugins/processing/otb/description/doc/Quicklook.html index 932956154e03..7eecc2c879f4 100644 --- a/python/plugins/processing/otb/description/doc/Quicklook.html +++ b/python/plugins/processing/otb/description/doc/Quicklook.html @@ -1,2 +1,7 @@ -

Quick Look Application

Brief Description

Generates a subsampled version of an image extract

Tags

Image Manipulation

Long Description

Generates a subsampled version of an extract of an image defined by ROIStart and ROISize. - This extract is subsampled using the ration OR the output image Size

Parameters

Limitations

None

Authors

OTB-Team

See also

Example of use

\ No newline at end of file + + +

Quicklook

Brief Description

Generates a subsampled version of an image extract

Tags

Image Manipulation

Long Description

Generates a subsampled version of an extract of an image defined by ROIStart and ROISize. + This extract is subsampled using the ratio OR the output image Size.

Parameters

Limitations

This application does not provide yet the optimal way to decode coarser level of resolution from JPEG2000 images (like in Monteverdi). +Trying to subsampled huge JPEG200 image with the application will lead to poor performances for now.

Authors

OTB-Team

See Also

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/RadiometricIndices.html b/python/plugins/processing/otb/description/doc/RadiometricIndices.html new file mode 100644 index 000000000000..c05f1b956497 --- /dev/null +++ b/python/plugins/processing/otb/description/doc/RadiometricIndices.html @@ -0,0 +1,25 @@ + + +

RadiometricIndices

Brief Description

Compute radiometric indices.

Tags

Radiometric Indices,Feature Extraction

Long Description

This application computes radiometric indices using the relevant channels of the input image. The output is a multi band image into which each channel is one of the selected indices.

Parameters

Limitations

None

Authors

OTB-Team

See Also

otbVegetationIndicesFunctor, otbWaterIndicesFunctor and otbSoilIndicesFunctor classes

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/Rasterization.html b/python/plugins/processing/otb/description/doc/Rasterization.html index b50aba4351bc..ece033d5b68e 100644 --- a/python/plugins/processing/otb/description/doc/Rasterization.html +++ b/python/plugins/processing/otb/description/doc/Rasterization.html @@ -1 +1,6 @@ -

Rasterization Application

Brief Description

Reproject and Rasterize a Vector Data.

Tags

Vector data Manipulation

Long Description

Reproject and Rasterize a Vector Data.

Parameters

Limitations

None

Authors

OTB-Team

See also

Example of use

\ No newline at end of file + + +

Rasterization

Brief Description

Rasterize a vector dataset.

Tags

Vector Data Manipulation

Long Description

This application allows to reproject and rasterize a vector dataset. The grid of the rasterized output can be set by using a reference image, or by setting all parmeters (origin, size, spacing) by hand. In the latter case, at least the spacing (ground sampling distance) is needed (other parameters are computed automatically). The rasterized output can also be in a different projection reference system than the input dataset. + There are two rasterize mode available in the application. The first is the binary mode: it allows to render all pixels belonging to a geometry of the input dataset in the foreground color, while rendering the other in background color. The second one allows to render pixels belonging to a geometry woth respect to an attribute of this geometry. The field of the attribute to render can be set by the user. In the second mode, the background value is still used for unassociated pixels.

Parameters

Limitations

None

Authors

OTB-Team

See Also

For now, support of input dataset with multiple layers having different projection reference system is limited.

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/ReadImageInfo.html b/python/plugins/processing/otb/description/doc/ReadImageInfo.html index 5fbe804824f2..576123b7ae9e 100644 --- a/python/plugins/processing/otb/description/doc/ReadImageInfo.html +++ b/python/plugins/processing/otb/description/doc/ReadImageInfo.html @@ -1 +1,5 @@ -

Read image information Application

Brief Description

Get information about the image

Tags

Util, Image MetaData

Long Description

Display informations about the image in the logger tab.

Parameters

Limitations

None

Authors

OTB-Team

See also

Example of use

\ No newline at end of file + + +

ReadImageInfo

Brief Description

Get information about the image

Tags

Utilities,Image Manipulation,Image MetaData

Long Description

Display information about the input image like: image size, origin, spacing, metadata, projections...

Parameters

Limitations

None

Authors

OTB-Team

See Also

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/RefineSensorModel.html b/python/plugins/processing/otb/description/doc/RefineSensorModel.html new file mode 100644 index 000000000000..0376cade1342 --- /dev/null +++ b/python/plugins/processing/otb/description/doc/RefineSensorModel.html @@ -0,0 +1,5 @@ + + +

RefineSensorModel

Brief Description

Perform least-square fit of a sensor model to a set of tie points

Tags

Geometry

Long Description

This application reads a geom file containing a sensor model and a text file containing a list of ground control point, and performs a least-square fit of the sensor model adjustable parameters to these tie points. It produces an updated geom file as output, as well as an optional ground control points based statistics file and a vector file containing residues. The output geom file can then be used to ortho-rectify the data more accurately. Plaease note that for a proper use of the application, elevation must be correctly set (including DEM and geoid file). The map parameters allows to choose a map projection in which the accuracy will be estimated in meters.

Parameters

Limitations

None

Authors

OTB-Team

See Also

OrthoRectification,HomologousPointsExtraction

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/Rescale.html b/python/plugins/processing/otb/description/doc/Rescale.html index d52ea82cec8c..54e0c26923a5 100644 --- a/python/plugins/processing/otb/description/doc/Rescale.html +++ b/python/plugins/processing/otb/description/doc/Rescale.html @@ -1 +1,5 @@ -

Rescale Image Application

Brief Description

Rescale the image between two given values.

Tags

Image Manipulation

Long Description

This application scale the given image pixel intensity between two given values. By default min (resp. max) value is set to 0 (resp. 255).

Parameters

Limitations

None

Authors

OTB-Team

See also

Example of use

\ No newline at end of file + + +

Rescale

Brief Description

Rescale the image between two given values.

Tags

Image Manipulation

Long Description

This application scales the given image pixel intensity between two given values. By default min (resp. max) value is set to 0 (resp. 255).

Parameters

Limitations

None

Authors

OTB-Team

See Also

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/RigidTransformResample-id.html b/python/plugins/processing/otb/description/doc/RigidTransformResample-id.html new file mode 100644 index 000000000000..241b4346d913 --- /dev/null +++ b/python/plugins/processing/otb/description/doc/RigidTransformResample-id.html @@ -0,0 +1,5 @@ + + +

RigidTransformResample

Brief Description

Resample an image with a rigid transform

Tags

Conversion,Geometry

Long Description

This application performs a parametric transform on the input image. Scaling, translation and rotation with scaling factor are handled. Parameters of the transform is expressed in physical units, thus particular attention must be paid on pixel size (value, and sign). Moreover transform is expressed from input space to output space (on the contrary ITK Transforms are expressed form output space to input space).

Parameters

Limitations

None

Authors

OTB-Team

See Also

Translation

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/RigidTransformResample-rotation.html b/python/plugins/processing/otb/description/doc/RigidTransformResample-rotation.html new file mode 100644 index 000000000000..241b4346d913 --- /dev/null +++ b/python/plugins/processing/otb/description/doc/RigidTransformResample-rotation.html @@ -0,0 +1,5 @@ + + +

RigidTransformResample

Brief Description

Resample an image with a rigid transform

Tags

Conversion,Geometry

Long Description

This application performs a parametric transform on the input image. Scaling, translation and rotation with scaling factor are handled. Parameters of the transform is expressed in physical units, thus particular attention must be paid on pixel size (value, and sign). Moreover transform is expressed from input space to output space (on the contrary ITK Transforms are expressed form output space to input space).

Parameters

Limitations

None

Authors

OTB-Team

See Also

Translation

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/RigidTransformResample-translation.html b/python/plugins/processing/otb/description/doc/RigidTransformResample-translation.html new file mode 100644 index 000000000000..241b4346d913 --- /dev/null +++ b/python/plugins/processing/otb/description/doc/RigidTransformResample-translation.html @@ -0,0 +1,5 @@ + + +

RigidTransformResample

Brief Description

Resample an image with a rigid transform

Tags

Conversion,Geometry

Long Description

This application performs a parametric transform on the input image. Scaling, translation and rotation with scaling factor are handled. Parameters of the transform is expressed in physical units, thus particular attention must be paid on pixel size (value, and sign). Moreover transform is expressed from input space to output space (on the contrary ITK Transforms are expressed form output space to input space).

Parameters

Limitations

None

Authors

OTB-Team

See Also

Translation

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/RigidTransformResample.html b/python/plugins/processing/otb/description/doc/RigidTransformResample.html index 653de92c70ef..241b4346d913 100644 --- a/python/plugins/processing/otb/description/doc/RigidTransformResample.html +++ b/python/plugins/processing/otb/description/doc/RigidTransformResample.html @@ -1,2 +1,5 @@ -

Image resampling with a rigid transform

Brief Description

Resample an image with a rigid transform

Tags

Conversion, Geometry

Long Description

This application performs an translation on the input image. - Parameters of the translation can be set with tx and ty options.

Parameters

Limitations

None

Authors

OTB-Team

See also

Translation application

Example of use

\ No newline at end of file + + +

RigidTransformResample

Brief Description

Resample an image with a rigid transform

Tags

Conversion,Geometry

Long Description

This application performs a parametric transform on the input image. Scaling, translation and rotation with scaling factor are handled. Parameters of the transform is expressed in physical units, thus particular attention must be paid on pixel size (value, and sign). Moreover transform is expressed from input space to output space (on the contrary ITK Transforms are expressed form output space to input space).

Parameters

Limitations

None

Authors

OTB-Team

See Also

Translation

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/SFSTextureExtraction.html b/python/plugins/processing/otb/description/doc/SFSTextureExtraction.html new file mode 100644 index 000000000000..9d2f9ff24828 --- /dev/null +++ b/python/plugins/processing/otb/description/doc/SFSTextureExtraction.html @@ -0,0 +1,5 @@ + + +

SFSTextureExtraction

Brief Description

Computes Structural Feature Set textures on every pixel of the input image selected channel

Tags

Textures,Feature Extraction

Long Description

This application computes SFS textures on a mono band image

Parameters

Limitations

None

Authors

OTB-Team

See Also

otbSFSTexturesImageFilter class

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/SOMClassification.html b/python/plugins/processing/otb/description/doc/SOMClassification.html new file mode 100644 index 000000000000..e5a6742423ca --- /dev/null +++ b/python/plugins/processing/otb/description/doc/SOMClassification.html @@ -0,0 +1,5 @@ + + +

SOMClassification

Brief Description

SOM image classification.

Tags

Segmentation,Learning

Long Description

Unsupervised Self Organizing Map image classification.

Parameters

Limitations

None

Authors

OTB-Team

See Also

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/SarRadiometricCalibration.html b/python/plugins/processing/otb/description/doc/SarRadiometricCalibration.html index b8d4e5ad1ab0..718529a9d725 100644 --- a/python/plugins/processing/otb/description/doc/SarRadiometricCalibration.html +++ b/python/plugins/processing/otb/description/doc/SarRadiometricCalibration.html @@ -1 +1,5 @@ -

SAR Radiometric calibration application

Brief Description

Perform SAR calibration on input complex images

Tags

Calibration, SAR

Long Description

This application performs SAR calibration on input complex images.

Parameters

Limitations

None

Authors

OTB-Team

See also

Example of use

\ No newline at end of file + + +

SarRadiometricCalibration

Brief Description

Perform SAR calibration on input complex images

Tags

Calibration,SAR

Long Description

This application performs SAR calibration on input complex images.

Parameters

Limitations

None

Authors

OTB-Team

See Also

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/Segmentation-cc.html b/python/plugins/processing/otb/description/doc/Segmentation-cc.html new file mode 100644 index 000000000000..7fb053cc2c7c --- /dev/null +++ b/python/plugins/processing/otb/description/doc/Segmentation-cc.html @@ -0,0 +1,9 @@ + + +

Segmentation

Brief Description

Performs segmentation of an image, and output either a raster or a vector file. In vector mode, large input datasets are supported.

Tags

Segmentation

Long Description

This application allows to perform various segmentation algorithms on a multispectral image.Available segmentation algorithms are two different versions of Mean-Shift segmentation algorithm (one being multi-threaded), simple pixel based connected components according to a user-defined criterion, and watershed from the gradient of the intensity (norm of spectral bands vector). The application has two different modes that affects the nature of its output. + +In raster mode, the output of the application is a classical image of unique labels identifying the segmented regions. The labeled output can be passed to the ColorMapping application to render regions with contrasted colours. Please note that this mode loads the whole input image into memory, and as such can not handle large images. + +To segment large data, one can use the vector mode. In this case, the output of the application is a vector file or database. The input image is split into tiles (whose size can be set using the tilesize parameter), and each tile is loaded, segmented with the chosen algorithm, vectorized, and written into the output file or database. This piece-wise behavior ensure that memory will never get overloaded, and that images of any size can be processed. There are few more options in the vector mode. The simplify option allows to simplify the geometry (i.e. remove nodes in polygons) according to a user-defined tolerance. The stitch option allows to application to try to stitch together polygons corresponding to segmented region that may have been split by the tiling scheme.

Parameters

Limitations

In raster mode, the application can not handle large input images. Stitching step of vector mode might become slow with very large input images. MeanShift filter results depends on threads number.

Authors

OTB-Team

See Also

MeanShiftSegmentation

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/Segmentation-edison.html b/python/plugins/processing/otb/description/doc/Segmentation-edison.html new file mode 100644 index 000000000000..7fb053cc2c7c --- /dev/null +++ b/python/plugins/processing/otb/description/doc/Segmentation-edison.html @@ -0,0 +1,9 @@ + + +

Segmentation

Brief Description

Performs segmentation of an image, and output either a raster or a vector file. In vector mode, large input datasets are supported.

Tags

Segmentation

Long Description

This application allows to perform various segmentation algorithms on a multispectral image.Available segmentation algorithms are two different versions of Mean-Shift segmentation algorithm (one being multi-threaded), simple pixel based connected components according to a user-defined criterion, and watershed from the gradient of the intensity (norm of spectral bands vector). The application has two different modes that affects the nature of its output. + +In raster mode, the output of the application is a classical image of unique labels identifying the segmented regions. The labeled output can be passed to the ColorMapping application to render regions with contrasted colours. Please note that this mode loads the whole input image into memory, and as such can not handle large images. + +To segment large data, one can use the vector mode. In this case, the output of the application is a vector file or database. The input image is split into tiles (whose size can be set using the tilesize parameter), and each tile is loaded, segmented with the chosen algorithm, vectorized, and written into the output file or database. This piece-wise behavior ensure that memory will never get overloaded, and that images of any size can be processed. There are few more options in the vector mode. The simplify option allows to simplify the geometry (i.e. remove nodes in polygons) according to a user-defined tolerance. The stitch option allows to application to try to stitch together polygons corresponding to segmented region that may have been split by the tiling scheme.

Parameters

Limitations

In raster mode, the application can not handle large input images. Stitching step of vector mode might become slow with very large input images. MeanShift filter results depends on threads number.

Authors

OTB-Team

See Also

MeanShiftSegmentation

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/Segmentation-meanshift.html b/python/plugins/processing/otb/description/doc/Segmentation-meanshift.html new file mode 100644 index 000000000000..7fb053cc2c7c --- /dev/null +++ b/python/plugins/processing/otb/description/doc/Segmentation-meanshift.html @@ -0,0 +1,9 @@ + + +

Segmentation

Brief Description

Performs segmentation of an image, and output either a raster or a vector file. In vector mode, large input datasets are supported.

Tags

Segmentation

Long Description

This application allows to perform various segmentation algorithms on a multispectral image.Available segmentation algorithms are two different versions of Mean-Shift segmentation algorithm (one being multi-threaded), simple pixel based connected components according to a user-defined criterion, and watershed from the gradient of the intensity (norm of spectral bands vector). The application has two different modes that affects the nature of its output. + +In raster mode, the output of the application is a classical image of unique labels identifying the segmented regions. The labeled output can be passed to the ColorMapping application to render regions with contrasted colours. Please note that this mode loads the whole input image into memory, and as such can not handle large images. + +To segment large data, one can use the vector mode. In this case, the output of the application is a vector file or database. The input image is split into tiles (whose size can be set using the tilesize parameter), and each tile is loaded, segmented with the chosen algorithm, vectorized, and written into the output file or database. This piece-wise behavior ensure that memory will never get overloaded, and that images of any size can be processed. There are few more options in the vector mode. The simplify option allows to simplify the geometry (i.e. remove nodes in polygons) according to a user-defined tolerance. The stitch option allows to application to try to stitch together polygons corresponding to segmented region that may have been split by the tiling scheme.

Parameters

Limitations

In raster mode, the application can not handle large input images. Stitching step of vector mode might become slow with very large input images. MeanShift filter results depends on threads number.

Authors

OTB-Team

See Also

MeanShiftSegmentation

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/Segmentation-mprofiles.html b/python/plugins/processing/otb/description/doc/Segmentation-mprofiles.html new file mode 100644 index 000000000000..7fb053cc2c7c --- /dev/null +++ b/python/plugins/processing/otb/description/doc/Segmentation-mprofiles.html @@ -0,0 +1,9 @@ + + +

Segmentation

Brief Description

Performs segmentation of an image, and output either a raster or a vector file. In vector mode, large input datasets are supported.

Tags

Segmentation

Long Description

This application allows to perform various segmentation algorithms on a multispectral image.Available segmentation algorithms are two different versions of Mean-Shift segmentation algorithm (one being multi-threaded), simple pixel based connected components according to a user-defined criterion, and watershed from the gradient of the intensity (norm of spectral bands vector). The application has two different modes that affects the nature of its output. + +In raster mode, the output of the application is a classical image of unique labels identifying the segmented regions. The labeled output can be passed to the ColorMapping application to render regions with contrasted colours. Please note that this mode loads the whole input image into memory, and as such can not handle large images. + +To segment large data, one can use the vector mode. In this case, the output of the application is a vector file or database. The input image is split into tiles (whose size can be set using the tilesize parameter), and each tile is loaded, segmented with the chosen algorithm, vectorized, and written into the output file or database. This piece-wise behavior ensure that memory will never get overloaded, and that images of any size can be processed. There are few more options in the vector mode. The simplify option allows to simplify the geometry (i.e. remove nodes in polygons) according to a user-defined tolerance. The stitch option allows to application to try to stitch together polygons corresponding to segmented region that may have been split by the tiling scheme.

Parameters

Limitations

In raster mode, the application can not handle large input images. Stitching step of vector mode might become slow with very large input images. MeanShift filter results depends on threads number.

Authors

OTB-Team

See Also

MeanShiftSegmentation

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/Segmentation-watershed.html b/python/plugins/processing/otb/description/doc/Segmentation-watershed.html new file mode 100644 index 000000000000..7fb053cc2c7c --- /dev/null +++ b/python/plugins/processing/otb/description/doc/Segmentation-watershed.html @@ -0,0 +1,9 @@ + + +

Segmentation

Brief Description

Performs segmentation of an image, and output either a raster or a vector file. In vector mode, large input datasets are supported.

Tags

Segmentation

Long Description

This application allows to perform various segmentation algorithms on a multispectral image.Available segmentation algorithms are two different versions of Mean-Shift segmentation algorithm (one being multi-threaded), simple pixel based connected components according to a user-defined criterion, and watershed from the gradient of the intensity (norm of spectral bands vector). The application has two different modes that affects the nature of its output. + +In raster mode, the output of the application is a classical image of unique labels identifying the segmented regions. The labeled output can be passed to the ColorMapping application to render regions with contrasted colours. Please note that this mode loads the whole input image into memory, and as such can not handle large images. + +To segment large data, one can use the vector mode. In this case, the output of the application is a vector file or database. The input image is split into tiles (whose size can be set using the tilesize parameter), and each tile is loaded, segmented with the chosen algorithm, vectorized, and written into the output file or database. This piece-wise behavior ensure that memory will never get overloaded, and that images of any size can be processed. There are few more options in the vector mode. The simplify option allows to simplify the geometry (i.e. remove nodes in polygons) according to a user-defined tolerance. The stitch option allows to application to try to stitch together polygons corresponding to segmented region that may have been split by the tiling scheme.

Parameters

Limitations

In raster mode, the application can not handle large input images. Stitching step of vector mode might become slow with very large input images. MeanShift filter results depends on threads number.

Authors

OTB-Team

See Also

MeanShiftSegmentation

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/Segmentation.html b/python/plugins/processing/otb/description/doc/Segmentation.html new file mode 100644 index 000000000000..7fb053cc2c7c --- /dev/null +++ b/python/plugins/processing/otb/description/doc/Segmentation.html @@ -0,0 +1,9 @@ + + +

Segmentation

Brief Description

Performs segmentation of an image, and output either a raster or a vector file. In vector mode, large input datasets are supported.

Tags

Segmentation

Long Description

This application allows to perform various segmentation algorithms on a multispectral image.Available segmentation algorithms are two different versions of Mean-Shift segmentation algorithm (one being multi-threaded), simple pixel based connected components according to a user-defined criterion, and watershed from the gradient of the intensity (norm of spectral bands vector). The application has two different modes that affects the nature of its output. + +In raster mode, the output of the application is a classical image of unique labels identifying the segmented regions. The labeled output can be passed to the ColorMapping application to render regions with contrasted colours. Please note that this mode loads the whole input image into memory, and as such can not handle large images. + +To segment large data, one can use the vector mode. In this case, the output of the application is a vector file or database. The input image is split into tiles (whose size can be set using the tilesize parameter), and each tile is loaded, segmented with the chosen algorithm, vectorized, and written into the output file or database. This piece-wise behavior ensure that memory will never get overloaded, and that images of any size can be processed. There are few more options in the vector mode. The simplify option allows to simplify the geometry (i.e. remove nodes in polygons) according to a user-defined tolerance. The stitch option allows to application to try to stitch together polygons corresponding to segmented region that may have been split by the tiling scheme.

Parameters

Limitations

In raster mode, the application can not handle large input images. Stitching step of vector mode might become slow with very large input images. MeanShift filter results depends on threads number.

Authors

OTB-Team

See Also

MeanShiftSegmentation

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/Smoothing-anidif.html b/python/plugins/processing/otb/description/doc/Smoothing-anidif.html new file mode 100644 index 000000000000..56a08faab8b7 --- /dev/null +++ b/python/plugins/processing/otb/description/doc/Smoothing-anidif.html @@ -0,0 +1,5 @@ + + +

Smoothing

Brief Description

Apply a smoothing filter to an image

Tags

Image Filtering

Long Description

This application applies smoothing filter to an image. Either gaussian, mean, or anisotropic diffusion are available.

Parameters

Limitations

None

Authors

OTB-Team

See Also

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/Smoothing-gaussian.html b/python/plugins/processing/otb/description/doc/Smoothing-gaussian.html new file mode 100644 index 000000000000..56a08faab8b7 --- /dev/null +++ b/python/plugins/processing/otb/description/doc/Smoothing-gaussian.html @@ -0,0 +1,5 @@ + + +

Smoothing

Brief Description

Apply a smoothing filter to an image

Tags

Image Filtering

Long Description

This application applies smoothing filter to an image. Either gaussian, mean, or anisotropic diffusion are available.

Parameters

Limitations

None

Authors

OTB-Team

See Also

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/Smoothing-mean.html b/python/plugins/processing/otb/description/doc/Smoothing-mean.html new file mode 100644 index 000000000000..56a08faab8b7 --- /dev/null +++ b/python/plugins/processing/otb/description/doc/Smoothing-mean.html @@ -0,0 +1,5 @@ + + +

Smoothing

Brief Description

Apply a smoothing filter to an image

Tags

Image Filtering

Long Description

This application applies smoothing filter to an image. Either gaussian, mean, or anisotropic diffusion are available.

Parameters

Limitations

None

Authors

OTB-Team

See Also

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/Smoothing.html b/python/plugins/processing/otb/description/doc/Smoothing.html index 633868ed6a3d..56a08faab8b7 100644 --- a/python/plugins/processing/otb/description/doc/Smoothing.html +++ b/python/plugins/processing/otb/description/doc/Smoothing.html @@ -1 +1,5 @@ -

Smoothing Application

Brief Description

Apply a smoothing filter to an image

Tags

Image Filtering

Long Description

This application applies smoothing filter to an image. Either gaussian, mean, or anisotropic diffusion are available.

Parameters

Limitations

None

Authors

OTB-Team

See also

Example of use

\ No newline at end of file + + +

Smoothing

Brief Description

Apply a smoothing filter to an image

Tags

Image Filtering

Long Description

This application applies smoothing filter to an image. Either gaussian, mean, or anisotropic diffusion are available.

Parameters

Limitations

None

Authors

OTB-Team

See Also

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/SplitImage.html b/python/plugins/processing/otb/description/doc/SplitImage.html index deedec9d2323..c5c0238f2d68 100644 --- a/python/plugins/processing/otb/description/doc/SplitImage.html +++ b/python/plugins/processing/otb/description/doc/SplitImage.html @@ -1 +1,5 @@ -

Split Image Application

Brief Description

Split a N multiband image into N images

Tags

Image Manipulation

Long Description

This application splits a N multiband image into N images. The output images filename will be generated from the output one. Thus if the input image has 2 channels, and the user has set ad output outimage.tif, the generated images will be outimage_0.tif and outimage_1.tif

Parameters

Limitations

None

Authors

OTB-Team

See also

Example of use

\ No newline at end of file + + +

SplitImage

Brief Description

Split a N multiband image into N images

Tags

Image Manipulation

Long Description

This application splits a N-bands image into N mono-band images. The output images filename will be generated from the output parameter. Thus if the input image has 2 channels, and the user has set an output outimage.tif, the generated images will be outimage_0.tif and outimage_1.tif

Parameters

Limitations

None

Authors

OTB-Team

See Also

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/StereoFramework.html b/python/plugins/processing/otb/description/doc/StereoFramework.html new file mode 100644 index 000000000000..d0c1b5118959 --- /dev/null +++ b/python/plugins/processing/otb/description/doc/StereoFramework.html @@ -0,0 +1,16 @@ + + +

StereoFramework

Brief Description

Compute the ground elevation based on one or multiple stereo pair(s)

Tags

Stereo

Long Description

Compute the ground elevation with a stereo block matching algorithm between one or mulitple stereo pair in sensor geometry. The output is projected in desired geographic or cartographic map projection (UTM by default). The pipeline is made of the following steps: +for each sensor pair : + - compute the epipolar deformation grids from the stereo pair (direct and inverse) + - resample the stereo pair into epipolar geometry using BCO interpolation + - create masks for each epipolar image : remove black borders and resample input masks + - compute horizontal disparities with a block matching algorithm + - refine disparities to sub-pixel precision with a dichotomy algorithm + - apply an optional median filter + - filter disparities based on the correlation score and exploration bounds + - translate disparities in sensor geometry + convert disparity to 3D Map. +Then fuse all 3D maps to produce DSM.

Parameters

Limitations

Authors

OTB-Team

See Also

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/StereoRectificationGridGenerator.html b/python/plugins/processing/otb/description/doc/StereoRectificationGridGenerator.html new file mode 100644 index 000000000000..1df1bb8479f3 --- /dev/null +++ b/python/plugins/processing/otb/description/doc/StereoRectificationGridGenerator.html @@ -0,0 +1,5 @@ + + +

StereoRectificationGridGenerator

Brief Description

Generates two deformation fields to stereo-rectify (i.e. resample in epipolar geometry) a pair of stereo images up to the sensor model precision

Tags

Stereo

Long Description

This application generates a pair of deformation grid to stereo-rectify a pair of stereo images according to sensor modelling and a mean elevation hypothesis. The deformation grids can be passed to the StereoRectificationGridGenerator application for actual resampling in epipolar geometry.

Parameters

Limitations

Generation of the deformation grid is not streamable, pay attention to this fact when setting the grid step.

Authors

OTB-Team

See Also

otbGridBasedImageResampling

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/Superimpose.html b/python/plugins/processing/otb/description/doc/Superimpose.html index e3b68526637e..0381f6569bdf 100644 --- a/python/plugins/processing/otb/description/doc/Superimpose.html +++ b/python/plugins/processing/otb/description/doc/Superimpose.html @@ -1 +1,5 @@ -

Superimpose sensor application

Brief Description

Using available image metadata, project one image onto another one

Tags

Geometry, Image Manipulation, Superimposition

Long Description

This application performs /....

Parameters

Limitations

None

Authors

OTB-Team

See also

Example of use

\ No newline at end of file + + +

Superimpose

Brief Description

Using available image metadata, project one image onto another one

Tags

Geometry,Superimposition

Long Description

This application performs the projection of an image into the geometry of another one.

Parameters

Limitations

None

Authors

OTB-Team

See Also

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/TestApplication.html b/python/plugins/processing/otb/description/doc/TestApplication.html new file mode 100644 index 000000000000..c74750943211 --- /dev/null +++ b/python/plugins/processing/otb/description/doc/TestApplication.html @@ -0,0 +1,5 @@ + + +

TestApplication

Brief Description

This application helps developers to test parameters types

Tags

Test

Long Description

The purpose of this application is to test parameters types.

Parameters

Limitations

None

Authors

OTB-Team

See Also

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/TileFusion.html b/python/plugins/processing/otb/description/doc/TileFusion.html new file mode 100644 index 000000000000..142dc73da58a --- /dev/null +++ b/python/plugins/processing/otb/description/doc/TileFusion.html @@ -0,0 +1,5 @@ + + +

TileFusion

Brief Description

Fusion of an image made of several tile files.

Tags

Image Manipulation

Long Description

Concatenate several tile files into a single image file.

Parameters

Limitations

None

Authors

OTB-Team

See Also

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/TrainImagesClassifier-ann.html b/python/plugins/processing/otb/description/doc/TrainImagesClassifier-ann.html new file mode 100644 index 000000000000..f50791258f5d --- /dev/null +++ b/python/plugins/processing/otb/description/doc/TrainImagesClassifier-ann.html @@ -0,0 +1,11 @@ + + +

TrainImagesClassifier

Brief Description

Train a classifier from multiple pairs of images and training vector data.

Tags

Learning

Long Description

This application performs a classifier training from multiple pairs of input images and training vector data. Samples are composed of pixel values in each band optionally centered and reduced using an XML statistics file produced by the ComputeImagesStatistics application. + The training vector data must contain polygons with a positive integer field representing the class label. The name of this field can be set using the "Class label field" parameter. Training and validation sample lists are built such that each class is equally represented in both lists. One parameter allows to control the ratio between the number of samples in training and validation sets. Two parameters allow to manage the size of the training and validation sets per class and per image. + Several classifier parameters can be set depending on the chosen classifier. In the validation process, the confusion matrix is organized the following way: rows = reference labels, columns = produced labels. In the header of the optional confusion matrix output file, the validation (reference) and predicted (produced) class labels are ordered according to the rows/columns of the confusion matrix. + This application is based on LibSVM and on OpenCV Machine Learning classifiers, and is compatible with OpenCV 2.3.1 and later.

Parameters

Limitations

None

Authors

OTB-Team

See Also

OpenCV documentation for machine learning http://docs.opencv.org/modules/ml/doc/ml.html

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/TrainImagesClassifier-bayes.html b/python/plugins/processing/otb/description/doc/TrainImagesClassifier-bayes.html new file mode 100644 index 000000000000..f50791258f5d --- /dev/null +++ b/python/plugins/processing/otb/description/doc/TrainImagesClassifier-bayes.html @@ -0,0 +1,11 @@ + + +

TrainImagesClassifier

Brief Description

Train a classifier from multiple pairs of images and training vector data.

Tags

Learning

Long Description

This application performs a classifier training from multiple pairs of input images and training vector data. Samples are composed of pixel values in each band optionally centered and reduced using an XML statistics file produced by the ComputeImagesStatistics application. + The training vector data must contain polygons with a positive integer field representing the class label. The name of this field can be set using the "Class label field" parameter. Training and validation sample lists are built such that each class is equally represented in both lists. One parameter allows to control the ratio between the number of samples in training and validation sets. Two parameters allow to manage the size of the training and validation sets per class and per image. + Several classifier parameters can be set depending on the chosen classifier. In the validation process, the confusion matrix is organized the following way: rows = reference labels, columns = produced labels. In the header of the optional confusion matrix output file, the validation (reference) and predicted (produced) class labels are ordered according to the rows/columns of the confusion matrix. + This application is based on LibSVM and on OpenCV Machine Learning classifiers, and is compatible with OpenCV 2.3.1 and later.

Parameters

Limitations

None

Authors

OTB-Team

See Also

OpenCV documentation for machine learning http://docs.opencv.org/modules/ml/doc/ml.html

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/TrainImagesClassifier-boost.html b/python/plugins/processing/otb/description/doc/TrainImagesClassifier-boost.html new file mode 100644 index 000000000000..f50791258f5d --- /dev/null +++ b/python/plugins/processing/otb/description/doc/TrainImagesClassifier-boost.html @@ -0,0 +1,11 @@ + + +

TrainImagesClassifier

Brief Description

Train a classifier from multiple pairs of images and training vector data.

Tags

Learning

Long Description

This application performs a classifier training from multiple pairs of input images and training vector data. Samples are composed of pixel values in each band optionally centered and reduced using an XML statistics file produced by the ComputeImagesStatistics application. + The training vector data must contain polygons with a positive integer field representing the class label. The name of this field can be set using the "Class label field" parameter. Training and validation sample lists are built such that each class is equally represented in both lists. One parameter allows to control the ratio between the number of samples in training and validation sets. Two parameters allow to manage the size of the training and validation sets per class and per image. + Several classifier parameters can be set depending on the chosen classifier. In the validation process, the confusion matrix is organized the following way: rows = reference labels, columns = produced labels. In the header of the optional confusion matrix output file, the validation (reference) and predicted (produced) class labels are ordered according to the rows/columns of the confusion matrix. + This application is based on LibSVM and on OpenCV Machine Learning classifiers, and is compatible with OpenCV 2.3.1 and later.

Parameters

Limitations

None

Authors

OTB-Team

See Also

OpenCV documentation for machine learning http://docs.opencv.org/modules/ml/doc/ml.html

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/TrainImagesClassifier-dt.html b/python/plugins/processing/otb/description/doc/TrainImagesClassifier-dt.html new file mode 100644 index 000000000000..f50791258f5d --- /dev/null +++ b/python/plugins/processing/otb/description/doc/TrainImagesClassifier-dt.html @@ -0,0 +1,11 @@ + + +

TrainImagesClassifier

Brief Description

Train a classifier from multiple pairs of images and training vector data.

Tags

Learning

Long Description

This application performs a classifier training from multiple pairs of input images and training vector data. Samples are composed of pixel values in each band optionally centered and reduced using an XML statistics file produced by the ComputeImagesStatistics application. + The training vector data must contain polygons with a positive integer field representing the class label. The name of this field can be set using the "Class label field" parameter. Training and validation sample lists are built such that each class is equally represented in both lists. One parameter allows to control the ratio between the number of samples in training and validation sets. Two parameters allow to manage the size of the training and validation sets per class and per image. + Several classifier parameters can be set depending on the chosen classifier. In the validation process, the confusion matrix is organized the following way: rows = reference labels, columns = produced labels. In the header of the optional confusion matrix output file, the validation (reference) and predicted (produced) class labels are ordered according to the rows/columns of the confusion matrix. + This application is based on LibSVM and on OpenCV Machine Learning classifiers, and is compatible with OpenCV 2.3.1 and later.

Parameters

Limitations

None

Authors

OTB-Team

See Also

OpenCV documentation for machine learning http://docs.opencv.org/modules/ml/doc/ml.html

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/TrainImagesClassifier-gbt.html b/python/plugins/processing/otb/description/doc/TrainImagesClassifier-gbt.html new file mode 100644 index 000000000000..f50791258f5d --- /dev/null +++ b/python/plugins/processing/otb/description/doc/TrainImagesClassifier-gbt.html @@ -0,0 +1,11 @@ + + +

TrainImagesClassifier

Brief Description

Train a classifier from multiple pairs of images and training vector data.

Tags

Learning

Long Description

This application performs a classifier training from multiple pairs of input images and training vector data. Samples are composed of pixel values in each band optionally centered and reduced using an XML statistics file produced by the ComputeImagesStatistics application. + The training vector data must contain polygons with a positive integer field representing the class label. The name of this field can be set using the "Class label field" parameter. Training and validation sample lists are built such that each class is equally represented in both lists. One parameter allows to control the ratio between the number of samples in training and validation sets. Two parameters allow to manage the size of the training and validation sets per class and per image. + Several classifier parameters can be set depending on the chosen classifier. In the validation process, the confusion matrix is organized the following way: rows = reference labels, columns = produced labels. In the header of the optional confusion matrix output file, the validation (reference) and predicted (produced) class labels are ordered according to the rows/columns of the confusion matrix. + This application is based on LibSVM and on OpenCV Machine Learning classifiers, and is compatible with OpenCV 2.3.1 and later.

Parameters

Limitations

None

Authors

OTB-Team

See Also

OpenCV documentation for machine learning http://docs.opencv.org/modules/ml/doc/ml.html

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/TrainImagesClassifier-knn.html b/python/plugins/processing/otb/description/doc/TrainImagesClassifier-knn.html new file mode 100644 index 000000000000..f50791258f5d --- /dev/null +++ b/python/plugins/processing/otb/description/doc/TrainImagesClassifier-knn.html @@ -0,0 +1,11 @@ + + +

TrainImagesClassifier

Brief Description

Train a classifier from multiple pairs of images and training vector data.

Tags

Learning

Long Description

This application performs a classifier training from multiple pairs of input images and training vector data. Samples are composed of pixel values in each band optionally centered and reduced using an XML statistics file produced by the ComputeImagesStatistics application. + The training vector data must contain polygons with a positive integer field representing the class label. The name of this field can be set using the "Class label field" parameter. Training and validation sample lists are built such that each class is equally represented in both lists. One parameter allows to control the ratio between the number of samples in training and validation sets. Two parameters allow to manage the size of the training and validation sets per class and per image. + Several classifier parameters can be set depending on the chosen classifier. In the validation process, the confusion matrix is organized the following way: rows = reference labels, columns = produced labels. In the header of the optional confusion matrix output file, the validation (reference) and predicted (produced) class labels are ordered according to the rows/columns of the confusion matrix. + This application is based on LibSVM and on OpenCV Machine Learning classifiers, and is compatible with OpenCV 2.3.1 and later.

Parameters

Limitations

None

Authors

OTB-Team

See Also

OpenCV documentation for machine learning http://docs.opencv.org/modules/ml/doc/ml.html

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/TrainImagesClassifier-libsvm.html b/python/plugins/processing/otb/description/doc/TrainImagesClassifier-libsvm.html new file mode 100644 index 000000000000..f50791258f5d --- /dev/null +++ b/python/plugins/processing/otb/description/doc/TrainImagesClassifier-libsvm.html @@ -0,0 +1,11 @@ + + +

TrainImagesClassifier

Brief Description

Train a classifier from multiple pairs of images and training vector data.

Tags

Learning

Long Description

This application performs a classifier training from multiple pairs of input images and training vector data. Samples are composed of pixel values in each band optionally centered and reduced using an XML statistics file produced by the ComputeImagesStatistics application. + The training vector data must contain polygons with a positive integer field representing the class label. The name of this field can be set using the "Class label field" parameter. Training and validation sample lists are built such that each class is equally represented in both lists. One parameter allows to control the ratio between the number of samples in training and validation sets. Two parameters allow to manage the size of the training and validation sets per class and per image. + Several classifier parameters can be set depending on the chosen classifier. In the validation process, the confusion matrix is organized the following way: rows = reference labels, columns = produced labels. In the header of the optional confusion matrix output file, the validation (reference) and predicted (produced) class labels are ordered according to the rows/columns of the confusion matrix. + This application is based on LibSVM and on OpenCV Machine Learning classifiers, and is compatible with OpenCV 2.3.1 and later.

Parameters

Limitations

None

Authors

OTB-Team

See Also

OpenCV documentation for machine learning http://docs.opencv.org/modules/ml/doc/ml.html

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/TrainImagesClassifier-rf.html b/python/plugins/processing/otb/description/doc/TrainImagesClassifier-rf.html new file mode 100644 index 000000000000..f50791258f5d --- /dev/null +++ b/python/plugins/processing/otb/description/doc/TrainImagesClassifier-rf.html @@ -0,0 +1,11 @@ + + +

TrainImagesClassifier

Brief Description

Train a classifier from multiple pairs of images and training vector data.

Tags

Learning

Long Description

This application performs a classifier training from multiple pairs of input images and training vector data. Samples are composed of pixel values in each band optionally centered and reduced using an XML statistics file produced by the ComputeImagesStatistics application. + The training vector data must contain polygons with a positive integer field representing the class label. The name of this field can be set using the "Class label field" parameter. Training and validation sample lists are built such that each class is equally represented in both lists. One parameter allows to control the ratio between the number of samples in training and validation sets. Two parameters allow to manage the size of the training and validation sets per class and per image. + Several classifier parameters can be set depending on the chosen classifier. In the validation process, the confusion matrix is organized the following way: rows = reference labels, columns = produced labels. In the header of the optional confusion matrix output file, the validation (reference) and predicted (produced) class labels are ordered according to the rows/columns of the confusion matrix. + This application is based on LibSVM and on OpenCV Machine Learning classifiers, and is compatible with OpenCV 2.3.1 and later.

Parameters

Limitations

None

Authors

OTB-Team

See Also

OpenCV documentation for machine learning http://docs.opencv.org/modules/ml/doc/ml.html

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/TrainImagesClassifier-svm.html b/python/plugins/processing/otb/description/doc/TrainImagesClassifier-svm.html new file mode 100644 index 000000000000..f50791258f5d --- /dev/null +++ b/python/plugins/processing/otb/description/doc/TrainImagesClassifier-svm.html @@ -0,0 +1,11 @@ + + +

TrainImagesClassifier

Brief Description

Train a classifier from multiple pairs of images and training vector data.

Tags

Learning

Long Description

This application performs a classifier training from multiple pairs of input images and training vector data. Samples are composed of pixel values in each band optionally centered and reduced using an XML statistics file produced by the ComputeImagesStatistics application. + The training vector data must contain polygons with a positive integer field representing the class label. The name of this field can be set using the "Class label field" parameter. Training and validation sample lists are built such that each class is equally represented in both lists. One parameter allows to control the ratio between the number of samples in training and validation sets. Two parameters allow to manage the size of the training and validation sets per class and per image. + Several classifier parameters can be set depending on the chosen classifier. In the validation process, the confusion matrix is organized the following way: rows = reference labels, columns = produced labels. In the header of the optional confusion matrix output file, the validation (reference) and predicted (produced) class labels are ordered according to the rows/columns of the confusion matrix. + This application is based on LibSVM and on OpenCV Machine Learning classifiers, and is compatible with OpenCV 2.3.1 and later.

Parameters

Limitations

None

Authors

OTB-Team

See Also

OpenCV documentation for machine learning http://docs.opencv.org/modules/ml/doc/ml.html

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/TrainImagesClassifier.html b/python/plugins/processing/otb/description/doc/TrainImagesClassifier.html new file mode 100644 index 000000000000..f50791258f5d --- /dev/null +++ b/python/plugins/processing/otb/description/doc/TrainImagesClassifier.html @@ -0,0 +1,11 @@ + + +

TrainImagesClassifier

Brief Description

Train a classifier from multiple pairs of images and training vector data.

Tags

Learning

Long Description

This application performs a classifier training from multiple pairs of input images and training vector data. Samples are composed of pixel values in each band optionally centered and reduced using an XML statistics file produced by the ComputeImagesStatistics application. + The training vector data must contain polygons with a positive integer field representing the class label. The name of this field can be set using the "Class label field" parameter. Training and validation sample lists are built such that each class is equally represented in both lists. One parameter allows to control the ratio between the number of samples in training and validation sets. Two parameters allow to manage the size of the training and validation sets per class and per image. + Several classifier parameters can be set depending on the chosen classifier. In the validation process, the confusion matrix is organized the following way: rows = reference labels, columns = produced labels. In the header of the optional confusion matrix output file, the validation (reference) and predicted (produced) class labels are ordered according to the rows/columns of the confusion matrix. + This application is based on LibSVM and on OpenCV Machine Learning classifiers, and is compatible with OpenCV 2.3.1 and later.

Parameters

Limitations

None

Authors

OTB-Team

See Also

OpenCV documentation for machine learning http://docs.opencv.org/modules/ml/doc/ml.html

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/VectorDataDSValidation.html b/python/plugins/processing/otb/description/doc/VectorDataDSValidation.html index 824883eb4e7a..dcc02ceb53fc 100644 --- a/python/plugins/processing/otb/description/doc/VectorDataDSValidation.html +++ b/python/plugins/processing/otb/description/doc/VectorDataDSValidation.html @@ -1 +1,5 @@ -

Vector Data validation Application

Brief Description

Vector data validation based on the fusion of features using Dempster-Shafer evidence theory framework.

Tags

Feature Extraction

Long Description

Vector data validation based on the fusion of features using Dempster-Shafer evidence theory framework.

Parameters

Limitations

None.

Authors

OTB-Team

See also

Example of use

\ No newline at end of file + + +

VectorDataDSValidation

Brief Description

Vector data validation based on the fusion of features using Dempster-Shafer evidence theory framework.

Tags

Feature Extraction

Long Description

This application validates or unvalidate the studied samples using the Dempster-Shafer theory.

Parameters

Limitations

None.

Authors

OTB-Team

See Also

http://en.wikipedia.org/wiki/Dempster-Shafer_theory

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/VectorDataExtractROIApplication.html b/python/plugins/processing/otb/description/doc/VectorDataExtractROIApplication.html index 01f64e6d27cb..74831ebd0499 100644 --- a/python/plugins/processing/otb/description/doc/VectorDataExtractROIApplication.html +++ b/python/plugins/processing/otb/description/doc/VectorDataExtractROIApplication.html @@ -1 +1,5 @@ -

VectorData Extract ROI Application

Brief Description

Perform an extract ROI on the input vector data according to the input image extent

Tags

Vector data Manipulation

Long Description

This application extract the VectorData features belonging to a region specified by the support image envelope

Parameters

Limitations

None

Authors

OTB-Team

See also

Example of use

\ No newline at end of file + + +

VectorDataExtractROIApplication

Brief Description

Perform an extract ROI on the input vector data according to the input image extent

Tags

Vector Data Manipulation

Long Description

This application extracts the vector data features belonging to a region specified by the support image envelope

Parameters

Limitations

None

Authors

OTB-Team

See Also

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/VectorDataReprojection.html b/python/plugins/processing/otb/description/doc/VectorDataReprojection.html index 851309208d5e..a3c5f1c2ecb6 100644 --- a/python/plugins/processing/otb/description/doc/VectorDataReprojection.html +++ b/python/plugins/processing/otb/description/doc/VectorDataReprojection.html @@ -1,489 +1,7 @@ - - -Vector Data reprojection - - - - - - - - -

[next] [prev] [prev-tail] [tail] [up]

-

4.2.4 Vector Data reprojection

-

This application allows to reproject a vector data using support image projection reference, or a user -specified map projection
-

Detailed description
-

This application allows to reproject a vector data using support image projection reference, or a user given -map projection.
If given, image keywordlist can be added to reprojected vectordata. -

Parameters
-

This section describes in details the parameters available for this application. Table 4.13, page 305 -presents a summary of these parameters and the parameters keys to be used in command-line and -programming languages. Application key is VectorDataReprojection.

- - -

- - -
-

-

- - - - - - - - - - - - - - - - - - -

Parameter key

Parameter type

Parameter description

in

Group

Input data

in.vd

Input File name

Input vector data

in.kwl

Input image

Use image keywords list

out

Group

Output data

out.vd

Output File name

Output vector data

out.proj

Choices

Output Projection choice

out.proj image

Choice

Use image projection ref

out.proj user

Choice

User defined projection

out.proj.image.in

Input image

Image used to get projection map

out.proj.user.map

Choices

Output Cartographic Map Projection

out.proj.user.map utm

Choice

Universal Trans-Mercator (UTM)

out.proj.user.map lambert2

Choice

Lambert II Etendu

out.proj.user.map lambert93

Choice

Lambert93

out.proj.user.map wgs

Choice

WGS 84

out.proj.user.map epsg

Choice

EPSG Code

out.proj.user.map.utm.zone

Int

Zone number

out.proj.user.map.utm.northhem

Boolean

Northern Hemisphere

out.proj.user.map.epsg.code

Int

EPSG Code

-
-
Table 4.13: Parameters table for Vector Data reprojection.
- - -
-
-

Input data -

-

Output data -

-

-

Example
-

To run this example in command-line, use the following: -

otbcli_VectorDataReprojection -in.vd VectorData_QB1.shp -out.proj image -out.proj.image ROI_QB_MUL_1.tif -out.vd reprojected_vd.shp -
-

To run this example from Python, use the following code snippet: -

#!/usr/bin/python 
 
# Import the otb applications package 
import otbApplication 
 
# The following line creates an instance of the VectorDataReprojection application 
VectorDataReprojection = otbApplication.Registry.CreateApplication("VectorDataReprojection") 
 
# The following lines set all the application parameters: 
VectorDataReprojection.SetParameterString("in.vd", "VectorData_QB1.shp") 
 
VectorDataReprojection.SetParameterString("out.proj","image") 
 
# The following line execute the application 
VectorDataReprojection.ExecuteAndWriteOutput() -
-

-

Authors
-

This application has been written by OTB-Team. - - -

[next] [prev] [prev-tail] [front] [up]

-

- + + +

VectorDataReprojection

Brief Description

This application allows to reproject a vector data using support image projection reference, or a user specified map projection +

Tags

Geometry,Vector Data Manipulation,Coordinates

Long Description

This application allows to reproject a vector data using support image projection reference, or a user given map projection. + If given, image keywordlist can be added to reprojected vectordata.

Parameters

Limitations

Authors

OTB-Team

See Also

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/VectorDataSetField.html b/python/plugins/processing/otb/description/doc/VectorDataSetField.html index 096a7385056b..f28354e410dd 100644 --- a/python/plugins/processing/otb/description/doc/VectorDataSetField.html +++ b/python/plugins/processing/otb/description/doc/VectorDataSetField.html @@ -1 +1,5 @@ -

Vector data set field Application

Brief Description

Set a field in vector data.

Tags

Vector data Manipulation

Long Description

Set a specified field to a specified value on all features of a vector data (Note: doesn't work with KML files yet)

Parameters

Limitations

None

Authors

OTB-Team

See also

Example of use

\ No newline at end of file + + +

VectorDataSetField

Brief Description

Set a field in vector data.

Tags

Vector Data Manipulation

Long Description

Set a specified field to a specified value on all features of a vector data.

Parameters

Limitations

Doesn't work with KML files yet

Authors

OTB-Team

See Also

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/VectorDataTransform.html b/python/plugins/processing/otb/description/doc/VectorDataTransform.html index 1a51014f7da8..2b64b0b78aa0 100644 --- a/python/plugins/processing/otb/description/doc/VectorDataTransform.html +++ b/python/plugins/processing/otb/description/doc/VectorDataTransform.html @@ -1 +1,5 @@ -

Vector Data Transformation Application

Brief Description

Apply a transform to each vertex of the input VectorData

Tags

Vector data Manipulation

Long Description

This application performs a transformation to an input vector data transforming each vertex that composed the vector data. The applied transformation manages translation, rotation and scale, and be be centered or not.

Parameters

Limitations

None

Authors

OTB-Team

See also

Example of use

\ No newline at end of file + + +

VectorDataTransform

Brief Description

Apply a transform to each vertex of the input VectorData

Tags

Vector Data Manipulation

Long Description

This application performs a transformation of an input vector data transforming each vertex in the vector data. The applied transformation manages translation, rotation and scale, and can be centered or not.

Parameters

Limitations

None

Authors

OTB-Team

See Also

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/description/doc/VertexComponentAnalysis.html b/python/plugins/processing/otb/description/doc/VertexComponentAnalysis.html index 681594c69e0c..14422d1b8425 100644 --- a/python/plugins/processing/otb/description/doc/VertexComponentAnalysis.html +++ b/python/plugins/processing/otb/description/doc/VertexComponentAnalysis.html @@ -1 +1,5 @@ -

Vertex Component Analysis

Brief Description

Find endmembers in hyperspectral images with Vertex Component Analysis

Tags

Hyperspectral, Dimensionality Reduction

Long Description

Applies the Vertex Component Analysis to an hyperspectral image to extract endmembers

Parameters

Limitations

None

Authors

OTB-Team

See also

Example of use

\ No newline at end of file + + +

VertexComponentAnalysis

Brief Description

Find endmembers in hyperspectral images with Vertex Component Analysis

Tags

Hyperspectral,Dimensionality Reduction

Long Description

Applies the Vertex Component Analysis to an hyperspectral image to extract endmembers

Parameters

Limitations

None

Authors

OTB-Team

See Also

Example of use

\ No newline at end of file diff --git a/python/plugins/processing/otb/maintenance/OTBHelper.py b/python/plugins/processing/otb/maintenance/OTBHelper.py new file mode 100644 index 000000000000..4354f71f6d8f --- /dev/null +++ b/python/plugins/processing/otb/maintenance/OTBHelper.py @@ -0,0 +1,618 @@ +# -*- coding: utf-8 -*- + +""" +*************************************************************************** + OTBHelper.py + --------------------- + Copyright : (C) 2013 by CS Systemes d'information (CS SI) + Email : otb at c-s dot fr (CS SI) + Contributors : Julien Malik (CS SI) - File creation + Oscar Picas (CS SI) - + Alexia Mondot (CS SI) - Add particular case in xml creation +*************************************************************************** +* * +* This program is free software; you can redistribute it and/or modify * +* it under the terms of the GNU General Public License as published by * +* the Free Software Foundation; either version 2 of the License, or * +* (at your option) any later version. * +* * +*************************************************************************** +""" +__author__ = 'Julien Malik, Oscar Picas, Alexia Mondot' +__copyright__ = '(C) 2013, CS Systemes d\'information (CS SI)' +# This will get replaced with a git SHA1 when you do a git archive +__revision__ = '$Format:%H$' +__version__ = "3.8" + +import os +import copy + +try: + import processing +except ImportError, e: + raise Exception("Processing must be installed and available in PYTHONPATH") + +try: + import otbApplication +except ImportError, e: + raise Exception("OTB python plugins must be installed and available in PYTHONPATH") + +import xml.etree.ElementTree as ET +import traceback + +import processing.otb.OTBSpecific_XMLcreation as OTBSpecific_XMLcreation +from contextlib import contextmanager +import shutil + +@contextmanager +def tag(name, c): + c.append("<%s>" % name) + yield + if ' ' in name: + c.append("" % name.split(' ')[0]) + else: + c.append("" % name) + +@contextmanager +def opentag(name, c): + c.append("<%s>" % name) + yield + +def get_group( appInstance ) : + tags = appInstance.GetDocTags() + sectionTags = ["Image Manipulation","Vector Data Manipulation", "Calibration","Geometry", "Image Filtering","Feature Extraction","Stereo","Learning","Segmentation"] + for sectionTag in sectionTags: + for tag in tags: + if tag == sectionTag: + return sectionTag + return "Miscellaneous" + +def set_OTB_log(): + import logging + logger = logging.getLogger('OTBGenerator') + hdlr = logging.FileHandler('OTBGenerator.log') + hdlr.setLevel(logging.DEBUG) + cons = logging.StreamHandler() + cons.setLevel(logging.CRITICAL) + formatter = logging.Formatter('%(asctime)s %(levelname)s %(message)s') + hdlr.setFormatter(formatter) + logger.addHandler(hdlr) + logger.addHandler(cons) + logger.setLevel(logging.DEBUG) + +def get_OTB_log(): + import logging + logger = logging.getLogger('OTBGenerator') + if not logger.handlers: + set_OTB_log() + logger = logging.getLogger('OTBGenerator') + return logger + +def indent(elem, level = 0): + i = "\n" + level*" " + if len(elem): + if not elem.text or not elem.text.strip(): + elem.text = i + " " + if not elem.tail or not elem.tail.strip(): + elem.tail = i + for elem in elem: + indent(elem, level + 1) + if not elem.tail or not elem.tail.strip(): + elem.tail = i + else: + if level and (not elem.tail or not elem.tail.strip()): + elem.tail = i + +set_OTB_log() + +def get_parameters(): + parameters = { getattr(otbApplication, each): each for each in dir(otbApplication) if 'ParameterType_' in each} + return parameters + +def get_inverted_parameters(): + """ + This function allows to map otb parameters with processing parameters. + """ + parameters = { getattr(otbApplication, each): each for each in dir(otbApplication) if 'ParameterType_' in each} + parameters_clone = copy.deepcopy(parameters) + + inverted_parameters = { key: value for value, key in parameters.items() } + inverted_parameters['ParameterType_Radius'] = 1 + inverted_parameters['ParameterType_RAM'] = 1 + inverted_parameters['ParameterType_ComplexInputImage'] = 9 + inverted_parameters['ParameterType_ComplexOutputImage'] = 13 + + inverted_parameters_clone = copy.deepcopy(inverted_parameters) + inverted_parameters_clone['ParameterType_Empty'] = 'ParameterBoolean' + inverted_parameters_clone['ParameterType_Int'] = 'ParameterNumber' + inverted_parameters_clone['ParameterType_Float'] = 'ParameterNumber' + inverted_parameters_clone['ParameterType_String'] = 'ParameterString' + inverted_parameters_clone['ParameterType_StringList'] = 'ParameterString' + inverted_parameters_clone['ParameterType_InputFilename'] = 'ParameterFile' + inverted_parameters_clone['ParameterType_OutputFilename'] = 'OutputFile' + inverted_parameters_clone['ParameterType_Directory'] = 'ParameterFile' + inverted_parameters_clone['ParameterType_Choice'] = 'ParameterSelection' + inverted_parameters_clone['ParameterType_InputImage'] = 'ParameterRaster' + inverted_parameters_clone['ParameterType_InputImageList'] = 'ParameterMultipleInput' + inverted_parameters_clone['ParameterType_InputVectorData'] = 'ParameterVector' + inverted_parameters_clone['ParameterType_InputVectorDataList'] = 'ParameterMultipleInput' + inverted_parameters_clone['ParameterType_OutputImage'] = 'OutputRaster' + inverted_parameters_clone['ParameterType_OutputVectorData'] = 'OutputVector' + inverted_parameters_clone['ParameterType_Radius'] = 'ParameterNumber' + inverted_parameters_clone['ParameterType_Group'] = None + inverted_parameters_clone['ParameterType_ListView'] = 'ParameterSelection' + inverted_parameters_clone['ParameterType_ComplexInputImage'] = 'ParameterRaster' + inverted_parameters_clone['ParameterType_ComplexOutputImage'] = 'OutputRaster' + inverted_parameters_clone['ParameterType_RAM'] = 'ParameterNumber' + inverted_parameters_clone['ParameterType_InputProcessXML'] = 'ParameterFile' + inverted_parameters_clone['ParameterType_OutputProcessXML'] = 'ParameterFile' + inverted_parameters_clone['ParameterType_InputFilenameList'] = 'ParameterMultipleExternalInput' # 'ParameterString' + + return inverted_parameters_clone + +def retrieve_module_name(param): + """ + returns the file parameter of the given processing parameter + """ + import processing + if param: + try : + if 'Parameter' in param: + return eval('processing.parameters.%s.__file__' % param).replace('pyc', 'py') + if 'Output' in param: + return eval('processing.outputs.%s.__file__' % param).replace('pyc', 'py') + except TypeError: + print "Error parsing ", param + return None + +def get_constructor_parameters_from_filename(py_file): + import ast + asto = ast.parse(open(py_file).read()) + e1 = [each for each in asto.body if type(each) is ast.ClassDef] + e2 = [each for each in e1[0].body if hasattr(each, "name") and each.name == "__init__"] + if len(e2) > 0: + e3 = len(e2[0].args.args) + e4 = e2[0].args.args + else: + e4 = [] + e5 = [each.id for each in e4] + return e5 + +def get_xml_description_from_application_name(our_app, criteria = None): + """ + creates an xml containing informations about the given our_app + """ + # creates the application to get the description + # header + app_instance = otbApplication.Registry.CreateApplication(our_app) + root = ET.Element('root') + app = ET.SubElement(root, 'key') + app.text = our_app + executable = ET.SubElement(root, 'exec') + executable.text = "otbcli_" + our_app + longname = ET.SubElement(root, 'longname') + longname.text = app_instance.GetDocName() + group = ET.SubElement(root, 'group') + group.text = get_group(app_instance) + desc = ET.SubElement(root, 'description') + desc.text = app_instance.GetDescription() + + if not criteria: + real_criteria = lambda x: True + else: + if not callable(criteria): + raise Exception("criteria parameter must be a valid python callable") + + real_criteria = criteria + + if len(our_app) == 0: + raise Exception("App name is empty !") + + # get parameters + param_keys = [param_key for param_key in app_instance.GetParametersKeys()] + param_keys = filter(real_criteria, param_keys) + + for param_key in param_keys: + if not param_key == "inxml" and not param_key == "outxml" : + get_param_descriptor(app.text, app_instance, param_key, root) + indent(root) + return root + +def get_the_choices(app_instance, our_descriptor, root): + choices = ET.SubElement(root, 'choices') + for choice in app_instance.GetChoiceKeys(our_descriptor): + choice_node = ET.SubElement(choices, 'choice') + choice_node.text = choice + +def get_param_descriptor(appkey, app_instance, our_descriptor, root): + """ + update the root xml with the data of the parameter given by "our_descriptor" + """ + logger = get_OTB_log() + parameters = get_parameters() + our_type = parameters[app_instance.GetParameterType(our_descriptor)] + + #get the list of mapped parameters (otb/processing) + inverted_parameters = get_inverted_parameters() + + mapped_parameter = inverted_parameters[our_type] + + file_parameter = retrieve_module_name(mapped_parameter) + + if not file_parameter: + logger.info("Type %s is not handled yet. (%s, %s)" % (our_type, appkey, our_descriptor)) + return + + param = ET.SubElement(root, 'parameter') + attrs = {'source_parameter_type' : parameters[app_instance.GetParameterType(our_descriptor)]} + if appkey == "Segmentation" : + if parameters[app_instance.GetParameterType(our_descriptor)] == "ParameterType_OutputFilename" : + attrs = {'source_parameter_type' : 'ParameterType_OutputVectorData'} + if appkey == "LSMSVectorization" : + if parameters[app_instance.GetParameterType(our_descriptor)] == "ParameterType_OutputFilename" : + attrs = {'source_parameter_type' : 'ParameterType_OutputVectorData'} + if appkey == "SplitImage" : + if parameters[app_instance.GetParameterType(our_descriptor)] == "ParameterType_OutputImage" : + attrs = {'source_parameter_type' : 'ParameterType_OutputFilename'} + + param_type = ET.SubElement(param, 'parameter_type', attrib = attrs) + + param_type.text = inverted_parameters[parameters[app_instance.GetParameterType(our_descriptor)]] + if appkey == "Segmentation" : + if parameters[app_instance.GetParameterType(our_descriptor)] == "ParameterType_OutputFilename" : + param_type.text = "OutputVector" + if appkey == "LSMSVectorization" : + if parameters[app_instance.GetParameterType(our_descriptor)] == "ParameterType_OutputFilename" : + param_type.text = "OutputVector" + if appkey == "SplitImage" : + if parameters[app_instance.GetParameterType(our_descriptor)] == "ParameterType_OutputImage" : + param_type.text = "OutputFile" + + the_params = get_constructor_parameters_from_filename(file_parameter) + if len(the_params) == 0: + if 'Output' in file_parameter: + file_path = os.path.join(os.path.dirname(file_parameter), 'Output.py') + the_params = get_constructor_parameters_from_filename(file_path) + if 'Parameter' in file_parameter: + file_path = os.path.join(os.path.dirname(file_parameter), 'Parameter.py') + the_params = (file_path) + + if "self" in the_params: + the_params = the_params[1:] + else: + raise Exception("Unexpected constructor parameters") + + key = ET.SubElement(param, 'key') + key.text = our_descriptor + is_choice_type = False + for each in the_params: + if each == "name": + name = ET.SubElement(param, 'name') + name.text = app_instance.GetParameterName(our_descriptor) + elif each == "description": + desc = ET.SubElement(param, 'description') + desc.text = app_instance.GetParameterDescription(our_descriptor) + elif each == "optional": + optional = ET.SubElement(param, 'optional') + optional.text = str(not app_instance.IsMandatory(our_descriptor)) + elif each == "default": + done = False + reason = [] + try: + default_value = str(app_instance.GetParameterAsString(our_descriptor)) + done = True + except: + reason.append(traceback.format_exc()) + if not done: + try: + default_value = str(app_instance.GetParameterFloat(our_descriptor)) + done = True + except: + reason.append(traceback.format_exc()) + if not done: + try: + default_value = str(app_instance.GetParameterInt(our_descriptor)) + done = True + except: + reason.append(traceback.format_exc()) + + if done: + default = ET.SubElement(param, 'default') + default.text = default_value + + if is_choice_type: + the_keys = [a_key for a_key in app_instance.GetChoiceKeys(our_descriptor)] + if default_value in the_keys: + default.text = str(the_keys.index(default_value)) + else: + default.text = '' + else: + logger.debug("A parameter transformation failed, trying default values : for %s, %s, type %s!, conversion message: %s" % (appkey, our_descriptor, parameters[app_instance.GetParameterType(our_descriptor)], str(reason))) + the_type = parameters[app_instance.GetParameterType(our_descriptor)] + if the_type == "ParameterType_Int": + default_value = "0" + elif the_type == "ParameterType_Float": + default_value = "0.0" + elif the_type == "ParameterType_Empty": + default_value = "True" + else: + raise Exception("Unable to adapt %s, %s, %s, conversion message: %s" % (appkey, our_descriptor, parameters[app_instance.GetParameterType(our_descriptor)], str(reason))) + + default = ET.SubElement(param, 'default') + default.text = default_value + else: + is_choice_type = 'Selection' in param_type.text + node = ET.SubElement(param, each) + if is_choice_type: + get_the_choices(app_instance, our_descriptor, node) + + +def get_default_parameter_value(app_instance, param): + parameters = get_parameters() + try: + return app_instance.GetParameterAsString(param) + except: + the_type = parameters[app_instance.GetParameterType(param)] + default_value = "0" + if the_type == "ParameterType_Int": + default_value = "0" + elif the_type == "ParameterType_Float": + default_value = "0.0" + elif the_type == "ParameterType_Empty": + default_value = "True" + return default_value + +def escape_html(par): + if 'Int' in par: + return '<int32>' + if 'Float' in par: + return '<float>' + if 'Empty' in par: + return '<boolean>' + if 'Radius' in par: + return '<int32>' + if 'RAM' in par: + return '<int32>' + return '<string>' + +def is_a_parameter(app_instance, param): + if app_instance.GetName() == "HaralickTextureExtraction" : + if param.startswith( "parameters." ): + return True + if '.' in param: + return False + try: + app_instance.GetChoiceKeys(param) + return False + except: + return True + + +def describe_app(app_instance): + parameters = get_parameters() + result = [] + with tag('html', result): + with tag('head', result): + how = """ + +""" + result.append(how) + with tag('body', result): + with tag('h1', result): + result.append(app_instance.GetName()) + with tag('h2', result): + result.append('Brief Description') + result.append(app_instance.GetDescription()) + with tag('h2', result): + result.append('Tags') + result.append(','.join(app_instance.GetDocTags())) + with tag('h2', result): + result.append('Long Description') + result.append(app_instance.GetDocLongDescription()) + with tag('h2', result): + result.append('Parameters') + params = app_instance.GetParametersKeys() + level = 0 + with tag('ul', result): + for param in params: + if is_a_parameter(app_instance, param): + with tag('li', result): + result.append('%s -%s %s ' % ('[param]', param, escape_html(parameters[app_instance.GetParameterType(param)]) )) + result.append('%s. Mandatory: %s. Default Value: "%s"' %(app_instance.GetParameterDescription(param), str(app_instance.IsMandatory(param)), get_default_parameter_value(app_instance, param))) + choices_tags = [each for each in params if (not is_a_parameter(app_instance, each)) and (not '.' in each)] + for choice in choices_tags: + result.append('%s -%s %s %s. Mandatory: %s. Default Value: "%s"' % ('[choice]', choice, app_instance.GetParameterDescription(choice), ','.join(app_instance.GetChoiceKeys(choice)), str(app_instance.IsMandatory(choice)), get_default_parameter_value(app_instance, choice))) + choices = app_instance.GetChoiceKeys(choice) + + with tag('ul', result): + for subchoice in choices: + with tag('li', result): + result.append('%s -%s' % ('[group]', subchoice)) + with tag('ul', result): + param_tags = [each for each in params if '.%s' % subchoice in each] + for param_tag in param_tags: + with tag('li', result): + result.append('%s -%s ' % ('[param]', param_tag)) + result.append("%s %s. Mandatory: %s. Default Value: "%s"" % ( escape_html(parameters[app_instance.GetParameterType(param_tag)]) ,app_instance.GetParameterDescription(param_tag), str(app_instance.IsMandatory(param_tag)), get_default_parameter_value(app_instance, param_tag))) + with tag('h2', result): + result.append('Limitations') + result.append(app_instance.GetDocLimitations()) + with tag('h2', result): + result.append('Authors') + result.append(app_instance.GetDocAuthors()) + with tag('h2', result): + result.append('See Also') + result.append(app_instance.GetDocSeeAlso()) + with tag('h2', result): + result.append('Example of use') + result.append(app_instance.GetHtmlExample()) + if app_instance.GetName() == "HaralickTextureExtraction" : + index = result.index("[param] -parameters <string> ") + del result[index +2] + del result[index +1] + del result[index] + del result[index -1] + return "".join(result) + +def get_list_from_node(myet, available_app): + all_params = [] + for parameter in myet.iter('parameter'): + rebuild = [] + par_type = parameter.find('parameter_type').text + key = parameter.find('key').text + name = parameter.find('name').text + source_par_type = parameter.find('parameter_type').attrib['source_parameter_type'] + rebuild.append(source_par_type) + rebuild.append(par_type) + rebuild.append(key) + rebuild.append(name) + for each in parameter[4:]: + if not each.tag in ["hidden"]: + if len(each.getchildren()) == 0: + if each.tag in ["default"]: + if "-" in available_app: + available_app = available_app.split("-")[0] + app_instance = otbApplication.Registry.CreateApplication(available_app) + rebuild.append(get_default_parameter_value(app_instance, key)) + else: + rebuild.append(each.text) + else: + rebuild.append([item.text for item in each.iter('choice')]) + all_params.append(rebuild) + return all_params + +def adapt_list_to_string(c_list): + a_list = c_list[1:] + if a_list[0] in ["ParameterVector", "ParameterMultipleInput"]: + if c_list[0] == "ParameterType_InputImageList": + a_list[3] = 3 + else: + a_list[3] = -1 + + if a_list[0] in ["ParameterRaster", "ParameterFile", "ParameterMultipleInput", "OutputRaster", "OutputFile"]: + if "Output" in a_list[0]: + a_list.append("/tmp/processing/output.tif") + else: + import os + import sys + a_list.append(os.path.join(os.path.abspath(os.curdir), "helper/QB_Toulouse_Ortho_PAN.tif")) + + if a_list[0] in ["ParameterSelection"]: + pass + + a_list[1]="-%s" % a_list[1] + def mystr(par): + if type(par) == type([]): + return ";".join(par) + return str(par) + + if a_list[-1] is None: + return "" + + b_list = map(mystr, a_list) + b_list = [b_list[1], b_list[-1]] + res = " ".join(b_list) + return res + + +def get_automatic_ut_from_xml_description(the_root): + dom_model = the_root + + try: + appkey = dom_model.find('key').text + cliName = dom_model.find('exec').text + name = dom_model.find('longname').text + group = dom_model.find('group').text + + if not cliName.startswith("otbcli_"): + raise Exception('Wrong client executable') + + rebu = get_list_from_node(dom_model, appkey) + the_result = map(adapt_list_to_string,rebu) + ut_command = cliName + " " + " ".join(the_result) + return ut_command + except Exception, e: + ET.dump(dom_model) + raise + +def list_reader(file_name, version): + tree = ET.parse(file_name) + root = tree.getroot() + nodes = [each.text for each in root.findall("./version[@id='%s']/app_name" % version)] + return nodes + +def get_otb_version(): + #TODO Find a way to retrieve installed otb version, force exception and parse otb-X.XX.X ? + return "3.18" + +def get_white_list(): + nodes = list_reader("white_list.xml",get_otb_version()) + return nodes + +def get_black_list(): + nodes = list_reader("black_list.xml",get_otb_version()) + return nodes + +def create_xml_descriptors(): + import os + if not os.path.exists("description"): + os.mkdir("description") + if not os.path.exists("html"): + os.mkdir("html") + + logger = get_OTB_log() + + white_list = get_white_list() + black_list = get_black_list() + + from processing.otb.OTBSpecific_XMLcreation import * + for available_app in otbApplication.Registry.GetAvailableApplications(): + try: + if 'get%s' % available_app in locals(): + if available_app in white_list and not available_app in black_list: + the_root = get_xml_description_from_application_name(available_app) + the_list = locals()['get%s' % available_app](available_app, the_root) + if the_list: + for each_dom in the_list: + try: + ut_command = get_automatic_ut_from_xml_description(each_dom) + except: + logger.error("Unit test for command %s must be fixed: %s" % (available_app , traceback.format_exc())) + else: + logger.warning("%s is not in white list." % available_app) + + else: + if available_app in white_list and not available_app in black_list: + logger.warning("There is no adaptor for %s, check white list and versions" % available_app) + # TODO Remove this default code when all apps are tested... + fh = open("description/%s.xml" % available_app, "w") + the_root = get_xml_description_from_application_name(available_app) + ET.ElementTree(the_root).write(fh) + fh.close() + try: + ut_command = get_automatic_ut_from_xml_description(the_root) + except: + logger.error("Unit test for command %s must be fixed: %s" % (available_app , traceback.format_exc())) + + except Exception, e: + logger.error(traceback.format_exc()) + + for available_app in otbApplication.Registry.GetAvailableApplications(): + try: + fh = open("description/doc/%s.html" % available_app, "w") + app_instance = otbApplication.Registry.CreateApplication(available_app) + app_instance.UpdateParameters() + ct = describe_app(app_instance) + fh.write(ct) + fh.close() + except Exception, e: + logger.error(traceback.format_exc()) + + sub_algo = [each for each in os.listdir("description") if "-" in each and ".xml" in each] + for key in sub_algo: + shutil.copy("description/doc/%s" % key.split("-")[0] + ".html","description/doc/%s" % key.split(".")[0] + ".html") + +if __name__ == "__main__": + create_xml_descriptors() diff --git a/python/plugins/processing/otb/maintenance/OTBSpecific_XMLcreation.py b/python/plugins/processing/otb/maintenance/OTBSpecific_XMLcreation.py new file mode 100644 index 000000000000..39ac507f0809 --- /dev/null +++ b/python/plugins/processing/otb/maintenance/OTBSpecific_XMLcreation.py @@ -0,0 +1,681 @@ +# -*- coding: utf-8 -*- + +""" +*************************************************************************** + OTBUtils.py + --------------------- + Date : 11-12-13 + Copyright : (C) 2013 by CS Systemes d'information (CS SI) + Email : otb at c-s dot fr (CS SI) + Contributors : Julien Malik (CS SI) - creation of otbspecific + Oscar Picas (CS SI) - + Alexia Mondot (CS SI) - split otbspecific into 2 files + add functions +*************************************************************************** +* * +* This program is free software; you can redistribute it and/or modify * +* it under the terms of the GNU General Public License as published by * +* the Free Software Foundation; either version 2 of the License, or * +* (at your option) any later version. * +* * +*************************************************************************** + +When QGIS is run, OTB algorithms are created according to xml files from description/ directory. +""" + +__author__ = 'Julien Malik, Oscar Picas, Alexia Mondot' +__date__ = 'December 2013' +__copyright__ = '(C) 2013, CS Systemes d\'information (CS SI)' +# This will get replaced with a git SHA1 when you do a git archive +__revision__ = '$Format:%H$' +__version__ = "3.8" + +import copy + +try: + import processing +except ImportError, e: + raise Exception("Processing must be installed and available in PYTHONPATH") + +try: + import otbApplication +except ImportError, e: + raise Exception("OTB python plugins must be installed and available in PYTHONPATH") + +from processing.core.ProcessingLog import ProcessingLog +from processing.core.ProcessingConfig import ProcessingConfig + +from processing.otb.OTBUtils import (renameValueField, + remove_dependant_choices, + remove_other_choices, + remove_parameter_by_key, + defaultSplit, + split_by_choice, + defaultWrite, + remove_choice, + remove_independant_choices ) + + +def getBinaryMorphologicalOperation(available_app, original_dom_document): + """ + Let ball as only available structype. + Split the application according to its filter dilate, erode, opening, closing. + """ + the_root = original_dom_document + renameValueField(the_root, 'structype.ball.xradius', 'name', 'The Structuring Element Radius') + renameValueField(the_root, 'structype.ball.xradius', 'description', 'The Structuring Element Radius') + remove_dependant_choices(the_root, 'structype', 'ball') + remove_other_choices(the_root, 'structype', 'ball') + remove_dependant_choices(the_root, 'filter', 'dilate') + remove_parameter_by_key(the_root, 'structype.ball.yradius') + #defaultWrite(available_app, the_root) + the_list = defaultSplit(available_app, the_root, 'filter') + return the_list + + +def getEdgeExtraction(available_app, original_dom_document): + """ + Let ball as only available filter (not an oval). + Split the application according to its filter gradient, sobel, touzi. + """ + the_root = original_dom_document + renameValueField(the_root, 'filter.touzi.xradius', 'name', 'The Radius') + renameValueField(the_root, 'filter.touzi.xradius', 'description', 'The Radius') + remove_parameter_by_key(the_root, 'filter.touzi.yradius') + splitted = split_by_choice(the_root, 'filter') + the_list = [] + for key in splitted: + defaultWrite('%s-%s' % (available_app, key), splitted[key]) + the_list.append(splitted[key]) + return the_list + + +def getGrayScaleMorphologicalOperation(available_app, original_dom_document): + """ + Let ball as only available structype. + Split the application according to its filter dilate, erode, opening, closing. + """ + the_root = original_dom_document + renameValueField(the_root, 'structype.ball.xradius', 'name', 'The Structuring Element Radius') + renameValueField(the_root, 'structype.ball.xradius', 'description', 'The Structuring Element Radius') + remove_dependant_choices(the_root, 'structype', 'ball') + remove_other_choices(the_root, 'structype', 'ball') + remove_parameter_by_key(the_root, 'structype.ball.yradius') + + splitted = defaultSplit(available_app, the_root, 'filter') + return splitted + + +def getOrthoRectification(available_app, original_dom_document): + """ + Let only mode auto. + Remove all parameters which should be updated once the input file given. + Split by SRS : EPSG, fit to ortho, lambert-wgs84 and UTM. + Each of these SRS have their own parameters modified in this fonction. + Delete GEOID and DEM parameter as they are not updated at the creation of the otb algorithms when you launch QGIS. + The values are picked from the settings. + """ + the_root = original_dom_document + + remove_choice(the_root, 'outputs.mode', 'auto') + remove_independant_choices(the_root, 'outputs.mode', 'auto') + remove_choice(the_root, 'outputs.mode', 'outputroi') + remove_independant_choices(the_root, 'outputs.mode', 'outputroi') + remove_parameter_by_key(the_root, 'outputs.ulx') + remove_parameter_by_key(the_root, 'outputs.uly') + remove_parameter_by_key(the_root, 'outputs.sizex') + remove_parameter_by_key(the_root, 'outputs.sizey') + remove_parameter_by_key(the_root, 'outputs.spacingx') + remove_parameter_by_key(the_root, 'outputs.spacingy') + remove_parameter_by_key(the_root, 'outputs.lrx') + remove_parameter_by_key(the_root, 'outputs.lry') + remove_parameter_by_key(the_root, 'opt.rpc') + + deleteGeoidSrtm(the_root) + + remove_parameter_by_key(the_root, 'outputs.isotropic') + + emptyMap = copy.deepcopy(the_root) + + remove_parameter_by_key(the_root, 'outputs.ortho') + remove_choice(the_root, 'outputs.mode', 'orthofit') + remove_independant_choices(the_root, 'outputs.mode', 'orthofit') + merged = copy.deepcopy(the_root) + + + + + splitted = split_by_choice(the_root, 'map') + the_list = [] + + for key in splitted: + if key == 'utm': + the_doc = splitted[key] + remove_parameter_by_key(the_doc, 'map.epsg.code') + defaultWrite('%s-%s' % (available_app, key), the_doc) + the_list.append(the_doc) + elif key == 'epsg': + the_doc = splitted[key] + remove_parameter_by_key(the_doc, 'map.utm.northhem') + remove_parameter_by_key(the_doc, 'map.utm.zone') + defaultWrite('%s-%s' % (available_app, key), the_doc) + the_list.append(the_doc) + + remove_choice(merged, 'map', 'utm') + remove_choice(merged, 'map', 'epsg') + remove_parameter_by_key(merged, 'map.epsg.code') + remove_parameter_by_key(merged, 'map.utm.northhem') + remove_parameter_by_key(merged, 'map.utm.zone') + old_app_name = merged.find('key').text + merged.find('key').text = '%s-%s' % (old_app_name, 'lambert-WGS84') + old_longname = merged.find('longname').text + merged.find('longname').text = '%s (%s)' % (old_app_name, 'lambert-WGS84') + defaultWrite('%s-%s' % (available_app, 'lambert-WGS84'), merged) + the_list.append(merged) + + remove_parameter_by_key(emptyMap, 'map') + remove_parameter_by_key(emptyMap, 'map.epsg.code') + remove_parameter_by_key(emptyMap, 'map.utm.northhem') + remove_parameter_by_key(emptyMap, 'map.utm.zone') + remove_choice(emptyMap, 'outputs.mode', 'autosize') + remove_independant_choices(emptyMap, 'outputs.mode', 'autosize') + remove_choice(emptyMap, 'outputs.mode', 'autospacing') + remove_independant_choices(emptyMap, 'outputs.mode', 'autospacing') + old_app_name = emptyMap.find('key').text + emptyMap.find('key').text = '%s-%s' % (old_app_name, 'fit-to-ortho') + old_longname = emptyMap.find('longname').text + emptyMap.find('longname').text = '%s (%s)' % (old_app_name, 'fit-to-ortho') + defaultWrite('%s-%s' % (available_app, 'fit-to-ortho'), emptyMap) + the_list.append(emptyMap) + + return the_list + + +def getDimensionalityReduction(available_app, original_dom_document): + """ + Remove rescale.outmin and rescale.outmax and split by method (ica, maf, napca and pca) and adjust parameters of each resulting app. + """ + the_root = original_dom_document + remove_parameter_by_key(the_root, 'rescale.outmin') + remove_parameter_by_key(the_root, 'rescale.outmax') + splitted = split_by_choice(the_root, 'method') + the_list = [] + for key in splitted: + if key == 'maf': + the_doc = splitted[key] + remove_parameter_by_key(the_doc, 'outinv') + defaultWrite('%s-%s' % (available_app, key), the_doc) + the_list.append(the_doc) + else: + defaultWrite('%s-%s' % (available_app, key), splitted[key]) + the_list.append(splitted[key]) + return the_list + + +def getPansharpening(available_app, original_dom_document): + """ + Split by method (bayes, lmvm, rcs) + """ + the_root = original_dom_document + splitted = split_by_choice(the_root, 'method') + the_list = [] + for key in splitted: + defaultWrite('%s-%s' % (available_app, key), splitted[key]) + the_list.append(splitted[key]) + return the_list + + +def getPixelValue(available_app, original_dom_document): + the_root = original_dom_document + remove_parameter_by_key(the_root, 'cl') + defaultWrite(available_app, the_root) + return [the_root] + + +def getExtractROI(available_app, original_dom_document): + """ + Split by mode (standard, fit) + Adapt parameters of each resulting app. + Delete GEOID and DEM parameter as they are not updated at the creation of the otb algorithms when you launch QGIS. + The values are picked from the settings. + """ + the_root = original_dom_document + remove_parameter_by_key(the_root, 'cl') + deleteGeoidSrtm(the_root) + splitted = split_by_choice(the_root, 'mode') + the_list = [] + for key in splitted: + if key == 'standard': + the_doc = splitted[key] + remove_parameter_by_key(the_doc, 'mode.fit.elev.dem') + remove_parameter_by_key(the_doc, 'mode.fit.elev.geoid') + remove_parameter_by_key(the_doc, 'mode.fit.elev.default') + remove_parameter_by_key(the_doc, 'mode.fit.ref') + defaultWrite('%s-%s' % (available_app, key), the_doc) + the_list.append(the_doc) + else: + #key == 'fit' + the_doc = splitted[key] + remove_parameter_by_key(the_doc, 'startx') + remove_parameter_by_key(the_doc, 'starty') + remove_parameter_by_key(the_doc, 'sizex') + remove_parameter_by_key(the_doc, 'sizey') + defaultWrite('%s-%s' % (available_app, key), the_doc) + the_list.append(splitted[key]) + return the_list + + +def getQuicklook(available_app, original_dom_document): + the_root = original_dom_document + remove_parameter_by_key(the_root, 'cl') + defaultWrite(available_app, the_root) + return [the_root] + + +def getRigidTransformResample(available_app, original_dom_document): + """ + split by transformation (id, rotation, translation) + """ + the_root = original_dom_document + splitted = split_by_choice(the_root, 'transform.type') + the_list = [] + for key in splitted: + defaultWrite('%s-%s' % (available_app, key), splitted[key]) + the_list.append(splitted[key]) + return the_list + + +def getHomologousPointsExtraction(available_app, original_dom_document): + the_list = defaultSplit(available_app, original_dom_document, 'mode') + return the_list + + +def getGenerateRPCSensorModel(available_app, original_dom_document): + the_root = original_dom_document + remove_dependant_choices(the_root, 'map', 'wgs') + remove_other_choices(the_root, 'map', 'wgs') + defaultWrite(available_app, the_root) + return [the_root] + + +def getRefineSensorModel(available_app, original_dom_document): + the_root = original_dom_document + remove_dependant_choices(the_root, 'map', 'wgs') + remove_other_choices(the_root, 'map', 'wgs') + defaultWrite(available_app, the_root) + return [the_root] + + +def getSegmentation(available_app, original_dom_document): + """ + Remove the choice raster and split by filter (cc, edison, meanshift, mprofiles, watershed) + """ + the_root = original_dom_document + #remove_choice(the_root, 'filter', 'edison') + #remove_independant_choices(the_root, 'filter', 'edison') + #remove_choice(the_root, 'filter', 'meanshift') + #remove_independant_choices(the_root, 'filter', 'meanshift') + remove_choice(the_root, 'mode', 'raster') + remove_independant_choices(the_root, 'mode', 'raster') + splitted = split_by_choice(the_root, 'filter') + the_list = [] + for key in splitted: + defaultWrite('%s-%s' % (available_app, key), splitted[key]) + the_list.append(splitted[key]) + return the_list + + +def getKMeansClassification(available_app, original_dom_document): + the_root = original_dom_document + remove_parameter_by_key(the_root, 'rand') + defaultWrite(available_app, the_root) + return [the_root] + + +def getTrainSVMImagesClassifier(available_app, original_dom_document): + the_root = original_dom_document + remove_parameter_by_key(the_root, 'rand') + defaultWrite(available_app, the_root) + return [the_root] + + +def getComputeConfusionMatrix(available_app, original_dom_document): + """ + Split by ref (raster, vector) + """ + the_root = original_dom_document + #remove_independant_choices(the_root, 'ref', 'vector') + #remove_choice(the_root, 'ref', 'vector') + #defaultWrite(available_app, the_root) + + splitted = split_by_choice(the_root, 'ref') + the_list = [] + for key in splitted: + defaultWrite('%s-%s' % (available_app, key), splitted[key]) + the_list.append(splitted[key]) + return the_list + + return [the_root] + + +def getOpticalCalibration(available_app, original_dom_document): + """ + Remove toc options (let toa) and remove all about atmo + """ + #the_list = defaultSplit(available_app, original_dom_document, 'level') + the_root = original_dom_document + remove_independant_choices(the_root, 'level', 'toc') + remove_choice(the_root, 'level', 'toc') + remove_parameter_by_key(the_root, 'atmo.aerosol') + remove_parameter_by_key(the_root, 'atmo.oz') + remove_parameter_by_key(the_root, 'atmo.wa') + remove_parameter_by_key(the_root, 'atmo.pressure') + remove_parameter_by_key(the_root, 'atmo.opt') + remove_parameter_by_key(the_root, 'atmo.aeronet') + remove_parameter_by_key(the_root, 'radius') + defaultWrite(available_app, the_root) + return [the_root] + + +def getSarRadiometricCalibration(available_app, original_dom_document): + # TODO ** before doing anything, check support for SAR data in Qgis + the_root = original_dom_document + defaultWrite(available_app, the_root) + return [the_root] + + +def getSmoothing(available_app, original_dom_document): + """ + Split by type (anidif, gaussian, mean) + """ + + #import copy + #the_root = copy.deepcopy(original_dom_document) + #remove_dependant_choices(the_root, 'type', 'anidif') + #remove_other_choices(the_root, 'type', 'anidif') + #defaultWrite('%s-anidif' % available_app, the_root) + + #the_root = copy.deepcopy(original_dom_document) + #remove_independant_choices(the_root, 'type', 'anidif') + #remove_choice(the_root, 'type', 'anidif') + #defaultWrite(available_app, the_root) + + the_root = original_dom_document + splitted = split_by_choice(the_root, 'type') + the_list = [] + for key in splitted: + defaultWrite('%s-%s' % (available_app, key), splitted[key]) + the_list.append(splitted[key]) + + return the_list + #splitted = split_by_choice(the_root, 'type') + #the_list = [] + #for key in splitted: + # defaultWrite('%s-%s' % (available_app, key), splitted[key]) + # the_list.append(splitted[key]) + #return the_list + +def getColorMapping(available_app, original_dom_document): + """ + Remove the option colortolabel + Split by method : custom, continous, optimal and image and adapt parameters of each resulting app + """ + the_root = original_dom_document + remove_independant_choices(the_root, 'op', 'colortolabel') + remove_choice(the_root, 'op', 'colortolabel') + splitted = split_by_choice(the_root, 'method') + the_list = [] + for key in splitted: + if key == 'custom': + the_doc = splitted[key] + remove_parameter_by_key(the_doc, 'method.continuous.lut') + remove_parameter_by_key(the_doc, 'method.continuous.min') + remove_parameter_by_key(the_doc, 'method.continuous.max') + remove_parameter_by_key(the_doc, 'method.optimal.background') + remove_parameter_by_key(the_doc, 'method.image.in') + remove_parameter_by_key(the_doc, 'method.image.low') + remove_parameter_by_key(the_doc, 'method.image.up') + defaultWrite('%s-%s' % (available_app, key), the_doc) + the_list.append(the_doc) + elif key == 'continuous': + the_doc = splitted[key] + remove_parameter_by_key(the_doc, 'method.custom.lut') + remove_parameter_by_key(the_doc, 'method.optimal.background') + remove_parameter_by_key(the_doc, 'method.image.in') + remove_parameter_by_key(the_doc, 'method.image.low') + remove_parameter_by_key(the_doc, 'method.image.up') + defaultWrite('%s-%s' % (available_app, key), the_doc) + the_list.append(the_doc) + elif key == 'optimal': + the_doc = splitted[key] + remove_parameter_by_key(the_doc, 'method.custom.lut') + remove_parameter_by_key(the_doc, 'method.continuous.lut') + remove_parameter_by_key(the_doc, 'method.continuous.min') + remove_parameter_by_key(the_doc, 'method.continuous.max') + remove_parameter_by_key(the_doc, 'method.image.in') + remove_parameter_by_key(the_doc, 'method.image.low') + remove_parameter_by_key(the_doc, 'method.image.up') + defaultWrite('%s-%s' % (available_app, key), the_doc) + the_list.append(the_doc) + else: + #key == 'image' + the_doc = splitted[key] + remove_parameter_by_key(the_doc, 'method.custom.lut') + remove_parameter_by_key(the_doc, 'method.continuous.lut') + remove_parameter_by_key(the_doc, 'method.continuous.min') + remove_parameter_by_key(the_doc, 'method.continuous.max') + remove_parameter_by_key(the_doc, 'method.optimal.background') + defaultWrite('%s-%s' % (available_app, key), the_doc) + the_list.append(splitted[key]) + return the_list + + + +def getFusionOfClassifications(available_app, original_dom_document): + """ + Split by method of fusion of classification (dempstershafer, majorityvoting) + """ + the_root = original_dom_document + splitted = split_by_choice(the_root, 'method') + the_list = [] + for key in splitted: + defaultWrite('%s-%s' % (available_app, key), splitted[key]) + the_list.append(splitted[key]) + return the_list + + +def getTrainImagesClassifier(available_app, original_dom_document): + """ + Split by classifier (ann, bayes, boost, dt, gbt, knn, libsvm, rf, svm) + Delete GEOID and DEM parameter as they are not updated at the creation of the otb algorithms when you launch QGIS. + The values are picked from the settings. + """ + the_root = original_dom_document + deleteGeoidSrtm(the_root) + splitted = split_by_choice(the_root, 'classifier') + the_list = [] + for key in splitted: + defaultWrite('%s-%s' % (available_app, key), splitted[key]) + the_list.append(splitted[key]) + return the_list + + + +def getLineSegmentDetection(available_app, original_dom_document): + """ + Delete GEOID and DEM parameter as they are not updated at the creation of the otb algorithms when you launch QGIS. + The values are picked from the settings. + """ + the_root = original_dom_document + remove_parameter_by_key(the_root, 'elev.default') + remove_parameter_by_key(the_root, 'elev.geoid') + remove_parameter_by_key(the_root, 'elev.dem') + defaultWrite(available_app, the_root) + return [the_root] + + + +def getImageEnvelope(available_app, original_dom_document): + """ + Delete GEOID and DEM parameter as they are not updated at the creation of the otb algorithms when you launch QGIS. + The values are picked from the settings. + """ + the_root = original_dom_document + remove_parameter_by_key(the_root, 'elev.default') + remove_parameter_by_key(the_root, 'elev.geoid') + remove_parameter_by_key(the_root, 'elev.dem') + defaultWrite(available_app, the_root) + return [the_root] + + +def getReadImageInfo(available_app, original_dom_document): + """ + Remove parameters that are output of the application. + """ + the_root = original_dom_document + remove_parameter_by_key(the_root, 'outkwl') + remove_parameter_by_key(the_root, 'indexx') + remove_parameter_by_key(the_root, 'indexy') + remove_parameter_by_key(the_root, 'sizex') + remove_parameter_by_key(the_root, 'sizey') + remove_parameter_by_key(the_root, 'spacingx') + remove_parameter_by_key(the_root, 'spacingy') + remove_parameter_by_key(the_root, 'originx') + remove_parameter_by_key(the_root, 'originy') + remove_parameter_by_key(the_root, 'estimatedgroundspacingx') + remove_parameter_by_key(the_root, 'estimatedgroundspacingy') + remove_parameter_by_key(the_root, 'numberbands') + remove_parameter_by_key(the_root, 'sensor') + remove_parameter_by_key(the_root, 'id') + remove_parameter_by_key(the_root, 'time') + remove_parameter_by_key(the_root, 'ullat') + remove_parameter_by_key(the_root, 'ullon') + remove_parameter_by_key(the_root, 'urlat') + remove_parameter_by_key(the_root, 'urlon') + remove_parameter_by_key(the_root, 'lrlat') + remove_parameter_by_key(the_root, 'lrlon') + remove_parameter_by_key(the_root, 'lllat') + remove_parameter_by_key(the_root, 'lllon') + remove_parameter_by_key(the_root, 'town') + remove_parameter_by_key(the_root, 'country') + remove_parameter_by_key(the_root, 'rgb.r') + remove_parameter_by_key(the_root, 'rgb.g') + remove_parameter_by_key(the_root, 'rgb.b') + remove_parameter_by_key(the_root, 'projectionref') + remove_parameter_by_key(the_root, 'keyword') + remove_parameter_by_key(the_root, 'gcp.count') + remove_parameter_by_key(the_root, 'gcp.proj') + defaultWrite(available_app, the_root) + return [the_root] + + + +def getComputeModulusAndPhase(available_app, original_dom_document): + """ + Split the application according the field nbinput. + For each of the resulting apps, give a new name. + """ + the_root = original_dom_document + splitted = split_by_choice(the_root, 'nbinput') + the_list = [] + for key in splitted: + if key == 'one': + the_doc = splitted[key] + old_app_name = the_doc.find('key').text + the_doc.find('key').text = '%s-%s' % (old_app_name, 'OneEntry') + old_longname = the_doc.find('longname').text + the_doc.find('longname').text = '%s (%s)' % (old_app_name, 'OneEntry') + defaultWrite('%s-%s' % (available_app, 'OneEntry'), the_doc) + the_list.append(the_doc) + else : + the_doc = splitted[key] + old_app_name = the_doc.find('key').text + the_doc.find('key').text = '%s-%s' % (old_app_name, 'TwoEntries') + old_longname = the_doc.find('longname').text + the_doc.find('longname').text = '%s (%s)' % (old_app_name, 'TwoEntries') + defaultWrite('%s-%s' % (available_app, 'TwoEntries'), the_doc) + the_list.append(the_doc) + return the_list + + +def getCompareImages(available_app, original_dom_document): + """ + Remove mse, mae, psnr as they are output of the algorithm. + """ + the_root = original_dom_document + remove_parameter_by_key(the_root, 'mse') + remove_parameter_by_key(the_root, 'mae') + remove_parameter_by_key(the_root, 'psnr') + defaultWrite(available_app, the_root) + return [the_root] + + +def getRadiometricIndices(available_app, original_dom_document): + """ + These 3 indices are missing. Remove them from the list. + """ + the_root = original_dom_document + remove_choice(the_root, 'list', 'laindvilog') + remove_choice(the_root, 'list', 'lairefl') + remove_choice(the_root, 'list', 'laindviformo') + defaultWrite(available_app, the_root) + return [the_root] + + +def getConnectedComponentSegmentation(available_app, original_dom_document): + """ + Delete GEOID and DEM parameter as they are not updated at the creation of the otb algorithms when you launch QGIS. + The values are picked from the settings. + """ + the_root = original_dom_document + deleteGeoidSrtm( the_root ) + defaultWrite(available_app, the_root) + return [the_root] + + +def getKmzExport(available_app, original_dom_document): + """ + Delete GEOID and DEM parameter as they are not updated at the creation of the otb algorithms when you launch QGIS. + The values are picked from the settings. + """ + the_root = original_dom_document + deleteGeoidSrtm( the_root ) + defaultWrite(available_app, the_root) + return [the_root] + + +def getSuperimpose(available_app, original_dom_document): + """ + Delete GEOID and DEM parameter as they are not updated at the creation of the otb algorithms when you launch QGIS. + The values are picked from the settings. + """ + the_root = original_dom_document + deleteGeoidSrtm( the_root ) + defaultWrite(available_app, the_root) + return [the_root] + + +def getStereoFramework(available_app, original_dom_document): + """ + Delete GEOID and DEM parameter as they are not updated at the creation of the otb algorithms when you launch QGIS. + The values are picked from the settings. + """ + the_root = original_dom_document + deleteGeoidSrtm( the_root ) + defaultWrite(available_app, the_root) + return [the_root] + + + +def deleteGeoidSrtm(doc) : + """ + Delete GEOID and DEM parameter as they are not updated at the creation of the otb algorithms when you launch QGIS. + The values are picked from the settings. + """ + t4 = [item for item in doc.findall('.//parameter') if item.find('key').text.endswith("elev.geoid")] + for t5 in t4: + doc.remove(t5) + + t4 = [item for item in doc.findall('.//parameter') if item.find('key').text.endswith("elev.dem")] + for t5 in t4: + doc.remove(t5) diff --git a/python/plugins/processing/otb/maintenance/OTBTester.py b/python/plugins/processing/otb/maintenance/OTBTester.py new file mode 100644 index 000000000000..9701df546df4 --- /dev/null +++ b/python/plugins/processing/otb/maintenance/OTBTester.py @@ -0,0 +1,432 @@ +# -*- coding: utf-8 -*- + +""" +*************************************************************************** + OTBTester.py + --------------------- + Copyright : (C) 2013 by CS Systemes d'information (CS SI) + Email : otb at c-s dot fr (CS SI) + Contributors : Julien Malik (CS SI) + Oscar Picas (CS SI) +*************************************************************************** +* * +* This program is free software; you can redistribute it and/or modify * +* it under the terms of the GNU General Public License as published by * +* the Free Software Foundation; either version 2 of the License, or * +* (at your option) any later version. * +* * +*************************************************************************** +""" +__author__ = 'Julien Malik, Oscar Picas' +__copyright__ = '(C) 2013, CS Systemes d\'information (CS SI)' +# This will get replaced with a git SHA1 when you do a git archive +__revision__ = '$Format:%H$' + +import unittest +import ConfigParser +import io + +from parsing import ( + File, Command, Comment, BlankLine, Arg, parse, prettify) + +from string import Template +import os +import traceback +import logging +import copy + +from ConfigParser import SafeConfigParser + +from processing.otb.OTBHelper import get_OTB_log + +class LowerTemplate(Template): + def safe_substitute(self, param): + ret = super(LowerTemplate, self).safe_substitute(param).lower() + return ret + +class MakefileParser(object): + def __init__(self): + self.maxDiff = None + self.parser = SafeConfigParser() + self.parser.read('otbcfg.ini') + if not os.path.exists('otbcfg.ini'): + raise Exception("OTB_SOURCE_DIR and OTB_BINARY_DIR must be specified in the file otbcfg.ini") + + self.root_dir = self.parser.get('otb','checkout_dir') + if not os.path.exists(self.root_dir): + raise Exception("Check otbcfg.ini : OTB_SOURCE_DIR and OTB_BINARY_DIR must be specified there") + self.build_dir = self.parser.get('otb', 'build_dir') + if not os.path.exists(self.build_dir): + raise Exception("Check otbcfg.ini : OTB_SOURCE_DIR and OTB_BINARY_DIR must be specified there") + self.logger = get_OTB_log() + + def test_CMakelists(self): + provided = {} + provided["OTB_SOURCE_DIR"] = self.root_dir + provided["OTB_BINARY_DIR"] = self.build_dir + provided["OTB_DATA_LARGEINPUT_ROOT"] = os.path.normpath(os.path.join(self.root_dir, "../OTB-Data/Input")) + + try: + with open(os.path.join(self.root_dir, "CMakeLists.txt")) as file_input: + content = file_input.read() + output = parse(content) + + defined_paths = [each for each in output if 'Command' in str(type(each)) and "FIND_PATH" in each.name] + the_paths = {key.body[0].contents: [thing.contents for thing in key.body[1:]] for key in defined_paths} + + the_sets = [each for each in output if 'Command' in str(type(each)) and "SET" in each.name.upper()] + the_sets = {key.body[0].contents: [thing.contents for thing in key.body[1:]] for key in the_sets} + the_sets = {key : " ".join(the_sets[key]) for key in the_sets} + + the_strings = set([each.body[-1].contents for each in output if 'Command' in str(type(each)) and "STRING" in each.name.upper()] ) + + def mini_clean(item): + if item.startswith('"') and item.endswith('"') and " " not in item: + return item[1:-1] + return item + + the_sets = {key : mini_clean(the_sets[key]) for key in the_sets} + + def templatize(item): + if "$" in item: + return Template(item) + return item + + for key in the_sets: + if key in the_strings: + the_sets[key] = the_sets[key].lower() + + the_sets = {key : templatize(the_sets[key]) for key in the_sets} + + for path in the_paths: + target_file = the_paths[path][1] + suggested_paths = [] + if len(the_paths[path]) > 2: + suggested_paths = the_paths[path][2:] + + try: + provided[path] = find_file(target_file) + except Exception, e: + for each in suggested_paths: + st = Template(each) + pac = os.path.abspath(st.safe_substitute(provided)) + if os.path.exists(pac): + provided[path] = pac + break + + resolve_dict(provided, the_sets) + provided.update(the_sets) + + return provided + except Exception, e: + traceback.print_exc() + self.fail(e.message) + + def add_make(self, previous_context, new_file): + input = open(new_file).read() + output = parse(input) + apps = [each for each in output if 'Command' in str(type(each))] + setcommands = [each for each in apps if 'SET' in each.name.upper()] + stringcommands = [each for each in apps if 'STRING' in each.name.upper()] + + environment = previous_context + + def mini_clean(item): + if item.startswith('"') and item.endswith('"') and " " not in item: + return item[1:-1] + return item + + new_env = {} + for command in setcommands: + key = command.body[0].contents + ct = " ".join([item.contents for item in command.body[1:]]) + ct = mini_clean(ct) + + if "$" in ct: + values = Template(ct) + else: + values = ct + + new_env[key] = values + + for stringcommand in stringcommands: + key = stringcommand.body[-1].contents + ct = stringcommand.body[-2].contents + ct = mini_clean(ct.lower()) + + if "$" in ct: + values = LowerTemplate(ct) + else: + values = ct + new_env[key] = values + + resolve_dict(environment, new_env) + environment.update(new_env) + + return environment + + def get_apps(self, the_makefile, the_dict): + input = open(the_makefile).read() + output = parse(input) + apps = [each for each in output if 'Command' in str(type(each))] + otb_apps = [each for each in apps if 'OTB_TEST_APPLICATION' in each.name.upper()] + return otb_apps + + def get_tests(self, the_makefile, the_dict): + input = open(the_makefile).read() + output = parse(input) + apps = [each for each in output if 'Command' in str(type(each))] + otb_tests = [each for each in apps if 'ADD_TEST' in each.name.upper()] + return otb_tests + + def get_apps_with_context(self, the_makefile, the_dict): + input = open(the_makefile).read() + output = parse(input) + + def is_a_command(item): + return 'Command' in str(type(item)) + + appz = [] + context = [] + for each in output: + if is_a_command(each): + if 'FOREACH' in each.name and 'ENDFOREACH' not in each.name: + args = [item.contents for item in each.body] + context.append(args) + elif 'ENDFOREACH' in each.name: + context.pop() + elif 'OTB_TEST_APPLICATION' in each.name.upper(): + appz.append((each, context[:])) + return appz + + def get_name_line(self, the_list, the_dict): + items = ('NAME', 'APP', 'OPTIONS', 'TESTENVOPTIONS', 'VALID') + itemz = [[], [], [], [], []] + last_index = 0 + for each in the_list: + if each.contents in items: + last_index = items.index(each.contents) + else: + itemz[last_index].append(each.contents) + result = itemz[0][0] + the_string = Template(result).safe_substitute(the_dict) + + if '$' in the_string: + neo_dict = the_dict + the_string = Template(the_string).safe_substitute(neo_dict) + while '$' in the_string: + try: + the_string = Template(the_string).substitute(neo_dict) + except KeyError, e: + self.logger.warning("Key %s is not found in makefiles" % e.message) + neo_dict[e.message] = "" + + if 'string.Template' in the_string: + raise Exception("Unexpected toString call in %s" % the_string) + + return the_string + + def get_command_line(self, the_list, the_dict): + items = ('NAME', 'APP', 'OPTIONS', 'TESTENVOPTIONS', 'VALID') + itemz = [[], [], [], [], []] + last_index = 0 + for each in the_list: + if each.contents in items: + last_index = items.index(each.contents) + else: + itemz[last_index].append(each.contents) + result = [] + result.extend(["otbcli_%s" % each for each in itemz[1]]) + + if len(result[0]) == 7: + raise Exception("App name is empty !") + + result.extend(itemz[2]) + result.append("-testenv") + result.extend(itemz[3]) + the_string = Template(" ".join(result)).safe_substitute(the_dict) + + if '$' in the_string: + neo_dict = the_dict + the_string = Template(" ".join(result)).safe_substitute(neo_dict) + while '$' in the_string: + try: + the_string = Template(the_string).substitute(neo_dict) + except KeyError, e: + self.logger.warning("Key %s is not found in makefiles" % e.message) + neo_dict[e.message] = "" + + if 'string.Template' in the_string: + raise Exception("Unexpected toString call in %s" % the_string) + + return the_string + + def get_test(self, the_list, the_dict): + items = ('NAME', 'APP', 'OPTIONS', 'TESTENVOPTIONS', 'VALID') + itemz = [[], [], [], [], []] + last_index = 0 + for each in the_list: + if each.contents in items: + last_index = items.index(each.contents) + else: + itemz[last_index].append(each.contents) + result = ["otbTestDriver"] + result.extend(itemz[4]) + + if len(result) == 1: + return "" + + the_string = Template(" ".join(result)).safe_substitute(the_dict) + + if '$' in the_string: + neo_dict = the_dict + the_string = Template(" ".join(result)).safe_substitute(neo_dict) + while '$' in the_string: + try: + the_string = Template(the_string).substitute(neo_dict) + except KeyError, e: + self.logger.warning("Key %s is not found in makefiles" % e.message) + neo_dict[e.message] = "" + + if 'string.Template' in the_string: + raise Exception("Unexpected toString call in %s" % the_string) + + return the_string + + def test_algos(self): + tests = {} + + algos_dir = os.path.join(self.root_dir, "Testing/Applications") + makefiles = find_files("CMakeLists.txt", algos_dir) + to_be_excluded = os.path.join(self.root_dir, "Testing/Applications/CMakeLists.txt") + if to_be_excluded in makefiles: + makefiles.remove(to_be_excluded) + + resolve_algos = {} + for makefile in makefiles: + intermediate_makefiles = [] + path = makefile.split(os.sep)[len(self.root_dir.split(os.sep)):-1] + for ind in range(len(path)): + tmp_path = path[:ind+1] + tmp_path.append("CMakeLists.txt") + tmp_path = os.sep.join(tmp_path) + candidate_makefile = os.path.join(self.root_dir, tmp_path) + if os.path.exists(candidate_makefile): + intermediate_makefiles.append(candidate_makefile) + resolve_algos[makefile] = intermediate_makefiles + + dict_for_algo = {} + for makefile in makefiles: + basic = self.test_CMakelists() + last_context = self.add_make(basic, os.path.join(self.root_dir, "Testing/Utilities/CMakeLists.txt")) + for intermediate_makefile in resolve_algos[makefile]: + last_context = self.add_make(last_context, intermediate_makefile) + dict_for_algo[makefile] = last_context + + for makefile in makefiles: + appz = self.get_apps_with_context(makefile, dict_for_algo[makefile]) + + for app, context in appz: + if len(context) == 0: + import copy + ddi = copy.deepcopy(dict_for_algo[makefile]) + tk_dict = autoresolve(ddi) + tk_dict = autoresolve(tk_dict) + + name_line = self.get_name_line(app.body, tk_dict) + command_line = self.get_command_line(app.body, tk_dict) + test_line = self.get_test(app.body, tk_dict) + + if '$' in test_line or '$' in command_line: + if '$' in command_line: + self.logger.error(command_line) + if '$' in test_line: + self.logger.warning(test_line) + else: + tests[name_line] = (command_line, test_line) + else: + contexts = {} + for iteration in context: + key = iteration[0] + values = [each[1:-1].lower() for each in iteration[1:]] + contexts[key] = values + + keyorder = contexts.keys() + import itertools + pool = [each for each in itertools.product(*contexts.values())] + + import copy + for poolinstance in pool: + neo_dict = copy.deepcopy(dict_for_algo[makefile]) + zipped = zip(keyorder, poolinstance) + for each in zipped: + neo_dict[each[0]] = each[1] + + ak_dict = autoresolve(neo_dict) + ak_dict = autoresolve(ak_dict) + ak_dict = autoresolve(ak_dict) + + ddi = ak_dict + + name_line = self.get_name_line(app.body, ddi) + command_line = self.get_command_line(app.body, ddi) + test_line = self.get_test(app.body, ddi) + + if '$' in command_line or '$' not in test_line: + if '$' in command_line: + self.logger.error(command_line) + if '$' in test_line: + self.logger.warning(test_line) + else: + tests[name_line] = (command_line, test_line) + + return tests + +def autoresolve(a_dict): + def as_template(item, b_dict): + if hasattr(item, 'safe_substitute'): + return item.safe_substitute(b_dict) + ate = Template(item) + return ate.safe_substitute(b_dict) + templatized = {key: as_template(a_dict[key], a_dict) for key in a_dict.keys() } + return templatized + + +def find_file(file_name, base_dir = os.curdir): + import os + for root, dirs, files in os.walk(base_dir, topdown=False): + for name in files: + if name == file_name: + return os.path.join(root, name) + raise Exception("File not found %s" % file_name) + +def find_files(file_name, base_dir = os.curdir): + import os + result = [] + for root, dirs, files in os.walk(base_dir, topdown=False): + for name in files: + if name == file_name: + result.append(os.path.join(root, name)) + return result + +def resolve_dict(adia, adib): + init = len(adia) + fin = len(adia) + 1 + def _resolve_dict(dia, dib): + for key in dib: + cand_value = dib[key] + if hasattr(cand_value, 'safe_substitute'): + value = cand_value.safe_substitute(dia) + if type(value) == type(".") and "$" not in value: + dia[key] = value + else: + dia[key] = cand_value + for key in dia: + if key in dib: + del dib[key] + + while(init != fin): + init = len(adia) + _resolve_dict(adia, adib) + fin = len(adia) + diff --git a/python/plugins/processing/otb/maintenance/README b/python/plugins/processing/otb/maintenance/README new file mode 100644 index 000000000000..dfadf450ae21 --- /dev/null +++ b/python/plugins/processing/otb/maintenance/README @@ -0,0 +1,11 @@ + +Requirement +1) qgis +2) sextante_taudem (TauDEM-1.1.1.zip) +3) sextante (sextante-1.0.9.zip) +4) PYTHONPATH=.:/usr/lib/otb/python:/usr/share/qgis/python/plugins:~/.qgis2/python/plugins +5) ITK_AUTOLOAD_PATH=/usr/lib/otb/applications + +Creating xml files +cd .qgis2/python/plugin/sextante/otb/maintenance +python ./OTBHelper.py diff --git a/python/plugins/processing/otb/maintenance/TestOTBAlgorithms.py b/python/plugins/processing/otb/maintenance/TestOTBAlgorithms.py new file mode 100644 index 000000000000..b3a37ccef0e8 --- /dev/null +++ b/python/plugins/processing/otb/maintenance/TestOTBAlgorithms.py @@ -0,0 +1,202 @@ +# -*- coding: utf-8 -*- + +""" +*************************************************************************** + TestOTBAlgorithms.py + --------------------- + Copyright : (C) 2013 by CS Systemes d'information + Email : otb at c-s dot fr + Contributors : Oscar Picas +*************************************************************************** +* * +* This program is free software; you can redistribute it and/or modify * +* it under the terms of the GNU General Public License as published by * +* the Free Software Foundation; either version 2 of the License, or * +* (at your option) any later version. * +* * +*************************************************************************** +""" + +# This will get replaced with a git SHA1 when you do a git archive +__revision__ = '$Format:%H$' + +import unittest +import signal +import sys +import os +import traceback +import xml.etree.ElementTree as ET +import shlex, subprocess +import shelve + +try: + import processing +except ImportError, e: + raise Exception("Processing must be installed and available in PYTHONPATH") + +try: + import otbApplication +except ImportError, e: + raise Exception("OTB python plugins must be installed and available in PYTHONPATH") + +from processing.otb.OTBAlgorithm import OTBAlgorithm +from processing.otb.OTBHelper import * +from processing.otb.OTBTester import MakefileParser + +class Alarm(Exception): + pass + +def alarm_handler(signum, frame): + raise Alarm + +class AlgoTestCase(unittest.TestCase): + def setUp(self): + self.logger = get_OTB_log() + self.the_files = [os.path.join(os.path.join(os.path.abspath(os.curdir), 'description'),each) for each in os.listdir(os.path.join(os.path.abspath(os.curdir), 'description')) if '.xml' in each] + + def tearDown(self): + self.logger = None + +class TestSequence(unittest.TestCase): + def setUp(self): + self.data = shelve.open("tests.shelve",writeback=True) + + def tearDown(self): + self.data.close() + +def ut_generator(test_name, a_tuple): + def test(self): + logger = get_OTB_log() + + needs_update = False + if test_name not in self.data: + needs_update = True + if test_name in self.data: + if (self.data[test_name][0] != a_tuple[0]) or (self.data[test_name][1] != a_tuple[1]) or (self.data[test_name][2] is False): + needs_update = True + + if needs_update: + signal.signal(signal.SIGALRM, alarm_handler) + signal.alarm(6*60) # 6 minutes + + black_list = [] + + ut_command = a_tuple[0] + self.assertTrue(ut_command != None) + self.assertTrue(ut_command != "") + + ut_command_validation = a_tuple[1] + self.assertTrue(ut_command_validation != None) + self.assertTrue(ut_command_validation != "") + + if ut_command.split(" ")[0] in black_list: + raise Exception("Blacklisted test !") + + args = shlex.split(ut_command) + failed = False + logger.info("Running [%s]" % ut_command) + p = subprocess.Popen(args, stdout=subprocess.PIPE, stderr=subprocess.PIPE) + (pout, perr) = p.communicate() + if ("ERROR" in pout or "ERROR" in perr) or ("FATAL" in pout or "FATAL" in perr) or ("CRITICAL" in pout or "CRITICAL" in perr): + error_text = "Command [%s] returned [%s]" % (ut_command, pout) + if "Invalid image filename" in pout or "Invalid vector data filename" in pout or "Failed to open" in pout: + logger.warning(error_text) + else: + logger.error(error_text) + self.fail(error_text) + failed = True + else: + logger.info(pout) + + if (len(ut_command_validation) > 0) and not failed: + new_ut_command_validation = ut_command_validation + " Execute " + ut_command + + logger.info("Running Unit test [%s]" % new_ut_command_validation) + argz = shlex.split(new_ut_command_validation) + q = subprocess.Popen(argz, stdout=subprocess.PIPE, stderr=subprocess.PIPE) + (qout, qerr) = q.communicate() + + if not ("Test EXIT SUCCESS" in qout or "Test EXIT SUCCESS" in qerr): + error_text = "Unit test [%s] returned [%s]" % (new_ut_command_validation, qout) + if "Invalid image filename" in qout or "Invalid vector data filename" in qout or "Failed to open" in qout: + logger.warning(error_text) + else: + logger.error(error_text) + self.fail(error_text) + else: + logger.info(qout) + + signal.alarm(0) + self.data[test_name] = [ a_tuple[0], a_tuple[1], failed ] + else: + logger.info("Passed test: %s" % test_name) + + + return test + +def get_client_apps(): + app_clients = [] + for available_app in otbApplication.Registry.GetAvailableApplications(): + app_instance = otbApplication.Registry.CreateApplication(available_app) + app_instance.UpdateParameters() + ct = "otbcli_" + available_app + app_clients.append(ct) + return app_clients + +def unfiltered_processing_mapping(): + mkf = MakefileParser() + the_tests = mkf.test_algos() + for t in the_tests: + test_name = 'test_std_%s' % t + if the_tests[t][1] is None: + skip = True + else: + if the_tests[t][1] == "": + skip = True + + if not skip: + test = ut_generator(test_name, the_tests[t]) + setattr(TestSequence, test_name, test) + + suite = unittest.TestLoader().loadTestsFromTestCase(TestSequence) + unittest.TextTestRunner(verbosity=2).run(suite) + +def test_processing_mapping(): + mkf = MakefileParser() + the_tests = mkf.test_algos() + clients = get_client_apps() + + already_tested = set() + + for t in the_tests: + test_name = 'test_%s' % t + if the_tests[t][0].split(" ")[0] in clients: + skip = False + if the_tests[t][1] is None: + skip = True + else: + if the_tests[t][1] == "": + skip = True + + if not skip: + runnable = the_tests[t][0].split(" ")[0] + if runnable not in already_tested: + test = ut_generator(test_name, the_tests[t]) + setattr(TestSequence, test_name, test) + already_tested.add(runnable) + + suite = unittest.TestLoader().loadTestsFromTestCase(TestSequence) + unittest.TextTestRunner(verbosity=2).run(suite) + +def test_xml_generation(): + create_xml_descriptors() + +if __name__ == '__main__': + import processing + mkf = MakefileParser() + the_tests = mkf.test_algos() + for t in the_tests: + test_name = 'test_%s' % t + test = ut_generator(test_name, the_tests[t]) + setattr(TestSequence, test_name, test) + unittest.main() diff --git a/python/plugins/processing/otb/maintenance/black_list.xml b/python/plugins/processing/otb/maintenance/black_list.xml new file mode 100644 index 000000000000..3bf5707c70dd --- /dev/null +++ b/python/plugins/processing/otb/maintenance/black_list.xml @@ -0,0 +1,45 @@ + + + + HomologousPointsExtraction + GenerateRPCSensorModel + RefineSensorModel + Quicklook + PixelValue + + + SarRadiometricCalibration + PixelValue + Quicklook + ConvertCartoToGeoPoint + ConvertSensorToGeoPoint + ObtainUTMZoneFromGeoPoint + BundleToPerfectSensor + Example + ComputePolylineFeatureFromImage + DSFuzzyModelEstimation + HomologousPointsExtraction + SFSTextureExtraction + VectorDataDSValidation + GenerateRPCSensorModel + GridBasedImageResampling + GeneratePlyFile + RefineSensorModel + MultiResolutionPyramid + HyperspectralUnmixing + OSMDownloader + VertexComponentAnalysis + Rasterization + VectorDataTransform + VectorDataReprojection + VectorDataSetField + VectorDataExtractROIApplication + Convert + DownloadSRTMTiles + DisparityMapToElevationMap + FineRegistration + StereoRectificationGridGenerator + BlockMatching + SplitImage + + diff --git a/python/plugins/processing/otb/maintenance/parsing.py b/python/plugins/processing/otb/maintenance/parsing.py new file mode 100644 index 000000000000..18a6e294b3f8 --- /dev/null +++ b/python/plugins/processing/otb/maintenance/parsing.py @@ -0,0 +1,172 @@ +# -*- coding: utf-8 -*- + +""" +*************************************************************************** + parsing.py + --------------------- + Copyright : (C) 2013 by CS Systemes d'information (CS SI) + Email : otb at c-s dot fr (CS SI) + Contributors : Julien Malik (CS SI) + Oscar Picas (CS SI) +*************************************************************************** +* * +* This program is free software; you can redistribute it and/or modify * +* it under the terms of the GNU General Public License as published by * +* the Free Software Foundation; either version 2 of the License, or * +* (at your option) any later version. * +* * +*************************************************************************** +""" +__author__ = 'Julien Malik, Oscar Picas' +__copyright__ = '(C) 2013, CS Systemes d\'information (CS SI)' + +from collections import namedtuple +import re +import os + +def merge_pairs(list, should_merge, merge): + """ + Merges adjacent elements of list using the function merge + if they satisfy the predicate should_merge. + """ + ret = [] + i = 0 + while i < len(list) - 1: + a = list[i] + b = list[i + 1] + if should_merge(a, b): + ret.append(merge(a, b)) + i += 2 + else: + ret.append(a) + i += 1 + if i == len(list) - 1: + ret.append(list[i]) + return ret + +QuotedString = namedtuple('QuotedString', 'contents comments') +_Arg = namedtuple('Arg', 'contents comments') +_Command = namedtuple('Command', 'name body comment') +BlankLine = namedtuple('BlankLine', '') + +class File(list): + def __repr__(self): + return 'File(' + repr(list(self)) + ')' + +class Comment(str): + def __repr__(self): + return 'Comment(' + str(self) + ')' + +def Arg(contents, comments=None): + return _Arg(contents, comments or []) + +def Command(name, body, comment=None): + return _Command(name, body, comment) + +class CMakeParseError(Exception): + pass + +def prettify(s): + """ + Returns the pretty-print of the contents of a CMakeLists file. + """ + return str(parse(s)) + +def parse(s): + ''' + Parses a string s in CMakeLists format whose + contents are assumed to have come from the + file at the given path. + ''' + nums_toks = tokenize(s) + nums_items = list(parse_file(nums_toks)) + nums_items = attach_comments_to_commands(nums_items) + items = [item for _, item in nums_items] + return File(items) + +def parse_file(toks): + ''' + Yields line number ranges and top-level elements of the syntax tree for + a CMakeLists file, given a generator of tokens from the file. + + toks must really be a generator, not a list, for this to work. + ''' + prev_type = 'newline' + for line_num, (typ, tok_contents) in toks: + if typ == 'comment': + yield ([line_num], Comment(tok_contents)) + elif typ == 'newline' and prev_type == 'newline': + yield ([line_num], BlankLine()) + elif typ == 'word': + line_nums, cmd = parse_command(line_num, tok_contents, toks) + yield (line_nums, cmd) + prev_type = typ + +def attach_comments_to_commands(nodes): + return merge_pairs(nodes, command_then_comment, attach_comment_to_command) + +def command_then_comment(a, b): + line_nums_a, thing_a = a + line_nums_b, thing_b = b + return (isinstance(thing_a, _Command) and + isinstance(thing_b, Comment) and + set(line_nums_a).intersection(line_nums_b)) + +def attach_comment_to_command(lnums_command, lnums_comment): + command_lines, command = lnums_command + _, comment = lnums_comment + return command_lines, Command(command.name, command.body[:], comment) + +def parse_command(start_line_num, command_name, toks): + cmd = Command(name=command_name, body=[], comment=None) + expect('left paren', toks) + for line_num, (typ, tok_contents) in toks: + if typ == 'right paren': + line_nums = range(start_line_num, line_num + 1) + return line_nums, cmd + elif typ == 'left paren': + raise ValueError('Unexpected left paren at line %s' % line_num) + elif typ in ('word', 'string'): + cmd.body.append(Arg(tok_contents, [])) + elif typ == 'comment': + c = tok_contents + if cmd.body: + cmd.body[-1].comments.append(c) + else: + cmd.comments.append(c) + msg = 'File ended while processing command "%s" started at line %s' % ( + command_name, start_line_num) + raise CMakeParseError(msg) + +def expect(expected_type, toks): + line_num, (typ, tok_contents) = toks.next() + if typ != expected_type: + msg = 'Expected a %s, but got "%s" at line %s' % ( + expected_type, tok_contents, line_num) + raise CMakeParseError(msg) + +# http://stackoverflow.com/questions/691148/pythonic-way-to-implement-a-tokenizer +scanner = re.Scanner([ + (r'#.*', lambda scanner, token: ("comment", token)), + (r'"[^"]*"', lambda scanner, token: ("string", token)), + (r"\(", lambda scanner, token: ("left paren", token)), + (r"\)", lambda scanner, token: ("right paren", token)), + (r'[^ \t\r\n()#"]+', lambda scanner, token: ("word", token)), + (r'\n', lambda scanner, token: ("newline", token)), + (r"\s+", None), # skip other whitespace +]) + +def tokenize(s): + """ + Yields pairs of the form (line_num, (token_type, token_contents)) + given a string containing the contents of a CMakeLists file. + """ + toks, remainder = scanner.scan(s) + line_num = 1 + if remainder != '': + msg = 'Unrecognized tokens at line %s: %s' % (line_num, remainder) + raise ValueError(msg) + for tok_type, tok_contents in toks: + yield line_num, (tok_type, tok_contents.strip()) + line_num += tok_contents.count('\n') + diff --git a/python/plugins/processing/otb/maintenance/white_list.xml b/python/plugins/processing/otb/maintenance/white_list.xml new file mode 100644 index 000000000000..5339156d9533 --- /dev/null +++ b/python/plugins/processing/otb/maintenance/white_list.xml @@ -0,0 +1,64 @@ + + + + BinaryMorphologicalOperation + EdgeExtraction + GrayScaleMorphologicalOperation + DimensionalityReduction + Pansharpening + ExtractROI + RigidTransformResample + Segmentation + KMeansClassification + TrainSVMImagesClassifier + ComputeConfusionMatrix + OpticalCalibration + SarRadiometricCalibration + Smoothing + + + MultivariateAlterationDetector + OpticalCalibration + StereoFramework + BinaryMorphologicalOperation + DimensionalityReduction + EdgeExtraction + GrayScaleMorphologicalOperation + LineSegmentDetection + LocalStatisticExtraction + RadiometricIndices + ConnectedComponentSegmentation + MeanShiftSmoothing + Segmentation + BandMath + ColorMapping + CompareImages + ConcatenateImages + ConcatenateVectorData + ExtractROI + KmzExport + ReadImageInfo + Rescale + Smoothing + TileFusion + Pansharpening + ClassificationMapRegularization + ComputeConfusionMatrix + ComputeImagesStatistics + FusionOfClassifications + ImageClassifier + KMeansClassification + SOMClassification + TrainImagesClassifier + ImageEnvelope + OrthoRectification + RigidTransformResample + Superimpose + ComputeModulusAndPhase + HaralickTextureExtraction + HooverCompareSegmentation + LSMSSegmentation + LSMSSmallRegionsMerging + LSMSVectorization + +