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I am trying run an exported QGIS model as Python script from Anaconda.

I followed Executing a standalone QGIS python script on Windows 10, and I get no error of modules, when running this I get no error nor output but some warnings of deprecation

import os, sys # Append QGIS Python library to python search path sys.path.append(r'C:\Program Files\QGIS 3.6\apps\Python37') # Append location of DLLs to current system PATH envrionment variable os.environ['PATH'] += r";C:\Program Files\QGIS 3.6\apps\qgis\python;" print (os.environ['PATH']) from qgis.core import QgsProcessing from qgis.core import QgsProcessingAlgorithm from qgis.core import QgsProcessingMultiStepFeedback from qgis.core import QgsProcessingParameterRasterLayer from qgis.core import QgsProcessingParameterFeatureSink sys.path.append(r'C:\Program Files\QGIS 3.6\apps\qgis\python\plugins') import processing class Trees(QgsProcessingAlgorithm): def initAlgorithm(self, config=None): self.addParameter(QgsProcessingParameterRasterLayer('dsm', 'DSM', defaultValue="Path/dsm.tif")) self.addParameter(QgsProcessingParameterRasterLayer('dtm', 'DTM', defaultValue="Path/dtm.tif")) self.addParameter(QgsProcessingParameterRasterLayer('zone', 'Zone', defaultValue="Path/odm_orthophoto.tif")) self.addParameter(QgsProcessingParameterFeatureSink('Finaltrees', 'FinalTrees', type=QgsProcessing.TypeVectorAnyGeometry, createByDefault=True, defaultValue='Path/finaltrees.shp')) def processAlgorithm(self, parameters, context, model_feedback): # Use a multi-step feedback, so that individual child algorithm progress reports are adjusted for the # overall progress through the model feedback = QgsProcessingMultiStepFeedback(20, model_feedback) results = {} outputs = {} # Heights calculator alg_params = { 'CELLSIZE': None, 'CRS': None, 'EXPRESSION': '\"DSM@1\" - \"DTM@1\"', 'EXTENT': None, 'LAYERS': parameters['dtm'], 'OUTPUT': QgsProcessing.TEMPORARY_OUTPUT } outputs['HeightsCalculator'] = processing.run('qgis:rastercalculator', alg_params, context=context, feedback=feedback, is_child_algorithm=True) feedback.setCurrentStep(1) if feedback.isCanceled(): return {} # NDVI calculator alg_params = { 'CELLSIZE': 0, 'CRS': None, 'EXPRESSION': 'sqrt(256* \"Zone@2\"- 256 * \"Zone@3\")', 'EXTENT': None, 'LAYERS': parameters['dtm'], 'OUTPUT': QgsProcessing.TEMPORARY_OUTPUT } outputs['NdviCalculator'] = processing.run('qgis:rastercalculator', alg_params, context=context, feedback=feedback, is_child_algorithm=True) feedback.setCurrentStep(2) if feedback.isCanceled(): return {} # NDVI Selector alg_params = { 'CELLSIZE': 0, 'CRS': None, 'EXPRESSION': '\"\'Output\' from algorithm \'NDVI calculator\'@1\"> 100', 'EXTENT': None, 'LAYERS': outputs['NdviCalculator']['OUTPUT'], 'OUTPUT': QgsProcessing.TEMPORARY_OUTPUT } outputs['NdviSelector'] = processing.run('qgis:rastercalculator', alg_params, context=context, feedback=feedback, is_child_algorithm=True) feedback.setCurrentStep(3) if feedback.isCanceled(): return {} # Only NDVI alg_params = { 'CELLSIZE': 0, 'CRS': None, 'EXPRESSION': '(\"\'Output\' from algorithm \'NDVI Selector\'@1\" =1)*\"\'Output\' from algorithm \'NDVI Selector\'@1\"', 'EXTENT': None, 'LAYERS': outputs['NdviSelector']['OUTPUT'], 'OUTPUT': QgsProcessing.TEMPORARY_OUTPUT } outputs['OnlyNdvi'] = processing.run('qgis:rastercalculator', alg_params, context=context, feedback=feedback, is_child_algorithm=True) feedback.setCurrentStep(4) if feedback.isCanceled(): return {} # Build virtual raster alg_params = { 'ADD_ALPHA': False, 'ASSIGN_CRS': None, 'INPUT': outputs['OnlyNdvi']['OUTPUT'], 'PROJ_DIFFERENCE': False, 'RESAMPLING': 0, 'RESOLUTION': 1, 'SEPARATE': False, 'SRC_NODATA': '0', 'OUTPUT': QgsProcessing.TEMPORARY_OUTPUT } outputs['BuildVirtualRaster'] = processing.run('gdal:buildvirtualraster', alg_params, context=context, feedback=feedback, is_child_algorithm=True) feedback.setCurrentStep(5) if feedback.isCanceled(): return {} # True NDVI alg_params = { 'CELLSIZE': 0, 'CRS': None, 'EXPRESSION': '(\"Zone@4\" -\"Zone@1\" ) /(\"Zone@4\" +\"Zone@1\" )', 'EXTENT': None, 'LAYERS': parameters['zone'], 'OUTPUT': QgsProcessing.TEMPORARY_OUTPUT } outputs['TrueNdvi'] = processing.run('qgis:rastercalculator', alg_params, context=context, feedback=feedback, is_child_algorithm=True) feedback.setCurrentStep(6) if feedback.isCanceled(): return {} # Polygonize (raster to vector) alg_params = { 'BAND': 1, 'EIGHT_CONNECTEDNESS': False, 'FIELD': 'Value', 'INPUT': outputs['BuildVirtualRaster']['OUTPUT'], 'OUTPUT': QgsProcessing.TEMPORARY_OUTPUT } outputs['PolygonizeRasterToVector'] = processing.run('gdal:polygonize', alg_params, context=context, feedback=feedback, is_child_algorithm=True) feedback.setCurrentStep(7) if feedback.isCanceled(): return {} # Extract by attribute alg_params = { 'FIELD': 'Value', 'INPUT': outputs['PolygonizeRasterToVector']['OUTPUT'], 'OPERATOR': 0, 'VALUE': '1', 'OUTPUT': QgsProcessing.TEMPORARY_OUTPUT } outputs['ExtractByAttribute'] = processing.run('native:extractbyattribute', alg_params, context=context, feedback=feedback, is_child_algorithm=True) feedback.setCurrentStep(8) if feedback.isCanceled(): return {} # Fix geometries alg_params = { 'INPUT': outputs['ExtractByAttribute']['OUTPUT'], 'OUTPUT': QgsProcessing.TEMPORARY_OUTPUT } outputs['FixGeometries'] = processing.run('native:fixgeometries', alg_params, context=context, feedback=feedback, is_child_algorithm=True) feedback.setCurrentStep(9) if feedback.isCanceled(): return {} # JUSTNDVI alg_params = { 'ALPHA_BAND': False, 'CROP_TO_CUTLINE': True, 'DATA_TYPE': 0, 'INPUT': outputs['TrueNdvi']['OUTPUT'], 'KEEP_RESOLUTION': False, 'MASK': outputs['FixGeometries']['OUTPUT'], 'MULTITHREADING': False, 'NODATA': None, 'OPTIONS': '', 'SET_RESOLUTION': False, 'SOURCE_CRS': None, 'TARGET_CRS': None, 'X_RESOLUTION': None, 'Y_RESOLUTION': None, 'OUTPUT': QgsProcessing.TEMPORARY_OUTPUT } outputs['Justndvi'] = processing.run('gdal:cliprasterbymasklayer', alg_params, context=context, feedback=feedback, is_child_algorithm=True) feedback.setCurrentStep(10) if feedback.isCanceled(): return {} # NDVIValues alg_params = { 'FIELD_NAME': 'NDVI', 'INPUT_RASTER': outputs['Justndvi']['OUTPUT'], 'RASTER_BAND': 1, 'OUTPUT': QgsProcessing.TEMPORARY_OUTPUT } outputs['Ndvivalues'] = processing.run('native:pixelstopoints', alg_params, context=context, feedback=feedback, is_child_algorithm=True) feedback.setCurrentStep(11) if feedback.isCanceled(): return {} # Clip raster by mask layer alg_params = { 'ALPHA_BAND': False, 'CROP_TO_CUTLINE': True, 'DATA_TYPE': 0, 'INPUT': outputs['HeightsCalculator']['OUTPUT'], 'KEEP_RESOLUTION': False, 'MASK': outputs['FixGeometries']['OUTPUT'], 'MULTITHREADING': False, 'NODATA': None, 'OPTIONS': '', 'SET_RESOLUTION': False, 'SOURCE_CRS': None, 'TARGET_CRS': None, 'X_RESOLUTION': None, 'Y_RESOLUTION': None, 'OUTPUT': QgsProcessing.TEMPORARY_OUTPUT } outputs['ClipRasterByMaskLayer'] = processing.run('gdal:cliprasterbymasklayer', alg_params, context=context, feedback=feedback, is_child_algorithm=True) feedback.setCurrentStep(12) if feedback.isCanceled(): return {} # Mean NDVI alg_params = { 'DISCARD_NONMATCHING': False, 'INPUT': outputs['FixGeometries']['OUTPUT'], 'JOIN': outputs['Ndvivalues']['OUTPUT'], 'JOIN_FIELDS': None, 'PREDICATE': 1, 'SUMMARIES': 6, 'OUTPUT': QgsProcessing.TEMPORARY_OUTPUT } outputs['MeanNdvi'] = processing.run('qgis:joinbylocationsummary', alg_params, context=context, feedback=feedback, is_child_algorithm=True) feedback.setCurrentStep(13) if feedback.isCanceled(): return {} # Heights alg_params = { 'FIELD_NAME': 'Height', 'INPUT_RASTER': outputs['ClipRasterByMaskLayer']['OUTPUT'], 'RASTER_BAND': 1, 'OUTPUT': QgsProcessing.TEMPORARY_OUTPUT } outputs['Heights'] = processing.run('native:pixelstopoints', alg_params, context=context, feedback=feedback, is_child_algorithm=True) feedback.setCurrentStep(14) if feedback.isCanceled(): return {} # Peaks alg_params = { 'DISCARD_NONMATCHING': True, 'INPUT': outputs['FixGeometries']['OUTPUT'], 'JOIN': outputs['Heights']['OUTPUT'], 'JOIN_FIELDS': None, 'PREDICATE': 1, 'SUMMARIES': 3, 'OUTPUT': QgsProcessing.TEMPORARY_OUTPUT } outputs['Peaks'] = processing.run('qgis:joinbylocationsummary', alg_params, context=context, feedback=feedback, is_child_algorithm=True) feedback.setCurrentStep(15) if feedback.isCanceled(): return {} # PeaksnNDVI alg_params = { 'DISCARD_NONMATCHING': True, 'INPUT': outputs['Peaks']['OUTPUT'], 'JOIN': outputs['MeanNdvi']['OUTPUT'], 'JOIN_FIELDS': 'NDVI_mean', 'METHOD': 1, 'PREDICATE': 2, 'PREFIX': '', 'OUTPUT': QgsProcessing.TEMPORARY_OUTPUT } outputs['Peaksnndvi'] = processing.run('qgis:joinattributesbylocation', alg_params, context=context, feedback=feedback, is_child_algorithm=True) feedback.setCurrentStep(16) if feedback.isCanceled(): return {} # Add geometry attributes alg_params = { 'CALC_METHOD': 0, 'INPUT': outputs['Peaksnndvi']['OUTPUT'], 'OUTPUT': QgsProcessing.TEMPORARY_OUTPUT } outputs['AddGeometryAttributes'] = processing.run('qgis:exportaddgeometrycolumns', alg_params, context=context, feedback=feedback, is_child_algorithm=True) feedback.setCurrentStep(17) if feedback.isCanceled(): return {} # Extract by expression alg_params = { 'EXPRESSION': 'NDVI_mean > 0.2 AND NDVI_mean IS NOT NULL AND Height_max > 1 AND Height_max IS NOT NULL AND area > 1', 'INPUT': outputs['AddGeometryAttributes']['OUTPUT'], 'OUTPUT': QgsProcessing.TEMPORARY_OUTPUT } outputs['ExtractByExpression'] = processing.run('native:extractbyexpression', alg_params, context=context, feedback=feedback, is_child_algorithm=True) feedback.setCurrentStep(18) if feedback.isCanceled(): return {} # Join attributes by field value alg_params = { 'DISCARD_NONMATCHING': True, 'FIELD': 'Height', 'FIELDS_TO_COPY': None, 'FIELD_2': 'Height_max', 'INPUT': outputs['Heights']['OUTPUT'], 'INPUT_2': outputs['ExtractByExpression']['OUTPUT'], 'METHOD': 1, 'PREFIX': '', 'OUTPUT': QgsProcessing.TEMPORARY_OUTPUT } outputs['JoinAttributesByFieldValue'] = processing.run('native:joinattributestable', alg_params, context=context, feedback=feedback, is_child_algorithm=True) feedback.setCurrentStep(19) if feedback.isCanceled(): return {} # Delete duplicates by attribute alg_params = { 'FIELDS': 'NDVI_mean', 'INPUT': outputs['JoinAttributesByFieldValue']['OUTPUT'], 'OUTPUT': parameters['Finaltrees'] } outputs['DeleteDuplicatesByAttribute'] = processing.run('native:removeduplicatesbyattribute', alg_params, context=context, feedback=feedback, is_child_algorithm=True) results['Finaltrees'] = outputs['DeleteDuplicatesByAttribute']['OUTPUT'] return results def name(self): return 'trees' def displayName(self): return 'trees' def group(self): return '' def groupId(self): return '' def createInstance(self): return Trees()

Is this possible?

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2 Answers 2

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1

With QGIS 3.4 and Windows 10 I have these deprecation warnings when running my standalone application :

C:\Program Files\QGIS 3.4\apps\qgis-ltr\python\qgis\utils.py:685: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses mod = _builtin_import(name, globals, locals, fromlist, level) C:\Program Files\QGIS 3.4\apps\qgis-ltr\python\plugins\db_manager\db_plugins\postgis\plugin.py:350: DeprecationWarning: invalid escape sequence \: uri = u"raster:gdal:%s:%s" % (self.name, re.sub(":", "\:", self.gdalUri())) C:\PROGRA~1\QGIS3~1.4\apps\Python37\lib\site-packages\PyQt5\uic\objcreator.py:152: DeprecationWarning: 'U' mode is deprecated plugin = open(filename, 'rU')

And everything works fine.

I guess we can rely on QGis and Pyqt teams to keep their libs up to date before the warnings become errors.

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  • my script worked for u? Commented Sep 3, 2019 at 19:29
  • @AN10 your script worked for me exactly like you: no error, just deprecation warnings (different warnings than the ones I have though). There is no output because the script does not have a main routine. Commented Sep 4, 2019 at 6:21
  • so should i just add a main that returns the output ? Commented Sep 4, 2019 at 21:29
  • @AN10 yes I guess Commented Sep 6, 2019 at 6:16
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Your script has the definition of the processing algorithm class but in order for it to do something you need to instantiate the Trees class and use it.

Add this at the end of the file and then run it:

trees = Trees() feedback = QgsProcessingFeedback() context = QgsProcessingContext() parameters = {} #add your parameters here trees.initAlgorithm() trees.processAlgorithm(parameters, context, feedback)
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