Merge pull request #148 from PUTvision/update_requirements

Update requirements

.github/workflows/python-app-ubuntu.yml

@@ -39,8 +39,8 @@ jobs:
     - name: Install dependencies
       run: |
         pip install --upgrade pip
-        pip install --upgrade -r requirements.txt
-        pip install --upgrade -r requirements_development.txt
+        pip install --upgrade -r ./src/deepness/python_requirements/requirements.txt
+        pip install --upgrade -r ./src/deepness/python_requirements/requirements_development.txt
     - name: Lint with flake8
       run: |
         # stop the build if there are Python syntax errors or undefined names
@@ -56,7 +56,7 @@ jobs:
         # apparently there is some issue with opencv-python-headless, we need to reinstall it 
         pip uninstall opencv-python-headless --yes
         
-        pip install opencv-python-headless==4.6.0.66
+        pip install --upgrade -r ./src/deepness/python_requirements/requirements.txt
         # run one this without pytest, because pytest creates obfuscated error messages
         # we need 'xvfb-run' to simulate UI - otherwise qgis crushes
         xvfb-run python3 test/test_map_processor_segmentation.py

.gitignore

@@ -333,7 +333,7 @@ compile_commands.json
 
 # End of https://www.toptal.com/developers/gitignore/api/python,pycharm,qt
 
-
+grid_data
 .idea/
-
+src/deepness/python3.10/
 _autosummary/

README.md

@@ -49,7 +49,7 @@ ln -s $PROJECT_DIR/src/deepness ~/.local/share/QGIS/QGIS3/profiles/default/pytho
 
 ```bash
 . venv/bin/activate
-pip install -r requirements.txt
+pip install -r ./src/deepness/python_requirements/requirements.txt
 ```
 
 - Run QGis in the virtual environment:

docs/source/main/main_installation.rst

@@ -2,37 +2,6 @@ Installation
 ============
 
 
-============
-Requirements
-============
-
-* Ubuntu
-
-  * (option 1) Install requirements using system Python interpreter:
-
-  .. code-block:: 
-
-    python3 -m pip install opencv-python-headless onnxruntime-gpu
-
-  * (option 2) Run QGIS and Python Console. Then call command:
-
-  .. code-block:: 
-
-    import pip; pip.main(['install', 'opencv-python-headless', 'onnxruntime-gpu'])
-
-
-* Windows
-
-  * Go to QGIS installation path (for example :code:`C:\Program Files\QGIS 3.26.3\`)
-  
-  * Run :code:`OSGeo4W.bat` and type installation command:
-
-  .. code-block:: 
-
-    python3 -m pip install opencv-python-headless onnxruntime-gpu
-
-* MacOS - SOON
-
 ===================
 Plugin installation
 ===================
@@ -69,3 +38,40 @@ Plugin installation
   * Select the ZIP file using system prompt
 
   * Click the Install Plugin button
+
+============
+Requirements
+============
+
+The plugin should install all required dependencies automatically during the first run. However, if you want to install them manually, you can use the following commands:
+
+.. note:: 
+
+     The plugin requirements and versions are listed in the `requirements.txt <https://github.com/PUTvision/qgis-plugin-deepness/blob/master/src/deepness/python_requirements/requirements.txt>`_ file.
+
+* Ubuntu
+
+  * (option 1) Install requirements using system Python interpreter:
+
+  .. code-block:: 
+
+    python3 -m pip install opencv-python-headless onnxruntime-gpu
+
+  * (option 2) Run QGIS and Python Console. Then call command:
+
+  .. code-block:: 
+
+    import pip; pip.main(['install', 'opencv-python-headless', 'onnxruntime-gpu'])
+
+
+* Windows
+
+  * Go to QGIS installation path (for example :code:`C:\Program Files\QGIS 3.26.3\`)
+  
+  * Run :code:`OSGeo4W.bat` and type installation command:
+
+  .. code-block:: 
+
+    python3 -m pip install opencv-python-headless onnxruntime-gpu
+
+* MacOS - SOON

src/deepness/deepness.py

@@ -25,7 +25,6 @@
                                                                      MapProcessingResultFailed,
                                                                      MapProcessingResultSuccess)
 from deepness.processing.map_processor.map_processor_training_data_export import MapProcessorTrainingDataExport
-from deepness.processing.models.model_types import ModelDefinition
 
 cv2 = LazyPackageLoader('cv2')
 
@@ -252,6 +251,8 @@ def _run_training_data_export(self, training_data_export_parameters: TrainingDat
         self._display_processing_started_info()
 
     def _run_model_inference(self, params: MapProcessingParameters):
+        from deepness.processing.models.model_types import ModelDefinition  # import here to avoid pulling external dependencies to early
+
         if not self._are_map_processing_parameters_are_correct(params):
             return
 

src/deepness/deepness_dockwidget.py

@@ -14,6 +14,7 @@
 from deepness.common.config_entry_key import ConfigEntryKey
 from deepness.common.defines import IS_DEBUG, PLUGIN_NAME
 from deepness.common.errors import OperationFailedException
+from deepness.common.lazy_package_loader import LazyPackageLoader
 from deepness.common.processing_overlap import ProcessingOverlap, ProcessingOverlapOptions
 from deepness.common.processing_parameters.detection_parameters import DetectionParameters, DetectorType
 from deepness.common.processing_parameters.map_processing_parameters import (MapProcessingParameters, ModelOutputFormat,
@@ -23,12 +24,11 @@
 from deepness.common.processing_parameters.segmentation_parameters import SegmentationParameters
 from deepness.common.processing_parameters.superresolution_parameters import SuperresolutionParameters
 from deepness.common.processing_parameters.training_data_export_parameters import TrainingDataExportParameters
-from deepness.processing.models.detector import Detector
 from deepness.processing.models.model_base import ModelBase
-from deepness.processing.models.model_types import ModelDefinition, ModelType
 from deepness.widgets.input_channels_mapping.input_channels_mapping_widget import InputChannelsMappingWidget
 from deepness.widgets.training_data_export_widget.training_data_export_widget import TrainingDataExportWidget
 
+
 FORM_CLASS, _ = uic.loadUiType(os.path.join(
     os.path.dirname(__file__), 'deepness_dockwidget.ui'))
 
@@ -156,6 +156,8 @@ def _rlayer_updated(self):
     def _setup_misc_ui(self):
         """ Setup some misceleounous ui forms
         """
+        from deepness.processing.models.model_types import ModelDefinition  # import here to avoid pulling external dependencies to early
+
         self._show_debug_warning()
         combobox = self.comboBox_processedAreaSelection
         for name in ProcessedAreaType.get_all_names():
@@ -166,7 +168,7 @@ def _setup_misc_ui(self):
 
         self.mMapLayerComboBox_inputLayer.setFilters(QgsMapLayerProxyModel.RasterLayer)
         self.mMapLayerComboBox_areaMaskLayer.setFilters(QgsMapLayerProxyModel.VectorLayer)
-        
+
         self.mGroupBox_8.setCollapsed(True)  # collapse the group by default
         self._set_processed_area_mask_options()
         self._set_processing_overlap_enabled()
@@ -212,6 +214,8 @@ def _create_connections(self):
         self.radioButton_processingTileOverlapPixels.toggled.connect(self._set_processing_overlap_enabled)
 
     def _model_type_changed(self):
+        from deepness.processing.models.model_types import ModelType  # import here to avoid pulling external dependencies to early
+
         model_type = ModelType(self.comboBox_modelType.currentText())
 
         segmentation_enabled = False
@@ -251,11 +255,11 @@ def _model_output_format_changed(self):
         model_output_format = ModelOutputFormat(txt)
         class_number_selection_enabled = bool(model_output_format == ModelOutputFormat.ONLY_SINGLE_CLASS_AS_LAYER)
         self.comboBox_outputFormatClassNumber.setEnabled(class_number_selection_enabled)
-        
+
     def _set_processing_overlap_enabled(self):
         overlap_percentage_enabled = self.radioButton_processingTileOverlapPercentage.isChecked()
         self.spinBox_processingTileOverlapPercentage.setEnabled(overlap_percentage_enabled)
-        
+
         overlap_pixels_enabled = self.radioButton_processingTileOverlapPixels.isChecked()
         self.spinBox_processingTileOverlapPixels.setEnabled(overlap_pixels_enabled)
 
@@ -284,15 +288,15 @@ def _browse_query_image_path(self):
         )
         if file_path:
             self.lineEdit_recognitionPath.setText(file_path)
-    
+
     def _load_default_model_parameters(self):
         """
         Load the default parameters from model metadata
         """
         value = self._model.get_metadata_resolution()
         if value is not None:
             self.doubleSpinBox_resolution_cm_px.setValue(value)
-            
+
         value = self._model.get_model_batch_size()
         if value is not None:
             self.spinBox_batchSize.setValue(value)
@@ -344,6 +348,8 @@ def _load_model_with_type_from_metadata(self, model_class_from_ui, file_path):
         If model has model_type in metadata - use this type to create proper model class.
         Otherwise model_class_from_ui will be used
         """
+        from deepness.processing.models.model_types import ModelDefinition, ModelType  # import here to avoid pulling external dependencies to early
+
         model_class = model_class_from_ui
 
         model_type_str_from_metadata = ModelBase.get_model_type_from_metadata(file_path)
@@ -361,6 +367,9 @@ def _load_model_and_display_info(self, abort_if_no_file_path: bool = False):
         """
         Tries to load the model and display its message.
         """
+        from deepness.processing.models.model_types import ModelType  # import here to avoid pulling external dependencies to early
+        import deepness.processing.models.detector as detector_module  # import here to avoid pulling external dependencies to early
+
         file_path = self.lineEdit_modelPath.text()
 
         if not file_path and abort_if_no_file_path:
@@ -383,13 +392,13 @@ def _load_model_and_display_info(self, abort_if_no_file_path: bool = False):
             # TODO idk how variable input will be handled
             self.spinBox_tileSize_px.setValue(input_size_px)
             self.spinBox_tileSize_px.setEnabled(False)
-            
+
             if batch_size is not None:
                 self.spinBox_batchSize.setValue(batch_size)
                 self.spinBox_batchSize.setEnabled(False)
             else:
                 self.spinBox_batchSize.setEnabled(True)
-            
+
             self._input_channels_mapping_widget.set_model(self._model)
 
             # super resolution
@@ -414,7 +423,7 @@ def _load_model_and_display_info(self, abort_if_no_file_path: bool = False):
 
         self.label_modelInfo.setText(txt)
 
-        if isinstance(self._model, Detector):
+        if isinstance(self._model, detector_module.Detector):
             detector_type = DetectorType(self.comboBox_detectorType.currentText())
             self._model.set_model_type_param(detector_type)
 
@@ -466,10 +475,12 @@ def _get_pixel_classification_threshold(self):
             return 0
         return self.doubleSpinBox_probabilityThreshold.value()
 
-    def get_selected_model_class_definition(self) -> ModelDefinition:
+    def get_selected_model_class_definition(self):   # -> ModelDefinition: # we cannot import it here yet
         """
         Get the currently selected model class (in UI)
         """
+        from deepness.processing.models.model_types import ModelDefinition, ModelType  # import here to avoid pulling external dependencies to early
+
         model_type_txt = self.comboBox_modelType.currentText()
         model_type = ModelType(model_type_txt)
         model_definition = ModelDefinition.get_definition_for_type(model_type)
@@ -479,6 +490,8 @@ def get_inference_parameters(self) -> MapProcessingParameters:
         """ Get the parameters for the model interface.
         The returned type is derived from `MapProcessingParameters` class, depending on the selected model type.
         """
+        from deepness.processing.models.model_types import ModelType  # import here to avoid pulling external dependencies to early
+
         map_processing_parameters = self._get_map_processing_parameters()
 
         if self._model is None:
@@ -537,7 +550,7 @@ def get_recognition_parameters(self, map_processing_parameters: MapProcessingPar
             query_image_path=self.lineEdit_recognitionPath.text(),
         )
         return params
-    
+
     def get_detection_parameters(self, map_processing_parameters: MapProcessingParameters) -> DetectionParameters:
 
         params = DetectionParameters(