Fixing typos + preprocessing params

SlicerBoneMorphing/Resources/UI/SlicerBoneMorphing.ui

@@ -176,26 +176,29 @@
          <item row="2" column="0">
           <widget class="QLabel" name="preprocessingNormalsEstimationRadiusLabel">
            <property name="toolTip">
-            <string>Maximum radius for calculating normals. Calculated as multiplier of the object's voxel size</string>
+            <string>Maximum radius for calculating normals. Calculated as percentage of the object's size</string>
            </property>
            <property name="text">
-            <string>Normals estimation radius: </string>
+            <string>Normals estimation radius [%]: </string>
            </property>
           </widget>
          </item>
          <item row="2" column="1">
           <widget class="QDoubleSpinBox" name="preprocessingNormalsEstimationRadiusDoubleSpinBox">
            <property name="toolTip">
-            <string>Maximum radius for calculating normals. Calculated as multiplier of the object's voxel size</string>
+            <string>Maximum radius for calculating normals. Calculated as percentage of the object's size</string>
+           </property>
+           <property name="decimals">
+            <number>3</number>
            </property>
            <property name="minimum">
-            <double>1.000000000000000</double>
+            <double>0.001000000000000</double>
            </property>
            <property name="maximum">
             <double>100.000000000000000</double>
            </property>
            <property name="value">
-            <double>4.000000000000000</double>
+            <double>8.000000000000000</double>
            </property>
           </widget>
          </item>
@@ -205,7 +208,7 @@
             <string>Maximum amount of points considered neighbouring. Calculated as percentage of the lower count of initial points of the source or target mesh</string>
            </property>
            <property name="text">
-            <string>Normals estimation max neighbours:</string>
+            <string>Normals estimation max neighbours [%]:</string>
            </property>
           </widget>
          </item>
@@ -228,26 +231,29 @@
          <item row="4" column="0">
           <widget class="QLabel" name="preprocessingFpfhRadiusLabel">
            <property name="toolTip">
-            <string>Maximum radius for calculating fast point feature histograms. Calculated as a multiplier of the object's voxel size</string>
+            <string>Maximum radius for calculating fast-point-feature histograms. Calculated as percentage of the object's size</string>
            </property>
            <property name="text">
-            <string>FPFH search radius:</string>
+            <string>FPFH search radius [%]:</string>
            </property>
           </widget>
          </item>
          <item row="4" column="1">
           <widget class="QDoubleSpinBox" name="preprocessingFpfhRadiusDoubleSpinBox">
            <property name="toolTip">
-            <string>Maximum radius for calculating fast point feature histograms. Calculated as a multiplier of the object's voxel size</string>
+            <string>Maximum radius for calculating fast-point-feature histograms. Calculated as percentage of the object's size</string>
+           </property>
+           <property name="decimals">
+            <number>3</number>
            </property>
            <property name="minimum">
-            <double>1.000000000000000</double>
+            <double>0.001000000000000</double>
            </property>
            <property name="maximum">
             <double>100.000000000000000</double>
            </property>
            <property name="value">
-            <double>10.000000000000000</double>
+            <double>20.000000000000000</double>
            </property>
           </widget>
          </item>

SlicerBoneMorphing/src/logic/Constants.py

@@ -24,14 +24,14 @@
 PREPROCESSING_KEY_DOWNSAMPLING_TARGET_TO_SOURCE = "dtts"
 PREPROCESSING_KEY_NORMALS_ESTIMATION_RADIUS = "ner"
 PREPROCESSING_KEY_FPFH_ESTIMATION_RADIUS = "fer"
-PREPROCESSING_KEY_MAX_NN_NORMALS = "mnnn"
-PREPROCESSING_KEY_MAX_NN_FPFH = "mnf"
+PREPROCESSING_KEY_NORMALS_MAX_NN = "mnnn"
+PREPROCESSING_KEY_FPFH_MAX_NN = "mnf"
 
 PREPROCESSING_DEFAULT_VALUE_DOWNSAMPLING_VOXEL_SIZE = 0.0
-PREPROCESSING_DEFAULT_VALUE_RADIUS_NORMAL_SCALE = 4
-PREPROCESSING_DEFAULT_VALUE_RADIUS_FEATURE_SCALE = 10
-PREPROCESSING_DEFAULT_VALUE_MAX_NN_NORMALS = 25
-PREPROCESSING_DEFAULT_VALUE_MAX_NN_FPFH = 50
+PREPROCESSING_DEFAULT_VALUE_NORMALS_ESTIMATION_RADIUS = 8
+PREPROCESSING_DEFAULT_VALUE_FPFPH_ESTIMATION_RADIUS = 20
+PREPROCESSING_DEFAULT_VALUE_NORMALS_MAX_NN = 25
+PREPROCESSING_DEFAULT_VALUE_FPFH_MAX_NN = 50
 
 ### REGISTRATION PARAMETERS ###
 REGISTRATION_KEY_RANSAC_DISTANCE_THRESHOLD = "rrdt"

SlicerBoneMorphing/src/logic/SlicerBoneMorphingLogic.py

@@ -224,23 +224,23 @@ def __preprocess_model(
         target_pcd = self.__convert_mesh_to_point_cloud(target_mesh)
 
         points_min = np.min([len(source_pcd.points), len(target_pcd.points)])
-        max_nn_normals = int(points_min * (parameters[const.PREPROCESSING_KEY_MAX_NN_NORMALS] / 100))
-        max_nn_fpfh = int(points_min * (parameters[const.PREPROCESSING_KEY_MAX_NN_FPFH] / 100))
+        max_nn_normals = int(points_min * (parameters[const.PREPROCESSING_KEY_NORMALS_MAX_NN] / 100))
+        max_nn_fpfh = int(points_min * (parameters[const.PREPROCESSING_KEY_FPFH_MAX_NN] / 100))
 
-        voxel_size = 0.0
+        object_size = 0.0
         if parameters[const.PREPROCESSING_KEY_DOWNSAMPLING] is True:
             if parameters[const.PREPROCESSING_KEY_DOWNSAMPLING_SOURCE_TO_TARGET] is True:
-                voxel_size = self.__calculate_object_size(target_pcd)
+                object_size = self.__calculate_object_size(target_pcd)
             elif parameters[const.PREPROCESSING_KEY_DOWNSAMPLING_TARGET_TO_SOURCE] is True:
-                voxel_size = self.__calculate_object_size(source_pcd)
+                object_size = self.__calculate_object_size(source_pcd)
             else:
                 print("ERROR: Downsampling is enabled but neither of the downsampling options was selected")
                 return [const.EXIT_FAILURE, None]
 
         print("Preprocessing source mesh...")
         source_pcd_downsampled, source_pcd_fpfh = self.__preprocess_point_cloud(
             source_pcd,
-            voxel_size,
+            object_size,
             parameters[const.PREPROCESSING_KEY_NORMALS_ESTIMATION_RADIUS],
             parameters[const.PREPROCESSING_KEY_FPFH_ESTIMATION_RADIUS],
             max_nn_normals,
@@ -250,21 +250,20 @@ def __preprocess_model(
         print("Preprocessing target mesh...")
         target_pcd_downsampled, target_pcd_fpfh = self.__preprocess_point_cloud(
             target_pcd,
-            voxel_size,
+            object_size,
             parameters[const.PREPROCESSING_KEY_NORMALS_ESTIMATION_RADIUS],
             parameters[const.PREPROCESSING_KEY_FPFH_ESTIMATION_RADIUS],
             max_nn_normals,
             max_nn_fpfh
         )
 
-        voxel_size = np.max([self.__calculate_object_size(source_pcd), self.__calculate_object_size(target_pcd)])
-        print("Calculated voxel size: " + str(voxel_size))
+        object_size = np.max([self.__calculate_object_size(source_pcd), self.__calculate_object_size(target_pcd)])
 
         try:
             result_ransac = self.__ransac_pcd_registration(
                 source_pcd_downsampled, target_pcd_downsampled,
                 source_pcd_fpfh, target_pcd_fpfh,
-                voxel_size * (parameters[const.REGISTRATION_KEY_RANSAC_DISTANCE_THRESHOLD] / 100),
+                object_size * (parameters[const.REGISTRATION_KEY_RANSAC_DISTANCE_THRESHOLD] / 100),
                 parameters[const.REGISTRATION_KEY_FITNESS_THRESHOLD],
                 parameters[const.REGISTRATION_KEY_MAX_ITERATIONS]
             )
@@ -276,7 +275,7 @@ def __preprocess_model(
 
         result_icp = o3d.pipelines.registration.registration_icp(
             source_pcd_downsampled, target_pcd_downsampled,
-            voxel_size * (parameters[const.REGISTRATION_KEY_ICP_DISTANCE_THRESHOLD] / 100),
+            object_size * (parameters[const.REGISTRATION_KEY_ICP_DISTANCE_THRESHOLD] / 100),
             result_ransac.transformation,
             o3d.pipelines.registration.TransformationEstimationPointToPlane()
         )
@@ -302,7 +301,7 @@ def __calculate_object_size(self, source: o3d.geometry.Geometry) -> float:
     def __preprocess_point_cloud(
             self,
             pcd: o3d.geometry.PointCloud,
-            downsampling_voxel_size: float,
+            downsampling_object_size: float,
             normals_estimation_radius: float,
             fpfh_estimation_radius: float,
             max_nn_normals: int,
@@ -313,8 +312,8 @@ def __preprocess_point_cloud(
 
             Parameters
             ----------
-            o3d.geometry.PointCloud pcd: Source point cloud
-            float downsampling_distance_threshold: Distance threshold for downsampling
+            o3d.geometry.PointCloud pcd: Point cloud to preprocess
+            float downsampling_object_size: Size of the object to downsample to
             float normals_estimation_radius: Radius for estimating normals
             float fpfh_estimation_radius: Radius for the FPFH computation
             int max_nn_normals: Maximum number of neighbours considered for normals estimation
@@ -327,15 +326,15 @@ def __preprocess_point_cloud(
                 - [1] = FPFH
         '''
 
-        pcd_voxel_size = self.__calculate_object_size(pcd)
-        if downsampling_voxel_size > 0.0 and downsampling_voxel_size != pcd_voxel_size and pcd_voxel_size > downsampling_voxel_size:
-            print("Downsampling point cloud with voxel size: " + str(pcd_voxel_size) + " to target voxel size: " + str(downsampling_voxel_size))
-            pcd = pcd.voxel_down_sample(downsampling_voxel_size)
+        pcd_object_size = self.__calculate_object_size(pcd)
+        if downsampling_object_size > 0.0 and downsampling_object_size != pcd_object_size and pcd_object_size > downsampling_object_size:
+            print("Downsampling point cloud with size: " + str(pcd_object_size) + " to target object size: " + str(downsampling_object_size))
+            pcd = pcd.object_down_sample(downsampling_object_size)
         else:
             print("Downsampling will not be performed. The target voxel size is either less than 0, equal to the calculated voxel size and/or larger, than current voxel size")
 
-        pcd.estimate_normals(o3d.geometry.KDTreeSearchParamHybrid(radius=(pcd_voxel_size * normals_estimation_radius), max_nn=max_nn_normals))
-        pcd_fpfh = o3d.pipelines.registration.compute_fpfh_feature(pcd, o3d.geometry.KDTreeSearchParamHybrid(radius=pcd_voxel_size * fpfh_estimation_radius, max_nn=max_nn_fpfh))
+        pcd.estimate_normals(o3d.geometry.KDTreeSearchParamHybrid(radius=(pcd_object_size * (normals_estimation_radius / 100)), max_nn=max_nn_normals))
+        pcd_fpfh = o3d.pipelines.registration.compute_fpfh_feature(pcd, o3d.geometry.KDTreeSearchParamHybrid(radius=pcd_object_size * (fpfh_estimation_radius / 100), max_nn=max_nn_fpfh))
         return pcd, pcd_fpfh
 
     def __ransac_pcd_registration(

SlicerBoneMorphing/src/widget/SlicerBoneMorphingWidget.py

@@ -62,10 +62,10 @@ def __reset_parameters_to_default(self) -> None:
         ## Preprocessing parameters ##
         self.__ui.preprocessingDownsamplingCheckBox.checked = False
         self.__ui.preprocessingDownsamplingSourceToTargetRadioButton.checked = True
-        self.__ui.preprocessingNormalsEstimationRadiusDoubleSpinBox.value = const.PREPROCESSING_DEFAULT_VALUE_RADIUS_NORMAL_SCALE
-        self.__ui.preprocessingNormalsEstimationMaxNeighboursSpinBox.value = const.PREPROCESSING_DEFAULT_VALUE_MAX_NN_NORMALS
-        self.__ui.preprocessingFpfhRadiusDoubleSpinBox.value = const.PREPROCESSING_DEFAULT_VALUE_RADIUS_FEATURE_SCALE
-        self.__ui.preprocessingFpfhMaxNeighboursSpinBox.value = const.PREPROCESSING_DEFAULT_VALUE_MAX_NN_FPFH
+        self.__ui.preprocessingNormalsEstimationRadiusDoubleSpinBox.value = const.PREPROCESSING_DEFAULT_VALUE_NORMALS_ESTIMATION_RADIUS
+        self.__ui.preprocessingNormalsEstimationMaxNeighboursSpinBox.value = const.PREPROCESSING_DEFAULT_VALUE_NORMALS_MAX_NN
+        self.__ui.preprocessingFpfhRadiusDoubleSpinBox.value = const.PREPROCESSING_DEFAULT_VALUE_FPFPH_ESTIMATION_RADIUS
+        self.__ui.preprocessingFpfhMaxNeighboursSpinBox.value = const.PREPROCESSING_DEFAULT_VALUE_FPFH_MAX_NN
 
         ## Registration parameters ##
         self.__ui.registrationMaxIterationsSpinBox.value = const.REGISTRATION_DEFAULT_VALUE_MAX_ITERATIONS
@@ -182,9 +182,9 @@ def __parse_parameters_preprocessing(self) -> dict:
         params[const.PREPROCESSING_KEY_DOWNSAMPLING_SOURCE_TO_TARGET] = self.__ui.preprocessingDownsamplingSourceToTargetRadioButton.checked
         params[const.PREPROCESSING_KEY_DOWNSAMPLING_TARGET_TO_SOURCE] = self.__ui.preprocessingDownsamplingTargetToSourceRadioButton.checked
         params[const.PREPROCESSING_KEY_NORMALS_ESTIMATION_RADIUS] = self.__ui.preprocessingNormalsEstimationRadiusDoubleSpinBox.value
-        params[const.PREPROCESSING_KEY_MAX_NN_NORMALS] = self.__ui.preprocessingNormalsEstimationMaxNeighboursSpinBox.value
+        params[const.PREPROCESSING_KEY_NORMALS_MAX_NN] = self.__ui.preprocessingNormalsEstimationMaxNeighboursSpinBox.value
         params[const.PREPROCESSING_KEY_FPFH_ESTIMATION_RADIUS] = self.__ui.preprocessingFpfhRadiusDoubleSpinBox.value
-        params[const.PREPROCESSING_KEY_MAX_NN_FPFH] = self.__ui.preprocessingFpfhMaxNeighboursSpinBox.value
+        params[const.PREPROCESSING_KEY_FPFH_MAX_NN] = self.__ui.preprocessingFpfhMaxNeighboursSpinBox.value
 
         # Registration
         params[const.REGISTRATION_KEY_MAX_ITERATIONS] = self.__ui.registrationMaxIterationsSpinBox.value