Update segmentation loader to have reasonable values

docs/source/benchmarking.md

@@ -45,7 +45,7 @@ Please put this in the conversation of the pull request, and not add it to the f
 ## Default Values
 If no options are provided for initial spacing, final spacing, or step size, the script uses the following default
 values:
-- **Initial Spacing**: 0.15mm
+- **Initial Spacing**: 0.2mm
 - **Final Spacing**: 0.25mm
 - **Step Size**: 0.05mm
 

simpa_examples/benchmarking/performance_check.py

@@ -28,10 +28,10 @@ def run_benchmarking_tests(spacing=0.4, profile: str = "TIME", savefolder: str =
 
     import simpa_examples
 
-    examples = [simpa_examples.run_linear_unmixing, simpa_examples.run_minimal_optical_simulation,
-                simpa_examples.run_minimal_optical_simulation_uniform_cube, simpa_examples.run_msot_invision_simulation,
+    examples = [simpa_examples.run_minimal_optical_simulation,
+                simpa_examples.run_minimal_optical_simulation_uniform_cube,
                 simpa_examples.run_optical_and_acoustic_simulation,
-                simpa_examples.run_perform_iterative_qPAI_reconstruction, simpa_examples.run_segmentation_loader]
+                simpa_examples.run_segmentation_loader]
 
     for example in examples:
         example(spacing=spacing, path_manager=None, visualise=False)

simpa_examples/benchmarking/run_benchmarking.sh

@@ -8,7 +8,7 @@ echo "For further details see readme"
 echo "Number of examples can be selected in performance_check.py"
 echo "For comparable benchmarks, please use default"
 echo "Options:"
-echo "  -i, --init           First spacing to benchmark: default = 0.15mm"
+echo "  -i, --init           First spacing to benchmark: default = 0.2mm"
 echo "  -c, --cease          Final spacing to benchmark: default = 0.25mm"
 echo "  -s, --step           Step between spacings: default = 0.05mm"
 echo "  -f, --file           Where to store the output files: default save in current directory; 'print' prints it in console"
@@ -59,7 +59,7 @@ shift 1
 done
 
 if [ "$start" == 0 ]; then
-  start=0.15
+  start=0.2
 fi
 
 if [ "$stop" == 0 ]; then

simpa_examples/msot_invision_simulation.py

@@ -152,7 +152,7 @@ def get_settings():
         }
 
         acoustic_settings = {
-            Tags.ACOUSTIC_SIMULATION_3D: True,
+            Tags.ACOUSTIC_SIMULATION_3D: False,
             Tags.ACOUSTIC_MODEL_BINARY_PATH: path_manager.get_matlab_binary_path(),
             Tags.KWAVE_PROPERTY_ALPHA_POWER: 0.00,
             Tags.KWAVE_PROPERTY_SENSOR_RECORD: "p",

simpa_examples/segmentation_loader.py

@@ -7,6 +7,7 @@
 import numpy as np
 from skimage.data import shepp_logan_phantom
 from scipy.ndimage import zoom
+from skimage.transform import resize
 
 # FIXME temporary workaround for newest Intel architectures
 import os
@@ -19,11 +20,12 @@
 
 
 @profile
-def run_segmentation_loader(spacing: float | int = .1, path_manager=None,
+def run_segmentation_loader(spacing: float | int = 1.0, input_spacing: float | int = 0.2, path_manager=None,
                             visualise: bool = True):
     """
 
-    :param spacing: The simulation spacing between voxels
+    :param spacing: The simulation spacing between voxels in mm
+    :param input_spacing: The input spacing between voxels in mm
     :param path_manager: the path manager to be used, typically sp.PathManager
     :param visualise: If VISUALIZE is set to True, the reconstruction result will be plotted
     :return: a run through of the example
@@ -34,10 +36,9 @@ def run_segmentation_loader(spacing: float | int = .1, path_manager=None,
     label_mask = shepp_logan_phantom()
 
     label_mask = np.digitize(label_mask, bins=np.linspace(0.0, 1.0, 11), right=True)
+    label_mask = label_mask[100:300, 100:300]
+    label_mask = np.reshape(label_mask, (label_mask.shape[0], 1, label_mask.shape[1]))
 
-    label_mask = np.reshape(label_mask, (400, 1, 400))
-
-    input_spacing = 0.2
     segmentation_volume_tiled = np.tile(label_mask, (1, 128, 1))
     segmentation_volume_mask = np.round(zoom(segmentation_volume_tiled, input_spacing/spacing,
                                              order=0)).astype(int)
@@ -67,9 +68,9 @@ def segmentation_class_mapping():
     settings[Tags.RANDOM_SEED] = 1234
     settings[Tags.WAVELENGTHS] = [700]
     settings[Tags.SPACING_MM] = spacing
-    settings[Tags.DIM_VOLUME_X_MM] = 400 / (spacing / input_spacing)
-    settings[Tags.DIM_VOLUME_Y_MM] = 128 / (spacing / input_spacing)
-    settings[Tags.DIM_VOLUME_Z_MM] = 400 / (spacing / input_spacing)
+    settings[Tags.DIM_VOLUME_X_MM] = segmentation_volume_mask.shape[0] * spacing
+    settings[Tags.DIM_VOLUME_Y_MM] = segmentation_volume_mask.shape[1] * spacing
+    settings[Tags.DIM_VOLUME_Z_MM] = segmentation_volume_mask.shape[2] * spacing
 
     settings.set_volume_creation_settings({
         Tags.INPUT_SEGMENTATION_VOLUME: segmentation_volume_mask,
@@ -105,9 +106,11 @@ def segmentation_class_mapping():
 
 if __name__ == "__main__":
     parser = ArgumentParser(description='Run the segmentation loader example')
-    parser.add_argument("--spacing", default=0.2, type=float, help='the voxel spacing in mm')
+    parser.add_argument("--spacing", default=1, type=float, help='the voxel spacing in mm')
+    parser.add_argument("--input_spacing", default=0.2, type=float, help='the input spacing in mm')
     parser.add_argument("--path_manager", default=None, help='the path manager, None uses sp.PathManager')
     parser.add_argument("--visualise", default=True, type=bool, help='whether to visualise the result')
     config = parser.parse_args()
 
-    run_segmentation_loader(spacing=config.spacing, path_manager=config.path_manager, visualise=config.visualise)
+    run_segmentation_loader(spacing=config.spacing, input_spacing=config.input_spacing,
+                            path_manager=config.path_manager, visualise=config.visualise)