Updated version for release

GANDLF/metrics/segmentation_panoptica.py

@@ -1,4 +1,5 @@
 from pathlib import Path
+import os
 
 from typing import Optional
 import numpy as np
@@ -19,12 +20,15 @@ def generate_instance_segmentation(
         prediction (np.ndarray): The input prediction containing objects.
         label_path (str): The path to the reference label.
         target (np.ndarray): The input target containing objects.
+        parameters (dict): The GaNDLF parameters from which panoptica config is to be extracted.
         panoptica_config_path (str): The path to the Panoptica configuration file.
 
     Returns:
         dict: The evaluation results.
     """
 
+    os.environ["PANOPTICA_CITATION_REMINDER"] = "False"
+
     # the parameters dict takes precedence over the panoptica_config_path
     evaluator = parameters.get("panoptica_config", None)
     if evaluator is None:

GANDLF/version.py

@@ -2,4 +2,4 @@
 # -*- coding: UTF-8 -*-
 
 # check GaNDLF wiki for versioning and release guidelines: https://github.com/mlcommons/GaNDLF/wiki
-__version__ = "0.1.4-dev"
+__version__ = "0.1.4"

samples/config_all_options.yaml

@@ -1,8 +1,8 @@
 # affix version
 version:
   {
-    minimum: 0.1.4-dev,
-    maximum: 0.1.4-dev # this should NOT be made a variable, but should be tested after every tag is created
+    minimum: 0.1.4,
+    maximum: 0.1.4 # this should NOT be made a variable, but should be tested after every tag is created
   }
 ## Choose the model parameters here
 model:

samples/config_classification.yaml

@@ -1,8 +1,8 @@
 # affix version
 version:
   {
-    minimum: 0.1.4-dev,
-    maximum: 0.1.4-dev # this should NOT be made a variable, but should be tested after every tag is created
+    minimum: 0.1.4,
+    maximum: 0.1.4 # this should NOT be made a variable, but should be tested after every tag is created
   }
 # Choose the model parameters here
 model:

samples/config_getting_started_classification_histo2d.yaml

@@ -94,6 +94,6 @@ scheduler:
 track_memory_usage: false
 verbose: false
 version:
-  maximum: 0.1.4-dev
+  maximum: 0.1.4
   minimum: 0.0.14
 weighted_loss: true

samples/config_getting_started_classification_rad3d.yaml

@@ -99,6 +99,6 @@ scheduler:
 track_memory_usage: false
 verbose: false
 version:
-  maximum: 0.1.4-dev
+  maximum: 0.1.4
   minimum: 0.0.14
 weighted_loss: true

samples/config_getting_started_regression_histo2d.yaml

@@ -59,6 +59,6 @@ scheduler:
 track_memory_usage: false
 verbose: false
 version:
-  maximum: 0.1.4-dev
+  maximum: 0.1.4
   minimum: 0.0.14
 weighted_loss: true

samples/config_getting_started_regression_rad3d.yaml

@@ -62,6 +62,6 @@ scheduler:
 track_memory_usage: false
 verbose: false
 version:
-  maximum: 0.1.4-dev
+  maximum: 0.1.4
   minimum: 0.0.14
 weighted_loss: false

samples/config_getting_started_segmentation_histo2d.yaml

@@ -66,6 +66,6 @@ scheduler:
 track_memory_usage: false
 verbose: true
 version:
-  maximum: 0.1.4-dev
+  maximum: 0.1.4
   minimum: 0.0.14
 weighted_loss: true

samples/config_regression.yaml

@@ -1,8 +1,8 @@
 # affix version
 version:
   {
-    minimum: 0.1.4-dev,
-    maximum: 0.1.4-dev # this should NOT be made a variable, but should be tested after every tag is created
+    minimum: 0.1.4,
+    maximum: 0.1.4 # this should NOT be made a variable, but should be tested after every tag is created
   }
 # Choose the model parameters here
 model:

samples/config_segmentation_brats.yaml

@@ -1,8 +1,8 @@
 # affix version
 version:
   {
-    minimum: 0.1.4-dev,
-    maximum: 0.1.4-dev # this should NOT be made a variable, but should be tested after every tag is created
+    minimum: 0.1.4,
+    maximum: 0.1.4 # this should NOT be made a variable, but should be tested after every tag is created
   }
 # Choose the model parameters here
 model:

samples/config_segmentation_histology.yaml

@@ -1,8 +1,8 @@
 # affix version
 version:
   {
-    minimum: 0.1.4-dev,
-    maximum: 0.1.4-dev # this should NOT be made a variable, but should be tested after every tag is created
+    minimum: 0.1.4,
+    maximum: 0.1.4 # this should NOT be made a variable, but should be tested after every tag is created
   }
 # Choose the model parameters here
 model:

samples/config_segmentation_metrics_brats_default.yaml

@@ -144,18 +144,21 @@ panoptica_config: !Panoptica_Evaluator
   save_group_times: false
   segmentation_class_groups: !SegmentationClassGroups
     groups:
-      ed: !LabelGroup
+      snfh: !LabelGroup
         single_instance: false
         value_labels: [2]
       et: !LabelGroup
         single_instance: false
         value_labels: [3]
-      net: !LabelGroup
+      netc: !LabelGroup
         single_instance: false
         value_labels: [1]
+      rc: !LabelGroup
+        single_instance: false
+        value_labels: [4]
       tc: !LabelMergeGroup
         single_instance: false
-        value_labels: [1, 3]
+        value_labels: [1, 3, 4]
       wt: !LabelMergeGroup
         single_instance: false
         value_labels: [1, 2, 3, 4]

testing/config_classification.yaml

@@ -55,7 +55,7 @@ save_output: false
 scaling_factor: 1
 scheduler: triangle
 version:
-  maximum: 0.1.4-dev
+  maximum: 0.1.4
   minimum: 0.0.14
 weighted_loss: True
 

testing/config_regression.yaml

@@ -38,7 +38,7 @@ save_output: false
 scaling_factor: 1
 scheduler: triangle
 version:
-  maximum: 0.1.4-dev
+  maximum: 0.1.4
   minimum: 0.0.14
 weighted_loss: false
 

testing/config_segmentation.yaml

@@ -3,7 +3,7 @@
 version:
   {
     minimum: 0.0.14,
-    maximum: 0.1.4-dev
+    maximum: 0.1.4
   }
 model:
   {