[libs.segmentation.engine.evaluator] Fix precision-recall estimates when precision and recall == 0

src/mednet/libs/segmentation/engine/evaluator.py

@@ -646,6 +646,11 @@ def run(
         recall_curve = tpr_curve = numpy.array([recall(*k) for k in counts])
         precision_curve = numpy.array([precision(*k) for k in counts])
 
+        # correction when precision is very small
+        precision_curve[
+            numpy.logical_and(precision_curve < 1e-8, recall_curve < 1e-8)
+        ] = 1.0
+
         # populates data to be recorded in JSON format
         eval_json_data.setdefault(split_name, {})["counts"] = {
             k: v for k, v in zip(threshold_list, counts)