[libs.segmentation.engine.evaluator] Fix doc strings

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

@@ -532,25 +532,33 @@ def run(
 
             * ``counts``: dictionary where keys are thresholds, and values are
               sequence of integers containing the TP, FP, TN, FN (in this order).
+
             * ``auc_score``: a float indicating the area under the ROC curve
               for the split.  It is calculated using a trapezoidal rule.
+
             * ``average_precision_score``: a float indicating the area under the
               precision-recall curve, calculated using a rectangle rule.
+
             * ``curves``: dictionary with 2 keys:
+
               * ``roc``: dictionary with 3 keys:
+
                 * ``fpr``: a list of floats with the false-positive rate
                 * ``tpr``: a list of floats with the true-positive rate
                 * ``thresholds``: a list of thresholds uniformily separated by
                   ``steps``, at which both ``fpr`` and ``tpr`` are evaluated.
               * ``precision_recall``: a dictionary with 3 keys:
+
                 * ``precision``: a list of floats with the precision
                 * ``recall``: a list of floats with the recall
                 * ``thresholds``: a list of thresholds uniformily separated by
                   ``steps``, at which both ``precision`` and ``recall`` are
                   evaluated.
+
             * ``threshold_a_priori``: boolean indicating if the threshold for unary
               metrics where computed with a threshold chosen a priori or a
               posteriori in this split.
+
             * ``<metric-name>``: a float representing the supported metric at the
               threshold that maximizes ``metric``.  There will be one entry of this
               type for each of the :py:obj:`SUPPORTED_METRIC_TYPE`'s.