feat(metrics): ✨ initial mean average recall metrics added

docs/metrics/mean_average_precision.md

@@ -1,6 +1,5 @@
 ---
 comments: true
-status: new
 ---
 
 # Mean Average Precision

docs/metrics/mean_average_recall.md

@@ -0,0 +1,18 @@
+---
+comments: true
+status: new
+---
+
+# Mean Average Recall
+
+<div class="md-typeset">
+    <h2><a href="#supervision.metrics.mean_average_recall.MeanAverageRecall">MeanAverageRecall</a></h2>
+</div>
+
+:::supervision.metrics.mean_average_recall.MeanAverageRecall
+
+<div class="md-typeset">
+    <h2><a href="#supervision.metrics.mean_average_recall.MeanAverageRecallResult">MeanAverageRecallResult</a></h2>
+</div>
+
+:::supervision.metrics.mean_average_recall.MeanAverageRecallResult

mkdocs.yml

@@ -65,7 +65,8 @@ nav:
           - Core: datasets/core.md
           - Utils: datasets/utils.md
       - Metrics:
-          - mAP: metrics/mean_average_precision.md
+          - Mean Avg. Precision (mAP): metrics/mean_average_precision.md
+          - Mean Avg. Recall (mAR): metrics/mean_average_recall.md
           - Precision: metrics/precision.md
           - Recall: metrics/recall.md
           - F1 Score: metrics/f1_score.md

supervision/metrics/__init__.py

@@ -8,6 +8,10 @@
     MeanAveragePrecision,
     MeanAveragePrecisionResult,
 )
+from supervision.metrics.mean_average_recall import (
+    MeanAverageRecall,
+    MeanAverageRecallResult,
+)
 from supervision.metrics.precision import Precision, PrecisionResult
 from supervision.metrics.recall import Recall, RecallResult
 from supervision.metrics.utils.object_size import (

supervision/metrics/mean_average_precision.py

@@ -406,7 +406,7 @@ class MeanAveragePrecisionResult:
     Attributes:
         metric_target (MetricTarget): the type of data used for the metric -
             boxes, masks or oriented bounding boxes.
-        class_agnostic (bool): When computing class-agnostic results, class ID
+        is_class_agnostic (bool): When computing class-agnostic results, class ID
             is set to `-1`.
         mAP_map50_95 (float): the mAP score at IoU thresholds from `0.5` to `0.95`.
         mAP_map50 (float): the mAP score at IoU threshold of `0.5`.