Update docs on visualization callback

src/super_gradients/training/utils/callbacks/extreme_batch_obb_visualization_callback.py

@@ -24,33 +24,30 @@ class ExtremeBatchOBBVisualizationCallback(ExtremeBatchCaseVisualizationCallback
     """
     ExtremeBatchOBBVisualizationCallback
 
-    Visualizes worst/best batch in an epoch for pose estimation task.
-    This class visualize horizontally-stacked GT and predicted poses.
-    It requires a key 'gt_samples' (List[PoseEstimationSample]) to be present in additional_batch_items dictionary.
+    Visualizes worst/best batch in an epoch for OBB detection task.
+    This class visualize horizontally-stacked GT and predicted boxes.
+    It requires a key 'gt_samples' (List[OBBSample]) to be present in additional_batch_items dictionary.
 
-    Supported models: YoloNASPose
-    Supported datasets: COCOPoseEstimationDataset
+    Supported models: YoloNAS-R
+    Supported datasets: DOTAOBBDataset
 
     Example usage in Yaml config:
 
         training_hyperparams:
           phase_callbacks:
-              - ExtremeBatchPoseEstimationVisualizationCallback:
-                  keypoint_colors: ${dataset_params.keypoint_colors}
-                  edge_colors: ${dataset_params.edge_colors}
-                  edge_links: ${dataset_params.edge_links}
-                  loss_to_monitor: YoloNASPoseLoss/loss
+              - ExtremeBatchOBBVisualizationCallback:
+                  loss_to_monitor: YoloNASRLoss/loss
                   max: True
                   freq: 1
                   max_images: 16
                   enable_on_train_loader: True
                   enable_on_valid_loader: True
                   post_prediction_callback:
-                    _target_: super_gradients.training.models.pose_estimation_models.yolo_nas_pose.YoloNASPosePostPredictionCallback
-                    pose_confidence_threshold: 0.01
-                    nms_iou_threshold: 0.7
-                    pre_nms_max_predictions: 300
-                    post_nms_max_predictions: 30
+                    _target_: super_gradients.training.models.detection_models.yolo_nas_r.yolo_nas_r_post_prediction_callback.YoloNASRPostPredictionCallback
+                    score_threshold: 0.25
+                    pre_nms_max_predictions: 4096
+                    post_nms_max_predictions: 512
+                    nms_iou_threshold: 0.6
 
     :param metric: Metric, will be the metric which is monitored.
 
@@ -73,9 +70,6 @@ class ExtremeBatchOBBVisualizationCallback(ExtremeBatchCaseVisualizationCallback
      the minimum (default=False).
 
     :param freq: int, epoch frequency to perform all of the above (default=1).
-
-
-
     """
 
     def __init__(