Surgical update to CenterNet keypoint postprocessing to use bounding boxes if...

Surgical update to CenterNet keypoint postprocessing to use bounding boxes if present. This is shown to reduce keypoint snapping across individuals.

PiperOrigin-RevId: 369432018

research/object_detection/meta_architectures/center_net_meta_arch.py

@@ -3484,6 +3484,7 @@ class CenterNetMetaArch(model.DetectionModel):
         fields.DetectionResultFields.num_detections: num_detections,
     }
 
+    boxes_strided = None
     if self._od_params:
       boxes_strided = (
           prediction_tensors_to_boxes(y_indices, x_indices,
@@ -3506,8 +3507,8 @@ class CenterNetMetaArch(model.DetectionModel):
       if len(self._kp_params_dict) == 1 and self._num_classes == 1:
         (keypoints, keypoint_scores,
          keypoint_depths) = self._postprocess_keypoints_single_class(
-             prediction_dict, channel_indices, y_indices, x_indices, None,
-             num_detections)
+             prediction_dict, channel_indices, y_indices, x_indices,
+             boxes_strided, num_detections)
         keypoints, keypoint_scores = (
             convert_strided_predictions_to_normalized_keypoints(
                 keypoints, keypoint_scores, self._stride, true_image_shapes,