Add test for DeepMAC builder.

PiperOrigin-RevId: 373010443

research/object_detection/builders/model_builder.py

@@ -34,6 +34,7 @@ from object_detection.core import post_processing
 from object_detection.core import target_assigner
 from object_detection.meta_architectures import center_net_meta_arch
 from object_detection.meta_architectures import context_rcnn_meta_arch
+from object_detection.meta_architectures import deepmac_meta_arch
 from object_detection.meta_architectures import faster_rcnn_meta_arch
 from object_detection.meta_architectures import rfcn_meta_arch
 from object_detection.meta_architectures import ssd_meta_arch

research/object_detection/builders/model_builder_tf2_test.py

@@ -25,6 +25,7 @@ from google.protobuf import text_format
 from object_detection.builders import model_builder
 from object_detection.builders import model_builder_test
 from object_detection.core import losses
+from object_detection.meta_architectures import deepmac_meta_arch
 from object_detection.models import center_net_hourglass_feature_extractor
 from object_detection.models.keras_models import hourglass_network
 from object_detection.protos import center_net_pb2
@@ -466,6 +467,57 @@ class ModelBuilderTF2Test(
     # Verify that there are up_sampling2d layers.
     self.assertGreater(num_up_sampling2d_layers, 0)
 
+  def test_create_center_net_deepmac(self):
+    """Test building a CenterNet DeepMAC model."""
+
+    proto_txt = """
+      center_net {
+        num_classes: 90
+        feature_extractor {
+          type: "hourglass_52"
+        }
+        image_resizer {
+          keep_aspect_ratio_resizer {
+            min_dimension: 512
+            max_dimension: 512
+            pad_to_max_dimension: true
+          }
+        }
+        object_detection_task {
+          task_loss_weight: 1.0
+          offset_loss_weight: 1.0
+          scale_loss_weight: 0.1
+          localization_loss {
+            l1_localization_loss {
+            }
+          }
+        }
+        object_center_params {
+          object_center_loss_weight: 1.0
+          min_box_overlap_iou: 0.7
+          max_box_predictions: 100
+          classification_loss {
+            penalty_reduced_logistic_focal_loss {
+              alpha: 2.0
+              beta: 4.0
+            }
+          }
+        }
+
+        deepmac_mask_estimation {
+          classification_loss {
+            weighted_sigmoid {}
+          }
+        }
+      }
+    """
+    # Set up the configuration proto.
+    config = text_format.Parse(proto_txt, model_pb2.DetectionModel())
+
+    # Build the model from the configuration.
+    model = model_builder.build(config, is_training=True)
+    self.assertIsInstance(model, deepmac_meta_arch.DeepMACMetaArch)
+
 
 if __name__ == '__main__':
   tf.test.main()