target assigner and similarity calculator fixes

research/object_detection/core/region_similarity_calculator.py

@@ -53,7 +53,7 @@ class RegionSimilarityCalculator(six.with_metaclass(ABCMeta, object)):
       a (float32) tensor of shape [N, M] with pairwise similarity score.
     """
     with tf.name_scope(scope, 'Compare', [boxlist1, boxlist2]) as scope:
-      return self._compare(boxlist1, boxlist2, groundtruth_labels, predicted_labels)
+      return self._compare(boxlist1, boxlist2)
 
   @abstractmethod
   def _compare(self, boxlist1, boxlist2,

research/object_detection/core/region_similarity_calculator_test.py

@@ -103,7 +103,8 @@ class RegionSimilarityCalculatorTest(test_case.TestCase):
       boxes2 = box_list.BoxList(corners2)
       boxes1.add_field(fields.BoxListFields.classes, groundtruth_labels)
       boxes2.add_field(fields.BoxListFields.classes, predicted_labels)
-      detr_similarity_calculator = region_similarity_calculator.DETRSimilarity()
+      detr_similarity_calculator = \
+          region_similarity_calculator.DETRSimilarity()
       detr_similarity = detr_similarity_calculator.compare(
           boxes1, boxes2, None)
       return detr_similarity

research/object_detection/core/target_assigner.py

@@ -437,9 +437,7 @@ def create_target_assigner(reference, stage=None,
     box_coder_instance = faster_rcnn_box_coder.FasterRcnnBoxCoder()
 
   elif reference == 'DETR':
-    similarity_calc = sim_calc.DETRSimilarity()
-    matcher = hungarian_matcher.HungarianBipartiteMatcher()
-    return DETRTargetAssigner(similarity_calc, matcher)
+    return DETRTargetAssigner()
 
   else:
     raise ValueError('No valid combination of reference and stage.')
@@ -1917,9 +1915,7 @@ class CenterNetCornerOffsetTargetAssigner(object):
 class DETRTargetAssigner(object):
   """Target assigner to compute classification and regression targets."""
 
-  def __init__(self,
-               matcher,
-               negative_class_weight=1.0):
+  def __init__(self, negative_class_weight=1.0):
     """Construct Object Detection Target Assigner.
 
     Args:
@@ -1931,8 +1927,6 @@ class DETRTargetAssigner(object):
         boxes (default: 1.0). The weight must be in [0., 1.].
 
     """
-    if not isinstance(matcher, mat.Matcher):
-      raise ValueError('matcher must be a Matcher')
     self._similarity_calc = sim_calc.DETRSimilarity()
     self._matcher = hungarian_matcher.HungarianBipartiteMatcher()
     self._negative_class_weight = negative_class_weight
@@ -2024,39 +2018,36 @@ class DETRTargetAssigner(object):
     groundtruth_boxes.add_field(fields.BoxListFields.classes, groundtruth_labels)
     box_preds.add_field(fields.BoxListFields.classes, class_predictions)
 
-    with tf.control_dependencies(
-        [unmatched_shape_assert, labels_and_box_shapes_assert]):
-      
-      match_quality_matrix = self._similarity_calc.compare(
-          groundtruth_boxes,
-          box_preds)
-      match = self._matcher.match(match_quality_matrix,
-                                  valid_rows=tf.greater(groundtruth_weights, 0))
+    match_quality_matrix = self._similarity_calc.compare(
+        groundtruth_boxes,
+        box_preds)
+    match = self._matcher.match(match_quality_matrix,
+                                valid_rows=tf.greater(groundtruth_weights, 0))
 
-      reg_targets = self._create_regression_targets(box_preds,
-                                                    groundtruth_boxes,
-                                                    match)
-      cls_targets = match.gather_based_on_match(
-          groundtruth_labels,
-          unmatched_value=unmatched_class_label,
-          ignored_value=unmatched_class_label)
-      reg_weights = match.gather_based_on_match(groundtruth_weights,
-                                                ignored_value=0.,
-                                                unmatched_value=0.)
-      cls_weights = match.gather_based_on_match(
-          groundtruth_weights,
-          ignored_value=0.,
-          unmatched_value=self._negative_class_weight)
-
-      # convert cls_weights from per-box_pred to per-class.
-      class_label_shape = tf.shape(cls_targets)[1:]
-      weights_shape = tf.shape(cls_weights)
-      weights_multiple = tf.concat(
-          [tf.ones_like(weights_shape), class_label_shape],
-          axis=0)
-      for _ in range(len(cls_targets.get_shape()[1:])):
-        cls_weights = tf.expand_dims(cls_weights, -1)
-      cls_weights = tf.tile(cls_weights, weights_multiple)
+    reg_targets = self._create_regression_targets(box_preds,
+                                                  groundtruth_boxes,
+                                                  match)
+    cls_targets = match.gather_based_on_match(
+        groundtruth_labels,
+        unmatched_value=unmatched_class_label,
+        ignored_value=unmatched_class_label)
+    reg_weights = match.gather_based_on_match(groundtruth_weights,
+                                              ignored_value=0.,
+                                              unmatched_value=0.)
+    cls_weights = match.gather_based_on_match(
+        groundtruth_weights,
+        ignored_value=0.,
+        unmatched_value=self._negative_class_weight)
+
+    # convert cls_weights from per-box_pred to per-class.
+    class_label_shape = tf.shape(cls_targets)[1:]
+    weights_shape = tf.shape(cls_weights)
+    weights_multiple = tf.concat(
+        [tf.ones_like(weights_shape), class_label_shape],
+        axis=0)
+    for _ in range(len(cls_targets.get_shape()[1:])):
+      cls_weights = tf.expand_dims(cls_weights, -1)
+    cls_weights = tf.tile(cls_weights, weights_multiple)
 
     num_box_preds = box_preds.num_boxes_static()
     if num_box_preds is not None:

research/object_detection/core/target_assigner_test.py

@@ -19,7 +19,6 @@ import tensorflow.compat.v1 as tf
 
 from object_detection.box_coders import keypoint_box_coder
 from object_detection.box_coders import mean_stddev_box_coder
-from object_detection.box_coders import detr_box_coder
 from object_detection.core import box_list
 from object_detection.core import region_similarity_calculator
 from object_detection.core import standard_fields as fields
@@ -2192,20 +2191,11 @@ class CornerOffsetTargetAssignerTest(test_case.TestCase):
     self.assertAllClose(foreground, np.zeros((1, 5, 5)))
 
 
-if __name__ == '__main__':
-  tf.enable_v2_behavior()
-  tf.test.main()
-
-
-class DETRTargetAssignerTest(testcase.TestCase):
+class DETRTargetAssignerTest(test_case.TestCase):
   def test_assign_detr(self):
     def graph_fn(anchor_means, groundtruth_box_corners,
                  groundtruth_labels, predicted_labels):
-      similarity_calc = region_similarity_calculator.DETRSimilarity()
-      matcher = hungarian_matcher.HungarianBipartiteMatcher()
-      box_coder = detr_box_coder.DETRBoxCoder()
-      detr_target_assigner = target_assigner.DETRTargetAssigner(
-          similarity_calc, matcher, box_coder)
+      detr_target_assigner = targetassigner.DETRTargetAssigner()
       anchors_boxlist = box_list.BoxList(anchor_means)
       groundtruth_boxlist = box_list.BoxList(groundtruth_box_corners)
       result = detr_target_assigner.assign(
@@ -2247,4 +2237,8 @@ class DETRTargetAssignerTest(testcase.TestCase):
     self.assertEqual(cls_targets_out.dtype, np.float32)
     self.assertEqual(cls_weights_out.dtype, np.float32)
     self.assertEqual(reg_targets_out.dtype, np.float32)
-    self.assertEqual(reg_weights_out.dtype, np.float32)
+    self.assertEqual(reg_weights_out.dtype, np.float32)
\ No newline at end of file
+
+if __name__ == '__main__':
+  tf.enable_v2_behavior()
+  tf.test.main()
\ No newline at end of file