updates

research/object_detection/core/box_list_ops.py

@@ -339,16 +339,12 @@ def giou_loss(boxlist1, boxlist2, scope=None):
   Returns:
     a tensor with shape [N, M] representing the pairwise GIoU loss.
   """
-  # Import done internally so this dependency is not required for
-  # the OD API as a whole.
-  import tensorflow_addons as tfa
-
   with tf.name_scope(scope, "PairwiseGIoU"):
     N = boxlist1.num_boxes()
     M = boxlist2.num_boxes()
     boxes1 = tf.repeat(boxlist1.get(), repeats=M, axis=0)
     boxes2 = tf.tile(boxlist2.get(), multiples=[N, 1])
-    return tf.reshape(tfa.losses.giou_loss(boxes1, boxes2), [N, M])
+    return tf.reshape(1.0 - ops.giou(boxes1, boxes2), [N, M])
 
 def matched_iou(boxlist1, boxlist2, scope=None):
   """Compute intersection-over-union between corresponding boxes in boxlists.
@@ -365,16 +361,11 @@ def matched_iou(boxlist1, boxlist2, scope=None):
     intersections = matched_intersection(boxlist1, boxlist2)
     areas1 = area(boxlist1)
     areas2 = area(boxlist2)
-    print("AREAS AND INTERSECTION", areas1, areas2, intersections)
     unions = areas1 + areas2 - intersections
     return tf.where(
         tf.equal(intersections, 0.0),
         tf.zeros_like(intersections), tf.truediv(intersections, unions))
 
-def matched_giou(boxlist1, boxlist2, scope=None):
-  with tf.name_scope(scope, 'MatchedGIOU'):
-    pass
-
 def ioa(boxlist1, boxlist2, scope=None):
   """Computes pairwise intersection-over-area between box collections.
 

research/object_detection/core/losses.py

@@ -37,7 +37,7 @@ from object_detection.core import box_list
 from object_detection.core import box_list_ops
 from object_detection.utils import ops
 from object_detection.utils import shape_utils
-import tensorflow_addons as tfa
+
 
 class Loss(six.with_metaclass(abc.ABCMeta, object)):
   """Abstract base class for loss functions."""
@@ -181,6 +181,7 @@ class WeightedSmoothL1LocalizationLoss(Loss):
         reduction=tf.losses.Reduction.NONE
     ), axis=2)
 
+
 class WeightedIOULocalizationLoss(Loss):
   """IOU localization loss function.
 
@@ -209,6 +210,8 @@ class WeightedIOULocalizationLoss(Loss):
                                                          target_boxes)
     return tf.reshape(weights, [-1]) * per_anchor_iou_loss
 
+
+
 class WeightedGIOULocalizationLoss(Loss):
   """IOU localization loss function.
 

research/object_detection/core/region_similarity_calculator.py

@@ -31,8 +31,6 @@ import tensorflow.compat.v1 as tf
 from object_detection.core import box_list_ops
 from object_detection.core import standard_fields as fields
 
-EPSILON = 1e-8
-
 class RegionSimilarityCalculator(six.with_metaclass(ABCMeta, object)):
   """Abstract base class for region similarity calculator."""
 
@@ -109,8 +107,8 @@ class DETRSimiliarity(RegionSimilarityCalculator):
     classification_scores = tf.matmul(groundtruth_labels,
         tf.nn.softmax(predicted_labels), transpose_b=True)
     return -5 * box_list_ops.l1(boxlist1, boxlist2) + \
-           classification_scores + \
-           2 * (1 - box_list_ops.giou_loss(boxlist1, boxlist2))
+           2 * (1 - box_list_ops.giou_loss(boxlist1, boxlist2)) + \
+           classification_scores
 
 class NegSqDistSimilarity(RegionSimilarityCalculator):
   """Class to compute similarity based on the squared distance metric.

research/object_detection/core/target_assigner.py

@@ -42,7 +42,6 @@ import tensorflow.compat.v2 as tf2
 
 from object_detection.box_coders import faster_rcnn_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_coder
 from object_detection.core import box_list
 from object_detection.core import box_list_ops