Internal change

PiperOrigin-RevId: 331045692

official/vision/beta/ops/anchor.py

@@ -17,12 +17,12 @@
 import collections
 # Import libraries
 import tensorflow as tf
+from official.vision import keras_cv
 from official.vision.beta.ops.experimental import anchor_generator
 from official.vision.detection.utils.object_detection import argmax_matcher
 from official.vision.detection.utils.object_detection import balanced_positive_negative_sampler
 from official.vision.detection.utils.object_detection import box_list
 from official.vision.detection.utils.object_detection import faster_rcnn_box_coder
-from official.vision.detection.utils.object_detection import region_similarity_calculator
 from official.vision.detection.utils.object_detection import target_assigner
 
 
@@ -135,7 +135,7 @@ class AnchorLabeler(object):
         upper-bound threshold to assign negative labels for anchors. An anchor
         with a score below the threshold is labeled negative.
     """
-    similarity_calc = region_similarity_calculator.IouSimilarity()
+    similarity_calc = keras_cv.ops.IouSimilarity()
     matcher = argmax_matcher.ArgMaxMatcher(
         match_threshold,
         unmatched_threshold=unmatched_threshold,

official/vision/detection/dataloader/anchor.py

@@ -21,11 +21,11 @@ from __future__ import print_function
 import collections
 
 import tensorflow as tf
+from official.vision import keras_cv
 from official.vision.detection.utils.object_detection import argmax_matcher
 from official.vision.detection.utils.object_detection import balanced_positive_negative_sampler
 from official.vision.detection.utils.object_detection import box_list
 from official.vision.detection.utils.object_detection import faster_rcnn_box_coder
-from official.vision.detection.utils.object_detection import region_similarity_calculator
 from official.vision.detection.utils.object_detection import target_assigner
 
 
@@ -134,7 +134,7 @@ class AnchorLabeler(object):
         upper-bound threshold to assign negative labels for anchors. An anchor
         with a score below the threshold is labeled negative.
     """
-    similarity_calc = region_similarity_calculator.IouSimilarity()
+    similarity_calc = keras_cv.ops.IouSimilarity()
     matcher = argmax_matcher.ArgMaxMatcher(
         match_threshold,
         unmatched_threshold=unmatched_threshold,

official/vision/detection/utils/object_detection/target_assigner.py

@@ -151,8 +151,8 @@ class TargetAssigner(object):
       groundtruth_weights = tf.ones([num_gt_boxes], dtype=tf.float32)
     with tf.control_dependencies(
         [unmatched_shape_assert, labels_and_box_shapes_assert]):
-      match_quality_matrix = self._similarity_calc.compare(
-          groundtruth_boxes, anchors)
+      match_quality_matrix = self._similarity_calc(
+          groundtruth_boxes.get(), anchors.get())
       match = self._matcher.match(match_quality_matrix, **params)
       reg_targets = self._create_regression_targets(anchors, groundtruth_boxes,
                                                     match)

official/vision/keras_cv/__init__.py

@@ -15,3 +15,4 @@
 """Keras-NLP package definition."""
 # pylint: disable=wildcard-import
 from official.vision.keras_cv.losses import *
+from official.vision.keras_cv.ops import *

official/vision/keras_cv/ops/__init__.py

+# Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+"""Keras-CV layers package definition."""
+from official.vision.keras_cv.ops.iou_similarity import IouSimilarity

official/vision/keras_cv/ops/iou_similarity.py

+# Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+"""Region Similarity Calculators."""
+
+import tensorflow as tf
+
+
+def area(box):
+  """Computes area of boxes.
+
+  Args:
+    box: a float Tensor with [N, 4].
+
+  Returns:
+    a float tensor with [N].
+  """
+  with tf.name_scope('Area'):
+    y_min, x_min, y_max, x_max = tf.split(
+        value=box, num_or_size_splits=4, axis=1)
+    return tf.squeeze((y_max - y_min) * (x_max - x_min), [1])
+
+
+def intersection(box1, box2):
+  """Compute pairwise intersection areas between boxes.
+
+  Args:
+    box1: a float Tensor with [N, 4].
+    box2: a float Tensor with [M, 4].
+
+  Returns:
+    a float tensor with shape [N, M] representing pairwise intersections
+  """
+  with tf.name_scope('Intersection'):
+    y_min1, x_min1, y_max1, x_max1 = tf.split(
+        value=box1, num_or_size_splits=4, axis=1)
+    y_min2, x_min2, y_max2, x_max2 = tf.split(
+        value=box2, num_or_size_splits=4, axis=1)
+    y_min_max = tf.minimum(y_max1, tf.transpose(a=y_max2))
+    y_max_min = tf.maximum(y_min1, tf.transpose(a=y_min2))
+    intersect_heights = tf.maximum(0.0, y_min_max - y_max_min)
+    x_min_max = tf.minimum(x_max1, tf.transpose(a=x_max2))
+    x_max_min = tf.maximum(x_min1, tf.transpose(a=x_min2))
+    intersect_widths = tf.maximum(0.0, x_min_max - x_max_min)
+    return intersect_heights * intersect_widths
+
+
+def iou(box1, box2):
+  """Computes pairwise intersection-over-union between box collections.
+
+  Args:
+    box1: a float Tensor with [N, 4].
+    box2: a float Tensor with [M, 4].
+
+  Returns:
+    a tensor with shape [N, M] representing pairwise iou scores.
+  """
+  intersections = intersection(box1, box2)
+  areas1 = area(box1)
+  areas2 = area(box2)
+  unions = (
+      tf.expand_dims(areas1, 1) + tf.expand_dims(areas2, 0) - intersections)
+  return tf.where(
+      tf.equal(intersections, 0.0), tf.zeros_like(intersections),
+      tf.truediv(intersections, unions))
+
+
+class IouSimilarity():
+  """Class to compute similarity based on Intersection over Union (IOU) metric.
+
+  """
+
+  def __call__(self, groundtruth_boxes, anchors):
+    """Compute pairwise IOU similarity between ground truth boxes and anchors.
+
+    Args:
+      groundtruth_boxes: a float Tensor with N boxes.
+      anchors: a float Tensor with M boxes.
+
+    Returns:
+      A tensor with shape [N, M] representing pairwise iou scores.
+
+    Input shape:
+      groundtruth_boxes: [N, 4]
+      anchors: [M, 4]
+
+    Output shape:
+      [N, M]
+    """
+    with tf.name_scope('IOU'):
+      return iou(groundtruth_boxes, anchors)