import `resize_and_rescale_offsets` fn

official/vision/beta/projects/panoptic_maskrcnn/ops/mask_ops.py

+# Copyright 2022 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.
+
+"""Utility functions for masks."""
+
+
+import tensorflow as tf
+
+
+def resize_and_rescale_offsets(input_tensor: tf.Tensor, target_size):
+  """Bilinearly resizes and rescales the offsets.
+  Args:
+    input_tensor: A tf.Tensor of shape [batch, height, width, 2].
+    target_size: A list or tuple or 1D tf.Tensor that specifies the height and
+      width after resizing.
+    reference: 
+      https://github.com/google-research/deeplab2/blob/main/model/utils.py#L157
+  Returns:
+    The input_tensor resized to shape `[batch, target_height, target_width, 2]`.
+      Moreover, the offsets along the y-axis are rescaled by a factor equal to
+      (target_height - 1) / (reference_height - 1) and the offsets along the
+      x-axis are rescaled by a factor equal to
+      (target_width - 1) / (reference_width - 1).
+  """
+  input_size_y = tf.shape(input_tensor)[1]
+  input_size_x = tf.shape(input_tensor)[2]
+
+  scale_y = tf.cast(target_size[0] - 1, tf.float32) / tf.cast(
+      input_size_y - 1, tf.float32)
+  scale_x = tf.cast(target_size[1] - 1, tf.float32) / tf.cast(
+      input_size_x - 1, tf.float32)
+
+  target_y, target_x = tf.split(
+      value=input_tensor, num_or_size_splits=2, axis=3)
+  target_y *= scale_y
+  target_x *= scale_x
+  target = tf.concat([target_y, target_x], 3)
+  return tf.image.resize(
+      input_tensor,
+      size=target_size,
+      method=tf.image.ResizeMethod.BILINEAR)