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# Copyright 2023 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.
"""Tests for mask_ops.py."""
# Import libraries
import numpy as np
import tensorflow as tf, tf_keras
from official.vision.ops import mask_ops
class MaskUtilsTest(tf.test.TestCase):
def testPasteInstanceMasks(self):
image_height = 10
image_width = 10
mask_height = 6
mask_width = 6
masks = np.random.randint(0, 255, (1, mask_height, mask_width))
detected_boxes = np.array([[0.0, 2.0, mask_width, mask_height]])
_ = mask_ops.paste_instance_masks(
masks, detected_boxes, image_height, image_width)
def testPasteInstanceMasksV2(self):
image_height = 10
image_width = 10
mask_height = 6
mask_width = 6
masks = np.random.randint(0, 255, (1, mask_height, mask_width))
detected_boxes = np.array([[0.0, 2.0, mask_width, mask_height]])
image_masks = mask_ops.paste_instance_masks_v2(
masks, detected_boxes, image_height, image_width)
self.assertNDArrayNear(
image_masks[:, 2:8, 0:6],
np.array(masks > 0.5, dtype=np.uint8),
1e-5)
def testInstanceMasksOverlap(self):
boxes = tf.constant([[[0, 0, 4, 4], [1, 1, 5, 5]]])
masks = tf.constant([[
[
[0.9, 0.8, 0.1, 0.2],
[0.8, 0.7, 0.3, 0.2],
[0.6, 0.7, 0.4, 0.3],
[1.0, 0.7, 0.1, 0.0],
],
[
[0.9, 0.8, 0.8, 0.7],
[0.8, 0.7, 0.6, 0.8],
[0.1, 0.2, 0.4, 0.3],
[0.2, 0.1, 0.1, 0.0],
],
]])
gt_boxes = tf.constant([[[1, 1, 5, 5], [2, 2, 6, 6]]])
gt_masks = tf.constant([[
[
[1.0, 0.0, 0.0, 0.0],
[1.0, 0.0, 0.0, 0.0],
[1.0, 0.0, 0.0, 0.0],
[1.0, 0.0, 0.0, 0.0],
],
[
[1.0, 1.0, 1.0, 1.0],
[1.0, 1.0, 1.0, 1.0],
[1.0, 1.0, 1.0, 1.0],
[1.0, 1.0, 1.0, 1.0],
],
]])
iou, ioa = mask_ops.instance_masks_overlap(
boxes,
masks,
gt_boxes,
gt_masks,
output_size=[10, 10],
)
self.assertAllClose(iou, [[[1 / 3, 0], [1 / 5, 1 / 7]]], atol=1e-4)
self.assertAllClose(ioa, [[[3 / 8, 0], [1 / 4, 3 / 8]]], atol=1e-4)
if __name__ == '__main__':
tf.test.main()
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