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# coding=utf-8 | |
# Copyright 2021 The Deeplab2 Authors. | |
# | |
# 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 autoaugment_utils.py.""" | |
import numpy as np | |
import tensorflow as tf | |
from deeplab2.data.preprocessing import autoaugment_utils | |
class AutoaugmentUtilsTest(tf.test.TestCase): | |
def testAugmentWithNamedPolicy(self): | |
num_classes = 3 | |
np_image = np.random.randint(256, size=(13, 13, 3)) | |
image = tf.constant(np_image, dtype=tf.uint8) | |
np_label = np.random.randint(num_classes, size=(13, 13, 1)) | |
label = tf.constant(np_label, dtype=tf.int32) | |
image, label = autoaugment_utils.distort_image_with_autoaugment( | |
image, label, ignore_label=255, | |
augmentation_name='simple_classification_policy') | |
self.assertTrue(image.numpy().any()) | |
self.assertTrue(label.numpy().any()) | |
if __name__ == '__main__': | |
tf.test.main() | |