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e4b9a7b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 | # Copyright 2020 MONAI Consortium
# 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.
import unittest
import numpy as np
from parameterized import parameterized
from monai.transforms import AsChannelFirstd
TEST_CASE_1 = [{"keys": ["image", "label", "extra"], "channel_dim": -1}, (4, 1, 2, 3)]
TEST_CASE_2 = [{"keys": ["image", "label", "extra"], "channel_dim": 3}, (4, 1, 2, 3)]
TEST_CASE_3 = [{"keys": ["image", "label", "extra"], "channel_dim": 2}, (3, 1, 2, 4)]
class TestAsChannelFirstd(unittest.TestCase):
@parameterized.expand([TEST_CASE_1, TEST_CASE_2, TEST_CASE_3])
def test_shape(self, input_param, expected_shape):
test_data = {
"image": np.random.randint(0, 2, size=[1, 2, 3, 4]),
"label": np.random.randint(0, 2, size=[1, 2, 3, 4]),
"extra": np.random.randint(0, 2, size=[1, 2, 3, 4]),
}
result = AsChannelFirstd(**input_param)(test_data)
self.assertTupleEqual(result["image"].shape, expected_shape)
self.assertTupleEqual(result["label"].shape, expected_shape)
self.assertTupleEqual(result["extra"].shape, expected_shape)
if __name__ == "__main__":
unittest.main()
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