File size: 2,418 Bytes
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 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 | # 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 CropForegroundd
TEST_CASE_1 = [
{
"keys": ["img", "label"],
"source_key": "label",
"select_fn": lambda x: x > 0,
"channel_indices": None,
"margin": 0,
},
{
"img": np.array([[[1, 0, 2, 0, 1], [0, 1, 2, 1, 0], [2, 2, 3, 2, 2], [0, 1, 2, 1, 0], [1, 0, 2, 0, 1]]]),
"label": np.array([[[0, 0, 0, 0, 0], [0, 1, 0, 1, 0], [0, 0, 1, 0, 0], [0, 1, 0, 1, 0], [0, 0, 0, 0, 0]]]),
},
np.array([[[1, 2, 1], [2, 3, 2], [1, 2, 1]]]),
]
TEST_CASE_2 = [
{"keys": ["img"], "source_key": "img", "select_fn": lambda x: x > 1, "channel_indices": None, "margin": 0},
{"img": np.array([[[0, 0, 0, 0, 0], [0, 1, 1, 1, 0], [0, 1, 3, 1, 0], [0, 1, 1, 1, 0], [0, 0, 0, 0, 0]]])},
np.array([[[3]]]),
]
TEST_CASE_3 = [
{"keys": ["img"], "source_key": "img", "select_fn": lambda x: x > 0, "channel_indices": 0, "margin": 0},
{"img": np.array([[[0, 0, 0, 0, 0], [0, 1, 2, 1, 0], [0, 2, 3, 2, 0], [0, 1, 2, 1, 0], [0, 0, 0, 0, 0]]])},
np.array([[[1, 2, 1], [2, 3, 2], [1, 2, 1]]]),
]
TEST_CASE_4 = [
{"keys": ["img"], "source_key": "img", "select_fn": lambda x: x > 0, "channel_indices": None, "margin": 1},
{"img": np.array([[[0, 0, 0, 0, 0], [0, 1, 2, 1, 0], [0, 2, 3, 2, 0], [0, 0, 0, 0, 0], [0, 0, 0, 0, 0]]])},
np.array([[[0, 0, 0, 0, 0], [0, 1, 2, 1, 0], [0, 2, 3, 2, 0], [0, 0, 0, 0, 0]]]),
]
class TestCropForegroundd(unittest.TestCase):
@parameterized.expand([TEST_CASE_1, TEST_CASE_2, TEST_CASE_3, TEST_CASE_4])
def test_value(self, argments, image, expected_data):
result = CropForegroundd(**argments)(image)
np.testing.assert_allclose(result["img"], expected_data)
if __name__ == "__main__":
unittest.main()
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