File size: 4,582 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 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 | # 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
import torch
from parameterized import parameterized
from monai.transforms import AffineGrid
TEST_CASES = [
[
{"as_tensor_output": False, "device": torch.device("cpu:0")},
{"spatial_size": (2, 2)},
np.array([[[-0.5, -0.5], [0.5, 0.5]], [[-0.5, 0.5], [-0.5, 0.5]], [[1.0, 1.0], [1.0, 1.0]]]),
],
[
{"as_tensor_output": True, "device": None},
{"spatial_size": (2, 2)},
torch.tensor([[[-0.5, -0.5], [0.5, 0.5]], [[-0.5, 0.5], [-0.5, 0.5]], [[1.0, 1.0], [1.0, 1.0]]]),
],
[{"as_tensor_output": False, "device": None}, {"grid": np.ones((3, 3, 3))}, np.ones((3, 3, 3))],
[{"as_tensor_output": True, "device": torch.device("cpu:0")}, {"grid": np.ones((3, 3, 3))}, torch.ones((3, 3, 3))],
[{"as_tensor_output": False, "device": None}, {"grid": torch.ones((3, 3, 3))}, np.ones((3, 3, 3))],
[
{"as_tensor_output": True, "device": torch.device("cpu:0")},
{"grid": torch.ones((3, 3, 3))},
torch.ones((3, 3, 3)),
],
[
{
"rotate_params": (1.0, 1.0),
"scale_params": (-20, 10),
"as_tensor_output": True,
"device": torch.device("cpu:0"),
},
{"grid": torch.ones((3, 3, 3))},
torch.tensor(
[
[[-19.2208, -19.2208, -19.2208], [-19.2208, -19.2208, -19.2208], [-19.2208, -19.2208, -19.2208]],
[[-11.4264, -11.4264, -11.4264], [-11.4264, -11.4264, -11.4264], [-11.4264, -11.4264, -11.4264]],
[[1.0, 1.0, 1.0], [1.0, 1.0, 1.0], [1.0, 1.0, 1.0]],
]
),
],
[
{
"rotate_params": (1.0, 1.0, 1.0),
"scale_params": (-20, 10),
"as_tensor_output": True,
"device": torch.device("cpu:0"),
},
{"grid": torch.ones((4, 3, 3, 3))},
torch.tensor(
[
[
[[-9.5435, -9.5435, -9.5435], [-9.5435, -9.5435, -9.5435], [-9.5435, -9.5435, -9.5435]],
[[-9.5435, -9.5435, -9.5435], [-9.5435, -9.5435, -9.5435], [-9.5435, -9.5435, -9.5435]],
[[-9.5435, -9.5435, -9.5435], [-9.5435, -9.5435, -9.5435], [-9.5435, -9.5435, -9.5435]],
],
[
[[-20.2381, -20.2381, -20.2381], [-20.2381, -20.2381, -20.2381], [-20.2381, -20.2381, -20.2381]],
[[-20.2381, -20.2381, -20.2381], [-20.2381, -20.2381, -20.2381], [-20.2381, -20.2381, -20.2381]],
[[-20.2381, -20.2381, -20.2381], [-20.2381, -20.2381, -20.2381], [-20.2381, -20.2381, -20.2381]],
],
[
[[-0.5844, -0.5844, -0.5844], [-0.5844, -0.5844, -0.5844], [-0.5844, -0.5844, -0.5844]],
[[-0.5844, -0.5844, -0.5844], [-0.5844, -0.5844, -0.5844], [-0.5844, -0.5844, -0.5844]],
[[-0.5844, -0.5844, -0.5844], [-0.5844, -0.5844, -0.5844], [-0.5844, -0.5844, -0.5844]],
],
[
[[1.0000, 1.0000, 1.0000], [1.0000, 1.0000, 1.0000], [1.0000, 1.0000, 1.0000]],
[[1.0000, 1.0000, 1.0000], [1.0000, 1.0000, 1.0000], [1.0000, 1.0000, 1.0000]],
[[1.0000, 1.0000, 1.0000], [1.0000, 1.0000, 1.0000], [1.0000, 1.0000, 1.0000]],
],
]
),
],
]
class TestAffineGrid(unittest.TestCase):
@parameterized.expand(TEST_CASES)
def test_affine_grid(self, input_param, input_data, expected_val):
g = AffineGrid(**input_param)
result = g(**input_data)
self.assertEqual(torch.is_tensor(result), torch.is_tensor(expected_val))
if torch.is_tensor(result):
np.testing.assert_allclose(result.cpu().numpy(), expected_val.cpu().numpy(), rtol=1e-4, atol=1e-4)
else:
np.testing.assert_allclose(result, expected_val, rtol=1e-4, atol=1e-4)
if __name__ == "__main__":
unittest.main()
|