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import torch |
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from torchio import RandomFlip |
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3
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from ...utils import TorchioTestCase |
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4
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5
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6
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class TestRandomFlip(TorchioTestCase): |
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"""Tests for `RandomFlip`.""" |
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def test_2d(self): |
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sample = self.make_2d(self.sample) |
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10
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transform = RandomFlip(axes=(1, 2), flip_probability=1) |
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transformed = transform(sample) |
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self.assertTensorEqual( |
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sample.t1.data.numpy()[..., ::-1, ::-1], |
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transformed.t1.data.numpy(), |
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15
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) |
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16
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17
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def test_out_of_range_axis(self): |
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with self.assertRaises(ValueError): |
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RandomFlip(axes=3) |
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21
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def test_out_of_range_axis_in_tuple(self): |
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with self.assertRaises(ValueError): |
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RandomFlip(axes=(0, -1, 2)) |
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25
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def test_wrong_axes_type(self): |
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with self.assertRaises(ValueError): |
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RandomFlip(axes=None) |
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29
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def test_wrong_flip_probability_type(self): |
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with self.assertRaises(ValueError): |
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RandomFlip(flip_probability='wrong') |
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32
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33
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def test_anatomical_axis(self): |
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transform = RandomFlip(axes=['i'], flip_probability=1) |
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tensor = torch.rand(1, 2, 3, 4) |
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transformed = transform(tensor) |
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self.assertTensorEqual( |
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tensor.numpy()[..., ::-1], |
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transformed.numpy(), |
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) |
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fepegar /
torchio
