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import tempfile |
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import unittest |
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from pathlib import Path |
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import torch |
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import numpy as np |
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import nibabel as nib |
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import SimpleITK as sitk |
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from ..utils import TorchioTestCase |
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from torchio.data import io, Image |
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11
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class TestIO(TorchioTestCase): |
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"""Tests for `io` module.""" |
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def setUp(self): |
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super().setUp() |
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self.write_dicom() |
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string = ( |
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'1.5 0.18088 -0.124887 0.65072 ' |
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'-0.20025 0.965639 -0.165653 -11.6452 ' |
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'0.0906326 0.18661 0.978245 11.4002 ' |
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'0 0 0 1 ' |
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) |
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tensor = torch.from_numpy(np.fromstring(string, sep=' ').reshape(4, 4)) |
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self.matrix = tensor |
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def write_dicom(self): |
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self.dicom_dir = self.dir / 'dicom' |
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self.dicom_dir.mkdir(exist_ok=True) |
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self.dicom_path = self.dicom_dir / 'dicom.dcm' |
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self.nii_path = self.get_image_path('read_image') |
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writer = sitk.ImageFileWriter() |
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writer.SetFileName(str(self.dicom_path)) |
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image = sitk.ReadImage(str(self.nii_path)) |
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image = sitk.Cast(image, sitk.sitkUInt16) |
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image = image[0] # dicom reader supports 2D only |
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writer.Execute(image) |
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38
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def test_read_image(self): |
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# I need to find something readable by nib but not sitk |
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io.read_image(self.nii_path) |
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io.read_image(self.nii_path, itk_first=True) |
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def test_read_dicom_file(self): |
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io.read_image(self.dicom_path) |
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def test_read_dicom_dir(self): |
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io.read_image(self.dicom_dir) |
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49
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def test_dicom_dir_missing(self): |
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with self.assertRaises(FileNotFoundError): |
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io._read_dicom('missing') |
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def test_dicom_dir_no_files(self): |
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empty = self.dir / 'empty' |
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empty.mkdir() |
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with self.assertRaises(FileNotFoundError): |
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io._read_dicom(empty) |
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def write_read_matrix(self, suffix): |
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out_path = self.dir / f'matrix{suffix}' |
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io.write_matrix(self.matrix, out_path) |
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matrix = io.read_matrix(out_path) |
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assert torch.allclose(matrix, self.matrix) |
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65
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def test_matrix_itk(self): |
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self.write_read_matrix('.tfm') |
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self.write_read_matrix('.h5') |
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68
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69
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def test_matrix_txt(self): |
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self.write_read_matrix('.txt') |
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72
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def save_load_save_load(self, dimensions): |
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path = self.dir / f'img{dimensions}d.nii' |
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shape = [4] |
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for _ in range(dimensions - 1): |
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shape.append(shape[-1] + 1) |
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nii = nib.Nifti1Image(np.random.rand(*shape), np.eye(4)) |
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nii.to_filename(path) |
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tensor, _ = io.read_image(path) |
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assert tensor.ndim == dimensions |
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image = Image(path) |
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image.save(path) |
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tensor, _ = io.read_image(path) |
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assert tensor.ndim == dimensions |
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86
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def test_nd(self): |
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87
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self.save_load_save_load(2) |
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88
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self.save_load_save_load(3) |
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89
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self.save_load_save_load(4) |
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90
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fepegar /
torchio
