# 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 os import tempfile import unittest import nibabel as nib import numpy as np from parameterized import parameterized from monai.data import Dataset from monai.transforms import Compose, LoadNiftid, SimulateDelayd TEST_CASE_1 = [(128, 128, 128)] class TestDataset(unittest.TestCase): @parameterized.expand([TEST_CASE_1]) def test_shape(self, expected_shape): test_image = nib.Nifti1Image(np.random.randint(0, 2, size=[128, 128, 128]), np.eye(4)) with tempfile.TemporaryDirectory() as tempdir: nib.save(test_image, os.path.join(tempdir, "test_image1.nii.gz")) nib.save(test_image, os.path.join(tempdir, "test_label1.nii.gz")) nib.save(test_image, os.path.join(tempdir, "test_extra1.nii.gz")) nib.save(test_image, os.path.join(tempdir, "test_image2.nii.gz")) nib.save(test_image, os.path.join(tempdir, "test_label2.nii.gz")) nib.save(test_image, os.path.join(tempdir, "test_extra2.nii.gz")) test_data = [ { "image": os.path.join(tempdir, "test_image1.nii.gz"), "label": os.path.join(tempdir, "test_label1.nii.gz"), "extra": os.path.join(tempdir, "test_extra1.nii.gz"), }, { "image": os.path.join(tempdir, "test_image2.nii.gz"), "label": os.path.join(tempdir, "test_label2.nii.gz"), "extra": os.path.join(tempdir, "test_extra2.nii.gz"), }, ] test_transform = Compose( [ LoadNiftid(keys=["image", "label", "extra"]), SimulateDelayd(keys=["image", "label", "extra"], delay_time=[1e-7, 1e-6, 1e-5]), ] ) dataset = Dataset(data=test_data, transform=test_transform) data1 = dataset[0] data2 = dataset[1] self.assertTupleEqual(data1["image"].shape, expected_shape) self.assertTupleEqual(data1["label"].shape, expected_shape) self.assertTupleEqual(data1["extra"].shape, expected_shape) self.assertTupleEqual(data2["image"].shape, expected_shape) self.assertTupleEqual(data2["label"].shape, expected_shape) self.assertTupleEqual(data2["extra"].shape, expected_shape) dataset = Dataset(data=test_data, transform=LoadNiftid(keys=["image", "label", "extra"])) data1_simple = dataset[0] data2_simple = dataset[1] self.assertTupleEqual(data1_simple["image"].shape, expected_shape) self.assertTupleEqual(data1_simple["label"].shape, expected_shape) self.assertTupleEqual(data1_simple["extra"].shape, expected_shape) self.assertTupleEqual(data2_simple["image"].shape, expected_shape) self.assertTupleEqual(data2_simple["label"].shape, expected_shape) self.assertTupleEqual(data2_simple["extra"].shape, expected_shape) if __name__ == "__main__": unittest.main()