def test_hdf5_loading_multimap() -> None:
"""
Check that multimap returns correct image
"""
image_header = io_util.load_image(f"{good_h5_path}|segmentation|0")
seg_header = io_util.load_image(f"{good_h5_path}|segmentation|0|1")
expected = image_header.image == 1
assert np.array_equal(expected, seg_header.image)
def test_hdf5_loading() -> None:
"""
Check that when we access and invalid dataset we get a good exception
"""
with pytest.raises(ValueError) as valueError:
io_util.load_image(f"{good_h5_path}|doesnotexist|0|1")
assert str(good_h5_path) in str(valueError.value)
assert "doesnotexist" in str(valueError.value)
def _test_load_images_from_channels(
metadata: Any,
image_channel: Any,
ground_truth_channel: Any,
mask_channel: Any) -> None:
"""
Test if images are loaded as expected from channels
"""
sample = io_util.load_images_from_dataset_source(
PatientDatasetSource(
metadata=metadata,
image_channels=[image_channel] * 2,
ground_truth_channels=[ground_truth_channel] * 4,
mask_channel=mask_channel
)
)
if image_channel:
image_with_header = io_util.load_image(image_channel)
assert list(sample.image.shape) == [2] + list(image_with_header.image.shape)
assert all([np.array_equal(x, image_with_header.image) for x in sample.image]) # type: ignore
if mask_channel:
assert np.array_equal(sample.mask, image_with_header.image)
if ground_truth_channel:
assert list(sample.labels.shape) == [5] + list(image_with_header.image.shape)
assert np.all(sample.labels[0] == 0) and np.all(sample.labels[1:] == 1)
def test_hdf5_loading_multimap_class_do_not_exists() -> None:
"""
Check that multimap returns correct image if class does not exist
"""
seg_header = io_util.load_image(
f"{good_h5_path}|segmentation|0|555555555555")
assert np.all(seg_header.image == 0)
def save_and_reload_image(
data: np.array, # type: ignore
mode: str) -> None:
path = test_output_dirs.root_dir / f"{mode}.png"
image = Image.fromarray(data, mode=mode)
image.save(path)
scipy_image = imageio.imread(path).astype(np.float)
assert scipy_image.dtype == np.float # type: ignore
assert np.array_equal(data, scipy_image)
image_with_header = io_util.load_image(path)
assert image_with_header.image.dtype == np.float # type: ignore
assert np.array_equal(data, image_with_header.image)
