def test_load_dicom_image_random(test_output_dirs: OutputFolderForTests,
is_signed: bool, is_monochrome2: bool, bits_stored: int) -> None:
"""
Test loading of 2D Dicom images of type (uint16) and (int16).
"""
array_size = (20, 30)
if not is_signed:
array = np.random.randint(0, 200, size=array_size, dtype='uint16')
else:
array = np.random.randint(-200, 200, size=array_size, dtype='int16')
assert array.shape == array_size
if is_monochrome2:
to_write = array
else:
if not is_signed:
to_write = 2 ** bits_stored - 1 - array
else:
to_write = -1 * array - 1
dcm_file = test_output_dirs.root_dir / "file.dcm"
assert is_dicom_file_path(dcm_file)
write_test_dicom(array=to_write, path=dcm_file)
with mock.patch.object(sitk.ImageFileReader, 'GetMetaData',
new=get_mock_function(is_monochrome2=is_monochrome2, bits_stored=bits_stored)):
image = load_dicom_image(dcm_file)
assert image.ndim == 3 and image.shape == (1,) + array_size
assert np.array_equal(image, array[None, ...])
image_and_segmentation = load_image_in_known_formats(dcm_file, load_segmentation=False)
assert image_and_segmentation.images.ndim == 3 and image_and_segmentation.images.shape == (1,) + array_size
assert np.array_equal(image_and_segmentation.images, array[None, ...])
def plot_image_from_filepath(filepath: Path, im_size: Tuple) -> bool:
"""
Plots a 2D image given the filepath. Returns false if the image could not be plotted (for example, if it was 3D).
:param filepath: Path to image
:param im_size: Display size for image
:return: True if image was plotted, False otherwise
"""
image = load_image_in_known_formats(filepath,
load_segmentation=False).images
if not image.ndim == 2 and not (image.ndim == 3 and image.shape[0] == 1):
print_header(f"Image has unsupported shape {image.shape}", level=0)
return False
if image.ndim == 3 and image.shape[0] == 1:
image = image.squeeze(0)
# normalize to make sure pixels are plottable
min = image.min()
max = image.max()
image = (image - min) / (max - min)
image = image * 255.
image = np.repeat(image[:, :, None], 3, 2)
image = image.astype(np.uint8)
display(Image.fromarray(image).resize(im_size))
return True
def test_load_numpy_image(test_output_dirs: OutputFolderForTests) -> None:
array_size = (20, 30, 40)
array = np.ones(array_size)
assert array.shape == array_size
npy_file = test_output_dirs.root_dir / "file.npy"
assert is_numpy_file_path(npy_file)
np.save(npy_file, array)
image = load_numpy_image(npy_file)
assert image.shape == array_size
image_and_segmentation = load_image_in_known_formats(npy_file, load_segmentation=False)
assert image_and_segmentation.images.shape == array_size
def test_load_dicom_image_ones(test_output_dirs: TestOutputDirectories,
is_signed: bool, is_monochrome2: bool) -> None:
"""
Test loading of 2D Dicom images filled with binary array of type (uint16) and (int16).
"""
array_size = (20, 30)
if not is_signed:
array = np.ones(array_size, dtype='uint16')
array[::2] = 0
else:
array = -1 * np.ones(array_size, dtype='int16')
array[::2] = 0
assert array.shape == array_size
if is_monochrome2:
to_write = array
else:
if not is_signed:
to_write = np.zeros(array_size, dtype='uint16')
to_write[::2] = 1
else:
to_write = np.zeros(array_size, dtype='int16')
to_write[::2] = -1
dcm_file = Path(test_output_dirs.root_dir) / "file.dcm"
assert is_dicom_file_path(dcm_file)
write_test_dicom(array=to_write, path=dcm_file)
with mock.patch.object(sitk.ImageFileReader,
'GetMetaData',
new=get_mock_function(is_monochrome2=is_monochrome2,
bits_stored=1)):
image = load_dicom_image(dcm_file)
assert image.ndim == 3 and image.shape == (1, ) + array_size
assert np.array_equal(image, array[None, ...])
image_and_segmentation = load_image_in_known_formats(
dcm_file, load_segmentation=False)
assert image_and_segmentation.images.ndim == 3 and image_and_segmentation.images.shape == (
1, ) + array_size
assert np.array_equal(image_and_segmentation.images, array[None, ...])
def test_load_dicom_image_ones(test_output_dirs: OutputFolderForTests,
is_signed: bool, is_monochrome2: bool) -> None:
"""
Test loading of 2D Dicom images filled with binary array of type (uint16) and (int16).
"""
array_size = (20, 30)
if not is_signed:
array = np.ones(array_size, dtype='uint16')
array[::2] = 0
else:
array = -1 * np.ones(array_size, dtype='int16')
array[::2] = 0
assert array.shape == array_size
if is_monochrome2:
to_write = array
else:
if not is_signed:
to_write = np.zeros(array_size, dtype='uint16')
to_write[::2] = 1
else:
to_write = np.zeros(array_size, dtype='int16')
to_write[::2] = -1
dcm_file = test_output_dirs.root_dir / "file.dcm"
assert is_dicom_file_path(dcm_file)
write_test_dicom(array=to_write,
path=dcm_file,
is_monochrome2=is_monochrome2,
bits_stored=1)
image = load_dicom_image(dcm_file)
assert image.ndim == 2 and image.shape == array_size
assert np.array_equal(image, array)
image_and_segmentation = load_image_in_known_formats(
dcm_file, load_segmentation=False)
assert image_and_segmentation.images.ndim == 2 and image_and_segmentation.images.shape == array_size
assert np.array_equal(image_and_segmentation.images, array)
def test_load_dicom_image_random_signed(
test_output_dirs: TestOutputDirectories) -> None:
"""
Test loading of 2D Dicom images of type (int16).
"""
array_size = (20, 30)
array = np.random.randint(-200, 200, size=array_size, dtype='int16')
assert array.shape == array_size
dcm_file = Path(test_output_dirs.root_dir) / "file.dcm"
assert is_dicom_file_path(dcm_file)
write_test_dicom(array, dcm_file)
image = load_dicom_image(dcm_file)
assert image.ndim == 3 and image.shape == (1, ) + array_size
assert np.array_equal(image, array[None, ...])
image_and_segmentation = load_image_in_known_formats(
dcm_file, load_segmentation=False)
assert image_and_segmentation.images.ndim == 3 and image_and_segmentation.images.shape == (
1, ) + array_size
assert np.array_equal(image_and_segmentation.images, array[None, ...])
def test_load_image(file_path: str, expected_shape: Tuple) -> None:
full_file_path = full_ml_test_data_path() / file_path
image_and_segmentation = load_image_in_known_formats(full_file_path, load_segmentation=False)
assert image_and_segmentation.images.shape == expected_shape
