def test_keep_size(self):
key = "img"
zoom_fn = Zoomd(key, zoom=0.6, keep_size=True)
zoomed = zoom_fn({key: self.imt[0]})
self.assertTrue(np.array_equal(zoomed[key].shape, self.imt.shape[1:]))
zoom_fn = Zoomd(key, zoom=1.3, keep_size=True)
zoomed = zoom_fn({key: self.imt[0]})
self.assertTrue(np.array_equal(zoomed[key].shape, self.imt.shape[1:]))
def test_keep_size(self):
key = "img"
zoom_fn = Zoomd(key,
zoom=0.6,
keep_size=True,
padding_mode="constant",
constant_values=2)
for p in TEST_NDARRAYS_ALL:
zoomed = zoom_fn({key: p(self.imt[0])})
np.testing.assert_array_equal(zoomed[key].shape,
self.imt.shape[1:])
zoom_fn = Zoomd(key, zoom=1.3, keep_size=True)
zoomed = zoom_fn({key: self.imt[0]})
self.assertTrue(
np.array_equal(zoomed[key].shape, self.imt.shape[1:]))
def test_gpu_zoom(self, _, zoom, order, mode, cval, prefilter):
key = "img"
if importlib.util.find_spec("cupy"):
zoom_fn = Zoomd(
key,
zoom=zoom,
interp_order=order,
mode=mode,
cval=cval,
prefilter=prefilter,
use_gpu=True,
keep_size=False,
)
zoomed = zoom_fn({key: self.imt[0]})
expected = list()
for channel in self.imt[0]:
expected.append(
zoom_scipy(channel,
zoom=zoom,
mode=mode,
order=order,
cval=cval,
prefilter=prefilter))
expected = np.stack(expected).astype(np.float32)
self.assertTrue(np.allclose(expected, zoomed[key]))
def test_correct_results(self, zoom, order, mode, cval, prefilter, use_gpu,
keep_size):
key = "img"
zoom_fn = Zoomd(
key,
zoom=zoom,
interp_order=order,
mode=mode,
cval=cval,
prefilter=prefilter,
use_gpu=use_gpu,
keep_size=keep_size,
)
zoomed = zoom_fn({key: self.imt[0]})
expected = list()
for channel in self.imt[0]:
expected.append(
zoom_scipy(channel,
zoom=zoom,
mode=mode,
order=order,
cval=cval,
prefilter=prefilter))
expected = np.stack(expected).astype(np.float32)
self.assertTrue(np.allclose(expected, zoomed[key]))
def test_correct_results(self, zoom, mode, keep_size):
key = "img"
zoom_fn = Zoomd(key, zoom=zoom, mode=mode, keep_size=keep_size,)
zoomed = zoom_fn({key: self.imt[0]})
_order = 0
if mode.endswith("linear"):
_order = 1
expected = list()
for channel in self.imt[0]:
expected.append(zoom_scipy(channel, zoom=zoom, mode="nearest", order=_order, prefilter=False))
expected = np.stack(expected).astype(np.float32)
np.testing.assert_allclose(expected, zoomed[key], atol=1.0)
def _zoom(x, scale: uniform = 1.0):
zoom = Zoomd(keys=['image'],
zoom=scale,
order=0,
mode='constant',
cval=0,
prefilter=True,
use_gpu=False,
keep_size=True)
data_dict = {'image': x.data}
zoom_dict = zoom(data_dict)
x = zoom_dict['image'][0]
x = torch.Tensor(x[None])
return x
def test_correct_results(self, zoom, mode, keep_size):
key = "img"
zoom_fn = Zoomd(key, zoom=zoom, mode=mode, keep_size=keep_size)
for p in TEST_NDARRAYS:
zoomed = zoom_fn({key: p(self.imt[0])})
_order = 0
if mode.endswith("linear"):
_order = 1
expected = [
zoom_scipy(channel,
zoom=zoom,
mode="nearest",
order=_order,
prefilter=False) for channel in self.imt[0]
]
expected = np.stack(expected).astype(np.float32)
assert_allclose(zoomed[key], p(expected), atol=1.0)
RandRotate90d(KEYS, prob=1, spatial_axes=(1, 2)),
))
TESTS.append(
("Spacingd 3d", "3D", 3e-2, Spacingd(KEYS, [0.5, 0.7, 0.9],
diagonal=False)))
TESTS.append(("Resized 2d", "2D", 2e-1, Resized(KEYS, [50, 47])))
TESTS.append(("Resized 3d", "3D", 5e-2, Resized(KEYS, [201, 150, 78])))
TESTS.append((
"Zoomd 1d",
"1D odd",
0,
Zoomd(KEYS, zoom=2, keep_size=False),
))
TESTS.append((
"Zoomd 2d",
"2D",
2e-1,
Zoomd(KEYS, zoom=0.9),
))
TESTS.append((
"Zoomd 3d",
"3D",
3e-2,
Zoomd(KEYS, zoom=[2.5, 1, 3], keep_size=False),
))
def test_invalid_inputs(self, _, zoom, mode, raises):
key = "img"
with self.assertRaises(raises):
zoom_fn = Zoomd(key, zoom=zoom, mode=mode)
zoom_fn({key: self.imt[0]})
def test_invalid_inputs(self, _, zoom, mode, raises):
key = "img"
for p in TEST_NDARRAYS_ALL:
with self.assertRaises(raises):
zoom_fn = Zoomd(key, zoom=zoom, mode=mode)
zoom_fn({key: p(self.imt[0])})
overwrite=True)))
TESTS.append((
"RandLambdad 3d",
"3D",
5e-2,
False,
RandLambdad(KEYS,
func=lambda x: x * 10,
inv_func=lambda x: x / 10,
overwrite=True,
prob=0.5),
))
TESTS.append(
("Zoomd 1d", "1D odd", 0, True, Zoomd(KEYS, zoom=2, keep_size=False)))
TESTS.append(("Zoomd 2d", "2D", 2e-1, True, Zoomd(KEYS, zoom=0.9)))
TESTS.append(("Zoomd 3d", "3D", 3e-2, True,
Zoomd(KEYS, zoom=[2.5, 1, 3], keep_size=False)))
TESTS.append(("RandZoom 3d", "3D", 9e-2, True,
RandZoomd(KEYS,
1, [0.5, 0.6, 0.9], [1.1, 1, 1.05],
keep_size=True)))
TESTS.append(("RandRotated, prob 0", "2D", 0, True,
RandRotated(KEYS, prob=0, dtype=np.float64)))
TESTS.append((
def test_invalid_inputs(self, _, zoom, order, raises):
key = "img"
with self.assertRaises(raises):
zoom_fn = Zoomd(key, zoom=zoom, interp_order=order)
zoom_fn({key: self.imt[0]})