def test_downsize():
x = cp.zeros((10, 10), dtype=np.double)
x[2:4, 2:4] = 1
scaled = resize(x, (5, 5), order=0, anti_aliasing=False, mode="constant")
assert_array_equal(scaled.shape, (5, 5))
assert_array_equal(scaled[1, 1], 1)
assert_array_equal(scaled[2:, :].sum(), 0)
assert_array_equal(scaled[:, 2:].sum(), 0)
def test_bool_array_warnings():
img = cp.zeros((10, 10), dtype=bool)
with expected_warnings(["Input image dtype is bool"]):
rescale(img, 0.5, anti_aliasing=True)
with expected_warnings(["Input image dtype is bool"]):
resize(img, (5, 5), anti_aliasing=True)
with expected_warnings(["Input image dtype is bool"]):
rescale(img, 0.5, order=1)
with expected_warnings(["Input image dtype is bool"]):
resize(img, (5, 5), order=1)
with expected_warnings(["Input image dtype is bool"]):
warp(img, cp.eye(3), order=1)
def test_bool_img_resize():
img = cp.ones((12, 18), dtype=bool)
img[2:-2, 4:-4] = False
res = resize(img, (6, 9))
expected = cp.ones((6, 9))
expected[1:-1, 2:-2] = False
assert_array_equal(res, expected)
def test_resize3d_keep():
# keep 3rd dimension
x = cp.zeros((5, 5, 3), dtype=np.double)
x[1, 1, :] = 1
resized = resize(x, (10, 10),
order=0,
anti_aliasing=False,
mode="constant")
with pytest.raises(ValueError):
# output_shape too short
resize(x, (10, ), order=0, anti_aliasing=False, mode="constant")
ref = cp.zeros((10, 10, 3))
ref[2:4, 2:4, :] = 1
assert_array_almost_equal(resized, ref)
resized = resize(x, (10, 10, 3),
order=0,
anti_aliasing=False,
mode="constant")
assert_array_almost_equal(resized, ref)
def test_resize2d():
x = cp.zeros((5, 5), dtype=np.double)
x[1, 1] = 1
resized = resize(x, (10, 10),
order=0,
anti_aliasing=False,
mode="constant")
ref = cp.zeros((10, 10))
ref[2:4, 2:4] = 1
assert_array_almost_equal(resized, ref)
def test_resize3d_2din_3dout():
# 3D output with 2D input
x = cp.zeros((5, 5), dtype=np.double)
x[1, 1] = 1
resized = resize(x, (10, 10, 1),
order=0,
anti_aliasing=False,
mode="constant")
ref = cp.zeros((10, 10, 1))
ref[2:4, 2:4] = 1
assert_array_almost_equal(resized, ref)
def test_resize3d_resize():
# resize 3rd dimension
x = cp.zeros((5, 5, 3), dtype=np.double)
x[1, 1, :] = 1
resized = resize(x, (10, 10, 1),
order=0,
anti_aliasing=False,
mode="constant")
ref = cp.zeros((10, 10, 1))
ref[2:4, 2:4] = 1
assert_array_almost_equal(resized, ref)
def test_downsize_anti_aliasing_invalid_stddev():
x = cp.zeros((10, 10), dtype=np.double)
with pytest.raises(ValueError):
resize(
x,
(5, 5),
order=0,
anti_aliasing=True,
anti_aliasing_sigma=-1,
mode="constant",
)
with expected_warnings(["Anti-aliasing standard deviation greater"]):
resize(
x,
(5, 15),
order=0,
anti_aliasing=True,
anti_aliasing_sigma=(1, 1),
mode="reflect",
)
resize(
x,
(5, 15),
order=0,
anti_aliasing=True,
anti_aliasing_sigma=(0, 1),
mode="reflect",
)
def test_resize_dtype():
x = cp.zeros((5, 5))
x_f32 = x.astype(np.float32)
x_u8 = x.astype(np.uint8)
x_b = x.astype(bool)
assert resize(x, (10, 10), preserve_range=False).dtype == x.dtype
assert resize(x, (10, 10), preserve_range=True).dtype == x.dtype
assert resize(x_u8, (10, 10), preserve_range=False).dtype == np.double
assert resize(x_u8, (10, 10), preserve_range=True).dtype == np.double
assert resize(x_b, (10, 10), preserve_range=False).dtype == np.double
assert resize(x_b, (10, 10), preserve_range=True).dtype == np.double
assert resize(x_f32, (10, 10), preserve_range=False).dtype == x_f32.dtype
assert resize(x_f32, (10, 10), preserve_range=True).dtype == x_f32.dtype
def test_resize_nd():
for dim in range(1, 6):
shape = 2 + np.arange(dim) * 2
x = cp.ones(tuple(shape))
out_shape = np.asarray(shape) * 1.5
resized = resize(x,
out_shape,
order=0,
mode="reflect",
anti_aliasing=False)
expected_shape = 1.5 * shape
assert_array_equal(resized.shape, expected_shape)
assert cp.all(resized == 1)
def test_resize2d_4d():
# resize with extra output dimensions
x = cp.zeros((5, 5), dtype=np.double)
x[1, 1] = 1
out_shape = (10, 10, 1, 1)
resized = resize(x,
out_shape,
order=0,
anti_aliasing=False,
mode="constant")
ref = cp.zeros(out_shape)
ref[2:4, 2:4, ...] = 1
assert_array_almost_equal(resized, ref)
def test_resize3d_bilinear():
# bilinear 3rd dimension
x = cp.zeros((5, 5, 2), dtype=np.double)
x[1, 1, 0] = 0
x[1, 1, 1] = 1
resized = resize(x, (10, 10, 1),
order=1,
mode="constant",
anti_aliasing=False)
ref = cp.zeros((10, 10, 1))
ref[1:5, 1:5, :] = 0.03125
ref[1:5, 2:4, :] = 0.09375
ref[2:4, 1:5, :] = 0.09375
ref[2:4, 2:4, :] = 0.28125
assert_array_almost_equal(resized, ref)
def test_downsize_anti_aliasing():
x = cp.zeros((10, 10), dtype=np.double)
x[2, 2] = 1
scaled = resize(x, (5, 5), order=1, anti_aliasing=True, mode="constant")
assert_array_equal(scaled.shape, (5, 5))
assert cp.all(scaled[:3, :3] > 0)
assert_array_equal(scaled[3:, :].sum(), 0)
assert_array_equal(scaled[:, 3:].sum(), 0)
sigma = 0.125
out_size = (5, 5)
resize(
x,
out_size,
order=1,
mode="constant",
anti_aliasing=True,
anti_aliasing_sigma=sigma,
)
resize(
x,
out_size,
order=1,
mode="edge",
anti_aliasing=True,
anti_aliasing_sigma=sigma,
)
resize(
x,
out_size,
order=1,
mode="symmetric",
anti_aliasing=True,
anti_aliasing_sigma=sigma,
)
resize(
x,
out_size,
order=1,
mode="reflect",
anti_aliasing=True,
anti_aliasing_sigma=sigma,
)
resize(
x,
out_size,
order=1,
mode="wrap",
anti_aliasing=True,
anti_aliasing_sigma=sigma,
)
with pytest.raises(ValueError): # Unknown mode, or cannot translate mode
resize(
x,
out_size,
order=1,
mode="non-existent",
anti_aliasing=True,
anti_aliasing_sigma=sigma,
)