def test_set_patches_around_landmarks():
patch_shape = (21, 12)
image = mio.import_builtin_asset.lenna_png()
patches1 = image.extract_patches_around_landmarks(
patch_shape=patch_shape, as_single_array=True)
new_image1 = Image.init_blank(image.shape, image.n_channels)
new_image1.landmarks['LJSON'] = image.landmarks['LJSON']
new_image1.set_patches_around_landmarks(patches1)
patches2 = image.extract_patches_around_landmarks(
patch_shape=patch_shape, as_single_array=False)
new_image2 = Image.init_blank(image.shape, image.n_channels)
new_image2.landmarks['LJSON'] = image.landmarks['LJSON']
new_image2.set_patches_around_landmarks(patches2)
assert_array_equal(new_image1.pixels, new_image2.pixels)
def test_set_patches_around_landmarks():
patch_shape = (21, 12)
image = mio.import_builtin_asset.takeo_ppm()
patches1 = image.extract_patches_around_landmarks(patch_shape=patch_shape,
as_single_array=True)
new_image1 = Image.init_blank(image.shape, image.n_channels)
new_image1.landmarks["PTS"] = image.landmarks["PTS"]
extracted1 = new_image1.set_patches_around_landmarks(patches1)
patches2 = image.extract_patches_around_landmarks(patch_shape=patch_shape,
as_single_array=False)
new_image2 = Image.init_blank(image.shape, image.n_channels)
new_image2.landmarks["PTS"] = image.landmarks["PTS"]
extracted2 = new_image2.set_patches_around_landmarks(patches2)
assert_array_equal(extracted1.pixels, extracted2.pixels)
def test_set_patches_around_landmarks():
patch_shape = (21, 12)
image = mio.import_builtin_asset.takeo_ppm()
patches1 = image.extract_patches_around_landmarks(
patch_shape=patch_shape, as_single_array=True)
new_image1 = Image.init_blank(image.shape, image.n_channels)
new_image1.landmarks['PTS'] = image.landmarks['PTS']
extracted1 = new_image1.set_patches_around_landmarks(patches1)
patches2 = image.extract_patches_around_landmarks(
patch_shape=patch_shape, as_single_array=False)
new_image2 = Image.init_blank(image.shape, image.n_channels)
new_image2.landmarks['PTS'] = image.landmarks['PTS']
extracted2 = new_image2.set_patches_around_landmarks(patches2)
assert_array_equal(extracted1.pixels, extracted2.pixels)
def test_int_pointcloud():
image = Image.init_blank([100, 100])
patch_shape = (16, 16)
landmarks = PointCloud(np.array([[50, 50]]))
patches = image.extract_patches(
landmarks, patch_shape=patch_shape, as_single_array=False
)
assert patches[0].pixels.dtype == np.float
def test_uint16_type():
image = Image.init_blank([100, 100], dtype=np.uint16)
patch_shape = (16, 16)
landmarks = PointCloud(np.array([[50, 50.]]))
patches = image.extract_patches(landmarks,
patch_shape=patch_shape,
as_single_array=False)
assert (patches[0].pixels.dtype == np.uint16)
def test_int_pointcloud():
image = Image.init_blank([100, 100])
patch_shape = (16, 16)
landmarks = PointCloud(np.array([[50, 50]]))
patches = image.extract_patches(landmarks,
patch_shape=patch_shape,
as_single_array=False)
assert(patches[0].pixels.dtype == np.float)
def test_single_list_patch():
patch_shape = (21, 7)
n_channels = 4
im = Image.init_blank(patch_shape, n_channels)
patch = [Image(np.ones((n_channels,) + patch_shape)),
Image(2 * np.ones((n_channels,) + patch_shape))]
patch_center = PointCloud(np.array([[10., 3.], [11., 3.]]))
im.set_patches(patch, patch_center, offset=(0, 0), offset_index=0)
res = np.ones(patch_shape)
res[1:-1, :] = 2
assert_array_equal(im.pixels[2, ...], res)
def test_single_ndarray_patch():
patch_shape = (21, 7)
n_channels = 4
im = Image.init_blank(patch_shape, n_channels)
patch = np.zeros((2, 2, n_channels) + patch_shape)
patch[1, 0, ...] = np.ones((n_channels, ) + patch_shape)
patch[1, 1, ...] = 2 * np.ones((n_channels, ) + patch_shape)
patch_center = PointCloud(np.array([[10., 3.], [11., 3.]]))
new_im = im.set_patches(patch, patch_center, offset=(0, 0), offset_index=1)
res = np.zeros(patch_shape)
res[1:-1, :] = 2
assert_array_equal(new_im.pixels[2, ...], res)
def test_single_ndarray_patch():
patch_shape = (21, 7)
n_channels = 4
im = Image.init_blank(patch_shape, n_channels)
patch = np.zeros((2, 2, n_channels) + patch_shape)
patch[1, 0, ...] = np.ones((n_channels,) + patch_shape)
patch[1, 1, ...] = 2 * np.ones((n_channels,) + patch_shape)
patch_center = PointCloud(np.array([[10., 3.], [11., 3.]]))
new_im = im.set_patches(patch, patch_center, offset=(0, 0), offset_index=1)
res = np.zeros(patch_shape)
res[1:-1, :] = 2
assert_array_equal(new_im.pixels[2, ...], res)
def test_single_ndarray_patch():
patch_shape = (8, 7)
n_channels = 4
im = Image.init_blank((32, 32), n_channels)
patch = np.zeros((2, 2, n_channels) + patch_shape)
patch[0, 0, ...] = np.full((n_channels,) + patch_shape, 1) # Should be unused
patch[0, 1, ...] = np.full((n_channels,) + patch_shape, 2)
patch[1, 0, ...] = np.full((n_channels,) + patch_shape, 3) # Should be unused
patch[1, 1, ...] = np.full((n_channels,) + patch_shape, 4)
patch_center = PointCloud(np.array([[4.0, 4.0], [16.0, 16.0]]))
new_im = im.set_patches(patch, patch_center, offset_index=1)
res = np.zeros((32, 32))
res[:8, 1:8] = 2
res[12:20, 13:20] = 4
assert_array_equal(new_im.pixels[2], res)
def test_single_list_patch():
patch_shape = (8, 7)
n_channels = 4
im = Image.init_blank((32, 32), n_channels)
patch = [
Image(np.full((n_channels,) + patch_shape, 1)),
Image(np.full((n_channels,) + patch_shape, 2)), # Should be unused
Image(np.full((n_channels,) + patch_shape, 3)),
Image(np.full((n_channels,) + patch_shape, 4)),
] # Should be unused
patch_center = PointCloud(np.array([[4.0, 4.0], [16.0, 16.0]]))
new_im = im.set_patches(patch, patch_center, offset_index=0)
res = np.zeros((32, 32))
res[:8, 1:8] = 1
res[12:20, 13:20] = 3
assert_array_equal(new_im.pixels[0], res)
