Skip to content

Fix bug in "xy" mode for bilinear interpolation #845

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 4 commits into from
Jan 9, 2020
Merged

Fix bug in "xy" mode for bilinear interpolation #845

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
4 commits
Select commit Hold shift + click to select a range
bd33479
Fix bug in "xy" mode for bilinear interpolation
djl11 Jan 9, 2020
70d1b47
fixed error in interp implementation, and added test for non-square i…
djl11 Jan 9, 2020
7478352
removed erroneous non-square test, and modified small_grid tests to b…
djl11 Jan 9, 2020
1d5e798
Lint
seanpmorgan Jan 9, 2020
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
4 changes: 2 additions & 2 deletions tensorflow_addons/image/dense_image_warp.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -116,11 +116,11 @@ def interpolate_bilinear(grid, query_points, indexing="ij", name=None):
index_order = [0, 1] if indexing == "ij" else [1, 0]
unstacked_query_points = tf.unstack(query_points, axis=2, num=2)

for dim in index_order:
for i, dim in enumerate(index_order):
with tf.name_scope("dim-" + str(dim)):
queries = unstacked_query_points[dim]

size_in_indexing_dimension = grid_shape[dim + 1]
size_in_indexing_dimension = grid_shape[i + 1]

# max_floor is size_in_indexing_dimension - 2 so that max_floor + 1
# is still a valid index into the grid.
Expand Down
24 changes: 15 additions & 9 deletions tensorflow_addons/image/dense_image_warp_test.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -30,22 +30,28 @@
@test_utils.run_all_in_graph_and_eager_modes
class InterpolateBilinearTest(tf.test.TestCase):
def test_interpolate_small_grid_ij(self):
grid = tf.constant([[0., 1., 2.], [3., 4., 5.], [6., 7., 8.]],
shape=[1, 3, 3, 1])
query_points = tf.constant([[0., 0.], [1., 0.], [2., 0.5], [1.5, 1.5]],
shape=[1, 4, 2])
expected_results = np.reshape(np.array([0., 3., 6.5, 6.]), [1, 4, 1])
grid = tf.constant(
[[0., 1., 2.], [3., 4., 5.], [6., 7., 8.], [9., 10., 11.]],
shape=[1, 4, 3, 1])
query_points = tf.constant(
[[0., 0.], [1., 0.], [2., 0.5], [1.5, 1.5], [3., 2.]],
shape=[1, 5, 2])
expected_results = np.reshape(
np.array([0., 3., 6.5, 6., 11.]), [1, 5, 1])

interp = interpolate_bilinear(grid, query_points)

self.assertAllClose(expected_results, interp)

def test_interpolate_small_grid_xy(self):
grid = tf.constant([[0., 1., 2.], [3., 4., 5.], [6., 7., 8.]],
shape=[1, 3, 3, 1])
grid = tf.constant(
[[0., 1., 2.], [3., 4., 5.], [6., 7., 8.], [9., 10., 11.]],
shape=[1, 4, 3, 1])
query_points = tf.constant(
[[0., 0.], [0., 1.], [0.5, 2.0], [1.5, 1.5]], shape=[1, 4, 2])
expected_results = np.reshape(np.array([0., 3., 6.5, 6.]), [1, 4, 1])
[[0., 0.], [0., 1.], [0.5, 2.0], [1.5, 1.5], [2., 3.]],
shape=[1, 5, 2])
expected_results = np.reshape(
np.array([0., 3., 6.5, 6., 11.]), [1, 5, 1])

interp = interpolate_bilinear(grid, query_points, indexing="xy")

Expand Down