def testRandomPadOrTrimToEmpty(self):
points = tf.constant([[1., 2., 3.]])
features = tf.constant([[100.]])
points, features = detection_3d_lib.RandomPadOrTrimTo(
[points[0:0], features[0:0]], 10, seed=123)[0]
with self.session() as sess:
points_np, features_np = sess.run([points, features])
self.assertAllClose(points_np, np.zeros(shape=(10, 3)))
self.assertAllClose(features_np, np.zeros(shape=(10, 1)))
def testRandomPadOrTrimToTrim(self):
points = tf.constant([[1., 2., 3.], [4., 5., 6.], [7., 8., 9.],
[10., 11., 12.]])
features = tf.constant([[100.], [200.], [300.], [400.]])
points, features = detection_3d_lib.RandomPadOrTrimTo(
[points, features], 2, seed=123)[0]
with self.session() as sess:
points_np, features_np = sess.run([points, features])
# Slicing choose a random 2 points.
self.assertAllClose([[1., 2., 3.], [10., 11., 12.]], points_np)
self.assertAllClose([[100.], [400.]], features_np)
def testRandomPadOrTrimToPad(self):
points = tf.constant([[1., 2., 3.], [4., 5., 6.], [7., 8., 9.],
[10., 11., 12.]])
features = tf.constant([[100.], [200.], [300.], [400.]])
points, features = detection_3d_lib.RandomPadOrTrimTo(
[points, features], 10, seed=123)[0]
with self.session() as sess:
points_np, features_np = sess.run([points, features])
# Padding repeats a random set of points.
self.assertAllClose([[1., 2., 3.], [1., 2., 3.], [10., 11., 12.],
[7., 8., 9.], [7., 8., 9.], [4., 5., 6.]],
points_np[4:])
self.assertAllClose(
[[100.], [100.], [400.], [300.], [300.], [200.]],
features_np[4:])
