def test_compute_centroid():
"""
Testing compute centroid function
and comparing to expected values.
"""
array_ones = np.ones((2, 2))
tensor_mask = np.zeros((3, 2, 2, 2))
tensor_mask[0, :, :, :] = array_ones
tensor_mask = tf.convert_to_tensor(tensor_mask, dtype=tf.float32)
tensor_grid = np.zeros((2, 2, 2, 3))
tensor_grid[:, :, :, 0] = array_ones
tensor_grid = tf.convert_to_tensor(tensor_grid, dtype=tf.float32)
expect = np.ones((3, 3))
expect[0, 1:3] = 0
get = label.compute_centroid(tensor_mask, tensor_grid)
assert is_equal_tf(get, expect)
def test_compute_centroid():
"""
Testing compute centroid function
and comparing to expected values.
"""
tensor_mask = np.zeros((3, 2, 2, 2))
tensor_mask[0, :, :, :] = np.ones((2, 2, 2))
tensor_mask = tf.constant(tensor_mask, dtype=tf.float32)
tensor_grid = np.ones((2, 2, 2, 3))
tensor_grid[:, :, :, 1] *= 2
tensor_grid[:, :, :, 2] *= 3
tensor_grid = tf.constant(tensor_grid, dtype=tf.float32)
expected = np.ones((3, 3)) # use 1 because 0/0 ~= (0+eps)/(0+eps) = 1
expected[0, :] = [1, 2, 3]
got = label.compute_centroid(tensor_mask, tensor_grid)
assert is_equal_tf(got, expected)