import tensorflow as tf

            samples_object = centernet_utils.transform_pointcloud(
                tf.reshape(samples_world, [1, 1, -1, 3]),
                tf.reshape(poses[2][i], [1, 1, 3]),
                tf.reshape(poses[0][i], [1, 1, 3, 3]),
                tf.reshape(poses[1][i], [1, 1, 3]), inverse=True) * 2.0
            samples_object = \
                (samples_object * (29.0/32.0) / 2.0 + 0.5) * 32.0 - 0.5
            samples = tf.squeeze(samples_object)
            interpolated = trilinear.interpolate(sdf, samples)

            sdf_values += tf.math.sign(tf.nn.relu(interpolated + self.tol))
            status2 = False
            if status2:
              a = 2
