code/umi/traj_eval/compute_trajectory_errors.py

#!/usr/bin/env python2

import os
import numpy as np

import umi.traj_eval.trajectory_utils as tu
import umi.traj_eval.transformations as tf


def compute_relative_error(
    p_es, q_es, p_gt, q_gt, T_cm, dist, max_dist_diff, accum_distances=[], scale=1.0
):

    if len(accum_distances) == 0:
        accum_distances = tu.get_distance_from_start(p_gt)
    comparisons = tu.compute_comparison_indices_length(
        accum_distances, dist, max_dist_diff
    )

    n_samples = len(comparisons)
    print("number of samples = {0} ".format(n_samples))
    if n_samples < 2:
        print("Too few samples! Will not compute.")
        return (
            np.array([]),
            np.array([]),
            np.array([]),
            np.array([]),
            np.array([]),
            np.array([]),
            np.array([]),
        )

    T_mc = np.linalg.inv(T_cm)
    errors = []
    for idx, c in enumerate(comparisons):
        if not c == -1:
            T_c1 = tu.get_rigid_body_trafo(q_es[idx, :], p_es[idx, :])
            T_c2 = tu.get_rigid_body_trafo(q_es[c, :], p_es[c, :])
            T_c1_c2 = np.dot(np.linalg.inv(T_c1), T_c2)
            T_c1_c2[:3, 3] *= scale

            T_m1 = tu.get_rigid_body_trafo(q_gt[idx, :], p_gt[idx, :])
            T_m2 = tu.get_rigid_body_trafo(q_gt[c, :], p_gt[c, :])
            T_m1_m2 = np.dot(np.linalg.inv(T_m1), T_m2)

            T_m1_m2_in_c1 = np.dot(T_cm, np.dot(T_m1_m2, T_mc))
            T_error_in_c2 = np.dot(np.linalg.inv(T_m1_m2_in_c1), T_c1_c2)
            T_c2_rot = np.eye(4)
            T_c2_rot[0:3, 0:3] = T_c2[0:3, 0:3]
            T_error_in_w = np.dot(
                T_c2_rot, np.dot(T_error_in_c2, np.linalg.inv(T_c2_rot))
            )
            errors.append(T_error_in_w)

    error_trans_norm = []
    error_trans_perc = []
    error_yaw = []
    error_gravity = []
    e_rot = []
    e_rot_deg_per_m = []
    for e in errors:
        tn = np.linalg.norm(e[0:3, 3])
        error_trans_norm.append(tn)
        error_trans_perc.append(tn / dist * 100)
        ypr_angles = tf.euler_from_matrix(e, "rzyx")
        e_rot.append(tu.compute_angle(e))
        error_yaw.append(abs(ypr_angles[0]) * 180.0 / np.pi)
        error_gravity.append(
            np.sqrt(ypr_angles[1] ** 2 + ypr_angles[2] ** 2) * 180.0 / np.pi
        )
        e_rot_deg_per_m.append(e_rot[-1] / dist)
    return (
        errors,
        np.array(error_trans_norm),
        np.array(error_trans_perc),
        np.array(error_yaw),
        np.array(error_gravity),
        np.array(e_rot),
        np.array(e_rot_deg_per_m),
    )


def compute_temporal_relative_error(
    p_es, q_es, p_gt, q_gt, T_cm, window_steps, scale=1.0
):

    all_idxs = np.arange(len(p_gt))
    comparisons = list()
    for i in range(1, window_steps):
        comparisons.append(np.stack([all_idxs[:-i], all_idxs[i:]]).T)
    comparisons = np.concatenate(comparisons, axis=0)

    n_samples = len(comparisons)
    print("number of samples = {0} ".format(n_samples))
    if n_samples < 2:
        print("Too few samples! Will not compute.")
        return (
            np.array([]),
            np.array([]),
            np.array([]),
            np.array([]),
            np.array([]),
            np.array([]),
            np.array([]),
        )

    T_mc = np.linalg.inv(T_cm)
    errors = []
    # for idx, c in enumerate(comparisons):
    for idx, c in comparisons:
        if not c == -1:
            T_c1 = tu.get_rigid_body_trafo(q_es[idx, :], p_es[idx, :])
            T_c2 = tu.get_rigid_body_trafo(q_es[c, :], p_es[c, :])
            T_c1_c2 = np.dot(np.linalg.inv(T_c1), T_c2)
            T_c1_c2[:3, 3] *= scale

            T_m1 = tu.get_rigid_body_trafo(q_gt[idx, :], p_gt[idx, :])
            T_m2 = tu.get_rigid_body_trafo(q_gt[c, :], p_gt[c, :])
            T_m1_m2 = np.dot(np.linalg.inv(T_m1), T_m2)

            T_m1_m2_in_c1 = np.dot(T_cm, np.dot(T_m1_m2, T_mc))
            T_error_in_c2 = np.dot(np.linalg.inv(T_m1_m2_in_c1), T_c1_c2)
            T_c2_rot = np.eye(4)
            T_c2_rot[0:3, 0:3] = T_c2[0:3, 0:3]
            T_error_in_w = np.dot(
                T_c2_rot, np.dot(T_error_in_c2, np.linalg.inv(T_c2_rot))
            )
            errors.append(T_error_in_w)

    error_trans_norm = []
    error_yaw = []
    error_gravity = []
    e_rot = []
    for e in errors:
        tn = np.linalg.norm(e[0:3, 3])
        error_trans_norm.append(tn)
        ypr_angles = tf.euler_from_matrix(e, "rzyx")
        e_rot.append(tu.compute_angle(e))
        error_yaw.append(abs(ypr_angles[0]) * 180.0 / np.pi)
        error_gravity.append(
            np.sqrt(ypr_angles[1] ** 2 + ypr_angles[2] ** 2) * 180.0 / np.pi
        )
    return (
        errors,
        np.array(error_trans_norm),
        np.array(error_yaw),
        np.array(error_gravity),
        np.array(e_rot),
    )


def compute_absolute_error(p_es_aligned, q_es_aligned, p_gt, q_gt):
    e_trans_vec = p_gt - p_es_aligned
    e_trans = np.sqrt(np.sum(e_trans_vec**2, 1))

    # orientation error
    e_rot = np.zeros(
        (
            len(
                e_trans,
            )
        )
    )
    e_ypr = np.zeros(np.shape(p_es_aligned))
    for i in range(np.shape(p_es_aligned)[0]):
        R_we = tf.matrix_from_quaternion(q_es_aligned[i, :])
        R_wg = tf.matrix_from_quaternion(q_gt[i, :])
        e_R = np.dot(R_we, np.linalg.inv(R_wg))
        e_ypr[i, :] = tf.euler_from_matrix(e_R, "rzyx")
        e_rot[i] = np.rad2deg(np.linalg.norm(tf.logmap_so3(e_R[:3, :3])))

    # scale drift
    motion_gt = np.diff(p_gt, 0)
    motion_es = np.diff(p_es_aligned, 0)
    dist_gt = np.sqrt(np.sum(np.multiply(motion_gt, motion_gt), 1))
    dist_es = np.sqrt(np.sum(np.multiply(motion_es, motion_es), 1))
    e_scale_perc = np.abs((np.divide(dist_es, dist_gt) - 1.0) * 100)

    return e_trans, e_trans_vec, e_rot, e_ypr, e_scale_perc