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viz_raw_DIP_TC.py
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viz_raw_DIP_TC.py
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# Copyright (c) Meta, Inc. and its affiliates.
# Copyright (c) Stanford University
# untested helper script for your convenience
import importlib.util
import pybullet_data
import scipy
import sys
import pybullet as pb
import numpy as np
from fairmotion.ops import conversions
from fairmotion.core.motion import Motion
import bullet_client
from data_utils import draw_ori
from preprocess_DIP_TC_new import load_and_augment_dip_motion
from bullet_agent import SimAgent
import constants as cst
DT = 1. / 60
acc_fd_N = 4
DT_FIN_ACC = DT * acc_fd_N
WIN_LEN = 11
NOMINAL_H = 1.7
rot_up_R = cst.rot_up_R
np.set_printoptions(threshold=sys.maxsize)
np.set_printoptions(suppress=True)
motion_name_imu = 'data/TotalCapture_60FPS_Original/s1_freestyle3.pkl'
motion_name_gt = 'data/TotalCapture/s1/freestyle3_poses.npz'
# motion_name_gt = motion_name_imu = 'data/DIP_IMU/s_01/03.pkl'
# motion_name_gt = motion_name_imu = 'data/DIP_IMU/s_10/05.pkl'
ROOT_COM_OFFSET = np.array([0.0, 0.1, -0.1]) # 0.1m up, -0.1m back
# 1 TC, 0 DIP
if 1:
ROT_MAT = conversions.A2R(np.array([np.pi / 2, 0, 0]))
else:
ROT_MAT = rot_up_R
def viz_motion_and_imu_dip(m: Motion, imu_R: np.ndarray, imu_acc: np.ndarray):
cur_time = 0.0 / 2.0
imu_idx = 0
#
# link_ind = 11 # lknee
# link_ind_pb = char_info.lknee
# link_ind = 12 # rknee
# link_ind_pb = char_info.rknee
# link_ind = 8 # rwrist
# link_ind_pb = char_info.rwrist
link_ind = 7 # lwrist
link_ind_pb = char_info.lwrist
# link_ind = 0 # head
# link_ind_pb = char_info.upperneck
plot_log_real = []
plot_log_syn = []
while cur_time < 20.0: # test half
cur_pose = m.get_pose_by_time(cur_time)
robot.set_pose(cur_pose, None)
###########################################
real_imu_belly_a = [0., 0, 0]
imu_idx_prev = max(imu_idx - WIN_LEN//2, 0)
real_imu_belly_a_s = imu_acc[imu_idx_prev:imu_idx + (WIN_LEN//2+1), 2, :]
if np.all(np.isfinite(np.nanmean(real_imu_belly_a_s, axis=0))):
real_imu_belly_a = np.nanmean(real_imu_belly_a_s, axis=0)
# real_imu_belly_a = imu_acc[imu_idx, 2, :] # （3，） 2->belly
real_imu_belly_a = ROT_MAT.dot(real_imu_belly_a)
cur_xyz = robot.get_root_local_point_p(ROOT_COM_OFFSET)
prev_pose = m.get_pose_by_time(cur_time - DT_FIN_ACC)
robot2.set_pose(prev_pose, None)
prev_xyz = robot2.get_root_local_point_p(ROOT_COM_OFFSET)
next_pose = m.get_pose_by_time(cur_time + DT_FIN_ACC)
robot3.set_pose(next_pose, None)
next_xyz = robot3.get_root_local_point_p(ROOT_COM_OFFSET)
pb_belly_a = -2 * cur_xyz + prev_xyz + next_xyz
pb_belly_a /= (DT_FIN_ACC ** 2)
#
# pb_client.addUserDebugLine((0, 0, 0), list(pb_belly_a), (0, 1, 0), 5)
# pb_client.addUserDebugLine((0, 0, 0), list(real_imu_belly_a), (1, 0, 0), 5)
# all other five acc
real_imu_j_a = [0., 0, 0]
imu_idx_prev = max(imu_idx - WIN_LEN//2, 0)
real_imu_j_a_s = imu_acc[imu_idx_prev:imu_idx + (WIN_LEN//2+1), link_ind, :]
if np.all(np.isfinite(np.nanmean(real_imu_j_a_s, axis=0))):
real_imu_j_a = np.nanmean(real_imu_j_a_s, axis=0)
# real_imu_j_a = imu_acc[imu_idx, link_ind, :]
real_imu_j_a = ROT_MAT.dot(real_imu_j_a)
func = robot.get_link_states
func2 = robot2.get_link_states
func3 = robot3.get_link_states
cur_xyz_l = func([link_ind_pb])[0]
prev_pose = m.get_pose_by_time(cur_time - DT_FIN_ACC)
robot2.set_pose(prev_pose, None)
prev_xyz_l = func2([link_ind_pb])[0]
next_pose = m.get_pose_by_time(cur_time + DT_FIN_ACC)
robot3.set_pose(next_pose, None)
next_xyz_l = func3([link_ind_pb])[0]
pb_j_a = -2 * cur_xyz_l + prev_xyz_l + next_xyz_l
pb_j_a /= (DT_FIN_ACC ** 2)
# pb_client.addUserDebugLine((0, 0, 0), list(pb_j_a), (0, 1, 0), 5)
# pb_client.addUserDebugLine((0, 0, 0), list(real_imu_j_a), (1, 0, 0), 5)
# plot_log_real.append(real_imu_belly_a)
# plot_log_syn.append(pb_belly_a)
plot_log_real.append(real_imu_j_a - real_imu_belly_a)
plot_log_syn.append(pb_j_a - pb_belly_a)
#############################
# # root offset
# real_imu_belly_R = imu_R[imu_idx, 2, :, :] # (3,3)
# real_imu_belly_R = ROT_MAT.dot(real_imu_belly_R)
#
# _, pb_belly_q, _, _ = robot.get_root_state()
# pb_belly_R = conversions.Q2R(pb_belly_q)
#
# plot_log_real.append(np.diag(real_imu_belly_R))
# plot_log_syn.append(np.diag(pb_belly_R))
#
# draw_ori(pb_client, real_imu_belly_R)
# draw_ori(pb_client, pb_belly_R)
#
# any other link among the five IMUs
real_imu_j_R = imu_R[imu_idx, link_ind, :, :]
real_imu_j_R = ROT_MAT.dot(real_imu_j_R)
_, pb_j_q, _, _ = robot.get_link_states_joint_frame([link_ind_pb])
pb_j_R = conversions.Q2R(pb_j_q)
# plot_log_real.append(np.diag(real_imu_j_R))
# plot_log_syn.append(np.diag(pb_j_R))
# draw_ori(pb_client, real_imu_j_R)
# draw_ori(pb_client, pb_j_R)
# pb_client.removeAllUserDebugItems()
cur_time += DT
imu_idx += 1
plot_log_real = np.array(plot_log_real)
plot_log_syn = np.array(plot_log_syn)
plot_log_syn = scipy.ndimage.uniform_filter1d(plot_log_syn, WIN_LEN, axis=0)
from matplotlib import pyplot as plt
plt.subplot(3, 1, 1)
plt.plot(plot_log_real[:, 0])
plt.plot(plot_log_syn[:, 0])
plt.subplot(3, 1, 2)
plt.plot(plot_log_real[:, 1])
plt.plot(plot_log_syn[:, 1])
plt.subplot(3, 1, 3)
plt.plot(plot_log_real[:, 2])
plt.plot(plot_log_syn[:, 2])
plt.show()
return
Mode = pb.GUI
pb_client = bullet_client.BulletClient(
connection_mode=Mode)
pb_client.setAdditionalSearchPath(pybullet_data.getDataPath())
pb_client.resetSimulation()
dt_sim = 1. / 60.
''' Load Character Info Moudle '''
spec = importlib.util.spec_from_file_location(
"char_info", "amass_char_info.py")
char_info = importlib.util.module_from_spec(spec)
spec.loader.exec_module(char_info)
robot = SimAgent(name='sim_agent_0',
pybullet_client=pb_client,
model_file="data/amass.urdf",
char_info=char_info,
scale=NOMINAL_H / 1.6,
ref_scale=NOMINAL_H / 1.6,
self_collision=False,
# actuation=spd,
kinematic_only=False,
verbose=True)
robot2 = SimAgent(name='sim_agent_1',
pybullet_client=pb_client,
model_file="data/amass.urdf",
char_info=char_info,
scale=NOMINAL_H / 1.6,
ref_scale=NOMINAL_H / 1.6,
self_collision=False,
# actuation=spd,
kinematic_only=True,
verbose=True)
robot2.change_visual_color([0.05, 0.05, 0.05, 0.05])
robot3 = SimAgent(name='sim_agent_2',
pybullet_client=pb_client,
model_file="data/amass.urdf",
char_info=char_info,
scale=NOMINAL_H / 1.6,
ref_scale=NOMINAL_H / 1.6,
self_collision=False,
# actuation=spd,
kinematic_only=True,
verbose=True)
robot3.change_visual_color([0.05, 0.05, 0.05, 0.05])
motion, imu_R, imu_acc = load_and_augment_dip_motion(robot, motion_name_gt, motion_name_imu)
viz_motion_and_imu_dip(motion, imu_R, imu_acc)