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tartanvo_node.py
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tartanvo_node.py
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#!/usr/bin/env python
# Software License Agreement (BSD License)
#
# Copyright (c) 2020, Wenshan Wang, Yaoyu Hu, CMU
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions
# are met:
#
# * Redistributions of source code must retain the above copyright
# notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above
# copyright notice, this list of conditions and the following
# disclaimer in the documentation and/or other materials provided
# with the distribution.
# * Neither the name of CMU nor the names of its
# contributors may be used to endorse or promote products derived
# from this software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
# "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
# LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
# FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
# COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
# INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
# BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
# LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
# LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
# ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
# POSSIBILITY OF SUCH DAMAGE.
import cv2
import numpy as np
import rospy
from sensor_msgs.msg import Image, CameraInfo
from geometry_msgs.msg import PoseStamped
from nav_msgs.msg import Odometry
from std_msgs.msg import Float32
from cv_bridge import CvBridge
from Datasets.utils import ToTensor, Compose, CropCenter, DownscaleFlow, make_intrinsics_layer
from Datasets.transformation import se2SE, SO2quat
from TartanVO import TartanVO
import time
class TartanVONode(object):
def __init__(self):
model_name = rospy.get_param('~model_name', 'tartanvo_1914.pkl')
w = rospy.get_param('~image_width', 640)
h = rospy.get_param('~image_height', 480)
fx = rospy.get_param('~focal_x', 320.0)
fy = rospy.get_param('~focal_y', 320.0)
ox = rospy.get_param('~center_x', 320.0)
oy = rospy.get_param('~center_y', 240.0)
self.cam_intrinsics = [w, h, fx, fy, ox, oy]
self.cv_bridge = CvBridge()
self.transform = Compose([CropCenter((448, 640)), DownscaleFlow(), ToTensor()])#, Normalize(mean=[0., 0., 0.],std=[1., 1., 1.])])
self.intrinsic = make_intrinsics_layer(w, h, fx, fy, ox, oy)
self.tartanvo = TartanVO(model_name)
self.pose_pub = rospy.Publisher("tartanvo_pose", PoseStamped, queue_size=10)
self.odom_pub = rospy.Publisher("tartanvo_odom", Odometry, queue_size=10)
rospy.Subscriber('rgb_image', Image, self.handle_img)
rospy.Subscriber('cam_info', CameraInfo, self.handle_caminfo)
rospy.Subscriber('vo_scale', Float32, self.handle_scale)
self.last_img = None
self.pose = np.matrix(np.eye(4,4))
self.scale = 1.0
def handle_caminfo(self, msg):
w = msg.width
h = msg.height
fx = msg.K[0]
fy = msg.K[4]
ox = msg.K[2]
oy = msg.K[5]
new_intrinsics = [w, h, fx, fy, ox, oy]
change = [xx!=yy for xx,yy in zip(new_intrinsics, self.cam_intrinsics)]
if True in change:
self.intrinsic = make_intrinsics_layer(w, h, fx, fy, ox, oy)
self.cam_intrinsics = [w, h, fx, fy, ox, oy]
print('Camera intrinsics updated..')
def handle_scale(self, msg):
self.scale = msg.data
def handle_img(self, msg):
starttime = time.time()
image_np = self.cv_bridge.imgmsg_to_cv2(msg, "bgr8")
if image_np.shape[0] != self.intrinsic.shape[0] or image_np.shape[1] != self.intrinsic.shape[1]:
print('The intrinsic parameter does not match the image parameter!')
return
if self.last_img is not None:
pose_msg = PoseStamped()
pose_msg.header.stamp = msg.header.stamp
pose_msg.header.frame_id = 'map'
sample = {'img1': self.last_img,
'img2': image_np,
'intrinsic': self.intrinsic
}
sample = self.transform(sample)
sample['img1'] = sample['img1'][None] # increase the dimension
sample['img2'] = sample['img2'][None]
sample['intrinsic'] = sample['intrinsic'][None]
motion, _ = self.tartanvo.test_batch(sample)
motion = motion[0]
# adjust the scale if available
if self.scale!=1:
trans = motion[:3]
trans = trans / np.linalg.norm(trans) * self.scale
motion[:3] = trans
print(self.scale)
motion_mat = se2SE(motion)
self.pose = self.pose * motion_mat
quat = SO2quat(self.pose[0:3,0:3])
pose_msg.pose.position.x = self.pose[0,3]
pose_msg.pose.position.y = self.pose[1,3]
pose_msg.pose.position.z = self.pose[2,3]
pose_msg.pose.orientation.x = quat[0]
pose_msg.pose.orientation.y = quat[1]
pose_msg.pose.orientation.z = quat[2]
pose_msg.pose.orientation.w = quat[3]
self.pose_pub.publish(pose_msg)
odom_msg = Odometry()
odom_msg.header = pose_msg.header
odom_msg.pose.pose = pose_msg.pose
self.odom_pub.publish(odom_msg)
self.last_img = image_np.copy()
print(" call back time: {}:".format(time.time()-starttime))
if __name__ == '__main__':
rospy.init_node("tartanvo_node", log_level=rospy.INFO)
node = TartanVONode()
rospy.spin()