Skip to content

Latest commit

 

History

History
97 lines (65 loc) · 2.41 KB

data.md

File metadata and controls

97 lines (65 loc) · 2.41 KB
Raw

RGB Image

The color images are stored as 640x480 8-bit RGB images in PNG format.

  • Load the image using OpenCV:
import cv2
img = cv2.imread(FILENAME)
cv2.imshow('img', img)
  • Load the image using Pillow:
from PIL import Image
img = Image.open(FILENAME)
img.show()

Camera intrinsics

fx = 320.0  # focal length x
fy = 320.0  # focal length y
cx = 320.0  # optical center x
cy = 240.0  # optical center y

fov = 90 deg # field of view    ??????????????

width = 640
height = 480

Depth image

The depth images are stored as 640x480 8-bit RGB images in PNG format.

The unit of the depth value is meter.

  • Load the depth image:
import cv2
depth = cv2.imread(FILENAME)

Semantic segmentation image

The semantic segmentation images are stored as 640x480 8-bit RGB images in PNG format.

  • Load the semantic segmentation image
import cv2
semantic = cv2.imread(FILENAME)

Change segmentation image

The semantic segmentation images are stored as 640x480 8-bit RGB images in PNG format.

  • Load the change segmentation image
import cv2
change = cv2.imread(FILENAME)

Pose file

The camera pose file is a text file containing the translation and orientation of the camera in a fixed coordinate frame. Note that our automatic evaluation tool expects both the ground truth trajectory and the estimated trajectory to be in this format.

  • Each line in the text file contains a single pose.

  • The number of lines/poses is the same as the number of image frames in that trajectory.

  • The format of each line is 'tx ty tz qx qy qz qw'.

  • tx ty tz (3 floats) give the position of the optical center of the color camera with respect to the world origin in the world frame.

  • qx qy qz qw (4 floats) give the orientation of the optical center of the color camera in the form of a unit quaternion with respect to the world frame.

  • The camera motion is defined in the NED frame. That is to say, the x-axis is pointing to the camera's forward, the y-axis is pointing to the camera's right, the z-axis is pointing to the camera's downward.

  • Load the pose file:

import numpy as np
pose = np.loadtxt(FILENAME)

Trajectory file

All poses mentioned above are merged into a trajectory.txt file for each sequence.

Rtabmap.db file

All data from the mapping stage. We can view using rtabmap-databaseViewer.

Cloud_map.ply file

3D reconstruction map from RTABMAP.