pip install vbr-devkitYou can install autocompletion for our package by typing:
vbr --install-completionyou might need to restart the shell for the autocompletion to take effect.
You can list the available sequences you can download by typing:
vbr listYou should see something similar to this
After choosing your sequence, you can type
vbr download <sequence_name> <save_directory>For instance, we could save campus_train0 as follows:
vbr download campus_train0 ~/data/N.B. The script will actually save the sequence at <save_directory>/vbr_slam/<sequence_prefix>/<sequence_name>. Moreover, by calling the previous command, we expect the following directory:
data
- vbr_slam
- campus
- campus_train0
- vbr_calib.yaml
- campus_train0_gt.txt
- campus_train0_00.bag
- campus_train0_01.bag
- campus_train0_02.bag
- campus_train0_03.bag
- campus_train0_04.bag
The sequences are provided in ROS1 format. We offer a convenient tool to change representation if you prefer working on a different format. You can see the supported formats by typing:
vbr convert --helpTo convert a bag or a sequence of bags, type:
vbr convert <desired_format> <input_directory/input_bag> <output_directory>for instance, we could convert the campus_train0 sequence to kitti format as follows:
vbr convert kitti ~/data/vbr_slam/campus/campus_train0/campus_train0_00.bag ~/data/campus_train0_00_kitti/We can expect the following result:
data
- campus_train0_00_kitti
- camera_left
- timestamps.txt
- data
- 0000000000.png
- 0000000001.png
- ...
- camera_right
- timestamps.txt
- data
- 0000000000.png
- 0000000001.png
- ...
- ouster_points
- timestamps.txt
- data
- .dtype.pkl
- 0000000000.bin
- 0000000001.bin
- ...
- ...
N.B. In KITTI format, point clouds are embedded in binary files that can be opened using Numpy and pickle as follows:
import numpy as np
import pickle
with open("campus_train0_00_kitti/ouster_points/data/.dtype.pkl", "rb") as f:
cdtype = pickle.load(f)
cloud_numpy = np.fromfile("/campus_train0_00_kitti/ouster_points/data/0000000000.bin", dtype=cdtype)