Use Kitti Dataset¶
In this notebook a sample of the Kitti-Dataset will be downloaded, converted to a rosbag-file and the velodyne data will converted to a pcs-dataset.¶
Some usage examples are provided, too.¶
[2]:
from pathlib import Path
import pointcloudset as pcs
INFO - 2021-05-07 10:39:56,250 - _logger - Log opened: Fri May 7 10:39:56 2021 UTC
INFO - 2021-05-07 10:39:56,341 - topics - topicmanager initialized
The following terminal commands will download and unzip the kitti sample. We didn’t want to include the bag file in the repo as it is too large and to avoid any license issues. Also KITTI does not provide bag files directly. In order to get the data you need to run the following cell. If you are using pointcloudset in a docker container you need to run the commands outside of the docker to avoid nested docker commands. This is the reason for the commented docker command.
The docker container (https://hub.docker.com/r/yoyo860224/kitti2bag) is used to convert the kitta data into a rosbag-file. To run the docker under windows use “docker run -v “absolutepathtofolderwheredatais”:/data -it yoyo860224/kitti2bag -t 2011_09_26 -r 0002 raw_synced”.
[3]:
!wget https://s3.eu-central-1.amazonaws.com/avg-kitti/raw_data/2011_09_26_drive_0002/2011_09_26_drive_0002_sync.zip
!wget https://s3.eu-central-1.amazonaws.com/avg-kitti/raw_data/2011_09_26_calib.zip
!unzip 2011_09_26_drive_0002_sync.zip
!unzip 2011_09_26_calib.zip
#!docker run -v `pwd`:/data -it yoyo860224/kitti2bag -t 2011_09_26 -r 0002 raw_synced
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extracting: 2011_09_26/2011_09_26_drive_0002_sync/velodyne_points/data/0000000012.bin
extracting: 2011_09_26/2011_09_26_drive_0002_sync/velodyne_points/data/0000000059.bin
extracting: 2011_09_26/2011_09_26_drive_0002_sync/velodyne_points/data/0000000016.bin
extracting: 2011_09_26/2011_09_26_drive_0002_sync/velodyne_points/data/0000000067.bin
extracting: 2011_09_26/2011_09_26_drive_0002_sync/velodyne_points/data/0000000061.bin
extracting: 2011_09_26/2011_09_26_drive_0002_sync/velodyne_points/timestamps_start.txt
extracting: 2011_09_26/2011_09_26_drive_0002_sync/velodyne_points/timestamps_end.txt
Archive: 2011_09_26_calib.zip
extracting: 2011_09_26/calib_cam_to_cam.txt
extracting: 2011_09_26/calib_imu_to_velo.txt
extracting: 2011_09_26/calib_velo_to_cam.txt
[4]:
kittibag = Path().cwd().joinpath("kitti_2011_09_26_drive_0002_synced.bag")
testpath = Path().cwd().parent.joinpath("tests/testdata/kitti_velodyne")
Convert bagfile to pcs-dataset:
[5]:
kittiset = pcs.Dataset.from_file(kittibag,topic="/kitti/velo/pointcloud",keep_zeros=False)
100%|██████████| 77/77 [00:24<00:00, 3.17it/s]
[6]:
kittiset[0:3].to_file(testpath)
Files written to: /workspaces/lidar/tests/testdata/kitti_velodyne/kitti_2011_09_26_drive_0002_synced
Do some analysis:
[8]:
def isolate_target(frame: pcs.PointCloud) -> pcs.PointCloud:
return frame.limit("i",0.9,1)
[9]:
intense_points = isolate_target(kittiset[0])
[10]:
intense_points.plot(color = "i")
[ ]: