config.yaml

# Comments are denoted by #

CORE_LIB_PATHS:
  # core libs are automatically imported by using: 
  # import config 
  g2o: thirdparty/g2opy/lib
  pangolin: thirdparty/pangolin
  orb_features: thirdparty/orbslam2_features/lib
  pyslam_utils: cpp/utils/lib
  thirdparty: thirdparty  # considering the folders in thirdparty as modules

LIB_PATHS:
  # the following libs are explicitely imported on demand by using, for instance:
  # import config \ config.cfg.set_lib('tfeat')
  lightglue: thirdparty/LightGlue
  xfeat: thirdparty/accelerated_features
  superpoint: thirdparty/superpoint
  hardnet: thirdparty/hardnet
  tfeat: thirdparty/tfeat
  geodesc: thirdparty/geodesc
  sosnet: thirdparty/SOSNet/codes 
  l2net: thirdparty/l2net
  l2net_keras: thirdparty/l2net_keras/src 
  logpolar: thirdparty/logpolar
  d2net: thirdparty/d2net 
  delf: thirdparty/tensorflow_models/research/delf,thirdparty/tensorflow_models/research/slim,thirdparty/tensorflow_models/research/
  contextdesc: thirdparty/contextdesc
  lfnet: thirdparty/lfnet
  r2d2: thirdparty/r2d2
  keynet: thirdparty/keynet
  disk: thirdparty/disk
  torch-dimcheck: thirdparty/disk/submodules/torch-dimcheck
  torch-localize: thirdparty/disk/submodules/torch-localize
  unets: thirdparty/disk/submodules/unets


DATASET:
  # select your dataset (decomment only one of the following lines!) 
  #type: EUROC_DATASET  
  #type: KITTI_DATASET
  #type: TUM_DATASET
  type: VIDEO_DATASET
  #type: FOLDER_DATASET
  #type: LIVE_DATASET  # Not recommended for current development stage


KITTI_DATASET:
  type: kitti
  sensor_type: stereo # here, sensor_type can be 'mono' or 'stereo'
  base_path: /home/luigi/Work/datasets/rgbd_datasets/kitti_color/dataset
  #
  name: '06'
  settings: settings/KITTI04-12.yaml # do not forget to set the corresponding camera settings file 
  #
  #name: '00'
  #settings: settings/KITTI00-02.yaml # do not forget to set the corresponding camera settings file 
  #
  is_color: True # do you have the color images for the kitti dataset? (image2 and image3 folders)
  groundtruth_file: auto


TUM_DATASET:
  type: tum
  sensor_type: rgbd # here, sensor_type can be 'mono' or 'rgbd'
  base_path: /home/luigi/Work/datasets/rgbd_datasets/tum
  #
  name: rgbd_dataset_freiburg1_room 
  settings: settings/TUM1.yaml # do not forget to set the corresponding camera settings file 
  #
  # name: rgbd_dataset_freiburg3_long_office_household
  # settings: settings/TUM3.yaml # do not forget to set the corresponding camera settings file  
  #
  associations: associations.txt
  groundtruth_file: auto


EUROC_DATASET:
  type: euroc
  sensor_type: stereo # here, sensor_type can be 'mono' or 'stereo'
  base_path: /home/luigi/Work/datasets/rgbd_datasets/euroc
  #name: MH01
  name: V102
  # 'settings' will be used when sensor_type: : 'mono'
  settings: settings/EuRoC_mono.yaml
  # 'settings_stereo' will be used when sensor_type: : 'stereo' (if available)
  settings_stereo: settings/EuRoC_stereo.yaml
  associations: associations.txt
  groundtruth_file: auto
  start_frame_id: 0


VIDEO_DATASET:
  type: video
  # here, sensor_type can be only 'mono' 
  sensor_type: mono
  #
  #base_path: ./videos/kitti00
  #settings: settings/KITTI00-02.yaml
  #name: video.mp4
  #
  base_path: ./videos/kitti06
  settings: settings/KITTI04-12.yaml
  name: video_color.mp4
  #
  #base_path: ./videos/webcam
  #settings: settings/WEBCAM.yaml 
  #name: video.mp4
  #
  groundtruth_file: groundtruth.txt


FOLDER_DATASET:
  type: folder 
  # here, sensor_type can be only 'mono'
  sensor_type: mono 
  base_path: /home/luigi/Work/rgbd_datasets2/kitti/dataset/sequences/00/image_0/
  # name is used for specifying a glob pattern, e.g. *png, *jpeg, etc...
  name: '*png'  
  settings: settings/KITTI00-02.yaml
  groundtruth_file: groundtruth.txt
  fps: 20 


# DO NOT USE [LIVE_DATASET]! This section is here for future developments. 
# At the present time (see the README file):
# - main_vo.py cannot be used with your webcam since it requires a grountruth for recovering a correct inter-frame scale (see the README file) 
# - main_slam.py does NOT have REAL-TIME processing capabilities yet!
# If you want to use your webcam, please, record a video by using calibration/save_video.py and then use it as a VIDEO_DATASET
LIVE_DATASET: 
  type: live 
  base_path: 
  name: /dev/video2
  settings: settings/WEBCAM.yaml 
  groundtruth_file: auto


SAVE_TRAJECTORY:
  save_trajectory: True
  format_type: kitti    # supported formats: `tum`, `kitti`, `euroc`
  filename: kitti_trajectory.txt