# registration methods from Open3D: 0-point-to-point icp; 1-point-to-plane icp; 2-GICP
registration_methods: 2
# set icp_max_distance when search the nearest point, larger value will make the search slower
icp_max_distance: 1.0

# accuracy_level, vector5d, we mainly use the result of the first element
# if inlier is very small, we can try to larger the value, e.g. for outdoors, [0.5, 0.3, 0.2, 0.1, 0.05]
accuracy_level: [0.2, 0.1, 0.08, 0.05, 0.01]

# initial_matrix, vector16d, the initial matrix of the registration
# make sure the format is correct, or you will got the error log: YAML::BadSubscript' what():  operator[] call on a scalar
# if you evaluate the LIO mapping result, you can use the CloudCompare to get the initial matrix first
initial_matrix:
  - [1.0, 0.0, 0.0, 0.0]
  - [0.0, 1.0, 0.0, 0.0]
  - [0.0, 0.0, 1.0, 0.0]
  - [0.0, 0.0, 0.0, 1.0]

# estimate map folder path, end with "/", make sure your estimate point cloud and map is renamed as "map.pcd"
# results path will also in the same folder:  estimate_map_path + "map_results"
estimate_map_path: /home/xchu/data/ltloc_result/parkinglot_raw_3_0.5/

# ground truth map file path
# note that we support ".pcd" or ".ply" format for ground truth map loading
gt_map_path: /media/xchu/e81eaf80-d92c-413a-a503-1c9b35b19963/home/xchu/data/evaluation/est_file/redbird_02/hkustgz_gt_filter.pcd


# scene name, not important, just for batch processing for a series of scenes
scene_name: redbird_02

# other settings
# if we save the immediate result to a text file
save_immediate_result: true

# if evaluate Mean Map Entropy (MME) if you do not have ground truth map
# but remember, MME can be only used for map comparison with the same scale, e.g., maps are for odometry.
# it costs a lot of time to calculate MME, so we set it as false by default
evaluate_mme: false

# if use TBB acceleration for MME calculation
use_tbb_mme: true

# if we have ground truth map, we also want to evaluate the MME of the ground truth map
evaluate_gt_mme: false

# NN search radius for MME calculation (m), larger value will make the search much more slower, even the memory overflow
nn_radius: 0.1

# if we want to evaluate the registration result using initial matrix without alignments, this operation will save time
# that means your estimate map is already aligned with the ground truth map, 
# or your estimate map and the ground truth map is already in the same coordinate system
# e.g. the estimate map is already aligned with the ground truth map
evaluate_using_initial: false

# we want to add noise to the ground truth map, and evaluate the registration result
# note that true will cause the system do not load the estimate map, instead the noise gt_map will be used
# just for algorithm robustness evaluation experiments, not for real-world application
# do not recommand to set it as true, since it will cause the memory overflow
evaluate_noise_gt: false

# vmd voxel size
# outdoor: 2.0-4.0; indoor: 2.0-3.0
vmd_voxel_size: 3.0

# downsample size for estimated and gt point cloud map
downsample_size: 0.01

# if show the evaluation error map after registration
use_visualization: true

# if print the debug info
enable_debug: false