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# This is a config file for the `TICPSequential.cpp` Example.
# When voxel_size is -1, no downsampling is performed.
# To run TICPSequential:
# 1. Download the Lyft dataset convert it to .pcd or .ply format.
# 2. Change the `dataset_path` accordingly.
# 4. Go to build/bin/examples
# 5. Run the following command:
# ./TICPSequential CPU:0 ../../../examples/cpp/registration_example_util/TICPSequentialConfigLyft.txt
# Change CPU:0 to CUDA:0 for running it on primary GPU.
# option to turn ON / OFF visualization:
visualization = ON
visualization_min = -1.0
visualization_max = 10.0
# Verbosity can be Info, Debug.
verbosity = Info
# Path of the downloaded dataset containing frames in .pcd or .ply format.
dataset_path = ../../../examples/test_data/open3d_downloads/datasets/lyft_samples/output/
# Range of frames is start_index to end_index.
start_index = 0
end_index = 500
# Registration method can be PointToPoint or PointToPlane.
registration_method = PointToPlane
# Multi-Scale ICP parameters:
# Scale 1:
voxel_size = 1.5
search_radii = 3.0
criteria.relative_fitness = 0.01
criteria.relative_rmse = 0.01
criteria.max_iterations = 10
# Scale 2:
voxel_size = 0.8
search_radii = 2.0
criteria.relative_fitness = 0.001
criteria.relative_rmse = 0.001
criteria.max_iterations = 10
# One can also add more scales ...
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