# This is a config file for the `TICPSequential.cpp` Example.
# When voxel_size is -1, no downsampling is performed.
# To run TICPSequential:
# 1. Run the `download_kitti.py` script.
#    python3 download_kitti.py 
#    This will download a city sequence in examples/test_data/open3d_downloads/datasets/kitti_samples/
#    if it does not exists, and save the processed frames in `/output/`.
# 2. If you are downloading it anywhere else, change the `dataset_path` accordingly.
# 3. Go to build/bin/examples directory.
# 4. Run the following command:
# ./TICPSequential CPU:0 ../../../examples/cpp/registration_example_util/TICPOdomConfigKitti.txt
# Change CPU:0 to CUDA:0 for running it on primary GPU.

# option to turn ON / OFF visualization:
visualization = ON
visualization_min = -1.5
visualization_max = 1.5

# 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/kitti_samples/output/

# Range of frames is start_index to end_index.
start_index = 0
end_index = 1000 

# Registration method can be PointToPoint or PointToPlane.
registration_method = PointToPlane

# Multi-Scale ICP parameters:

# Scale 1:
 voxel_size = 0.8
 search_radii = 1.2
 criteria.relative_fitness = 0.01
 criteria.relative_rmse = 0.01
 criteria.max_iterations = 10

# Scale 2:
 voxel_size = 0.5
 search_radii = 1.0
 criteria.relative_fitness = 0.001
 criteria.relative_rmse = 0.001
 criteria.max_iterations = 10

# One can also add more scales ...