fast_gicp iteration

[Lee-JaeWon]

I'm using fast_gicp bound to python.

How can I specify my own iteration here?

It would be nice to know the proper way to do it.

Thanks for the good work.

import pygicp

target = # Nx3 numpy array
source = # Mx3 numpy array

# 1. function interface
matrix = pygicp.align_points(target, source)

# optional arguments
# initial_guess               : Initial guess of the relative pose (4x4 matrix)
# method                      : GICP, VGICP, VGICP_CUDA, or NDT_CUDA
# downsample_resolution       : Downsampling resolution (used only if positive)
# k_correspondences           : Number of points used for covariance estimation
# max_correspondence_distance : Maximum distance for corresponding point search
# voxel_resolution            : Resolution of voxel-based algorithms
# neighbor_search_method      : DIRECT1, DIRECT7, DIRECT27, or DIRECT_RADIUS
# neighbor_search_radius      : Neighbor voxel search radius (for GPU-based methods)
# num_threads                 : Number of threads

# 2. class interface
# you may want to downsample the input clouds before registration
target = pygicp.downsample(target, 0.25)
source = pygicp.downsample(source, 0.25)

# pygicp.FastGICP has more or less the same interfaces as the C++ version
gicp = pygicp.FastGICP()
gicp.set_input_target(target)
gicp.set_input_source(source)
matrix = gicp.align()

# optional
gicp.set_num_threads(4)
gicp.set_max_correspondence_distance(1.0)
gicp.get_final_transformation()
gicp.get_final_hessian()

[koide3]

Sorry!! We are reducing the support for fast_gicp. Please consider using small_gicp, a new faster library with better portability. Meanwhile, feel free to open a PR if you have any improvements that can be merged into fast_gicp.