Show mesh registration features in slam

# Authors: Guillaume Auzias <guillaume.auzias@univ-amu.fr>

# License: MIT
# sphinx_gallery_thumbnail_number = 2

importation of slam modules

import slam.io as sio
import trimesh
import numpy as np

loading an two unregistered meshes

mesh_1 = sio.load_mesh("../examples/data/example_mesh.gii")
mesh_2 = sio.load_mesh("../examples/data/example_mesh_2.gii")

compute ICP registration this functionnality requires to install the optional package rtree

transf_mat, cost = trimesh.registration.mesh_other(
    mesh_2, mesh_1, samples=500, scale=False, icp_first=10, icp_final=100
)
print(transf_mat)
print(cost)

[[  0.78477579   0.17383362  -0.59490237 -28.73670715]
 [ -0.61373281   0.08420819  -0.7850102   72.94997505]
 [ -0.08636551   0.98116811   0.17277194 -54.91419634]
 [  0.           0.           0.           1.        ]]
0.016860840686193996

VISUALIZATION USING plotly

# # plot them to check the misalignment
joint_mesh = mesh_1 + mesh_2
joint_tex = np.ones((joint_mesh.vertices.shape[0],))
joint_tex[: mesh_1.vertices.shape[0]] = 10

import slam.plot as splt

display_settings = {}
mesh_data = {}
mesh_data['vertices'] = joint_mesh.vertices
mesh_data['faces'] = joint_mesh.faces
mesh_data['title'] = 'Before Registration'
intensity_data = {}
intensity_data['values'] = joint_tex
intensity_data["mode"] = "vertex"
fig1 = splt.plot_mesh(
    mesh_data=mesh_data,
    intensity_data=intensity_data,
    display_settings=display_settings)
fig1.show()
fig1

apply the estimated rigid transformation to the mesh

mesh_2.apply_transform(transf_mat)
joint_mesh = mesh_1 + mesh_2

display_settings = {}
mesh_data = {}
mesh_data['vertices'] = joint_mesh.vertices
mesh_data['faces'] = joint_mesh.faces
mesh_data['title'] = 'After Registration'
intensity_data = {}
intensity_data['values'] = joint_tex
intensity_data["mode"] = "vertex"
fig2 = splt.plot_mesh(
    mesh_data=mesh_data,
    intensity_data=intensity_data,
    display_settings=display_settings)
fig2.show()
fig2