Show mesh registration features in slam

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

# License: MIT
# sphinx_gallery_thumbnail_number = 2

NOTE: there is no visualization tool in slam, but we provide at the

end of this script exemplare code to do the visualization with an external solution

---

importation of slam modules

import slam.io as sio
import trimesh

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_1, mesh_2, samples=500, scale=False, icp_first=10, icp_final=100
)
print(transf_mat)
print(cost)

[[-0.59384355 -0.07673539  0.80091293 62.70247783]
 [ 0.09563733  0.98165202  0.16496308 52.87583172]
 [-0.7988763   0.17455944 -0.57560895 49.7707488 ]
 [ 0.          0.          0.          1.        ]]
0.01639672008364583

apply the estimated rigid transformation to the mesh

mesh_1.apply_transform(transf_mat)

<trimesh.Trimesh(vertices.shape=(2328, 3), faces.shape=(4652, 3))>

VISUALIZATION USING EXTERNAL TOOLS

# Visualization with visbrain import slam.plot as splt import numpy as np ############################################################################### # 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 visb_sc = splt.visbrain_plot(

mesh=joint_mesh, tex=joint_tex, caption=”before registration”

) visb_sc.preview() ############################################################################### # plot the two meshes to check they are now aligned joint_mesh = mesh_1 + mesh_2 visb_sc = splt.visbrain_plot(

mesh=joint_mesh, tex=joint_tex, caption=”after registration”

) visb_sc.preview()