Sampling points with PyTorch3D

sample_points_from_obj_pytorch3d.py

# install direct from our forked repository: https://github.com/Esri/pytorch3d/tree/multitexture-obj-high-precision
!pip install 'git+https://github.com/Esri/pytorch3d.git@multitexture-obj-high-precision'

from pytorch3d.ops import sample_points_from_obj

(
    points, # points sampled proportional to face area
    normals, # point normals based on mesh verts
    textures, # point textures sampled from faces
    mappers # an index to each points origin face
) = sample_points_from_obj(
    verts=obj[0],
    faces=obj[1].verts_idx,
    verts_uvs=obj[2].verts_uvs,
    faces_uvs=obj[1].textures_idx,
    texture_images=obj[2].texture_images,
    materials_idx=obj[1].materials_idx,
    texture_atlas=obj[2].texture_atlas,
    sample_all_faces=True, # optionally force sampler to provide at least one point per face
    min_sampling_factor=100, # control how dense the point cloud is where 0 is least dense and 1000 is very dense
    return_mappers=True, # whether to return the point to face mapping
    return_textures=True, # whether to return textures per point
    return_normals=True # whether to return normals per point
)