Hướng dẫn ply python

Contents

In this post, I want to share how to generate ply files in Python.

Open3D

We can use open3d. We can use pip to install it:

For CentOS 7, I met error when installing the latest version:

/lib64/libc.so.6: version `GLIBC_2.18' not found

A workaround is to use older versions:

pip install open3d==0.9.0

See also issue here for more discussions.

Below is is a simple snippet showing to read and write ply files using open3d.

import numpy as np
import open3d as o3d

def main[]:
    pts = np.random.randint[0, 100, [100, 3]]

    # whether to write in binary or text format
    write_text = True

    # use open3d
    use_o3d[pts, write_text]


def use_o3d[pts, write_text]:
    pcd = o3d.geometry.PointCloud[]

    # the method Vector3dVector[] will convert numpy array of shape [n, 3] to Open3D format.
    # see //www.open3d.org/docs/release/python_api/open3d.utility.Vector3dVector.html#open3d.utility.Vector3dVector
    pcd.points = o3d.utility.Vector3dVector[pts]

    # //www.open3d.org/docs/release/python_api/open3d.io.write_point_cloud.html#open3d.io.write_point_cloud
    o3d.io.write_point_cloud["my_pts.ply", pcd, write_ascii=write_text]

    # read ply file
    pcd = o3d.io.read_point_cloud['my_pts.ply']

    # visualize
    # o3d.visualization.draw_geometries[[pcd]]

Summary: powerful features and good documentation.

Ref:

• Create ply using open3d
  • //stackoverflow.com/a/62989523/6064933
  • //stackoverflow.com/q/71233749/6064933

Pyntcloud

We can also use pyntcloud:

Unlike open3d, for Pyntcloud, we need to convert Numpy array to Pandas data frames. Here is an example how to use Pyntcloud:

import pandas as pd
from pyntcloud import PyntCloud


def use_pyntcloud[pts, write_text]:
    # ref: //pyntcloud.readthedocs.io/en/latest/io.html
    # the doc is scarce and not complete

    n = len[pts]

    # The points must be written as a dataframe,
    # ref: //stackoverflow.com/q/70304087/6064933
    data = {'x': pts[:, 0],
            'y': pts[:, 1],
            'z': pts[:, 2],
            'red': np.random.rand[n],
            'blue': np.random.rand[n],
            'green': np.random.rand[n]
            }

    # build a cloud
    cloud = PyntCloud[pd.DataFrame[data]]

    # the argument for writing ply file can be found in
    # //github.com/daavoo/pyntcloud/blob/7dcf5441c3b9cec5bbbfb0c71be32728d74666fe/pyntcloud/io/ply.py#L173
    cloud.to_file['my_pts2.ply', as_text=write_text]

    # read file
    cloud = PyntCloud.from_file['my_pts2.ply']
    # print[cloud]

Summary: the documentation is terrible and lacking.

Python-plyfile

Another package is called Python-plyfile [pip install plyfile]. Here is how to use it:

from plyfile import PlyData, PlyElement


# use python-plyfile
use_plyfile[pts, write_text]


def use_plyfile[pts, write_text]:
    x, y, z = pts[:, 0], pts[:, 1], pts[:, 2]
    pts = list[zip[x, y, z]]

    # the vertex are required to a 1-d list
    vertex = np.array[pts, dtype=[['x', 'f4'], ['y', 'f4'], ['z', 'f4']]]

    el = PlyElement.describe[vertex, 'vertex']
    PlyData[[el], text=write_text].write['my_pts3.ply']

Summary: Not intuitive API design, at least for writing a ply file.

Meshio

Meshio [pip install meshio] can also do this:

import numpy as np
import meshio

vertices = np.random.rand[100, 3]
meshio.write["test.ply", mesh=meshio.Mesh[points=vertices, cells = []], binary=False]

Summary: no doc, hard to use. I need to check source code to know its parameters.

References

• Python plyfile vs pymesh: //stackoverflow.com/q/36920562/6064933

Author jdhao

LastMod 2022-05-27

License CC BY-NC-ND 4.0

Reward