https://github.com/daavoo/pyntcloud

pyntcloud is a Python library for working with 3D point clouds.
https://github.com/daavoo/pyntcloud

3d 3d-deep-learning 3d-graphics 3d-models 3d-point-clouds deep-learning point-clouds python python-library

Last synced: about 1 month ago
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pyntcloud is a Python library for working with 3D point clouds.

• Host: GitHub
• URL: https://github.com/daavoo/pyntcloud
• Owner: daavoo
• License: mit
• Created: 2016-10-03T16:16:44.000Z (almost 8 years ago)
• Default Branch: master
• Last Pushed: 2024-02-07T14:05:48.000Z (8 months ago)
• Last Synced: 2024-05-17T09:02:53.524Z (4 months ago)
• Topics: 3d, 3d-deep-learning, 3d-graphics, 3d-models, 3d-point-clouds, deep-learning, point-clouds, python, python-library
• Language: Python
• Homepage: http://pyntcloud.readthedocs.io
• Size: 14.7 MB
• Stars: 1,375
• Watchers: 43
• Forks: 221
• Open Issues: 59
• Metadata Files:
  • Readme: README.rst
  • Contributing: docs/contributing.rst
  • License: LICENSE.md
  • Code of conduct: CODE_OF_CONDUCT.md

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README

        
=============================

Making point clouds fun again

=============================

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**pyntcloud** is a Python **3** library for working with 3D point clouds leveraging the power of the Python scientific stack.

- Examples_ (We encourage you to try out the examples by launching `Binder `_.)

- Documentation_

.. _Examples: https://github.com/daavoo/pyntcloud/tree/master/examples

.. _Documentation: http://pyntcloud.readthedocs.io/en/latest/

Installation

============

.. code-block:: bash

    conda install pyntcloud -c conda-forge

Or:

.. code-block:: bash

    pip install pyntcloud

Quick Overview

==============

You can access most of pyntcloud's functionality from its core class: PyntCloud.

With PyntCloud you can perform complex 3D processing operations with minimum lines of

code. For example you can:

- Load a PLY point cloud from disk.

- Add 3 new scalar fields by converting RGB to HSV.

- Build a grid of voxels from the point cloud.

- Build a new point cloud keeping only the nearest point to each occupied voxel center.

- Save the new point cloud in numpy's NPZ format.

With the following concise code:

.. code-block:: python

    from pyntcloud import PyntCloud

    cloud = PyntCloud.from_file("some_file.ply")

    cloud.add_scalar_field("hsv")

    voxelgrid_id = cloud.add_structure("voxelgrid", n_x=32, n_y=32, n_z=32)

    new_cloud = cloud.get_sample("voxelgrid_nearest", voxelgrid_id=voxelgrid_id, as_PyntCloud=True)

    new_cloud.to_file("out_file.npz")

Integration with other libraries

================================

pyntcloud offers seamless integration with other 3D processing libraries.

You can create / convert PyntCloud instances from / to many 3D processing libraries using the `from_instance` / `to_instance` methods:

- `Open3D `_

.. code-block:: python

    import open3d as o3d

    from pyntcloud import PyntCloud

    # FROM Open3D

    original_triangle_mesh = o3d.io.read_triangle_mesh("diamond.ply")

    cloud = PyntCloud.from_instance("open3d", original_triangle_mesh)

    

    # TO Open3D

    cloud = PyntCloud.from_file("diamond.ply")

    converted_triangle_mesh = cloud.to_instance("open3d", mesh=True)  # mesh=True by default

    

- `PyVista `_

.. code-block:: python

    import pyvista as pv

    from pyntcloud import PyntCloud

    # FROM PyVista

    original_point_cloud = pv.read("diamond.ply")

    cloud = PyntCloud.from_instance("pyvista", original_point_cloud)

    

    # TO PyVista

    cloud = PyntCloud.from_file("diamond.ply")

    converted_triangle_mesh = cloud.to_instance("pyvista", mesh=True)