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https://github.com/strawlab/python-pcl
Python bindings to the pointcloud library (pcl)
https://github.com/strawlab/python-pcl
Last synced: 3 months ago
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Python bindings to the pointcloud library (pcl)
- Host: GitHub
- URL: https://github.com/strawlab/python-pcl
- Owner: strawlab
- License: other
- Archived: true
- Created: 2012-05-16T10:26:35.000Z (over 12 years ago)
- Default Branch: master
- Last Pushed: 2023-12-30T22:30:45.000Z (12 months ago)
- Last Synced: 2024-09-21T19:31:01.873Z (3 months ago)
- Language: Cython
- Homepage: http://strawlab.github.com/python-pcl/
- Size: 40.3 MB
- Stars: 2,004
- Watchers: 57
- Forks: 701
- Open Issues: 261
-
Metadata Files:
- Readme: readme.rst
- License: LICENSE
Awesome Lists containing this project
- awesome-robotic-tooling - python-pcl - Python bindings to the pointcloud library (Sensor Processing / Point Cloud Processing)
- awesome-robotic-tooling - python-pcl - Python bindings to the pointcloud library. (Sensor Processing / Lidar and Point Cloud Processing)
README
**⚠⚠ This repository has been archived as is it is no longer maintained.
Please see https://github.com/strawlab/python-pcl/issues/395 for details. ⚠⚠**
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Introduction
============
This is a small python binding to the `pointcloud `_ library.
Currently, the following parts of the API are wrapped (all methods operate on PointXYZ)
point types
* I/O and integration; saving and loading PCD files
* segmentation
* SAC
* smoothing
* filtering
* registration (ICP, GICP, ICP_NL)
The code tries to follow the Point Cloud API, and also provides helper function
for interacting with NumPy. For example (from tests/test.py)
.. code-block:: python
import pcl
import numpy as np
p = pcl.PointCloud(np.array([[1, 2, 3], [3, 4, 5]], dtype=np.float32))
seg = p.make_segmenter()
seg.set_model_type(pcl.SACMODEL_PLANE)
seg.set_method_type(pcl.SAC_RANSAC)
indices, model = seg.segment()
or, for smoothing
.. code-block:: python
import pcl
p = pcl.load("C/table_scene_lms400.pcd")
fil = p.make_statistical_outlier_filter()
fil.set_mean_k (50)
fil.set_std_dev_mul_thresh (1.0)
fil.filter().to_file("inliers.pcd")
Point clouds can be viewed as NumPy arrays, so modifying them is possible
using all the familiar NumPy functionality:
.. code-block:: python
import numpy as np
import pcl
p = pcl.PointCloud(10) # "empty" point cloud
a = np.asarray(p) # NumPy view on the cloud
a[:] = 0 # fill with zeros
print(p[3]) # prints (0.0, 0.0, 0.0)
a[:, 0] = 1 # set x coordinates to 1
print(p[3]) # prints (1.0, 0.0, 0.0)
More samples can be found in the `examples directory `_,
and in the `unit tests `_.
This work was supported by `Strawlab `_.
Requirements
============
This release has been tested on Linux Ubuntu 16.04 with
* Python 2.7.6, 3.5.x
* pcl 1.7.2(apt install)
* Cython <= 0.25.2
This release has been tested on Linux Ubuntu 18.04 with
* Python 2.7.6, 3.5.x
* pcl 1.8.1(apt install)
* Cython <= 0.25.2
and MacOS with
* Python 2.7.6, 3.5.x
* pcl 1.9.1(use homebrew)
* Cython <= 0.25.2
and Windows with
* (Miniconda/Anaconda) - Python 3.4
* pcl 1.6.0(VS2010)
* Cython <= 0.25.2
* Gtk+
and Windows with
* (Miniconda/Anaconda) - Python 3.5
* pcl 1.8.1(VS2015)
* Cython <= 0.25.2
* Gtk+
and Windows with
* (Miniconda/Anaconda) - Python 3.6
* pcl 1.8.1(VS2017[Priority High]/VS2015[not VS2017 Install])
* Cython == 0.25.2
* Gtk+
Installation
============
Linux(Ubuntu)
-------------
before Install module
^^^^^^^^^^^^^^^^^^^^^
Ubuntu16.04/18.04 (use official package)
1. Install PCL Module.
.. code-block:: bash
$ sudo apt-get update -y
$ sudo apt-get install libpcl-dev -y
Reference `here `_.
PCL 1.8.x/1.9.x and Ubuntu16.04/18.04(build module)([CI Test Timeout])
1. Build Module
Reference `here `_.
MacOSX
------
before Install module
^^^^^^^^^^^^^^^^^^^^^
Case1. use homebrew(PCL 1.9.1 - 2018/12/25 current)
1. Install PCL Module.
.. code-block:: bash
$ brew tap homebrew/science
$ brew install pcl
Case1. use old homebrew(PCL 1.8.1 - 2017/11/13 current)
1. Check git log.
.. code-block:: bash
$ cd /usr/local/Library/Formula
$ git log ...
2. git checkout (target hash) pcl.rb
.. code-block:: bash
write after.
Warning:
Current Installer (2017/10/02) Not generated pcl-2d-1.8.pc file.(Issue #119)
Reference PointCloudLibrary Issue.
`Pull request 1679 `_.
`Issue 1978 `_.
circumvent:
copy travis/pcl-2d-1.8.pc file to /usr/local/lib/pkgconfig folder.
Windows
-------
Using pip with a precompiled wheel
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
This is the simpliest method on windows. The wheel contains the PCL binaries _
and thus you do not need to install the original PCL library.
1. Go in the history on the `appveyor page `_
2. Click on the last successful revision (green) and click on the job corresponding to your python version
3. Go in the artfacts section for that job and download the wheel (the file with extension whl)
4. In the command line, move to your download folder and run the following command (replacing XXX by the right string)
.. code-block:: bat
pip install python_pcl-XXX.whl
Compiling the binding from source
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
If the method using the procompiled wheel does not work you can compile the binding from the source.
before Install module
~~~~~~~~~~~~~~~~~~~~~
Case1. use PCL 1.6.0
`Windows SDK 7.1 `_
`PCL All-In-One Installer `_
`32 bit `_
`64 bit `_
OpenNI2[(PCL Install FolderPath)\\3rdParty\\OpenNI\\OpenNI-(win32/x64)-1.3.2-Dev.msi]
Case2. use 1.8.1/1.9.1
`Visual Studio 2015 C++ Compiler Tools(use Python 2.7/3.5/3.6/3.7) `_
`Visual Studio 2017 C++ Compiler Tools(use Python 3.6.x/3.7.x) `_
`PCL All-In-One Installer `_
1.8.1
`Visual Studio 2015 - 32 bit `_
`Visual Studio 2017 - 32 bit `_
`Visual Studio 2015 - 64 bit `_
`Visual Studio 2017 - 64 bit `_
1.9.1
`Visual Studio 2017 - 32 bit `_
`Visual Studio 2017 - 64 bit `_
OpenNI2[(PCL Install FolderPath)\\3rdParty\\OpenNI2\\OpenNI-Windows-(win32/x64)-2.2.msi]
Common setting
`Windows Gtk+ Download `_ Download file unzip. Copy bin Folder to pkg-config Folder
Download file unzip. Copy bin Folder to pkg-config Folder
or execute powershell file [Install-GTKPlus.ps1].
`Python Version use VisualStudio Compiler `_
set before Environment variable
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
1. PCL_ROOT
.. code-block:: bat
set PCL_ROOT=(PCL Install/Build_Binary FolderPath)
2. PATH
.. code-block:: bat
(pcl 1.6.0)
set PATH=%PCL_ROOT%/bin/;%OPEN_NI_ROOT%/Tools;%VTK_ROOT%/bin;%PATH%
(pcl 1.8.1/1.9.1)
set PATH=%PCL_ROOT%/bin/;%OPEN_NI2_ROOT%/Tools;%VTK_ROOT%/bin;%PATH%
Common setting
--------------
1. pip module install.
.. code-block:: none
pip install --upgrade pip
pip install cython
pip install numpy
2. install python module
.. code-block:: none
python setup.py build_ext -i
python setup.py install
3. install python-pcl with conda (solved)
.. code-block:: none
conda create -n ipk # create a new conda env.
conda activate ipk # activate env.
conda update -n base -c defaults conda # update conda
conda config --add channels conda-forge # add conda-forge channels
conda install -c sirokujira python-pcl # pcl installation
conda install -c jithinpr2 gtk3 # Gtk+ Gui dependency
conda install -y ipython # install ipython
conda install -y jupyter # install jupyter
After that, run jupyter notebook or ipython shell to test pcl installation.
Build & Test Status
===================
windows(1.6.0/1.8.1/1.9.1)
.. image:: https://ci.appveyor.com/api/projects/status/w52fee7j22q211cm/branch/master?svg=true
:target: https://ci.appveyor.com/project/Sirokujira/python-pcl-iju42
Mac OSX(1.9.1)/Ubuntu16.04(1.7.2)
.. image:: https://travis-ci.org/strawlab/python-pcl.svg?branch=master
:target: https://travis-ci.org/strawlab/python-pcl
A note about types
------------------
Point Cloud is a heavily templated API, and consequently mapping this into
Python using Cython is challenging.
It is written in Cython, and implements enough hard bits of the API
(from Cythons perspective, i.e the template/smart_ptr bits) to
provide a foundation for someone wishing to carry on.
API Documentation
=================
`Read the docs `_.
For deficiencies in this documentation, please consult the
`PCL API docs `_, and the
`PCL tutorials `_.