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Copyright (C) 2011-2018 HERE Europe B.V.

The Point Processing Toolkit (pptk) is a Python package for visualizing and processing 2-d/3-d point clouds.

At present, pptk consists of the following features.

• A 3-d point cloud viewer that
  • accepts any 3-column numpy array as input,
  • renders tens of millions of points interactively using an octree-based level of detail mechanism,
  • supports point selection for inspecting and annotating point data.
• A fully parallelized point k-d tree that supports k-nearest neighbor queries and r-near range queries(both build and queries have been parallelized).
• A normal estimation routine based on principal component analysis of point cloud neighborhoods.

Homepage

The screenshots above show various point datasets visualized using pptk.Thebildstein1 Lidar point cloud from Semantic3D (left),Beijing GPS trajectories from Geolife (middle left),DistrictofColumbia.geojson 2-d polygons from US building footprints (middle right),and a Mobius strip (right).For details, see thetutorials.

Unless otherwise noted inLICENSE files for specific files or directories,theLICENSE in the root applies to all content in this repository.

One can either install pptk directly from PyPI

>> pip install pptk

or from the .whl file that results frombuilding pptk from source.

>> pip install <.whl file>

In Python, generate 100 random 3-d points.

>> import numpy as np>> x = np.random.rand(100, 3)

Visualize.

>> import pptk>> v = pptk.viewer(x)

Set point size to 0.01.

>> v.set(point_size=0.01)

For more advanced examples, seetutorials.

We provide CMake scripts for automating most of the build process, but ask theuser to manually preparedependencies and record their pathsin the following CMake cache variables.

• Numpy_INCLUDE_DIR
• PYTHON_INCLUDE_DIR
• PYTHON_LIBRARY
• Eigen_INCLUDE_DIR
• TBB_INCLUDE_DIR
• TBB_tbb_LIBRARY
• TBB_tbb_RUNTIME
• TBB_tbbmalloc_LIBRARY
• TBB_tbbmalloc_RUNTIME
• Qt5_DIR

To set these variables, either use one of CMake's GUIs (ccmake or cmake-gui),or provide an initial CMakeCache.txt in the target build folder(for examples of initial cache files, see the CMakeCache..txt files)

Listed are versions of libraries used to develop pptk, though earlier versionsof these libraries may also work.

• QT 5.4
• TBB 4.3
• Eigen 3.2.9
• Python 2.7+ or 3.6+
• Numpy 1.13

1. Create an empty build folder

>> mkdir <build_folder>

2. Create an initial CMakeCache.txt under <build_folder> and use it to providevalues for the CMake cache variables listed above. (e.g. see CMakeCache.win.txt)

3. Type the following...

>> cd <build_folder>>> cmake -G "NMake Makefiles" <source_folder>>> nmake>> python setup.py bdist_wheel>> pip install dist\<.whl file>

Similar to building on Windows.

Similar to building on Windows.