ign-pdal-tools
This repo contains various python tools based on PDAL that are used to work on LiDAR data in the LidarHD project at IGN (Institut National de l'Information Géographique et Forestière / French National Institute of Geographic and Forest Information) to work on LiDAR data.
We've decided to make them available because think that they may be useful to others, but this repo is NOT meant to be substantially modified from community input, and may be amended/completed depending on the fonctionalities that our team needs.
Content
This library contains pdal-based tools to:
- colorize a point cloud using images from Geoplateforme / cartes.gouv.fr (a portal from French government providing access to aerial imagery)
- stitch together LAS files using their location
- standardize LAS files
- unlock LAS files generated by TerraSolid
Installation / Usage
This library can be used in different ways:
- directly from sources:
make installcreates a mamba environment with the required dependencies - installed with
pipfrom pypi:pip install ign-pdal-tools - used in a docker container: see documentation Dockerfile
More details on the contained tools
Colorization
- color.py: Colorize a point cloud from Geoplateforme data
Las infos
Misc tools to get information on a las file, eg. retrieve metadata, find epsg value, find bounds, get parameters to pass to a writer. They are intended to be used from the pdaltools module, for example:
from pdaltools import las_infos
filename = ...
las_infos.las_info_metadata(filename)
Point cloud infos
Misc tools to get information on a point cloud (numpy array). Eg. get expected origin of a point cloud based on a square tiling:
from pdaltools import pcd_infos
points = ...
pcd_infos.get_pointcloud_origin_from_tile_width(points, tile_width=1000)
Stitching
- las_clip.py: crop a LAS file using 2d bounding box
- las_merge.py: merge a LAS file with its neighbors according to their filenames
- las_add_buffer.py: add points to a LAS file from a buffer (border) from its neighbors (using filenames to locate neighbors)
- replace_area_in_pointcloud.py: replace the points from a LAS file by the points of another LAS file inside areas defined in a vector file (geojson, shapefile)
WARNING: In las_merge.py and las_add_buffer.py, filenames are used to get the LAS files extents
and to find neighbors.
The naming convention is {prefix1}_{prefix2}_{xcoord}_{ycoord}_{postfix})} (eg. Semis_2021_0770_6278_LA93_IGN69.laz).
By default, xcoord and ycoord are given in kilometers and the shape of the tile is 1 km * 1 km
Standardization
- standardize_format.py: re-write a LAS file in a standard format (see code for details)
- count_occurences: count occurences for each value of a given attribute in a set of LAS files (initially used for classification)
- count_occurences_for_attribute.py: count occurences in one or several files and save the result in a json file.
- merge_occurences_counts.py: merge counts from several results of count_occurences_for_attribute (json files) into a single json file (used for parallelization)
- replace_attribute_in_las.py: using a json file containing a correspondance map, replace the occurences of each value in a LAS file by its corresponding value from the map.
Unlock
unlock_file.py: overwrite a LAS file in case PDAL raises this error:
readers.las: Global encoding WKT flag not set for point format 6 - 10. which is due to TerraSolid
malformed LAS output for LAS1.4 files with point format 6 to 10.
Add points in pointcloud
add_points_in_pointcloud.py: add points from some vector files (ex: shp, geojson, ...) inside Las/Laz:
- 2 kinds of geometries are handled:
- if the geometries in the vector file are points, they are added directly to the las file
- if the geometries are lines, points are added along this line using a
spacingparameter
- In case the points are 2D only, Z can be provided as a feature property (parametrized via
altitude_column) - The Classification attribute for these points is parametrized via
virtual_points_classes - All the other attributes are set to 0.
Dev / Build
Contribute
Every time the code is changed, think of updating the version file: pdaltools/_version.py
Please log your changes in CHANGELOG.md
Before committing your changes, run the precommit hooks. They can be installed to run automatically with make install-precommit
Tests
Create the conda environment: make install
Run unit tests: make testing
Pip package
To generate a pip package and deploy it on pypi, use the Makefile at the root of the repo:
make build: build the librarymake install: install the library in an editable way (pip -e)make deploy: deploy it on pypi
Docker image
To build a docker image with the library installed: make docker-build
To test the docker image: make docker-test
To build a docker image with a custom version of PDAL: make docker-build-custom-pdal ; the custom version is defined in the Makefile (see Makefile for details)
Release files for ign-pdal-tools 1.18.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
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Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| ign_pdal_tools-1.18.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 112.9 kB
Release files / ign_pdal_tools-1.18.0.tar.gz
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