Skip to content

Latest commit

 

History

History
158 lines (111 loc) · 3.92 KB

README.md

File metadata and controls

158 lines (111 loc) · 3.92 KB
Raw
CARS

Cars Point cloud to Mesh

Python

Contributions welcome

Overview • Requirements • Quick Start • Documentation • Contribution • References

Overview

Cars Point cloud to Mesh short description:

Mesh Generation of cities from CARS point cloud

Requirements

python >= 3.8
argparse                      # Python Argument Parser
cars==0.8.*
triangle>=20230923
numpy
numba
scipy
json-checker
rasterio

Quick Start

To install the plugin in a virtual environment:

git clone https://github.com/CS-SI/cars_point_cloud_to_mesh
cd cars-point-cloud-to-mesh

python3.8 -m venv venv
source venv/bin/activate

pip install -e .

# Patch a file in the current version of CARS (0.8.0), fixed in 0.9.0
patch --forward -p1 ./venv/lib/python3.8/site-packages/cars/applications/point_cloud_fusion/pc_tif_tools.py ./tests/cars_patch_data/patch_file_cars_pc_tif_tools

or

git clone https://github.com/CS-SI/cars_point_cloud_to_mesh
cd cars-point-cloud-to-mesh

make install-dev

To use the plugin, first create a new config file (or use the default configuration available below) with "pipeline" : "point_cloud_to_mesh".

Then, using the venv created previously, run :

cars ./config.json
Default configuration 
{
  "pipeline" : "point_cloud_to_mesh",
  "inputs": {
    "classification_buildings_description": ["building"],
    "dsm_color": "../clr.tif",
    "point_clouds": {
      "pc1": {
        "x": "epi_pc_X.tif",
        "y": "epi_pc_Y.tif",
        "z": "epi_pc_Z.tif",
        "classification": "epi_classification.tif",
        "color": "epi_pc_color.tif",
        "mask": "epi_pc_msk.tif"
      }
    }
  },
  "applications": {
    "create_dtm_mesh": {
      "method": "percentile_of_unclassified_points"
    },
    "point_clouds_and_polygons_to_mesh": {
      "method": "alpha_shape_delaunay_dtm_projection",
      "out_mesh_mode": "texture"
    }
  },
  "output": {
    "out_dir": "./out_meshes/",
    "out_epsg": 4978
  }
}

The files pointed at by the configuration must be the output of CARS's main pipeline with these options enabled :

{
  "triangulation": {
    "use_geoid_alt": true,
    "save_points_cloud": true
  },
  "point_cloud_rasterization": {
    "save_classif": true
  }
}

To generate files that may be useful, such as a geojson containing points where vegetation is present (with its height) or a png file with classifications such as water bodies and vegetation, run the notebooks located in /notebooks with the appropriate files pointed at by the configuration in the first cell of said notebooks.

Documentation

Go in docs/ directory

Contribution

See Contribution manual

LICENCE

See LICENCE

  • Free software: Apache Software License 2.0
  • The triangle library is published under the LGPL 3.0 : the licence is weak copyleft, where other licences are permissive licences. However, Triangle's terms of use ensure that its licence does not extend to other components of the project, nor to the project itself.

References

See CARS github