cars.applications.rasterization.point_cloud_rasterization
this module contains the abstract PointsCloudRasterization application class.
Module Contents
Classes
PointCloudRasterization |
- class cars.applications.rasterization.point_cloud_rasterization.PointCloudRasterization(conf=None)
Bases:
cars.applications.application_template.ApplicationTemplate
PointCloudRasterization
- available_applications: Dict
- default_application = 'simple_gaussian'
- classmethod __init_subclass__(short_name, **kwargs)
- abstract get_resolution()
Get the resolution used by rasterization application
- Returns
resolution in meters or degrees
- abstract get_margins()
Get the margin to use for terrain tiles
- Returns
margin in meters or degrees
- abstract get_optimal_tile_size(max_ram_per_worker, superposing_point_clouds=1, point_cloud_resolution=0.5)
Get the optimal tile size to use, depending on memory available
- Parameters
max_ram_per_worker (int) – maximum ram available
superposing_point_clouds (int) – number of point clouds superposing
point_cloud_resolution (float) – resolution of point cloud
- Returns
optimal tile size in meter
- Return type
float
- abstract run(points_clouds, epsg, orchestrator=None, dsm_file_name=None, color_file_name=None)
Run PointsCloudRasterisation application.
Creates a CarsDataset filled with dsm tiles.
- Parameters
points_clouds (CarsDataset filled with pandas.DataFrame) – merged point cloud
epsg (str) – epsg of raster data
orchestrator – orchestrator used
dsm_file_name (str) – path of dsm
color_file_name (str) – path of color
- Returns
raster DSM
- Return type
CarsDataset filled with xr.Dataset