cars.applications.triangulation.abstract_triangulation_app ========================================================== .. py:module:: cars.applications.triangulation.abstract_triangulation_app .. autoapi-nested-parse:: this module contains the abstract triangulation application class. Classes ------- .. autoapisummary:: cars.applications.triangulation.abstract_triangulation_app.Triangulation Module Contents --------------- .. py:class:: Triangulation(conf=None) Bases: :py:obj:`cars.applications.application_template.ApplicationTemplate` Triangulation .. py:attribute:: available_applications :type: Dict .. py:attribute:: default_application :value: 'line_of_sight_intersection' .. py:method:: __init_subclass__(short_name, **kwargs) :classmethod: .. py:method:: run(sensor_image_left, sensor_image_right, grid_left, grid_right, epipolar_disparity_map, geometry_plugin, epipolar_image, epsg=None, denoising_overload_fun=None, source_pc_names=None, orchestrator=None, pair_dump_dir=None, pair_key='PAIR_0', uncorrected_grid_right=None, geoid_path=None, cloud_id=None, performance_maps_param=None, depth_map_dir=None, point_cloud_dir=None, save_output_coordinates=False, save_output_color=False, save_output_classification=False, save_output_filling=False, save_output_performance_map=False, save_output_ambiguity=False, save_output_edges=False) :abstractmethod: Run Triangulation application. Created left and right CarsDataset filled with xarray.Dataset, corresponding to 3D point clouds, stored on epipolar geometry grid. :param sensor_image_left: tiled sensor left image Dict Must contain keys : "image", "texture", "geomodel", "no_data", "mask". Paths must be absolutes :type sensor_image_left: CarsDataset :param sensor_image_right: tiled sensor right image Dict Must contain keys : "image", "texture", "geomodel", "no_data", "mask". Paths must be absolutes :type sensor_image_right: CarsDataset :param grid_left: left epipolar grid. Grid CarsDataset contains : - A single tile stored in [0,0], containing a (N, M, 2) shape array in xarray Dataset - Attributes containing: "grid_spacing", "grid_origin", "epipolar_size_x", epipolar_size_y", "epipolar_origin_x", "epipolar_origin_y","epipolar_spacing_x", "epipolar_spacing", "disp_to_alt_ratio", :type grid_left: CarsDataset :param grid_right: right epipolar grid. Grid CarsDataset contains : - A single tile stored in [0,0], containing a (N, M, 2) shape array in xarray Dataset - Attributes containing: "grid_spacing", "grid_origin", "epipolar_size_x", epipolar_size_y", "epipolar_origin_x", "epipolar_origin_y","epipolar_spacing_x", "epipolar_spacing", "disp_to_alt_ratio", :type grid_right: CarsDataset :param epipolar_disparity_map: tiled left disparity map or sparse matches: - if CarsDataset is instance of "arrays", CarsDataset contains: - N x M Delayed tiles Each tile will be a future xarray Dataset containing: - data with keys : "disp", "disp_msk" - attrs with keys: profile, window, overlaps - attributes containing:"largest_epipolar_region" "opt_epipolar_tile_size" - if CarsDataset is instance of "points", CarsDataset contains: - N x M Delayed tiles Each tile will be a future pandas DataFrame containing: - data : (L, 4) shape matches - attributes containing:"disp_lower_bound","disp_upper_bound", "elevation_delta_lower_bound","elevation_delta_upper_bound" :type epipolar_disparity_map: CarsDataset :param epipolar_image: tiled epipolar left image :type epipolar_image: CarsDataset :param denoising_overload_fun: function to overload dataset :type denoising_overload_fun: fun :param source_pc_names: source pc names :type source_pc_names: list[str] :param orchestrator: orchestrator used :param pair_dump_dir: folder used as dump directory for current pair :type pair_dump_dir: str :param pair_key: pair key id :type pair_key: str :param uncorrected_grid_right: not corrected right epipolar grid used if self.snap_to_img1 :type uncorrected_grid_right: CarsDataset :param geoid_path: geoid path :type geoid_path: str :param performance_maps_param: parameters used to generate performance map :type performance_maps_param: dict or None :param depth_map_dir: directory to write triangulation output depth map. :type depth_map_dir: None or str :param save_output_coordinates: Save X, Y, Z coords in depth_map_dir :type save_output_coordinates: bool :param save_output_color: Save color depth map in depth_map_dir :type save_output_color: bool :param save_output_classification: Save classification depth map in depth_map_dir :type save_output_classification: bool :param save_output_filling: Save filling depth map in depth_map_dir :type save_output_filling: bool :param save_output_performance_map: Save performance map in depth_map_dir :type save_output_performance_map: bool :param save_output_edges: Save edges image(s) map in depth_map_dir :type save_output_edges: bool :return: point cloud The CarsDataset contains: - N x M Delayed tiles Each tile will be a future xarray Dataset containing: - data : with keys : "x", "y", "z", "corr_msk" optional: "texture", "msk", "z_inf", "z_sup" - attrs with keys: "margins", "epi_full_size", "epsg" - attributes containing: "disp_lower_bound", "disp_upper_bound", "elevation_delta_lower_bound","elevation_delta_upper_bound" :rtype: Tuple(CarsDataset, CarsDataset)