cars.applications.resampling.resampling

this module contains the abstract resampling application class.

Module Contents

Classes

Resampling

Resampling

class cars.applications.resampling.resampling.Resampling(conf=None)

Bases: cars.applications.application_template.ApplicationTemplate

Resampling

available_applications: Dict

default_application = 'bicubic'

classmethod __init_subclass__(short_name, **kwargs)

abstract run(sensor_image_left, sensor_image_right, grid_left, grid_right, orchestrator=None, pair_folder=None, pair_key='PAIR_0', margins_fun=None, tile_width=None, tile_height=None, step=None, add_color=True, epipolar_roi=None)

Run resampling application.

Creates left and right CarsDataset filled with xarray.Dataset, corresponding to sensor images resampled in epipolar geometry.

Parameters

• sensor_images_left (CarsDataset) – tiled sensor left image Dict Must contain keys : “image”, “color”, “geomodel”, “no_data”, “mask”, “classification”. Paths must be absolutes

• sensor_images_right (CarsDataset) – tiled sensor right image Dict Must contain keys : “image”, “color”, “geomodel”, “no_data”, “mask”, “classification”. Paths must be absolutes

• 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

• grid_right (CarsDataset) –

  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”,

• orchestrator – orchestrator used

• pair_folder (directory to save files to) – folder used for current pair

• pair_key (str) – pair id

• margins (xr.Dataset) – margins to use

• optimum_tile_size (int) – optimum tile size to use

• add_color (bool) – add color image to dataset

• epipolar_roi (list(int), [row_min, row_max, col_min, col_max]) – Epipolar roi to use if set. Set None tiles outsize roi

Returns

left epipolar image, right epipolar image. Each CarsDataset contains:

• N x M Delayed tiles. Each tile will be a future xarray Dataset containing:

  • data with keys : “im”, “msk”, “color”, “classif”

  • attrs with keys: “margins” with “disp_min” and “disp_max” “transform”, “crs”, “valid_pixels”, “no_data_mask”,

    ”no_data_img”

• attributes containing: “largest_epipolar_region”,”opt_epipolar_tile_size”

Return type

Tuple(CarsDataset, CarsDataset)