cars.applications.resampling.abstract_resampling_app
====================================================

.. py:module:: cars.applications.resampling.abstract_resampling_app

.. autoapi-nested-parse::

   this module contains the abstract resampling application class.



Classes
-------

.. autoapisummary::

   cars.applications.resampling.abstract_resampling_app.Resampling


Module Contents
---------------

.. py:class:: Resampling(conf=None)

   Bases: :py:obj:`cars.applications.application_template.ApplicationTemplate`


   Resampling


   .. py:attribute:: available_applications
      :type:  Dict


   .. py:attribute:: default_application
      :value: 'bicubic'



   .. py:method:: __init_subclass__(short_name, **kwargs)
      :classmethod:



   .. py:method:: run(sensor_image_left, sensor_image_right, grid_left, grid_right, geom_plugin, orchestrator=None, pair_folder=None, pair_key='PAIR_0', margins_fun=None, tile_width=None, tile_height=None, step=None, add_color=True, add_classif=True, epipolar_roi=None, required_bands=None, texture_bands=None, resolution=1)
      :abstractmethod:


      Run resampling application.

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

      :param sensor_images_left: tiled sensor left image
          Dict Must contain keys : "image", "texture", "geomodel",
          "no_data", "mask", "classification". Paths must be absolutes
      :type sensor_images_left: CarsDataset
      :param sensor_images_right: tiled sensor right image
          Dict Must contain keys : "image", "texture", "geomodel",
          "no_data", "mask", "classification". Paths must be absolutes
      :type sensor_images_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 orchestrator: orchestrator used
      :param pair_folder: folder used for current pair
      :type pair_folder: directory to save files to
      :param pair_key: pair id
      :type pair_key: str
      :param margins: margins to use
      :type margins: xr.Dataset
      :param optimum_tile_size: optimum tile size to use
      :type optimum_tile_size: int
      :param add_color: add color image to dataset
      :type add_color: bool
      :param epipolar_roi: Epipolar roi to use if set.
          Set None tiles outsize roi
      :type epipolar_roi: list(int), [row_min, row_max,  col_min, col_max]
      :param required_bands: bands to resample on left and right image
      :type required_bands: dict
      :param texture_bands: name of bands used for output texture
      :type texture_bands: list
      :param resolution: resolution for downsampling
      :type resolution: int

      :return: 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", "texture", "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"

      :rtype: Tuple(CarsDataset, CarsDataset)