cars.applications.dense_matching.dense_matching

this module contains the abstract matching application class.

Module Contents

Classes

DenseMatching

AbstractDenseMatching

class cars.applications.dense_matching.dense_matching.DenseMatching(conf=None)

Bases: cars.applications.application_template.ApplicationTemplate

AbstractDenseMatching

available_applications: Dict

default_application = 'census_sgm'

classmethod __init_subclass__(short_name, **kwargs)

abstract get_optimal_tile_size(disp_min, disp_max)

Get the optimal tile size to use during dense matching.

Parameters

• disp_min – minimum disparity

• disp_max – maximum disparity

Returns

optimal tile size

abstract get_margins(grid_left, disp_min=None, disp_max=None)

Get Margins needed by matching method, to use during resampling

Parameters

• grid_left – left epipolar grid

• disp_min – minimum disparity

• disp_max – maximum disparity

Returns

margins, updated disp_min, updated disp_max

abstract run(epipolar_images_left, epipolar_images_right, orchestrator=None, pair_folder=None, pair_key='PAIR_0', disp_min=None, disp_max=None, compute_disparity_masks=False, disp_to_alt_ratio=None)

Run Matching application.

Create left and right CarsDataset filled with xarray.Dataset , corresponding to epipolar disparities, on the same geometry that epipolar_images_left and epipolar_images_right.

Parameters

• epipolar_images_left (CarsDataset) –

  tiled left epipolar CarsDataset contains:

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

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

    • 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”

• epipolar_images_right (CarsDataset) –

  tiled right epipolar CarsDataset contains:

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

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

    • 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”

• orchestrator – orchestrator used

• pair_folder (str) – folder used for current pair

• pair_key (str) – pair id

• disp_min (int) – minimum disparity

• disp_max (int) – maximum disparity

• disp_to_alt_ratio (float) – disp to alti ratio used for performance map

Returns

left disparity map, right disparity map: Each 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”

Return type

Tuple(CarsDataset, CarsDataset)