pandora2d.matching_cost.matching_cost

This module contains functions associated to the matching cost computation step.

Module Contents

Classes

MatchingCost

Matching Cost class
class pandora2d.matching_cost.matching_cost.MatchingCost(cfg: Dict)[source]

Matching Cost class

_WINDOW_SIZE = 5[source]
_STEP = [1, 1][source]
margins[source]
check_conf(cfg: Dict) → Dict[str, str][source]

Check the matching cost configuration

Parameters:

cfg (dict) – user_config for matching cost

Returns:

cfg: global configuration

Return type:

cfg: dict

static allocate_cost_volumes(cost_volume_attr: dict, row: numpy.ndarray, col: numpy.ndarray, col_disparity: List[int], row_disparity: List[int], np_data: numpy.ndarray = None) → xarray.Dataset[source]

Allocate the cost volumes

Parameters:

  • cost_volume_attr – the cost_volume’s attributs product by Pandora

  • row (np.ndarray) – dimension of the image (row)

  • col (np.ndarray) – dimension of the image (columns)

  • col_disparity (List[int]) – min and max disparities for columns.

  • row_disparity (List[int]) – min and max disparities for rows.

  • np_data (np.ndarray) – 4D numpy.ndarray og cost_volumes. Defaults to None.

Returns:

cost_volumes: 4D Dataset containing the cost_volumes

Return type:

cost_volumes: xr.Dataset

allocate_cost_volume_pandora(img_left: xarray.Dataset, img_right: xarray.Dataset, grid_min_col: numpy.ndarray, grid_max_col: numpy.ndarray, cfg: Dict) → None[source]

Allocate the cost volume for pandora

Parameters:

  • img_left (xr.Dataset) – xarray.Dataset containing : - im : 2D (row, col) xarray.DataArray - msk : 2D (row, col) xarray.DataArray

  • grid_min_col (np.ndarray) – grid containing min disparities for columns.

  • grid_max_col (np.ndarray) – grid containing max disparities for columns.

  • cfg (Dict) – matching_cost computation configuration

Returns:

None

compute_cost_volumes(img_left: xarray.Dataset, img_right: xarray.Dataset, grid_min_col: numpy.ndarray, grid_max_col: numpy.ndarray, grid_min_row: numpy.ndarray, grid_max_row: numpy.ndarray) → xarray.Dataset[source]

Computes the cost volumes

Parameters:

  • img_left (xr.Dataset) – xarray.Dataset containing : - im : 2D (row, col) xarray.DataArray - msk : 2D (row, col) xarray.DataArray

  • img_right (xr.Dataset) – xarray.Dataset containing : - im : 2D (row, col) xarray.DataArray - msk : 2D (row, col) xarray.DataArray

  • grid_min_col (np.ndarray) – grid containing min disparities for columns.

  • grid_max_col (np.ndarray) – grid containing max disparities for columns.

  • grid_min_row (np.ndarray) – grid containing min disparities for rows.

  • grid_max_row (np.ndarray) – grid containing max disparities for rows.

Returns:

cost_volumes: 4D Dataset containing the cost_volumes

Return type:

cost_volumes: xr.Dataset