pandora.optimization.optimization

This module contains classes and functions associated to the cost volume optimization step.

Module Contents

Classes

AbstractOptimization

Abstract Optimizationinput class
class pandora.optimization.optimization.AbstractOptimization[source]

Abstract Optimizationinput class

__metaclass__[source]
optimization_methods_avail: Dict[source]
cfg[source]
margins[source]
classmethod register_subclass(short_name: str)[source]

Allows to register the subclass with its short name

Parameters:

short_name (string) – the subclass to be registered

abstract desc() → None[source]

Describes the optimization method :return: None

abstract optimize_cv(cv: xarray.Dataset, img_left: xarray.Dataset, img_right: xarray.Dataset) → xarray.Dataset[source]

Optimizes the cost volume

Parameters:

  • cv (xarray.Dataset) –

    the cost volume dataset with the data variables:

    • cost_volume 3D xarray.DataArray (row, col, disp)

    • confidence_measure 3D xarray.DataArray (row, col, indicator)

  • img_left (xarray.DataArray) – left Dataset image

  • img_right (xarray.DataArray) – right Dataset image

Returns:

the cost volume dataset with the data variables:

  • cost_volume 3D xarray.DataArray (row, col, disp)

  • confidence_measure 3D xarray.DataArray (row, col, indicator)

Return type:

xarray.Dataset