pandora.validation.interpolated_disparity ========================================= .. py:module:: pandora.validation.interpolated_disparity .. autoapi-nested-parse:: This module contains classes and functions associated to the interpolation of the disparity map for the validation step. Classes ------- .. autoapisummary:: pandora.validation.interpolated_disparity.AbstractInterpolation pandora.validation.interpolated_disparity.McCnnInterpolation pandora.validation.interpolated_disparity.SgmInterpolation Module Contents --------------- .. py:class:: AbstractInterpolation Abstract Interpolation class .. py:attribute:: __metaclass__ .. py:attribute:: interpolation_methods_avail :type: Dict .. py:method:: register_subclass(short_name: str) :classmethod: Allows to register the subclass with its short name :param short_name: the subclass to be registered :type short_name: string .. py:method:: desc() -> None :abstractmethod: Describes the disparity interpolation method for the validation step :return: None .. py:method:: interpolated_disparity(left: xarray.Dataset, img_left: xarray.Dataset = None, img_right: xarray.Dataset = None, cv: xarray.Dataset = None) -> None :abstractmethod: Interpolation of the left disparity map to resolve occlusion and mismatch conflicts. :param left: left Dataset with the variables : - disparity_map 2D xarray.DataArray (row, col) - confidence_measure 3D xarray.DataArray (row, col, indicator) - validity_mask 2D xarray.DataArray (row, col) :type left: xarray.Dataset :param img_left: left Datset image containing : - im: 2D (row, col) or 3D (band_im, row, col) xarray.DataArray float32 - disparity (optional): 3D (disp, row, col) xarray.DataArray float32 - msk (optional): 2D (row, col) xarray.DataArray int16 - classif (optional): 3D (band_classif, row, col) xarray.DataArray int16 - segm (optional): 2D (row, col) xarray.DataArray int16 - edges (optional): 2D (row, col) xarray.DataArray int16 :type img_left: xarray.Dataset :param img_right: right Dataset image containing : - im: 2D (row, col) or 3D (band_im, row, col) xarray.DataArray float32 - disparity (optional): 3D (disp, row, col) xarray.DataArray float32 - msk (optional): 2D (row, col) xarray.DataArray int16 - classif (optional): 3D (band_classif, row, col) xarray.DataArray int16 - segm (optional): 2D (row, col) xarray.DataArray int16 - edges (optional): 2D (row, col) xarray.DataArray int16 :type img_right: xarray.Dataset :param cv: cost_volume Dataset with the variables: - cost_volume 3D xarray.DataArray (row, col, disp) - confidence_measure 3D xarray.DataArray (row, col, indicator) :type cv: xarray.Dataset :return: None .. py:class:: McCnnInterpolation(**cfg: dict) Bases: :py:obj:`AbstractInterpolation` McCnnInterpolation class allows to perform the interpolation of the disparity map .. py:method:: check_config(**cfg: dict) -> None Check and update the configuration :param cfg: optional configuration, {} :type cfg: dictionary :return: None .. py:method:: desc() -> None Describes the disparity interpolation method :return: None .. py:method:: interpolated_disparity(left: xarray.Dataset, img_left: xarray.Dataset = None, img_right: xarray.Dataset = None, cv: xarray.Dataset = None) -> None Interpolation of the left disparity map to resolve occlusion and mismatch conflicts. :param left: left Dataset with the variables : - disparity_map 2D xarray.DataArray (row, col) - confidence_measure 3D xarray.DataArray (row, col, indicator) - validity_mask 2D xarray.DataArray (row, col) :type left: xarray.Dataset :param img_left: left Datset image containing : - im: 2D (row, col) or 3D (band_im, row, col) xarray.DataArray float32 - disparity (optional): 3D (disp, row, col) xarray.DataArray float32 - msk (optional): 2D (row, col) xarray.DataArray int16 - classif (optional): 3D (band_classif, row, col) xarray.DataArray int16 - segm (optional): 2D (row, col) xarray.DataArray int16 - edges (optional): 2D (row, col) xarray.DataArray int16 :type img_left: xarray.Dataset :param img_right: right Dataset image containing : - im: 2D (row, col) or 3D (band_im, row, col) xarray.DataArray float32 - disparity (optional): 3D (disp, row, col) xarray.DataArray float32 - msk (optional): 2D (row, col) xarray.DataArray int16 - classif (optional): 3D (band_classif, row, col) xarray.DataArray int16 - segm (optional): 2D (row, col) xarray.DataArray int16 - edges (optional): 2D (row, col) xarray.DataArray int16 :type img_right: xarray.Dataset :param cv: cost_volume Dataset with the variables: - cost_volume 3D xarray.DataArray (row, col, disp) - confidence_measure 3D xarray.DataArray (row, col, indicator) :type cv: xarray.Dataset :return: None .. py:method:: interpolate_occlusion_mc_cnn(disp: numpy.ndarray, valid: numpy.ndarray) :staticmethod: .. py:method:: interpolate_mismatch_mc_cnn(disp: numpy.ndarray, valid: numpy.ndarray) :staticmethod: .. py:class:: SgmInterpolation(**cfg: dict) Bases: :py:obj:`AbstractInterpolation` SgmInterpolation class allows to perform the interpolation of the disparity map .. py:method:: check_config(**cfg: dict) -> None Check and update the configuration :param cfg: optional configuration, {} :type cfg: dictionary :return: None .. py:method:: desc() -> None Describes the disparity interpolation method :return: None .. py:method:: interpolated_disparity(left: xarray.Dataset, img_left: xarray.Dataset = None, img_right: xarray.Dataset = None, cv: xarray.Dataset = None) -> None Interpolation of the left disparity map to resolve occlusion and mismatch conflicts. :param left: left Dataset with the variables : - disparity_map 2D xarray.DataArray (row, col) - confidence_measure 3D xarray.DataArray (row, col, indicator) - validity_mask 2D xarray.DataArray (row, col) :type left: xarray.Dataset :param img_left: left Datset image containing : - im: 2D (row, col) or 3D (band_im, row, col) xarray.DataArray float32 - disparity (optional): 3D (disp, row, col) xarray.DataArray float32 - msk (optional): 2D (row, col) xarray.DataArray int16 - classif (optional): 3D (band_classif, row, col) xarray.DataArray int16 - segm (optional): 2D (row, col) xarray.DataArray int16 - edges (optional): 2D (row, col) xarray.DataArray int16 :type img_left: xarray.Dataset :param img_right: right Dataset image containing : - im: 2D (row, col) or 3D (band_im, row, col) xarray.DataArray float32 - disparity (optional): 3D (disp, row, col) xarray.DataArray float32 - msk (optional): 2D (row, col) xarray.DataArray int16 - classif (optional): 3D (band_classif, row, col) xarray.DataArray int16 - segm (optional): 2D (row, col) xarray.DataArray int16 - edges (optional): 2D (row, col) xarray.DataArray int16 :type img_right: xarray.Dataset :param cv: cost_volume Dataset with the variables: - cost_volume 3D xarray.DataArray (row, col, disp) - confidence_measure 3D xarray.DataArray (row, col, indicator) :type cv: xarray.Dataset :return: None .. py:method:: interpolate_occlusion_sgm(disp: numpy.ndarray, valid: numpy.ndarray) :staticmethod: .. py:method:: interpolate_mismatch_sgm(disp: numpy.ndarray, valid: numpy.ndarray) :staticmethod: