pandora.validation.cpp.validation_cpp
=====================================

.. py:module:: pandora.validation.cpp.validation_cpp


Functions
---------

.. autoapisummary::

   pandora.validation.cpp.validation_cpp.interpolate_occlusion_sgm
   pandora.validation.cpp.validation_cpp.interpolate_mismatch_sgm
   pandora.validation.cpp.validation_cpp.interpolate_occlusion_mc_cnn
   pandora.validation.cpp.validation_cpp.interpolate_mismatch_mc_cnn


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

.. py:function:: interpolate_occlusion_sgm(disp, valid, msk_pixel_occlusion, msk_pixel_filled_occlusion, msk_pixel_invalid)

   Interpolation of the left disparity map to resolve occlusion conflicts.
   Interpolate occlusion by moving by selecting
   the right lowest value along paths from 8 directions.

   HIRSCHMULLER, Heiko. Stereo processing by semiglobal matching and mutual information.
   IEEE Transactions on pattern analysis and machine intelligence, 2007, vol. 30, no 2, p. 328-341.

   :param disp: disparity map
   :type disp: 2D np.array (row, col)
   :param valid: validity mask
   :type valid: 2D np.array (row, col)
   :param msk_pixel_occlusion: value for the PANDORA_MSK_PIXEL_OCCLUSION constant in pandora.constants
   :param msk_pixel_occlusion: int
   :param msk_pixel_filled_occlusion: value for the PANDORA_MSK_PIXEL_FILLED_OCCLUSION constant in pandora.constants
   :param msk_pixel_filled_occlusion: int
   :param msk_pixel_invalid: value for the PANDORA_MSK_PIXEL_INVALID constant in pandora.constants
   :param msk_pixel_invalid: int
   :return: the interpolate left disparity map, with the validity mask update :

       - If out & MSK_PIXEL_FILLED_OCCLUSION != 0 : Invalid pixel : filled occlusion
   :rtype: : tuple(2D np.array (row, col), 2D np.array (row, col))


.. py:function:: interpolate_mismatch_sgm(disp, valid, msk_pixel_mismatch, msk_pixel_filled_mismatch, msk_pixel_occlusion, msk_pixel_invalid)

   Interpolation of the left disparity map to resolve mismatch conflicts. Interpolate mismatch by finding the
   nearest correct pixels in 8 different directions and use the median of their disparities.
   Mismatched pixel areas that are direct neighbors of occluded pixels are treated as occlusions.

   HIRSCHMULLER, Heiko. Stereo processing by semiglobal matching and mutual information.
   IEEE Transactions on pattern analysis and machine intelligence, 2007, vol. 30, no 2, p. 328-341.

   :param disp: disparity map
   :type disp: 2D np.array (row, col)
   :param valid: validity mask
   :type valid: 2D np.array (row, col)
   :param msk_pixel_mismatch: value for the PANDORA_MSK_PIXEL_MISMATCH constant in pandora.constants
   :param msk_pixel_mismatch: int
   :param msk_pixel_filled_mismatch: value for the PANDORA_MSK_PIXEL_FILLED_MISMATCH constant in pandora.constants
   :param msk_pixel_filled_mismatch: int
   :param msk_pixel_occlusion: value for the PANDORA_MSK_PIXEL_OCCLUSION constant in pandora.constants
   :param msk_pixel_occlusion: int
   :param msk_pixel_invalid: value for the PANDORA_MSK_PIXEL_INVALID constant in pandora.constants
   :param msk_pixel_invalid: int
   :return: the interpolate left disparity map, with the validity mask update :

       - If out & MSK_PIXEL_FILLED_MISMATCH != 0 : Invalid pixel : filled mismatch
   :rtype: tuple(2D np.array (row, col), 2D np.array (row, col))


.. py:function:: interpolate_occlusion_mc_cnn(disp, valid, msk_pixel_occlusion, msk_pixel_filled_occlusion, msk_pixel_invalid)

   Interpolation of the left disparity map to resolve occlusion conflicts.
   Interpolate occlusion by moving left until
   we find a position labeled correct.

   Žbontar, J., & LeCun, Y. (2016). Stereo matching by training a convolutional neural network to compare image
   patches. The journal of machine learning research, 17(1), 2287-2318.

   :param disp: disparity map
   :type disp: 2D np.array (row, col)
   :param valid: validity mask
   :type valid: 2D np.array (row, col)
   :param msk_pixel_occlusion: value for the PANDORA_MSK_PIXEL_OCCLUSION constant in pandora.constants
   :param msk_pixel_occlusion: int
   :param msk_pixel_filled_occlusion: value for the PANDORA_MSK_PIXEL_FILLED_OCCLUSION constant in pandora.constants
   :param msk_pixel_filled_occlusion: int
   :param msk_pixel_invalid: value for the PANDORA_MSK_PIXEL_INVALID constant in pandora.constants
   :param msk_pixel_invalid: int
   :return: the interpolate left disparity map, with the validity mask update :

       - If out & MSK_PIXEL_FILLED_OCCLUSION != 0 : Invalid pixel : filled occlusion
   :rtype: tuple(2D np.array (row, col), 2D np.array (row, col))


.. py:function:: interpolate_mismatch_mc_cnn(disp, valid, msk_pixel_mismatch, msk_pixel_filled_mismatch, msk_pixel_invalid)

   Interpolation of the left disparity map to resolve mismatch conflicts.
   Interpolate mismatch by finding the nearest
   correct pixels in 16 different directions and use the median of their disparities.

   Žbontar, J., & LeCun, Y. (2016). Stereo matching by training a convolutional neural network to compare image
   patches. The journal of machine learning research, 17(1), 2287-2318.

   :param disp: disparity map
   :type disp: 2D np.array (row, col)
   :param valid: validity mask
   :type valid: 2D np.array (row, col)
   :param msk_pixel_mismatch: value for the PANDORA_MSK_PIXEL_MISMATCH constant in pandora.constants
   :param msk_pixel_mismatch: int
   :param msk_pixel_filled_mismatch: value for the PANDORA_MSK_PIXEL_FILLED_MISMATCH constant in pandora.constants
   :param msk_pixel_filled_mismatch: int
   :param msk_pixel_invalid: value for the PANDORA_MSK_PIXEL_INVALID constant in pandora.constants
   :param msk_pixel_invalid: int
   :return: the interpolate left disparity map, with the validity mask update :

       - If out & MSK_PIXEL_FILLED_MISMATCH != 0 : Invalid pixel : filled mismatch
   :rtype: tuple(2D np.array (row, col), 2D np.array (row, col))