pandora.validation.cpp.validation_cpp
Functions
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Interpolation of the left disparity map to resolve occlusion conflicts. |
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Interpolation of the left disparity map to resolve mismatch conflicts. Interpolate mismatch by finding the |
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Interpolation of the left disparity map to resolve occlusion conflicts. |
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Interpolation of the left disparity map to resolve mismatch conflicts. |
Module Contents
- pandora.validation.cpp.validation_cpp.interpolate_occlusion_sgm(disp, valid, msk_pixel_occlusion, msk_pixel_filled_occlusion, msk_pixel_invalid)[source]
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.
- Parameters:
disp (2D np.array (row, col)) – disparity map
valid (2D np.array (row, col)) – validity mask
msk_pixel_occlusion – value for the PANDORA_MSK_PIXEL_OCCLUSION constant in pandora.constants
msk_pixel_occlusion – int
msk_pixel_filled_occlusion – value for the PANDORA_MSK_PIXEL_FILLED_OCCLUSION constant in pandora.constants
msk_pixel_filled_occlusion – int
msk_pixel_invalid – value for the PANDORA_MSK_PIXEL_INVALID constant in pandora.constants
msk_pixel_invalid – int
- Returns:
the interpolate left disparity map, with the validity mask update :
If out & MSK_PIXEL_FILLED_OCCLUSION != 0 : Invalid pixel : filled occlusion
- Return type:
: tuple(2D np.array (row, col), 2D np.array (row, col))
- pandora.validation.cpp.validation_cpp.interpolate_mismatch_sgm(disp, valid, msk_pixel_mismatch, msk_pixel_filled_mismatch, msk_pixel_occlusion, msk_pixel_invalid)[source]
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.
- Parameters:
disp (2D np.array (row, col)) – disparity map
valid (2D np.array (row, col)) – validity mask
msk_pixel_mismatch – value for the PANDORA_MSK_PIXEL_MISMATCH constant in pandora.constants
msk_pixel_mismatch – int
msk_pixel_filled_mismatch – value for the PANDORA_MSK_PIXEL_FILLED_MISMATCH constant in pandora.constants
msk_pixel_filled_mismatch – int
msk_pixel_occlusion – value for the PANDORA_MSK_PIXEL_OCCLUSION constant in pandora.constants
msk_pixel_occlusion – int
msk_pixel_invalid – value for the PANDORA_MSK_PIXEL_INVALID constant in pandora.constants
msk_pixel_invalid – int
- Returns:
the interpolate left disparity map, with the validity mask update :
If out & MSK_PIXEL_FILLED_MISMATCH != 0 : Invalid pixel : filled mismatch
- Return type:
tuple(2D np.array (row, col), 2D np.array (row, col))
- pandora.validation.cpp.validation_cpp.interpolate_occlusion_mc_cnn(disp, valid, msk_pixel_occlusion, msk_pixel_filled_occlusion, msk_pixel_invalid)[source]
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.
- Parameters:
disp (2D np.array (row, col)) – disparity map
valid (2D np.array (row, col)) – validity mask
msk_pixel_occlusion – value for the PANDORA_MSK_PIXEL_OCCLUSION constant in pandora.constants
msk_pixel_occlusion – int
msk_pixel_filled_occlusion – value for the PANDORA_MSK_PIXEL_FILLED_OCCLUSION constant in pandora.constants
msk_pixel_filled_occlusion – int
msk_pixel_invalid – value for the PANDORA_MSK_PIXEL_INVALID constant in pandora.constants
msk_pixel_invalid – int
- Returns:
the interpolate left disparity map, with the validity mask update :
If out & MSK_PIXEL_FILLED_OCCLUSION != 0 : Invalid pixel : filled occlusion
- Return type:
tuple(2D np.array (row, col), 2D np.array (row, col))
- pandora.validation.cpp.validation_cpp.interpolate_mismatch_mc_cnn(disp, valid, msk_pixel_mismatch, msk_pixel_filled_mismatch, msk_pixel_invalid)[source]
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.
- Parameters:
disp (2D np.array (row, col)) – disparity map
valid (2D np.array (row, col)) – validity mask
msk_pixel_mismatch – value for the PANDORA_MSK_PIXEL_MISMATCH constant in pandora.constants
msk_pixel_mismatch – int
msk_pixel_filled_mismatch – value for the PANDORA_MSK_PIXEL_FILLED_MISMATCH constant in pandora.constants
msk_pixel_filled_mismatch – int
msk_pixel_invalid – value for the PANDORA_MSK_PIXEL_INVALID constant in pandora.constants
msk_pixel_invalid – int
- Returns:
the interpolate left disparity map, with the validity mask update :
If out & MSK_PIXEL_FILLED_MISMATCH != 0 : Invalid pixel : filled mismatch
- Return type:
tuple(2D np.array (row, col), 2D np.array (row, col))