Inputs

Pandora works with two stereo rectified one-channel or multi-channel images.

Configuration and parameters

Pandora input configuration files are divided into two parts: left and right.

Left input

Name	Description	Type	Default value	Required
img	Path to the left image	string		Yes
nodata	Nodata value for left image	int	-9999	No
disp	Path to the disparity grid of the left image or [min, max] values	string or [int, int]		Yes
mask	Path to the left mask	string	none	No
classif	Path to the left classification map	string	none	No
segm	Path to the left segmentation map	string	none	No

Right input

Name	Description	Type	Default value	Required
img	Path to the right image	string		Yes
nodata	Nodata value for right image	int	-9999	No
disp	Path to the disparity grid of the right image or [min, max] values	string or [int, int]	none	No
mask	Path to the right mask	string	none	No
classif	Path to the right classification map	string	none	No
segm	Path to the right segmentation map	string	none	No

Requirement

Note

disp parameter is only required for left image.

Images

• If the input images are multiband, the band’s names must be present on the image metadata. To see how to add band’s names on the image’s metadata, please see FAQ.

• For semantic segmentation classification, the band’s names must be present on the image metadata. To see how to add band’s names on the image’s metadata, please see FAQ.

• Only one-band masks are accepted by pandora. Mask must comply with the following convention :

  • Value equal to 0 for valid pixel

  • Value not equal to 0 for invalid pixel

• For more details please see As an API images subsection

Note

• Parameter left disp can be the disparity range (type list[int, int]) or the path to the grids that contain the minimum and maximum disparity of a pixel (type string).

• If left disp is a tuple of integers, then the range of disparities is fixed. The minimal and maximal disparity of the right image are automatically calculated : right disp[0] = - left disp[1] and right disp[1] = - left disp[0] where index 0 correspond to min and index 1 correspond to max.

• If left disp is a string, that means it is the path to grids of disparities which have the same size as the input images. Each pixel (x,y) of the grid corresponds to a local disparity (min for left disp[0] and max for left disp[1]) related to the same pixel (x, y) of the image.

• Cross-checking step is not applicable if only left grids are provided (i.e the right one must be provided).

Note

Mask must comply with the following convention

• Value equal to 0 for valid pixel

• Value not equal to 0 for invalid pixel

Note

If the input images are multiband, the band’s names must be present on the image metadata. To see how to add band’s names on the image’s metadata, please see FAQ.

Note

The input classification image must have one band per class (with value 1 on the pixels belonging to the class, and 0 for the rest), and the band’s names must be present on the image metadata. To see how to add band’s names on the classification image’s metadata, please see FAQ.