Inputs

Pandora2D needs a pair of images that rasterio can open and information about the no_data of the images and range disparities.

Configuration and parameters

Input section is composed of the following keys:

Table 2 Input section
Name	Description	Type	Default value	Required
left	Left image properties (see description below)	dict	None	Yes
right	Right image properties (see description below)	dict	None	Yes
col_disparity	The disparities for columns (see description below)	dict	None	If the estimation step is not present
row_disparity	The disparities for rows (see description below)	dict	None	If the estimation step is not present

Image (left and right) and disparity (col_disparity and row_disparity) properties are composed of the following keys:

Parameters :

Name	Description	Type	Default value	Required
img	Path to the image	string	None	Yes
nodata	Nodata value of the image	int, “NaN” or “inf”	-9999	No
mask	Path to the mask	string	None	No

Parameters :

Name	Description	Type	Default value	Required
init	Initial point or path to initial grid	int or string	None	Yes
range	The search radius (see Disparity range exploration)	int >= 0	None	Yes

Note

The initial disparity can be defined in two ways:

1. Constant value for all points

If the initial disparity is the same for every point in the image, the init dictionary key must be an integer.

2. Variable value for each point

If the initial disparity varies across the image, the init key must be a string pointing to one of the following:

A file path to a grid that contains an integer initial value for each point in the image.
Alternatively, a path to an output directory that holds the disparity grids generated by a previous Pandora2D run.

When using an output directory instead of a grid file, the following conditions must be met:

Both init values for the disparities must reference the same directory. Mixing grids from different runs is not allowed.
The step value defined in the pipeline configuration must match the one declared in the attributes.json file.

Note

When using a string initial disparity (i.e., a path to a grid or an output directory), it is possible to enter a no data value in the metadata of the initial disparity grid so that points with this value are ignored in Pandora2d calculations.

If a disparity map calculated by Pandora2D is used as the initial variable disparity grid, the invalid_disp value used in the Pandora2D disparity step configuration that calculated these disparity maps is automatically saved as no data in the metadata of the the row_map.tif and col_map.tif files.

Warning

If an output directory path is specified as input disparities and it contains disparity maps smaller than the image, these maps will serve as the ROI (see Region of interest).

Warning

If you provide a path to a disparity grid or an output directory as the initial disparity, and one of the initial disparity grids contains sub-pixel values, then these sub-pixel values are rounded to the nearest integer.

Values with a decimal of .5 are rounded to the nearest even integer (as is done in NumPy’s round function)

Warning

With sad/ssd matching_cost_method in the pipeline (see Sequencing), nodata only accepts int type.

In addition, when the nodata value entered is NaN or inf, it is replaced by -9999 in the image datasets to avoid disrupting processing.

Note

Only one-band masks are accepted by pandora2d. Mask must comply with the following convention:

Value equal to 0 for valid pixel
Value not equal to 0 for invalid pixel

Examples

Input with constant initial disparity

{
    "input":
    {
        "left": {
            "img": "./data/left.tif",
            "nodata": -9999,
            "mask": "./data/mask_left.tif"
        },
        "right": {
            "img": "/data/right.tif",
            "nodata": -9999
        },
        "col_disparity": {"init": 0, "range": 3},
        "row_disparity": {"init": 0, "range": 3}
    }
    ,
    "pipeline":
    {
        // pipeline content
    },
    "output":
    {
        // output content
    }
}

Input with variable initial disparity

{
    "input":
    {
        "left": {
            "img": "./data/left.tif",
            "nodata": -9999,
            "mask": "./data/mask_left.tif"
        },
        "right": {
            "img": "/data/right.tif",
            "nodata": -9999
        },
        "col_disparity": {"init": "./data/col_disparity_grid.tif", "range": 3},
        "row_disparity": {"init": "./data/row_disparity_grid.tif", "range": 3}
    }
    ,
    "pipeline" :
    {
        // pipeline content
    },
    "output":
    {
        // output content
    }
}