giant.imageΒΆ
This module provides the OpNavImage class, which is the primary image type used by GIANT.
The OpNavImage class is a container to store both an image itself (raw DN values) as well as metadata about the image
that is required in various routines. The metadata includes information like the observation_date and time the image
was taken, the name of the camera used to capture the image, the position, velocity, and orientation at the time the
image was captured, among other things (see the OpNavImage documentation for more thorough details).
The OpNavImage class is a subclass of the numpy
ndarray class, with the image data itself
being stored in the array (so that you can use all of the usual numpy indexing/ufuncs as if it was just an ndarray) and
the metadata being stored as extra attributes. As such, the image data can be any type (float, int, etc) but be aware
that many of the GIANT routines cast the images to float type internally.
In general, you should not use this class directly, but rather subclass it so that you can automatically parse the
metadata for an image instead of having to manually specify it each time (by overriding the NotImplemented
parse_data() method). This also allows you to specify custom image loading routines if your project uses a
non-default image format (by overriding the load_image() method). As an example, check out the
getting started page.
Classes
This is a subclass of a numpy array for images which adds various parameters to the ndarray class necessary for the GIANT algorithms as well as some helper methods for loading in an image. |
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This enumeration provides options for the different ways an image can be be classified in GIANT |