mia-2dseriessmoothgradMAD {-i string} {-o io} [ options ...] [ Plugin type: 2dimage/filter ...]


Given a set of images of temporal sucession, evaluate the temporal pixel-wise gaussian and evaluate pixel-wise its MAD.A spacial pre-filtering may be applied by specifying additional plugins (filter/2dimage)


-i, --in-file=(input, required); string

input segmentation set

-o, --out-file=(output, required); io

output file name. For supported file types see Plugin type: 2dimage/io

-k, --skip=0; ulong

Skip files at the beginning

-e, --enlarge-boundary=5; ulong

Enlarge cropbox by number of pixels

-c, --crop

crop image before running statistics

-g, --gauss=1; ulong

gauss filter width for moothing the gradient

Help & Info

-V, --verbose=warning; dict

verbosity of output, print messages of given level and higher priorities. Supported priorities starting at lowest level are:

info:Low level messages
trace:Function call trace
fail:Report test failures
error:Report errors
debug:Debug output
message:Normal messages
fatal:Report only fatal errors
--copyright=(); bool

print copyright information

-h, --help=(); bool

print this help

-?, --usage=(); bool

print a short help

--version=(); bool

print the version number and exit


--threads=-1; int

Maxiumum number of threads to use for processing,This number should be lower or equal to the number of logical processor cores in the machine. (-1: automatic estimation).


Evaluate the MAD-image of the bounding box surrounding the segmentation from a series segment.set after applying a temporal Gaussian filter of width 5. No spacial filtering will be applied. The bounding box will be enlarged by 3 pixels in all directions. Store the image in OpenEXR format.

mia-2dseriessmoothgradMAD -i segment.set -o mad.exr -g 2 -c -e 3


Gert Wollny