MRCAL

NAME

mrcal-cull-corners - Filters a corners.vnl on stdin to cut out some points

SYNOPSIS

$ < corners.vnl mrcal-cull-corners --cull-left-of 1000 > corners.culled.vnl

DESCRIPTION

This tool reads a set of corner detections on stdin, throws some of them out, and writes the result to stdout. This is useful for testing and evaluating the performance of the mrcal calibration tools.

The specific operation of this tool is defined on which --cull-... option is given. Exactly one is required:

--cull-left-of X: throw away all corner observations to the left of the given
X coordinate
--cull-rad-off-center D: throw away all corner observations further than D
away from the center. --imagersize or --where must be given also so that we
know where the center is. If D < 0: we cull the points -D or closer to the
corners: we use a radius of sqrt(widthˆ2 + heightˆ2)/2. - abs(D)
--cull-random-observations-ratio R: throws away a ratio R object observations
at random. To throw out half of all object observations, pass R = 0.5.
--object-width-n and --object-height-n are then required to make the parsing
work

--cull-left-of X and --cull-rad-off-center throw out individual points. This is
done by keeping the point in the output data stream, but setting its
decimation level to ’-’. The downstream tools then know to ignore those points

--cull-random-observations-ratio throws out whole object observations, not just
individual points. These removed observations do not appear in the output data
stream at all

This tool exists primarily for testing, and probably you don’t want to use it. The filtering is crude, and the tool might report chessboard observations with very few remaining points. You PROBABLY want to post-process the output to keep only observations with enough points. For instance:

mrcal-cull-corners ... > culled-raw.vnl
vnl-join --vnl-sort - -j filename culled-raw.vnl \
<(< culled-raw.vnl vnl-filter -p filename --has level |
vnl-uniq -c |
vnl-filter 'count > 20' -p filename ) \
> culled.vnl

options:
-h, --help show this help message and exit
--object-width-n OBJECT_WIDTH_N
How many points the calibration board has per
horizontal side. This is required if --cull-random-
observation-ratio
--object-height-n OBJECT_HEIGHT_N
How many points the calibration board has per vertical
side. If omitted, I assume a square object and use the
same value as --object-width-n
--imagersize IMAGERSIZE IMAGERSIZE
Size of the imager. If --cull-rad-off-center is given:
we require --imagersize or --where
--cull-left-of CULL_LEFT_OF
Throw out all observations with x < the given value.
Exclusive with the other --cull-... options
--cull-rad-off-center CULL_RAD_OFF_CENTER
Throw out all observations with dist_from_center > the
given value. Exclusive with the other --cull-...
options. If --cull-rad-off-center is given: we require
--imagersize or --where
--cull-random-observations-ratio CULL_RANDOM_OBSERVATIONS_RATIO
Throw out a random number of board observations. The
ratio of observations is given as the argument. 1.0 =
throw out ALL the observations; 0.0 = throw out NONE
of the observations. Exclusive with the other
--cull-... options
--where WHERE WHERE Used with --cull-rad-off-center. Specifies the
location of the "center" point. If omitted, we use the
center of the imager. May NOT be given if --cull-rad-
off-center < 0. If --cull-rad-off-center is given: we
require --imagersize or --where
--filename FILENAME Apply the filtering only to observations where the
filename matches the given regex. May be given
multiple times: filenames that match ANY of the given
regexen are culled. If omitted, we cull ALL the
observations. Exclusive with --cull-random-
observations-ratio

REPOSITORY

<https://www.github.com/dkogan/mrcal>

AUTHOR

Dima Kogan, "<dima@secretsauce.net>"

LICENSE AND COPYRIGHT

Copyright (c) 2017-2021 California Institute of Technology ("Caltech"). U.S. Government sponsorship acknowledged. All rights reserved.

Licensed under the Apache License, Version 2.0 (the "License"); You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0