table of contents
MRCAL(1) | mrcal: camera projection, calibration toolkit | MRCAL(1) |
NAME¶
mrcal-calibrate-cameras - Calibrate some synchronized, stationary cameras
SYNOPSIS¶
$ mrcal-calibrate-cameras --corners-cache corners.vnl --lensmodel LENSMODEL_OPENCV8 --focal 1700 --object-spacing 0.01 --object-width-n 10 --outdir /tmp --pairs 'left*.png' 'right*.png' ... lots of output as the solve runs ... Done! RMS reprojection error: 1.9 pixels Worst reprojection error: 7.8 pixels Noutliers: 319 out of 17100 total points: 1.9% of the data Wrote /tmp/camera0-0.cameramodel Wrote /tmp/camera0-1.cameramodel
DESCRIPTION¶
This tool uses the generic mrcal platform to solve a common specific problem of N-camera calibration using observations of a chessboard. Please see the mrcal documentation at <http://mrcal.secretsauce.net/how-to-calibrate.html> for details.
OPTIONS¶
POSITIONAL ARGUMENTS¶
images A glob-per-camera for the images. Include a glob for each camera. It is assumed that the image filenames in each glob are of of the form xxxNNNyyy where xxx and yyy are common to all images in the set, and NNN varies. This NNN is a frame number, and identical frame numbers across different globs signify a time- synchronized observation. I.e. you can pass 'left*.jpg' and 'right*.jpg' to find images 'left0.jpg', 'left1.jpg', ..., 'right0.jpg', 'right1.jpg', ...
OPTIONAL ARGUMENTS¶
-h, --help show this help message and exit --lensmodel LENSMODEL Which lens model we're using. This is a string "LENSMODEL_....". Required unless we have a --seed. See L<http://mrcal.secretsauce.net/how-to-calibrate.html> for notes about how to select a model --focal FOCAL Initial estimate of the focal length, in pixels. Required unless --seed is given. See L<http://mrcal.secretsauce.net/how-to-calibrate.html> for notes about how to estimate a focal length. This is either a single value to use for all the cameras, or a comma-separated whitespace-less list of values to use for each camera. If such a list is given, it must match the number of cameras being calibrated --imagersize IMAGERSIZE IMAGERSIZE Size of the imager. This is only required if we pass --corners-cache AND if none of the image files on disk actually exist and if we don't have a --seed. If we do have a --seed, the --imagersize values must match the --seed exactly --outdir OUTDIR Directory for the output camera models --object-spacing OBJECT_SPACING Width of each square in the calibration board, in meters --object-width-n OBJECT_WIDTH_N How many points the calibration board has per horizontal side. If omitted we default to 10 --object-height-n OBJECT_HEIGHT_N How many points the calibration board has per vertical side. If omitted, we assume a square object, setting height=width --seed SEED A comma-separated whitespace-less list of camera model globs to use as a seed for the intrinsics and extrinsics. The number of models must match the number of cameras exactly. Expanded globs are sorted alphanumerically. This is useful to bootstrap the solve or to validate an existing set of models, or to recompute just the extrinsics or just the intrinsics of a solve. If omitted, we estimate a seed. Exclusive with --focal. If given, --imagersize is omitted or it must match EXACTLY with whatever is in the --seed models --jobs JOBS, -j JOBS How much parallelization we want. Like GNU make. Affects only the chessboard corner finder. If we are reading a cache file, this does nothing --corners-cache CORNERS_CACHE Path to the corner-finder results. If this file exists, I use the corners in this file. If it doesn't exist, I invoke mrgingham to compute the corners, and I write the results to that path. And THEN I compute the calibration off those observations. This file is a vnlog with legend "# filename x y level" (exactly what mrgingham reports). Each rown is an observed corners. If an image had no observations, a single row "filename - - -" is expected. The "level" is the decimation level used in detecting that corner. "0" means "full-resolution", "1" means "half-resolution", "2" means "quarter-resolution" and so on. A level of "-" or <0 means "skip this point". This is how incomplete board observations are specified. A file with a missing "level" column will fill in "0" for all corners. A non-mrgingham grid detector may be used by running that separately, and using this option to read the output. A detector may output weights instead of a decimation level in the last column. Pass --corners- cache-has-weights to interpret the data in that way --corners-cache-has-weights By default the corners we read in --corners-cache have columns "filename x y level". If the last column is a weight instead of a decimation level, pass this option. This is useful to support non-mrgingham chessboard detectors --pairs By default, we are calibrating a set of N independent cameras. If we actually have a number of stereo pairs, pass this argument. It changes the filename format of the models written to disk (cameraPAIR- INDEXINPAIR.cameramodel), and will report some uncertainties about geometry inside each pair. Consecutive cameras in the given list are paired up, and an even number of cameras is required --skip-regularization By default we apply regularization in the solver in the final optimization. This discourages obviously- wrong solutions, but can introduce a bias. With this option, regularization isn't applied --skip-outlier-rejection By default we throw out outliers. This option turns that off --skip-extrinsics-solve Keep the seeded extrinsics, if given. Allowed only if --seed --skip-intrinsics-solve Keep the seeded intrinsics, if given. Allowed only if --seed --skip-calobject-warp-solve By default we assume the calibration target is slightly deformed, and we compute this deformation. If we want to assume that it is flat, pass this option. --valid-intrinsics-region-parameters VALID_INTRINSICS_REGION_PARAMETERS VALID_INTRINSICS_REGION_PARAMETERS VALID_INTRINSICS_REGION_PARAMETERS VALID_INTRINSICS_REGION_PARAMETERS VALID_INTRINSICS_REGION_PARAMETERS For convenience we compute a valid-intrinsics region to describe the results of the calibration. This is a watered-down interpretation of the projection uncertainty that is easy to interpret. The logic computing this is somewhat crude, and may go away in the future. The defaults should be reasonable, so if in doubt, leave these alone. The intent is to produce usable output even if we're using a lean lens model where the computed uncertainty is always overly optimistic. We bin the observations into a grid, and use mrcal._report_regional_statistics() to get the residual statistics in each bin. We then contour the bins to produce the valid-intrinsics region. If we're using a rich lens model (LENSMODEL_SPLINED_...), then we only look at the uncertainty, and not at the other statistics. This argument takes 5 parameters. The uncertainty is computed at a range valid_intrinsics_region_parameters[4]. If <= 0, I look out to infinity. The default is 0. A region is valid only if the projection uncertainty < valid_intrinsics_region_parameters[0] * observed_pixel_uncertainty. The default is 1. A region is valid only if the mean-abs-residuals is < valid_intrinsics_region_parameters[1] (only for lean models). The default is 0.5. A region is valid only if the residuals stdev is < valid_intrinsics_region_parameters[2] * observed_pixel_uncertainty (only for lean models). The default is 1.5. A region is valid only if it contains at least valid_intrinsics_region_parameters[3] observations (only for lean models). The default is 3. --verbose-solver By default the final stage of the solver doesn't say much. This option turns on verbosity to get lots of diagnostics. This is generally not very useful to end users --explore After the solve open an interactive shell to examine the solution
REPOSITORY¶
AUTHOR¶
Dima Kogan, "<dima@secretsauce.net>"
LICENSE AND COPYRIGHT¶
Copyright (c) 2017-2023 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
2024-11-16 | mrcal 2.4.1-3+b1 |