Most assignments require capability that you do not want to implement yourself. Thus you have to link against libraries. I will provide my version of tools that you can use to do the assignments, but you can use other libraries if you prefer (but then you are on your own regarding making it work and providing a compilable program that works on the graphics machines).
The TA and I will provide some support for these as they are used for research and are in continual development. Note that these libraries are currently unix (including MacOS which is unix) only. If you want to minimize your use of unix, then perhaps best to use Matlab.
The needed include files, library archive, and supporting libraries are available for the various machines on the UA CS network. Using the precompiled library is described next. In addition, a read only SVN repository is available (described below) for those that want to work on a machine outside the CS network. However, for full functionality, you will likely have to install additional libraries.
To get you started, there is an example program showing the use of a few functions here . There are hopefully enough comments in the code to get you started. The files
build.csh (tcsh users)
or
build.sh (bash users)
provide command lines that deal with the complexities of including and linking
for most machines on the CS network.
The files matrix.txt and image.tiff can be used as example data for the program.
Information on working with the vision lab library source code is available here.
Also available in html at: http://kobus.ca/research/resources/doc/kjb/KJB.html
Start with a "man kjb" or the above link. Note that the first part of the document is a bit overwhelming, as it is geared towards writing substantive vision components shared with the group and/or, writing code for the library itself. This document essentially gives you a template for the "INCLUDE AND LOAD" strategy described by "man kjb".
A key point is that "man kjb" gives a machine generated list of all routines which have at least minimal documentation. (Perhaps 1/2 of the routines of interest are documented.)
Note that there are man pages for the main data types. In particular, you can do:
man Vector
man Matrix
man KJB_image
man Pixel
(Either click on the link or use the "man" command.)
~kobus/doc/programming
I wrote it a few years back. Hopefully it is not too out of date.
Finally, the vision lab has a wiki that has a lot more information (not necessarily well organized) linked here. You will need the password. Email the instructor if you would it.
Specific routines for assignment two
For assignment one you might want to look at the man pages for:
read_matrix
get_random_matrix
multiply_matrices
max_matrix_element
ow_multiply_matrix_by_scalar
ow_subtract_scalar_from_matrix
ow_add_matrices
plot_open
plot_matrix_cols
get_MP_inverse
constrained_least_squares (grad students only)
(Either click on the link or use the "man" command.)
You will also want to use something like prompt_to_continue() so you (and the TA) can actually look at your plots. (This is used in the example program linked above).
For assignment three you might want to look at the man pages for:
multiply_by_transpose
multiply_with_transpose
diagonalize_symmetric
KJB_image (case sensitive; there is also a program kjb_image(1)).
Pixel
kjb_read_image
kjb_write_image
(Either click on the link or use the "man" command.)
For assignment four you might want to look at the man pages for:
least_squares (OK now that you know how to do it).
plot_open3
plot_matrix_values
(Either click on the link or use the "man" command.)
For assignment five you might want to look at the man pages for:
kjb_read_image
kjb_write_image
kjb_display_image
ow_make_black_and_white_image
bw_image_to_matrix
matrix_to_bw_image
get_1D_gaussian_mask
get_2D_gaussian_mask
x_convolve_matrix
y_convolve_matrix
convolve_matrix
init_cpu_time
get_cpu_time
(Either click on the link or use the "man" command.)