== Processing the InfraTec IR8300 data ==

The data are in ascii files with a .asc extension. They have 3 sections, the first 2 containing metadata and the 3rd containing the image data.

The procedure to process the data is:
* convert asc to tif files for easier managing / tagging using {{{convert_infratec_to_tif.sh}}}
* tag the images with the navigation information using {{{get_nav_for_infratec_image.py}}}

After this the images are ready to be geocorrected with APL using the photo geocorrection methodology, using {{{photo_geocorrection.py}}}

There is a helper script {{{infratec_quick_run.sh}}} and container {{{process_infratec}}} that can be used to make this a little easier, but loses some functionality of the individual scripts.

== Instructions for container method ==

Build the container if it doesn't already exist (it does!) by using the {{{make_docker.sh}}} script and the {{{-I}}} flag.

Then run it with the following inputs:
{{{
COMPULSORY
-i <dir> = input directory of asc files from Infratec instrument
-o <dir> = output directory where tifs and geocorrected imagery goes
-s <file> = SBET file of navigation to tag to images
-c <file> = the config file for the geocorrection

OPTIONAL
-d = delete the intermediate geocorrection files
-r = rotate the Infratec imagery by 180 degrees
}}}

It's important that the container can see the drives where the data are - if not in the user home space or /tmp then you must bind the drives to the container. This is easiest done by exporting the global variable SINGULARITY_BIND, e.g. to add the arsf data you may mount like this:

{{{export SINGULARITY_BIND="/users/rsg/arsf/arsf_data/:/users/rsg/arsf/arsf_data/}}}

The command then can be run:

{{{
process_infratec.sif -i  /users/rsg/arsf/arsf_data/2022/flight_data/uk/GB22_02-2022_230_Alconbury/thermal/infratec/ImageIR_8300/220818_151730_line14 -o /tmp/quickouts/ -s sbet_2022230.out -c photo_geocorrection.cfg -d -r
}}}