This project provides two singularity definition files and one program file for implementing pycudadecon as an open source option for the UQ image-processing portal. Also contains a json file and batch file for testing purposes (more below)

Both singularity definiton files can be built either locally using the command below (substituting XXXX for the desired base, version should not matter but testing was done with version 3.9.0-rc.3) or via the sylabs remote builder.

sudo singularity build XXXX_base.sif XXXX_base.def

To run either base requires a full installation of singularity (any version). Be sure to run them using the --nv option in order to use cuda libraries.

example

singularity exec --nv conda_base.sif nvidia-smi

The main program process.py runs at the command-line and requires one or more options to be set for any real functionality. These options can be split into functions and arguments, functions take a file or files and perform some form of processing, arguments allow you to change some of the default behaviour of this processing. Every call to this function will create a 'pycudadecon_output' folder and put all created files in that folder (unless a 'pycudadecon_output' folder already exists)

-o, --otf: takes a path to a pre-generated otf file to be used for deconvolution

--deskew: if set, program will assume files have already been deskewed

--keep_deskew: if set, program will also save the deskewed image before deconvolution

-d, --destination: takes a file path and allows the destination folder of processed images to be something other than $PWD/pycudadecon_output/

--dxdata: int of the XY pixel size of the data

--dzdata: int of the data's pixel depth

--angle: int angle of the microscope

--otf_xy: int XY pixel size of the psf file

--otf_z: int psf file pixel depth

--background: int average background value to subtract for deconvolution

-p, --psf: takes a path to a psf file and generates an otf file, if created in the same call as another operation that requires an otf file, that operation will use this created otf file (overides --otf)

-t, --files: takes one or more paths to tiff file/s and processes them

-f, --folder: takes the form path_to_folder/pattern, where path_to_folder is simply the path to the source folder containing images to be processed, and pattern is a unix-style search expression.

-j, --json: takes a json of the same or similar form as test_json.json and uses the information contained within to set arguments as needed. A single json is equivalent to a commandline execution of this program with either -t or -f set, not both.

cudaSetDevice() error, This is the most likely issue you might encounter, it means that cuda can not detect the necessary driver files. This is a host machine issue. Check that your graphics driver is cuda-capable, check that running 'nvidia-smi' returns something (that is, succesful output will look a table, unsuccesful output will not run), and/or re-install your nvidia driver.

ValueError: not enough values to unpack (expected 3, got 2), if you get this error when attempting to generate an otf from a psf file, there is something faulty with the psf file

write failed because no space left on device, this can occur whilst building the definition file on a local machine with insufficiant memory. Consider building using the sylabs remote builder.