Based on the paper: Koos et al.: DIC image reconstruction using an energy minimization framework to visualize optical path length distribution (Scientific Reports, 2016)
Requirements: OpenCV, OpenCL installed on your system. Build it with CMake!
Usage: dicgpu.exe [--str-conf <inline-config>|--file-conf <file-path>, ...], where inline-config=var1=value-of-var1,...,varn=value-of-varn
Default values for the variables:
verbose=1,wAccept=0.025f,wSmooth=0.0125f,direction=135.0f,nIter=20000,locSize=64,kernelSrcPath=dic-rec.cl,input='',output='',platformId=0,deviceId=0
The platformId and the deviceId controls which OpenCL device should be used for the computation. To discover the available devices on your system, run the app with the single parameter --get-devinfo that gives something like this:
0;0;Intel(R) HD Graphics Kabylake Halo GT2 (Intel)
1;0;GeForce GTX 1060 (NVIDIA Corporation)
It means that there are 2 devices discovered, the platform id is the first value while the device id is the second one. (The platform id and device id uniquely identifies a computing device.) The third value is the name and the manufacturer of the device, obviously.
input: the input file path, output: the output file path, kernelSrcPath: the path of the dic-rec.cl file.
In the case of the config file: every variable-value pair is in a separate line. Empty lines are allowed while the lines starting with # are treated as comments and won't be parsed.
You can combine multiple settings. The default settings will be overriden by the --str-conf or --file-conf setup.
For example, the following is a valid usage:
dicrec.exe --file-conf common-settings.conf --str-conf verbose=0 --str-conf nIter=20000,direction=135.0f --str-conf input=examples/bloog.png,output=examples/blood-reconstructed.tif