OpenPIV (c++)

An implementation of a PIV analysis engine in C++ using as few dependencies as possible; the implementation requires a c++23 compliant compiler.

Build

There are some external dependencies under external/, so when cloning use:

git clone --recursive <path to git repo>

Building uses cmake; pre-requisites are:

• a compiler (e.g. apt install build-essentials)
• cmake
• git
• (linux) pkg-config (e.g. apt install pkg-config)
• curl, zip, unzip, tar (e.g. apt install curl zip unzip tar)
• ninja (e.g. apt install ninja-build)

To build:

• cmake -B build -S .
• cmake --build build

To run tests:

• cd build
• ctest

To change the build type, add -DCMAKE_BUILD_TYPE e.g. cmake -DCMAKE_BUILD_TYPE=RelWithDebugInfo -B build -S ..

The binaries are located in the build directory:

• build
  • test -> *_test
  • examples
    • process
    • average_subtract
  • openpiv -> libopenpivcore.so

Python Bindings

Python bindings are made through pybind11. Building python modules appears to be a non-trivial subject, however a setup.py is provided to build the core library as well as the python bindings using cmake.

To build using pip/setuptools:

• create a venv at the same level as the openpivcore directory
• activate the venv
• run pip against the name of the directory containing the openpiv code e.g. pip install <path to source>
  • a clean step should happen as part of the build, this can also be run manually with python setup.py clean

To build using cmake:

• install pybind11 using pip
• install pytest using pip
• specify the location of the installed pybind11 libs/cmake modules using -Dpybind11_ROOT=$(pybind11-config --cmakedir)
• specify that the python bindings should be built: -DBUILD_PYBIND=ON

e.g.

cmake -B build -S . -DBUILD_PYBIND=ON -Dpybind11_ROOT=$(pybind11-config --cmakedir)

Examples

• under build/examples are two simple applications:
  • process: a straight-forward PIV cross correlator
  • average_subtract: a utility to read in n images, find the average and write out n new images with the mean subtracted

TODO

• build
  • travis/github actions/CI
  • add clang/windows/OS X build
  • python bindings
• core
  • logging
  • iostream ops for ImageLoaders
  • image allocator support
    • shared memory
    • pooled memory
  • image loading
    • load/save PNM files
      • save double image
    • support loading multiple images from files: modify loader interface to read header, report number of images, extract indexed images
    • memory map files - check performance for large files
    • PNG - lodepng
    • RAW - libraw looks less than ideal but no alternative?
    • b16/PCO
  • utilities
    • split RGB to 4xgreyscale
    • join 4xgreyscale to RGB
    • split complex to planes
    • create complex from planes
  • add ImageInterface data iterators
  • remove data() method from ImageInterface, ImageView
  • allow ImageView to be non-const
• algorithms
  • transpose
  • normalize
  • FFT
    • spectral correlation
    • optimize
    • openCL
    • apply kernel in Fourier space
    • use SIMD?
    • real -> complex FFT/correlation of real data
  • direct correlation
  • peak detection
  • un-bias peak detection - requires information about interrogation area geometry
  • peak fitting
• image processing
  • change image_view to use array of pointers for each row?
  • low/high pass filter
• examples
  • parallel cross-correlate
  • image processing
• processing framework
  • cartesian grid generator
  • further grid generators
  • median validation with secondary peak check and interpolation
  • store signal/noise value
  • processing
  • marking
  • iterative analysis
  • PIV guided PTV?
• data output
  • output registry
  • ASCII/CSV
  • gnuplot/pyplot?
  • tecplot
• GUI
  • Qt?
  • websockets/HTML5?
  • webassembly + JS/HTML5?