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https://github.com/alexlib/awesome_piv

List of repositories related to PIV (particle image velocimetry) to learn from
https://github.com/alexlib/awesome_piv

List: awesome_piv

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List of repositories related to PIV (particle image velocimetry) to learn from

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README 

        



# Awesome PIV

[![Awesome](https://awesome.re/badge-flat.svg)](https://github.com/sindresorhus/awesome#readme)

![CI](https://github.com/alexlib/awesome_piv/workflows/CI/badge.svg)



A curated list of repositories related to PIV (particle image velocimetry). 



*`Please send pull requests or raise issues to improve this list.`*






- [Awesome PIV](#awesome-piv)

  - [1. Synthetic image generation for PIV](#1-synthetic-image-generation-for-piv)

  - [2. PIV pre-processing](#2-piv-pre-processing)

  - [3. PIV analysis](#3-piv-analysis)

  - [4. Particle tracking](#4-particle-tracking)

  - [5. Post-processing](#5-post-processing)

  - [6. Neural Networks, Machine learning, AI](#6-neural-networks-machine-learning-ai)

  - [7. Dataset](#7-dataset)

  - [8. Visualization](#8-visualization)

  - [Unsorted](#unsorted)



--------------------------------



## 1. Synthetic image generation for PIV



- [matthewgiarra / piv-image-generation](https://github.com/matthewgiarra/piv-image-generation): Synthetic image generation for particle image velocimetry. ![matlab] ![cpp]



## 2. PIV pre-processing



- [scikit-image / scikit-image](https://github.com/scikit-image/scikit-image): Image processing in Python ![python]

- [opencv / opencv-python](https://github.com/opencv/opencv-python):  Open Source Computer Vision Library ![python]



## 3. PIV analysis



- [OpenPIV / openpiv-python](https://github.com/openpiv/openpiv-python): OpenPIV consists in a Python and Cython modules for scripting and executing the analysis of a set of PIV image pairs. ![python]

- [MattEdwards94 / AdaptivePIV](https://github.com/MattEdwards94/AdaptivePIV): A repository  analysis of PIV images using adaptive PIV image analysis approaches (also test cases) ![python]

- [gbcarlos/piv](https://github.com/gbcarlos/piv): Particle Image Velocimetry with Python (and few test pairs) ![python]

- [philippemiron / pypiv](https://github.com/philippemiron/pypiv): Simple PIV script (with synthetic images) ![python]

- [DidierMD / MyPyPIV](https://github.com/DidierMD/MyPyPIV): (nice notebook) ![python]

- [j-colas / piv_demo](https://github.com/j-colas/piv_demo): Simple Particle Image Velocimetry algorithm demo based on zero-mean cross correlation. (with affine transform test) ![python]

- [forughi / PIV](https://github.com/forughi/PIV): A flexible and hackable Particle Image Velocimetry (PIV) code in Python and Matlab. (educational) ![python] ![matlab]

- [kemeyer / par2vel](https://github.com/kemeyer/par2vel): Par2vel is a python toolbox for doing Particle Image Velocimetry (PIV). It is aimed for research and education. (educational)![python]

- [jruebsam / pypiv](https://github.com/jruebsam/pypiv): PyPIV is a python library for Particle Image Velocimetry (PIV), including pre and postprocessing functions. (great copy of the Matlab single-pixel package) ![python]

- [DidierMD / PolyPIV](https://github.com/DidierMD/PolyPIV): Particle Image Velocimetry software used for fluid analysis. ![cpp]

- [xylar / acciv](https://github.com/xylar/acciv): Advection-corrected Correlation Image Velocimetry ![cpp] ![matlab] ![python] 

- [rdeits / adaptive-PIV](https://github.com/rdeits/adaptive-PIV): An FPGA implementation of Particle Image Velocimetry for 6.375 at MIT  (real-time MIT implementation) ![matlab] ![cpp] ![python]

- [benjaminpelc / pivelocimetry](https://github.com/benjaminpelc/pivelocimetry):  C++ implementation of cross-correlation based particle image velocimetry ![cpp]

- [psellapp / USC_PIV](https://github.com/psellapp/USC_PIV): Particle Image Velocimetry(PIV) codes developed at USC ![matlab]

- [OpenPIV / openpiv-matlab](https://github.com/openpiv/openpiv-matlab): Matlab version of the OpenPIV project (open source Particle Image Velocimetry) ![matlab]

- [ufo2mstar / nu_piv_algorithm](https://github.com/ufo2mstar/nu_piv_algorithm): A Nu Particle Image Velocimetry Algorithm (better than FFT) in MatLab (genetic algorithm, claims to be better than FFT) ![matlab]

- [nnmrec / bfield_piv](https://github.com/nnmrec/bfield_piv): This code utilizes the MatPIV toolbox to perform the PIV calculations of velocity field. (extension of MATPIV) ![matlab] ![imagej]

- [MaxVWDV / glacier-image-velocimetry](https://github.com/MaxVWDV/glacier-image-velocimetry):  GUI based toolbox for calculating glacier surface velocities from satellite imagery. ![matlab]

- [eguvep / jpiv](https://github.com/eguvep/jpiv):  JPIV – Particle Image Velocimetry (PIV) evaluation software. ![java]

- [Tianshu-Liu / OpenOpticalFlow](https://github.com/Tianshu-Liu/OpenOpticalFlow): OpenOpticalFLow PIV ![matlab]

- [Kristian J. Sveen / MatPIV](https://www.mn.uio.no/math/english/people/aca/jks/matpiv/): MatPIV ![matlab]

- [William Thielicke / PIVLab](https://github.com/shrediquette/pivlab) PIVLab ![matlab]

- [

Gerber van der Graaf / GPIV](http://gpiv.sourceforge.net) GPIV ![cpp]

- [fluiddyn / fluidimage](https://foss.heptapod.net/fluiddyn/fluidimage/): Asynchronously parallelized libre framework for pre-processing, velocimetry and post-processing of large series of images. ![python]

- [dpivsoft_opencl](https://gitlab.com/jacabello/dpivsoft_python): OpenCL implementation of DPIVSoft on GPU ![python]



## 4. Particle tracking

- [jonnyhigham / PTVResearch](https://github.com/jonnyhigham/PTVResearch): Robust particle tracking for all types of research applications (Lucas Kanade) ![matlab]

- [fabiotosi92 / Optical-Tracking-Velocimetry](https://github.com/fabiotosi92/Optical-Tracking-Velocimetry): Optical tracking velocimetry (OTV) (optical flow and tracking) ![cpp]

- [jorishey1234 / tractrac](https://github.com/jorishey1234/tractrac): TracTrac: Massive Parallalized Particle Tracking Velocimetry Software ![matlab] ![python]

- [Part2Track / Part2Track](https://github.com/Part2Track/Part2Track): A MATLAB package for double frame and time resolved Particle Tracking Velocimetry ![matlab]

- [adavradou / Particle-Tracking-Velocimetry](https://github.com/adavradou/Particle-Tracking-Velocimetry) (extends https://site.physics.georgetown.edu/matlab/code.html) ![matlab]

- [JHU-NI-LAB / OpenLPT_Shake-The-Box](https://github.com/JHU-NI-LAB/OpenLPT_Shake-The-Box): Open-source C++ code for Shake-the-box, particle tracking algorithm ![cpp] ![matlab]

- [OpenPTV / openptv](https://github.com/openptv/openptv) OpenPTV - open source 3D-PTV software ![cpp]

- [OpenPTV / pyptv](https://github.com/openptv/pyptv) Python GUI for OpenPTV - open source three-dimensional particle tracking velocimetry ![python]



## 5. Post-processing



- [IOMRC / piv](https://github.com/IOMRC/piv): A variety of PTV and PIV experiments are taking place within the Indian Ocean Marine Research Centre. ![python]

- [SaraSis / PIV-data-process](https://github.com/SaraSis/PIV-data-process): Some codes used to process the fluid experiments data (dissipation, strain) ![python]

- [Jwely / pivpr](https://github.com/Jwely/pivpr): Exploration of the Pressure Relaxation phenomena with Particle Image Velocimetry (pressure relaxation with PIV) ![python] ![matlab]

- [OpenPIV / openpiv-spatial-analysis-toolbox](https://github.com/OpenPIV/openpiv-spatial-analysis-toolbox): Spatial Analysis Toolbox is a collection of Matlab subroutines and GUI to streamline the post-processing of the particle image velocimetry (PIV) data obtained by OpenPIV (or other) software. ![matlab]

- [philippemiron / piv-analysis](https://github.com/philippemiron/piv-analysis): Different code for particles image velocimetry analysis (C++, Tecplot) ![cpp]

- [hujc91 / PyPostPiv](https://github.com/hujc91/PyPostPiv): A high level library for post processing PIV results. ![python]

- [ronshnapp / vecpy](https://github.com/ronshnapp/vecpy): Python based package for manipulation and presentation of PIV (particle image velocimetry) results. (See https://github.com/alexlib/pivpy) ![python]

- [fabrylab / pyTFM](https://github.com/fabrylab/pyTFM): Two dimensional particle image velocimetry, traction force microscopy and monolayer stress microscopy (tracking force microscopy) ![python]

- [rplab / Ganz-Baker-Image-Velocimetry-Analysis](https://github.com/rplab/Ganz-Baker-Image-Velocimetry-Analysis): A set of Matlab functions for analyzing image velocimetry data on biological motility (PIVLab postprocessing) ![matlab] ![cpp] ![python]

- [mathLab / PyDMD](https://github.com/mathLab/PyDMD):  Python Dynamic Mode Decomposition ![python]

- [Moisy / PIVMAT](http://www.fast.u-psud.fr/pivmat/) Matlab toolbox for post-processing PIV data ![matlab]

- [alexlib / pivpy](https://github.com/alexlib/pivpy): PIVPy - Python clone of PIVMAT ![python]



## 6. Neural Networks, Machine learning, AI



- [yongleex / PIV-DCNN](https://github.com/yongleex/PIV-DCNN): Perform PIV image pair match using deep conv neural network ![matlab] ![cpp]

- [shengzesnail / PIV-LiteFlowNet-en](https://github.com/shengzesnail/PIV-LiteFlowNet-en): Particle image velocimetry via a deep neural network (LiteFlowNet) ![cpp] ![python] ![matlab]

- [erizmr / UnLiteFlowNet-PIV](https://github.com/erizmr/UnLiteFlowNet-PIV): Unsupervised learning of Particle Image Velocimetry. (ISC 2020) ![python]



## 7. Dataset



- [idies / pyJHTDB](https://github.com/idies/pyJHTDB):  Python wrapper for the Johns Hopkins turbulence database library ![python]

- [shengzesnail / PIV_dataset](https://github.com/shengzesnail/PIV_dataset):  PIV dataset ![matlab]



## 8. Visualization



- [matplotlib / matplotlib](https://github.com/matplotlib/matplotlib): matplotlib: plotting with Python ![python]

- [K3D-tools / K3D-jupyter](https://github.com/K3D-tools/K3D-jupyter): K3D lets you create 3D plots backed by WebGL with high-level API (surfaces, isosurfaces, voxels, mesh, cloud points, vtk objects, volume renderer, colormaps, etc). ![python] ![javascript]

- [QuantStack / ipygany](https://github.com/QuantStack/ipygany):  3-D Scientific Visualization in the Jupyter Notebook ![python]

- [InsightSoftwareConsortium / itkwidgets](https://github.com/InsightSoftwareConsortium/itkwidgets):  Interactive Jupyter widgets to visualize images, point sets, and meshes in 2D and 3D ![python] ![javascript]

- [NVIDIA / ipyparaview](https://github.com/NVIDIA/ipyparaview):  iPython widget for server-side ParaView rendering in Jupyter. ![python] ![javascript]



## Unsorted



- [alexlib / testcase_outofplane_PIV](https://github.com/alexlib/testcase_outofplane_PIV) ![python]

- [alexlib / openpiv_pivlab_comparison](https://github.com/alexlib/openpiv_pivlab_comparison): Discussion started on the forum about comparison with PIVLab and OpenPIV-Python, including PIVPy post-processing ![python]

- [alexlib / Particle-Image-Velocimetry-1](https://github.com/alexlib/Particle-Image-Velocimetry-1): 'Difference' Algorithm for PIV (Particle Image Velocimetry) , for finding flow field of particles. ![python]

- [vccimaging / RainbowPIV](https://github.com/vccimaging/RainbowPIV): This is the source code for 2017 SIGGRAPH paper "Rainbow Particle Imaging Velocimetry for Dense 3D Fluid Velocity Imaging" ![matlab]

- [olegsamoylov / ECEI_velocimetry](https://github.com/olegsamoylov/ECEI_velocimetry) ![python]

- [dscripka / photon-doppler-velocimetry-data-analysis](https://github.com/dscripka/photon-doppler-velocimetry-data-analysis): Webapp built with Bokeh and Python for analysis of Photon Doppler Velocimetry (PDV) data. (Bokeh app, wavelets) ![javascript]



[python]: https://img.shields.io/badge/Python-lightgrey.svg?logo=data%3Aimage%2Fpng%3Bbase64%2CiVBORw0KGgoAAAANSUhEUgAAABQAAAAUCAMAAAC6V%2B0%2FAAACClBMVEUAAABAgL83erM4ebA2eK43d603dqs3dak2dKg3c6Q5erM4ebA3d643caI3ebA3ea0AgIA3dqs3cKA3d643d603d6s3cJ44dq42dqs2dKk2dKc2cqU2cqM2bpw2ebQ3ebA3eK43d603dqs3dqk3dKg3c6U3cqQ3caI2bZr%2F2Ev%2F2Ej%2F1kf%2F1EU3erE4ebA2bJn%2F2Uj%2F0kI3eLA2a5f%2F1kb%2F0T83eK42a5T%2F1UT%2Fzz83caI4b6A4b542bpw2bps2bJk2a5c1apX80kb%2F00Q3dqs3cqM3cKH%2F31H%2F3k%2F%2F3E7%2F3Ez%2F2Ur%2F10r%2F1kf%2F1UU4dak3caL%2F4FH%2Fyzo3c6c4b6D%2F3k7%2FyTk1c6U3cJ7%2F3E7%2Fyjn%2Fxzg3caM3b543bp3%2F20z%2F00T%2F0kL%2F0UH%2F0D%2F%2Fzj%2F%2FzTz%2Fyzr%2Fyjn%2Fxzj%2F2kv%2F00P%2F0EL%2F0ED%2Fzj7%2FzDz%2F2En%2Fzj7%2FzTz%2Fyzv%2F10f%2Fzj7%2FzDP%2Fyjz%2Fyjr%2F1Ub%2F1ET%2FzDv%2FyTf%2F1UL%2F0UH%2F0ED%2Fzj7%2FzTz%2FzDz%2Fyzn%2Fyjj%2Fv0A3d603dqs3dak3dKc3c6U3cqQ3caI3cKA3b542bpw3eK42bZr%2F1kf%2F1UX%2F00Q2bJn%2F0kI3cqM2a5f%2F0UD%2F0UH%2Fzz%2F%2Fzj3%2F1ET%2FzDz%2F3k%2F%2F3E7%2F20z%2F2Ur%2F2En%2F1Ub%2FzTz%2F10f%2Fzj7%2Fyzr%2F2Uv%2F0kP%2F0D%2F%2F00P%2F0ED%2F%2F%2F9ywrbbAAAAhXRSTlMABGu%2F6vn25bJUkOWrfs%2BDAu%2Fbz%2FbV4G6IiIiI%2BOA9uMzMzMzMzMz84HDu5ncu%2BeB4VaHRe73fda%2F00K6qqqqqoldQ%2FPX%2BVFiou7u7u7vU4b9r8KiOwLA%2Bi836N2Hugs3NzMzMzMzMskDNioiIiHjN0vDiyPsKb%2BJm%2FrmdQqXY7vHjuWkEM28rJQAAAO9JREFUGNNVkK1OA1EYROfcO5emWTYNxeMRhFoUmhB4AhDFoUhwJHVYFBgUCo0hQZUXQKAIkkcogrTkErJB7C4sI8%2FM95NBkkSrT0mSJUl9OAPg%2FEOSQm3ZFwCkTjLBKQDuQMMVnECvgWt0VKwDL95gvPhloccYbpwOO8wGgoMXAGXNok2I9htAedvuJJgjj4BpnQT2syG4gLJgD%2BB9mLOhf2dTzg1AHOZslqvo4OkcG4hVw%2B4TOnjYhZ2vWD22n10jSTreilV%2BBrj8a2kpVrnc3Lb%2FFVLlwWzlKVEP1sn0Opitfo9SU11tadIemUjSD%2Bs0MpPwiOyPAAAAAElFTkSuQmCC



[matlab]: https://img.shields.io/badge/MATLAB-lightgrey.svg?logo=data%3Aimage%2Fpng%3Bbase64%2CiVBORw0KGgoAAAANSUhEUgAAABYAAAAUCAYAAACJfM0wAAAD3klEQVQ4y53UT4hVdRTA8e%2B5v%2Fvv3ffnzrw3M%2FiH0RjmT2PhkGZM9mdRL80MRWzjQhEXIZK6yBZBBS2iRRJChYsEg4yocBIUMfq3CDFKRWcMnJmmpkHnDTO%2BnJk3f9597977a%2FGQMhQZz%2BZszvlwOHCOsIDIb9uG6minmmvc0PXFkYOPFH4%2FnBszPiouEr1jaOq2WmMhMN3dVNo6FttDQ292ZQsrOlao16ZzstJTAP79wfkDB2D%2FfpFC4eVk36Xuzq45lq5hmeey65cR5PM2Fg7n162D9nY4dOgp48bE7uxwv9T7QmYxuC6bVi2h1ZQFwvmWFsjnYXi4Bct61%2BzvX9RYKeGGgmuBl2S5afCcI3Cs1b83nAfymzdDQ4PDyMhaUqmP9djYWq%2FvMnUJwQpAheAlEWXwYikkYf1navOOaLkMZ89CLtfG%2BfNvMzq6nomJrDEwgD9VJL1YkACMALwUKIM1lqbTEC7eMtT%2F0QSwbHoafeFCs5RKRygUNtHXl2B8HLf%2FKkvCWZbVC63NkErC7A0oTuBFMYOOcG5jvUvP38G%2FE%2B%2F94ze4fh1c1zbm5h6%2B9vWp16d6ep7h5k0QQTIZMlNFUq7g2qBDoAKOC7YN5QrrpyMOm8IcgLH32iB7tQatc2SzW4HP4jA80%2FTYqpey7S3IzAxYFvZYAV9iPIsaHAFVcJwabgirLKFTya0dz893MXTlBaJoC1G0kihyiGNM16Hp6ccxEgmKP%2F9KpjRJ2hE8CxwbtIY4BNMCNwHKIGdo8o5w4Virj0Ecr6dSeZUgWEMQOFSrEEWgNVopqhq8wij1piZpQtKtwQA6BtOEhFfLBmwoRWRMAYMwfJ9KZSfl8mWCACoViCJ0HHPjr1HKP%2FxILiyTMYWkDclEbRUCxDEoVYMdBwxhtSk8qgQMJidDJidPUa1upVr9lDCsRGEYTVwf1zMnT5MrjpO1hbQFGQ%2FStxADNGAo%2FrRtTpsW%2FcogpYQtvbOI8cETeejtg1JpSObn90TK3DWt7O0z33z3TtPw4EyTI9TZkE1D1gc%2FDZ4LSqG15rgy2eh5bI5CnhfhqCE8u9KjTe50ILsb0xTL2mrz1cH6BPsafGisg3of%2FBRkkpBwOZ6w2RPHjJsOfP8ViJAOY96KNaNyt5M%2ButonjHjwgaWcWdTE8pQHtgmmAjQ%2FodkBDDsW1L1X%2B8UnOnyAdKzpvivct9Nn3yfIqQ855ObYJ1XQ0xBOcmWuxHbT5FIQQMPB2x%2F88XYfQO4Ka%2B3DABDyJD4nCahjkIsM8QrNnIt7Qb0xxX2FHvHRV%2F2UnvBP6Dn%2FS93vP6S1j%2F7Wv2fvPzd4aYILeYaYAAAAAElFTkSuQmCC



[cpp]: https://img.shields.io/badge/C/C++-lightgrey.svg?logo=data%3Aimage%2Fpng%3Bbase64%2CiVBORw0KGgoAAAANSUhEUgAAADIAAAA4CAYAAAC%2FpKvXAAAG50lEQVR42tWYA3gkTRPH%2B7VtfrZtxznbTvLaPE6cnH1ZnG3b%2B8VeXWzvZsO16q3t57yYmUXwf55%2FMD3bXb%2FuqppJSKA0RySLiBLKzqO7r%2Fuc4xoZLIoSFv8wSig9joGDKyPMhdli6c%2FJQNXb62XPYKApaBMaWGyJFsgEMzcVvkAGihgG7p0jkk7D4NrQwNMaPL0PGeby%2FaQ%2FhQD%2FxWCkaPDRJf1SP7PFyu9HiWT7aBD%2B9fmYNOVPSaA1dZv0sWiBlMEFjWgIkM140quiBflPBawO8PhbAgbg3N3aHfUzdt%2B%2B%2B4g%2FhCfwJ5w4Cw39YexuhTFpsn%2F6Usiv445sw8nsaOh%2FS49jTN%2FhcQL5j16vAz0aBphNjvp5f3XFk8StAO7BYxyLN9f5sliMSA4Jhypg85UGOFbQBmelajgjVcHh3FbYhNeY%2FeX0Hh%2BBmrCGoh21e9cpyL%2BHg9m%2BTL70eBVklXeC3mQFNmmNVvh%2FiQZSj1X5CpQ1a5Psu9drQf6SL91oCQJUq3TgrcqatZBytNKn06GvOlFC%2BTpvJnh3kwIkuKt28F12nOSivJ3OyTMOfViy5MojM7ctJQ4ivhCf7yiBhnYD%2BFn0ZD%2Fdfo1TDONW5mY%2BMWt7I5koBnQT8QZC1WOCQEnVbYJPd7iHmbGhuOSN9w9IKcDt5gPx3mYFNGoMEGjVqvV0rbue9Jq%2FLjp39Z5JYisN3AcQ2pX6SLSr3Xj3ilySfvXBqZu7nQG8AFl1ugb4SqM1Q2WrDmpUetAarPwaAJo5UKJ4evaOOg8A%2FECiRTJo7jQCFxktNjhZ1Abz9pY5zbMAr12Qq8FotoEn4VqmGHFWGTsAT5D152q55Tbu%2FJc7S1jnm49ADS5qrddgsQvOV1Q8MGWThQbnbxBpXQ%2Bn1snjOUDvrb%2Fewq02O1xWqhtffWd3Bw3KG3PoVHQhT8LXEtqW%2BbbyuXtKcZO6O%2F8Zd4qtDnwHWcmhyI%2FktfKGmJVWXPPzz45n%2BgbAA%2BRATgtrd%2FliJ4%2FTEMi6%2Fhl78cp9UzYZ3QX14NRNcFHRBMKLpU5jz8zZTsdWnFLwA7mibAdPauowcIWwjV6Rnf7otG1qtt19ZPpmQGHaaZzGXn57Jx2TlLTwA8mu6ARPUtT3sEJMWZdf9ELMHk7tNK9KjZujA4csVhv9Oe1CCR0rbe6Clk49HTNZ6Bi%2Bfcu4geSwgMg9gMwWFDf9%2Bv096SQkMYeMTeNS0DTYXoMZHLLZ7fTnbZIKxxgNXGu03Oh0dGztWSXH1LqmAU9q1LhMLW3QglNX7gtNNJCgOLhuM4lIuUomCLv7JbUOshW7HeCzW2%2Br9tFL0tMfG7qkjQbvysFxGjJs2VVc3OoO5KFpmyG%2FWg27Miqdxp6L2k7HsBHwA1nN3n5pZ5uxrkjx2uQNcrcATkAJJWT02uI%2Ba7%2Fvb1GAjeWBiHlreWHMUjsNkIffmLgS9ktK1N99f1dzoEGoFQ09wCaJrA4eDEvkDPFQeCJklzSCQ3ojFu3xgtrHpm3WBhREcKEOUJxgXhyzjBXizUmrKMTdatb0Wt9Nu1iKfzzZAgFC%2Fw%2FV1mUELursNcBX4ovwyrjlLlMpfocEND168KSCihb9PxccrvA7yByBtJXZk68E7qLPAGWtCk7lVMCFwmqobumkvZ%2FP5%2F%2F%2B8TYpGS9o8geIKTLx0tUHw5J7HDu676oS%2Bko7LshunKSORCy%2BQiaI9F6BTFqZk%2FvUyOX1t6fGU8NTobS%2BHQIteU2bY6272nV8Mxm%2BMh2DtnMCmbm%2BqPRbU4XF7gr125NXQ6O6BwKlelU3rSV36yPQNTJ6fZkrkFZaB0KZ5q9fHLl6T3Ccla3rfGvyKiipV4O%2FJa1qhdevQ7DYRsKS08l4oeo6SAuZkybdQOsgPKmbz8PsiWEpNI%2F9pY2ni%2BicPB%2BqWlo%2FkzauJeS%2FCa%2FhBTUavHHY1ztpTnurgvJmCP1qJ53LS6tIMPMqofof81MSFC%2F3djJMRxgyfzccSi8Bg8kCbNIazLD7koJuAn7WewiMmcZ%2BhxjmXhychm5Dg7d%2BOCIJ%2Fv3pVnh39SlYuj8LBCcKqJN3p8M7eO0vH2yCRyKTfAieugOL%2FkPyb%2BZ%2B4laRyc%2BQoNgUvNmEhgFmC1pAwpNeIJz1P%2BaH%2BKETAwjiAvoXxGsFxQeR4DhFPwKUk%2BDYscQv%2Bp3gAZqTQXGdfQjQiynOkPDVDxG%2FK5R5Fk9nFS5iDSCADbNgG%2Flf4ksk0MKFfoILng4AxGUSGvcr0ucKiR2Ki1f5AaCetv5%2B1Vjmwev10%2B0FgJbWwb%2BZh8mAUWjiK7THc6sfO6bnPhLEvEkGrP7L%2FBYDlXiAyCX%2Fi%2FsLGRyCezDYCY6g0Rbq4NgcxzU6FgB9A0T9f5VBrS%2FNAAAAAElFTkSuQmCC



[imagej]: https://img.shields.io/badge/ImageJ-lightgrey.svg



[javascript]: https://img.shields.io/badge/JavaScript-lightgrey.svg?logo=data%3Aimage%2Fpng%3Bbase64%2CiVBORw0KGgoAAAANSUhEUgAAACgAAAAyCAMAAAAZbWmiAAABj1BMVEUAAADWujLbwkvYvTrYvjzTuDHZwEPWujHUuDHWujLWujHWujLXvDXWuzTWujLXuzXWujHXvDjWujLWujLWujLWujLWujHWujLWujLWujLWujLWujHWujLWujHVujTWujHWujLWujHWujHWujHWujHWujHWujLWujLWujLWujLVujHYvj3XuzTWujLWujL%2F%2F%2F%2F%2F2j7%2F%2Fvv%2F2kDVuTHs7vf%2F2DLVuS%2F%2F%2F%2F3j2KT40zHVtynr7O3%2F6ozp59vWujPXvDzr6%2Bn10jvUtyf31Dv%2F2Tb%2F2jv%2F8rr%2F5Xj%2F3D751T3dwDTs7fTUtiX%2F4WX%2F3Un82D3k2qvwzznXuzX%2F1y%2F%2F%2FO7%2F6IX%2F5nvcyWnaxFXryzjYvDLtyzDzzy7%2F99X%2F9cz%2F7qn%2B5HP%2F4GD%2F4Vr%2F31b%2F3ELXvkDmxjbhwjTavTPnxzLu8v%2F%2F%2FPP%2B%2BeT%2F9ML%2B8LL%2F5W%2Fdym%2F%2F4mf%2F42PZwlH%2F3k7%2F%2BuXq6eP%2B%2BN%2Fp6N%2Fo5dXo48%2F%2F7J3i1pzh1Zr%2F7Jfg0Yr%2B6Inezn%2F%2F6H3bxmH61DHAZCJOAAAALnRSTlMA%2FAIEjfwF%2Ff34meuLCHFWTT0zKiAR4NrQyb5fGAz98eW1qaGEfEhBOtSumGNoHFp97QAAA3FJREFUeNqN1QV78zYUBWA5XrDMzNxuV0lDxZDtMjMzfwxjhh%2B%2BI9%2BA%2B9SDU25ek3SkiP%2BfmrEv%2FjNjVYBfkkb%2FEY3KAYcoqP1HglQJWEsvEn0enLENsF574TaNrDNLAaoGbO9ymqj6trgQdmQBsAawopv89DxG2Jn1hyjVCWTECVNI1AiPlxJeP4oG64XwiBbH%2BERzudwUGVa8FGuRqKxBCF30OODW%2Fv77g4RxvTdfyN61oVFjhYJ9JZhIfxN72shNzsiI5CTlHyed1CyE8IlyJ5zNLE9MKZjkROS7Ey%2B1Cg%2FgAMMow%2BkYQ5mM2JEfj700KnRAx2Q7Yf7KkSvAEJhPVLnDszk7b9cevdQPpqMVfuKknPBqO24nfOelSkCPaoUb%2FGDmB%2FzeS202rA%2BS26VXzfGwHbsTOmBD2X%2FCYTCPqGgkzR2qcCfAkOao3w3Gzfj2dtxSnWgHxGdrYcSfw%2FHLi5nzs5nJFDrBcBTw5VN%2FvZOU%2BPHLZCc1%2BQSii5DbPUKpWZS76ESL8HArXGESDJ3YszvBsNIFAvFcv8NU9wrdvnSbG5Ty1ekcvqvyhPKwWsFUCeYmd1%2B%2FnfnwOb4WQXnsTjCsUSSXwLJiuLJ4Y8W3Tcu8TMpXnwErbegRdXC3%2B%2BlcLkF5GFbL8Ma8lHJnDZ2oYohWpKYOlmc33t%2BuJBjCYSGau1K%2BHsdUDzJEK1JTnzLTseXvNn6fzSgItXZx%2Fm0yKU8twFogFV%2BTgsh0LJYBzC2u7c7tqMFBz82HqMadwLdmXDo2neE8W1zyzV9b0a52hjpaEbjdmF2GLUFEjfc5OtHdUYC9pCVy6f2J75djy4V1LdGI0x9Xb7IaNeFRSq1IJXK5rT9%2F%2FmGad4rkzpvfrq1tM5wNqE7YZ%2FSJftKiRCnYldTBT79OTe7NXaxheDBKC5te6hF8Sr3UitRWdGolYe9mFlYBsnDopT6GjlawVRuprZB1BcuLcJCh2467gOU%2FIHx5OOwOF8Lrm3dHQfqKoQet8JOm%2BZ1QqcXN%2B6OAN6BFuROQoiNURgUb5XcF43CJvN4A%2FtHVUw%2BCMK0ONRICC7ppK3U7Zb1V7TyKDNWpK4ZCTUTk1zSKsuruq1YLWmfH0qPbdrh8hPJpDA12qCcFA3RQAYv%2F6LUDLUF%2Fc3lNBSuEnUOq8%2FrUf2trcHo%2BThTZ3wXJNxi0L3gjAAAAAElFTkSuQmCC



[Java]: https://img.shields.io/badge/Java-lightgrey.svg?logo=data%3Aimage%2Fpng%3Bbase64%2CiVBORw0KGgoAAAANSUhEUgAAAEAAAABACAMAAACdt4HsAAABFFBMVEUAAAD%2BvGH%2BuWT9ezz%2BjEO968n8aDH%2Bi0b%2BsVb5Wir%2BhkL8bTP%2BgUD5WSn9ymv6YC37ZjG89er9dTj8cDj5Xiz9dTn5XCv7Yi39lkn%2Bdzz9yW77ajT8ajL9dDnA89%2F9hT%2F6YS37bTb9bzP7ajL%2BhUFoyPU7iNI6gMl6z%2Fas7vtFk9c9jdJoxfFMm%2BE6gMYub7w2e8ZduvBBidAxdME8hctRouU5f8Y5gcVXquMucL8%2Bhc44ecSi8f6i6f6g2fh32fkubbo2e8Y0eMMyd8Mwc8E%2BjNI5gMhHmuFnwPI6gslWqelGkNVCitBCic85gdM2fcc6gshHktUvcsA%2Fhc1Gk9o2dr5fvulJlNz4WCn4WCoubLgubbjC8FcCAAAAWHRSTlMADRhYLgG6NCb4O6FO%2FBHnxwZriex489MkZAmuqHIDRd%2BSfbZAKG6SFQlcZCNNwfvPLn3umT3IvDX4qOAOERob%2Ftfk6vO%2BtEYaojhmdoNywq1w9oxU5ziO7qeVwQAAA0tJREFUeNqkldWBg2AQhHG3GB7Xkvj6b%2BTY88ew%2F0TQWRfrPdiOZQbXM%2BP7QWgmIIoTMwPSycyFLI8LE75TUvkG%2FFUAa5MAbGBr4oGbw86AH9bQ2Hp%2BW4JJETgNRg7YFZD6cupHXbaY3wfA0IukropHe3EBDMA48%2Ft9Sb1eXEuHFPLNYU5EA42nKKCJ2vXnQqghVSRyDfVROikGsWMpkphcwu5sYVTw7ROc5SSFWjMQL9%2B8ooZRwT%2Bc4ConR2CjKeH424MOOVGEoP4noDkoJFwhkOMNyDUTNcmpi29TSC0Fzt%2BDcARijQl9xUnqN8yVJvjOiYscU6DsLQW8bd1%2BrjXII0uDWz34XwmZVAKkEW9fbRk72qU4ziYkE9VhSfTuj%2Bfrt6R9seCjt7LYchSIwjAjrEbZjrCKFYHGoWmoUAUMHrdzct%2F%2FPaYq7RIZ%2FVY4l18o3usbkNIbqkdbpF3oOwM9PPTm6%2FsH503L1h108H7XAwB%2FIBzjMoAr%2BcD0lg4AYXSzJ0sowqNY5YywdHeZB8Q9ML%2FDH0BCz%2FcvPI%2BGSZoFgU4YepD96N4%2FAJxDAqq93CZwD7s1S4y83yvKu6kHGUAlHAbVTTtmWJNG0VwzRk%2B%2FtwXQXeH3UW0g1nGVu%2BKxAadAxvLRJIQ67Q8LM46QxOBO4AjJNw%2BVZqC3J1bJOVdxx4W30zS1s0UQLLLUqwXOEuzVySw3NjxFpy3af57uq8JpSstLdbJ3cWHTi8rSYvHmTC2f2Sg0Uk3T7I7wYxdF4f8hyvJvvw5ZuRGuGWFoTGfVsl3Vg19anMqnLuwgoIrwC5hTHZ5gF2fFfJ5fiXsBTCsPF2S3h2T0qhmcvlsu8gDW7v0%2BVjeFphUbFT8WAKOXKzQlAF55%2Bj1K%2BmKWVwEPnnZcbKSu%2BlSvXpxgvpdNN5x5oUaS%2BDAPCI%2B67mq%2BnBkpIYlzeSA3l0sjAA4TLaGen3PYr5GGaaYzOQFIkrc1OpY97A75axYEHkF0m%2Bb9SRFL%2FKJ41Z%2BG26MqYTZw01pjRttTNLc7QCI%2FHqlFz%2BFj0kYSTiFh1saNy2xcKewf269yI%2BGTkcxwitO3z70k03cPCVI6nfXblYnPapgcu6thb8LoDZVVUXdHkXTI4J%2BBCs8ToaFwLgAAAABJRU5ErkJggg%3D%3D