PlantCV: Plant phenotyping using computer vision
Please use, cite, and contribute to PlantCV!
If you have questions, please submit them via the
GitHub issues page.
Follow us on twitter @plantcv.
Introduction to PlantCV
PlantCV [1] is an imaging processing and trait extraction package designed for plant biology research
that is built upon open-source software platforms OpenCV [2], NumPy [3],
and MatPlotLib [4].
If you use PlantCV please cite us [1].
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The project website can be found at plantcv.danforthcenter.org
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Installation instructions can be found here
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Further documentation for PlantCV functions and use can be found at the
PlantCV Read the Docs site and we have added
interactive documentation. -
Test image sets can be found on our Data page.
We recommend first testing with sets from the Danforth Center. -
We recommend reading Reference [1], the first publication to detail PlantCV and provide examples of functionality.
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To contribute, please see the contribution guide
Citations:
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Fahlgren N, Feldman M, Gehan MA, Wilson MS, Shyu C, Bryant DW, Hill ST, McEntee CJ, Warnasooriya SN, Kumar I,
Ficor T, Turnipseed S, Gilbert KB, Brutnell TP, Carrington JC, Mockler TC, Baxter I. (2015) A versatile phenotyping
system and analytics platform reveals diverse temporal responses to water availability in Setaria. Molecular Plant 8:
1520-1535. http://doi.org/10.1016/j.molp.2015.06.005 -
Bradski G (2000) The OpenCV library. Dr. Dobb's Journal 25(11): 120-126.
http://www.drdobbs.com/open-source/the-opencv-library/184404319 -
Oliphant TE (2007) Python for Scientific Computing. Computing in Science & Engineering 9: 10-20.
http://doi.org/10.1109/MCSE.2007.58 -
Hunter JD (2007) Matplotlib: A 2D graphics environment. Computing in Science & Engineering 9: 90-95.
http://doi.org/10.1109/MCSE.2007.55
Issues with PlantCV?
Please file any PlantCV suggestions/issues/bugs via our
GitHub issues page. Please check to see if any related
issues have already been filed.
