plantcv's Introduction

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].

The project website can be found at plantcv.danforthcenter.org
Installation instructions can be found here
Further documentation for PlantCV functions and use can be found at the PlantCV Read the Docs site
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.
To contribute, please see the contribution guide

Citations:

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. Doctor Dobbs 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