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DIRT 1.1 - An automatic high throughput root phenotyping platform (c) 2014,2016 Alexander Bucksch - bucksch@uga.edu Web application by Abhiram Das - abhiram.das@gmail.com

http://dirt.iplantcollaborative.org

User and developer group: https://groups.google.com/forum/#!forum/dirt-users

University of Georgia, Athens

The software is written and tested in:

The software depends on:

Optionally binaries of standard OCR and BarCode software can be used for tag recognition:

Usage: <run file path> full path to the root image <unique id> ID which will be a folder name in the working directory. Integer value needed. <mask threshold> multiplier for the automatically determined mask threshold. 1.0 works fine and is default. For example, if a flashlight is used to take root images, then 0.6 is a good choice. <excised roots> number of roots placed at the right of the root crown, 0 - excised root analysis is off <crown root> 1 - crown root analysis is on, 0 - crown root analysis is off <segmentation> 1 - is on, 0 - is off. Off refers to a pre-existing segmention done with DIRT. Binary masks as input images are detected automatically. <marker diameter> a simple decimal e.g. 25.4. If 0.0 is used, then the output will have pixels as unit. <stem reconstruction> 1 - reconstruction is turned on, 0 - reconstruction is turned off <plots> 1 - plotting data is stored, 0 - plotting data is not stored <output format> 1 - the full trait set is put into one excel file containing empty cells for traits that were not computed, 0 - only computed files are written to the output file <working directory> full path to folder were the result is stored <trait file path> full path to .csv file containing the traits to be computed'

Example: python main.py /Documents/image_name.jpg 8 25.0 1 1 1 25.1 0 0 0 /Documents/image_folder/ /Documents/traits.csv

Notes on common questions:

For convenience we provide the runOnFolder script, that executes DIRT on all images in a specified folder. Note we made the masking threshold available on the command line because of user requests.

Example: python runOnFolder.py /Users/image_folder/ <masking threshold>

Please adjust line 86 according to the description above and note that the script uses 6 cores to compute images in parallel. The number of cores can be adjusted in line 80.

Updates in DIRT 1.1 (21 June 2019):

Updates in DIRT 1.1 (11 January 2016):

Updates in DIRT 1.1 (4 November 2015):

Changes in DIRT 1.1 (14 January 2015):