Outline

So the gist of the image-based workflow is:

So in a broader sense I see the workflow as roughly being: Get -> Calibrate -> Classify -> Analyse (adjacency). Since it’s structured in a fairly modular way there’s plenty of scope to expand stuff in the future as need be. e.g. more calibration options, different classification tools, or further analyses. But as it stands I think it offers a cool level of functionality.

Crappy examples

Load up.

devtools::install_github('rmaia/pavo@img')
library(pavo)

Load an image of a butterfly, and a series of images of simulated (based on real species) model/mimic aposematic snakes

# One image
papilio <- getimg(system.file("testdata/images/papilio.png", package = 'pavo'))

# Many images
snakes <- getimg(system.file("testdata/images/snakes", package = 'pavo'))
## 11 files found; importing images.

Some raw plots.

plot(papilio)