A small package for optimizing banana coverage on peanut butter and banana sandwiches. See blog post for more info.
Python 3.7+ is required.
nannernest is generally pip installable. Due to some C dependencies with the nesting library that I use nest2D, along with an outstanding PR, I would recommend the following way to install everything:
First, make sure you have boost and cmake installed. If you are on Linux, then you may have cmake installed, and you can install boost with
sudo apt-get install libboost-all-dev
I'm on a Mac, and I installed cmake with conda and boost with brew:
conda install cmake
brew install boost
Next, pip install my fork of nest2D:
pip install git+https://github.com/EthanRosenthal/nest2D.git@download-dependencies
Finally, pip install nannernest
pip install nannernest
Take a top-down picture that contains your banana and at least one slice of bread. Pass the image in via command line:
$ nannernest my_image.jpg
$ nannernest --help
Usage: nannernest [OPTIONS] IMAGE_PATH
Arguments:
IMAGE_PATH Image file which contains bread and banana [required]
Options:
--num-slices INTEGER Total number of slices to cut the banana
into. This number defines the slice
thickness. [default: 22]
--mask-threshold FLOAT Threshold of segmentation mask. [default:
0.6]
--peel-scaler FLOAT Fraction of slice that is assumed to belong
to banana insides versus the peel.
[default: 0.8]
--ellipse-ratio FLOAT Assumed ratio of minor axis to major axis of
banana slice ellipses [default: 0.85]
--plot-segmentation / --no-plot-segmentation
Whether or not to plot the segmentation
masks [default: False]
--plot-slicing / --no-plot-slicing
Whether or not to plot the slicing circle
and skeleton [default: False]
--output TEXT Name of file to output [default:
perfect_sandwich.jpg]