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I developed a computer vision algorithm using Python to automatically quantify the size leaves grown on agar plates. Below is figure 2 from our paper showing the leaf area detection steps.

The image-processing steps used for leaf identification. (A) Image converted to black and white using the B channel of the Lab color space. (B) Binary threshold. (C) Region of interest indicated by the blue lines. (D) Identification of individual shoots using clustering and splitting the image into six sections. Note that one seed failed to germinate so no leaf area was measured.

The software was actually used to collect leaf area for thousands of leaves in Katz et al 2022 as well!

Look at the code repository here

While still a work in progress, this package contains code relevant to analyzing the NGS data output from our Fluorescence Activated Cell Sorting assays as well as some simple tile design functions.

Shared code in a Python Package for collaborators

While these are all examples with fake data, they demonstrate some of the visualizations I can do completely in seaborn and matplotlib.