Chris Skalnik

How to Process Focal Male Photos

Instructions for Processing Focal Male Photos

Written by Chris Skalnik on Apr 24th, 2019

These instructions were written by Christopher Skalnik while working under Beau Alward in the Fernald Lab at Stanford University.

Copyright © 2019 Stanford University, All rights reserved. Note that this work is NOT released under the same license as the rest of the site.

This page was first posted on May 9, 2019, but it had previously been hosted elsewhere on this site. I made it a blog post so its link would be more permanent.

Overview

These instructions are for processing photos of focal males from dyad assays in the Fernald Lab.

Setup

Setup Work Folder

  1. Create a folder for your work. In this example, we'll call it ARalpha and place it in the home folder (~/ARalpha).
  2. Within that folder, add another folder containing photos of the focal males you want to analyze. These should be all the photos for the comparison, including both mutants and wildtypes. In this example, we'll call the folder fmPhotos so that the path to one photo called photo1.jpg is ~/ARalpha/fmPhotos/photo1.jpg.

Install Dependencies

  1. Install Python 3 from https://www.python.org/. You can also install Python using Homebrew on a Mac, just make sure you have version 3 of Python.
  2. Figure out what command you need to run to execute Python 3. You can check this by running python --version and python3 --version. If the python --version command prints a version starting with 3, you are good to go. If you need to run python3 to get that version to print, you will need to replace python and pip below with python3 and pip3.
  3. If you like using virtual environments or conda environments, now is the time to set one up. Activate it for the rest of the steps. Make sure to use Python version 3 when you create it.
  4. Along with Python comes a tool for installing python packages. You can run this tool using the pip command. We will do this in later steps.

Computing the Overlay

This is how we combine all the images to decide what regions to crop out.

Install Dependencies

  1. Download the overlay tool from GitHub by going to its GitHub page at https://github.com/U8NWXD/overlay, clicking the Clone or download button, and selecting Download ZIP. Unzip the downloaded file in the ARalpha directory so that you have an overlay.py file at the path ~/ARalpha/overlay-master/overlay/overlay.py. If you prefer to use git, you can instead run:

    $ git clone https://github.com/U8NWXD/overlay.git overlay-master

  2. To install the Python dependencies that overlay needs, run

    $ cd ~/ARalpha
$ pip install -r overlay-master/requirements.txt

    to tell pip to install all the dependencies listed in the overlay requirements file.

Run overlay

The shorthand reference for how to use the overlay tool is:

overlay.py [mean | median] img1 img2 [additional images]

This means that to compute the overlay of all our images in ~/ARalpha/fmPhotos/ by computing the median of the pixel values, we would run the following commands:

$ cd ~/ARalpha
$ overlay-master/overlay/overlay.py median fmPhotos/*

where the fmPhotos/* will get expanded by your terminal (technically it's expanded by bash) into a space-separated list of all the files in fmPhotos/. If you wanted to use the mean instead of the median, just replace median in the command with mean. The result will be a file ~/ARalpha/composite_median.jpg or ~/ARalpha/composite_mean.jpg which stores the composite image. Move this image into ~/ARalpha/fmPhotos/.

Generating the Crops

Install Dependencies

  1. Download the batch_crop tool from GitHub by going to its GitHub page at https://github.com/U8NWXD/batch_crop, clicking the Clone or download button, and selecting Download ZIP. Unzip the downloaded file in the ARalpha directory so that you have an overlay.py file at the path ~/ARalpha/batch_crop-master/batch_crop/batch_crop.py. If you prefer to use git, you can instead run:

    $ git clone https://github.com/U8NWXD/batch_crop.git batch_crop-master

  2. To install the Python dependencies that batch_crop needs, run

    $ cd ~/ARalpha
$ pip install -r batch_crop-master/requirements.txt

    to tell pip to install all the dependencies listed in the batch_crop requirements file.

Run batch_crop

Select Crop Regions

To run batch_crop, you just need to run the command

$ cd ~/ARalpha/batch_crop-master
$ python batch_crop/batch_crop.py

This will open up a graphical interface in a window you can use. On macOS Mojave, you may need to use light mode and slightly resize the window in order to see the button labels. Thanks to the answers to this StackOverflow post for helping me figure this out: https://stackoverflow.com/q/52529403.

Now, we need to select the regions we want to crop. We will use the composite image we created with overlay to choose these regions. We can load that image by clicking the Load Image button in the batch_crop window and selecting the composite image.

Next, click and drag on the image to draw out a rectangle. You can change your selection by just drawing another rectangle, which will replace the earlier one. For example, we might select the pectoral fin of the fish. Because we are using a composite image, this corresponds to where most of the photographed have their pectoral fins.

To make sure you can exactly replicate this crop in the future, click on the Save Coordinates button to save the coordinates of your selection. Note that coordinates are stored as relative positions, so this file will still work for differently-sized images.

Now, we are finally ready to make the crops. Click on Crop All Matching Images to generate crops for every file in the same folder and with the same file extension as the loaded image. Each crop will be of the selected region, but re-scaled for differently-sized images. To move these photos into a separate folder, run the commands:

$ cd ~/ARalpha/fmPhotos
$ mkdir pectoral
$ mv *_cropped.jpg pectoral

This moves all the crops into a folder called pectoral.

If in the future you want to replicate this crop, you can click on Load Coordinates and load in the file you saved off earlier.

Now you can repeat these steps for any other regions you wish to crop out. These crops can then be analyzed with other tools.