This project was an extension of the work I read in this blogpost It's a series of funcitons that batch analysze tiffs and then
note : These functions always run faster on smaller images. To save yourself someheadache scale down the images before you run them by using the sip command in bash.
Simply navigate to the image folder and execute:
sips -Z 100 *.jpg
This will generally preserve the colors but scale everything down.
I used instalooter to collect data but any scraping service that allows you to collect large amounts of images should work.
The function photo_colorbar.py takes two arguments: the location of the image and the number of color to extract
python3 photo_colorbar.py %PathToImage% nAs an example of n=5, we see this function will generate an output like this:
To find the primary colors in a series of images you can call the following function
python3 batch_color_analyzer.py %PathToImageDirectory% nThis will save a pickled python list of lists called "storage.pkl" containing the "n" most promoinent colors for each image in the directory.
To generate unique radial plots using the extracted data you can simple run the function:
python3 color_histogram_plot.pyThis will load "storage.pkl" and generate a smoothed radial histogram based on the hues of the scraped images.
*note: * There are many ways to visulaize distributions of color, here we simply discard black and white and look at the predominance of the colors
of the rainbow.

