This is a repo to demonstrate classifying book covers (specifically the winners of the Caldecott Medal) by the color compositions of their covers based on some pre-trained data.
To replicate this analysis run the scripts in this order:
1 - get_covers.py - downloads images of each book cover from Wikpedia
2 - build_model.py - Uses Tensorflow to
build a matrix of likely colors based on pre-trained color data
3 - classify_covers.py - Uses the colorgram python module to extract color profiles from each cover image and classify each book
cover using the model built in the prior step.
4 - make_figure.py - Uses Seaborn to
create the following figure of book color distributions by year:
