Initial Training Set

Posted: April 3, 2019 at 4:53 pm

In preparation for Machine Learning aspect of this project I’ve generated 1000 images (and the vectors that represent them) and labelled them as good, bad or neither good nor bad. There were 51 good, 376 bad and 513 neutral images in the training set.

The labelling is based in my intuitive compositional sense and is a stand-in for viewer interaction (via preferential looking and social media likes). The idea is to get a sense of this data set and train a few classifiers to see if they can discriminate good and bad compositions.

Good Compositions

The next step is to plot the corresponding vectors using t-sne in R and see how my labels are distributed in that vector space.