Envelope 85.422% – SOLD

Envelope 85.422%
Joanne Hastie original
Acrylic on Paper

11.75" x 16.5"


This abstract painting on paper was created as part of my Machine Learning Abstract Series. I am painting abstract paintings by hand while using Python code and TensorFlow algoithms to generate the compositions. After painting this geometric abstract by hand and not intending it to represent an object, I loaded the image into an artificial intelligence algorithm I use to title the paintings. Of all the potential objects the painting could represent including carton, washbasin and binder, I selected ‘Envelope’ as the title, the confidence score is the probability from the algorithm that it could be that object.

Inception v3 results:
envelope (confidence 85.422%)
web site, website, internet site, site (confidence 4.106357%)
carton (confidence 1.5356097%)
washbasin, handbasin, washbowl, lavabo, wash-hand basin (confidence 0.41590207%)
binder, ring-binder (confidence 0.36979087%)


I wrote Python code to collage and generate compositions of hand painted geometric shapes and then use an image classifier to rank the compositions based on my preferences.

Over time, I update the classifier as I hone my eye as to what looks good as a painting versus a digital thumbnail. After it is painted, I use an untrained classifier to title the painting. I get titles such as “Bulletproof Vest”, “Traffic Lights” and “Envelope”, because they are flat paintings (minimal depth) – most paintings are classified as “Envelope”. Can you see the objects in the painting?

This work has been featured in NeurIPS Online Gallery in 2018, at ‘Women in Data Science’ show in Zurich in 2018 and in RUSI Journal 2019.

To learn more about this project click below.


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