PhotoProject :: My #HandDrawnPhoto approach to #AIart

The success of the Belemy portrait auction, has encouraged me to compare Obvious’s DAG approach to my use of Google Deep Dream algorithm. Deep dream uses a convolutional (foreword chaining) neural network to find and/or enhance patterns in an image. This can be applied in two ways Style & Inception (google’s terms). The inception process tries to find the characteristics of a given object/pattern within a photo and tends to produce surreal images. Style on the other hand  seeks to put characteristic patterns back into a photo based on features the trained neural network has recognized. This is the technique I have become very interested in as a way to put my characteristic marks (and sometimes colours) back into a photo. Hence the name Hand Drawn Photos for my approach. The method does have superficial similarities to Onvious’s DAG Approach.

Here I am using my sketch for inktober as the image to be processed and a photo of the same trees as my training image used to build the neural network (AI). The Photo here is acting like the discriminator in Obvious’s approach. The result (below) is tonally similar to the photo and kind of a messy squiggly version of something I might sketch.  But…

In this, my preferred approach, I am using the photo as the image to be modified and my sketch as the image to train the neural network and letting the system modify the photo to “find” my characteristic mark making (aka style) and modify the photo. In this case I am taking the colours from the photograph, but that is not essential.

I feel this second result is much cleaner and fresher, closer to something creative and artistic, Although I am strongly guiding the outcome by using my own sketches (as opposed to an automated algorithm). So the big question is “Do you consider this #HandDrawnPhoto to be legitimate AI art? I’m warming to answering yes.

If you are interested here is the link to my profile and public images on Google Deep Dream website. (Its free to join and use)

Love to hear your views,  please leave your comments here.