Bishkek Synth
Master thesis by Altynai Nogoibaeva that seeks democratization of architectural imagination through generative neural networks.
In a core lies the idea of democratization of urban design. We offer a speculative instrument which allows residents to express and propose ideas and aspiration for urban design in a visual form. The focus is made on public spaces, which include greenery, urban furniture, light, and road infrastructure. An instrument is based on the latest openly available image-to-image translation neural network pix-2-pix. We trained the model with our own dataset which comprises public space and playground images. In addition, the model was trained with an openly available Streetscape dataset. As a result, we got an interactive web application powered by AI, in which citizens can roughly sketch their proposals for developing areas and get a realist looking image as an output.
– Altynai Nogoibaeva
- Client
- Shukhov Lab
- Role
- Supervisor
- Date
- Summer 2019
Results from a trained neural network.
Project location.
Typical look of Bishkek periphery.
Possible periphery generated by a generative neural network.
Architectural concept generation through the Pix2Pix algorithm.
Dataset labeling.