Skip to content
Deep learning classifier and image generator for building architecture.
Jupyter Notebook
Branch: master
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Type Name Latest commit message Commit time
Failed to load latest commit information.

Deep Learning Architectures for Building Architecture

Title: Building Deep Learning Architectures to Understand Building Architecture Styles

Authors: Caroline Ho & Cole Thomson {cho19, colet}

Course: CS 230 – Deep Learning



  • Install tabulate: pip install tabulate
  • Install TNT: pip install torchnet



This notebook uses transfer learning to classify images of buildings by architectural style.

Best Results: After pretraining a DenseNet on ImageNet, we achieve an accuracy of 0.795833 and a F1 score of 0.789431. (Visualizations available in notebook.)


This notebook generates images of buildings conditioned on architecture styles using a conditional GAN.

Results after 20 epochs:

cDCGAN results

Our most successful generated image is this example of Ancient Egyptian architecture, which is visibly a pyramid:

Generated Egyptian Pyramid

However, most of our images, including this example of American Craftsman architecture, are less clear. (If you look closely, you can see a blurry gabled brown roof and white walls.)

Generated American Craftsman


Much of our code has been adapted from the following sources.

You can’t perform that action at this time.