Get your pencils out! Harold is a machine learning app using Generative Adversarial Network (GAN) to transform your (very) flat 2D sketches into vibrant 3D models.
The app uses a GAN to transform a input picture of a 2D sketch into a output codified image where elements are easily identifiable by their color. This output image is then post-processed with image-processing techniques to extract structural elements and build the 3D model.
The GAN is based on the pix2pix by Isola et al, and using its tensorflow implementation pix2pix-tensorflow by Christopher Hesse.
The model has been trained on a set of 460 images like the ones shown below. Training took about 60 hours on an Intel CORE i5-6200U CPU processor (2 Cores, 4 logical processors). The model has been trained to identify four types of structural elements:
- Slabs (yellow)
- Walls (green)
- Columns (red)
- Openings (blue) Training the model to identify additional elements could be considered.
In order to easily distinguish elements in image post-processing, the model is trained to associate each elements with RGB colors having 0 or 255 on each channel (e.g. (255,0,0), (0,255,0) or (255,0,255)). This helps to differentiate colors and identify structural elements.
Due to size issues, storing the machine learning model within the app is not a solution. Therefore the trained machine learning model is uploaded in an Azure container with Tensorflow-Serving. The app sends requests to the container through gRPC framework.
To improve your experience you can connect your smartphone camera to your computer thanks to a third party app (like ivCam). You need to install the app both on your iPhone and your PC. Connection can be established through WiFi (both your PC and your iPhone must be connected to the same network, detection is then automatic). Your PC camera will always work as a default option.
Select your camera source in the drop-down list, then click the green PLAY button. Once you are happy with the picture shown on the capture window, click the CAMERA button to take a screenshot. That’s it! You can then play with the number of stories and the horizontal scaling of your model.
