Pix2Pix for Unity
This is an attempt to run pix2pix (image-to-image translation with deep neural network) in real time with Unity. It contains its own implementation of an inference engine, so it doesn't require installation of other neural network frameworks.
Sketch Pad demo
Sketch Pad is a demonstration that resembles the famous edges2cats demo but in real time. You can download a pre-built binary from the Releases page.
System requirements
- Unity 2018.1
- Compute shader capability (DX11, Metal, Vulkan, etc.)
Although it's implemented in a platform agnostic fashion, many parts of it are optimized for NVIDIA GPU architectures. To run the Sketch Pad demo flawlessly, it's highly recomended to use a Windows system with GeForce GTX 1070 or greater.
How to use a trained model
This repository doesn't contain any trained model to save the bandwidth and
storage quota. To run the example project on Unity Editor, download the
pre-trained edges2cats model and copy it into Assets/StreamingAssets.
This implementation only supports the .pict weight data format which is used
in Christopher Hesse's interactive demo. You can pick one of the pre-trained
models or train your own model with using pix2pix-tensorflow. To export
weight data from a checkpoint, please see the description in the
export-checkpoint.py script.