Diffusion models achieve remarkable results in image generation. They are able synthesize high-quality images guided by user instructions. In the same time, majority of diffusion-based image generation approaches are time-consuming due to the iterative denoising process.Pix2Pix-turbo model was proposed in One-Step Image Translation with Text-to-Image Models paper for addressing slowness of diffusion process in image-to-image translation task. It is based on SD-Turbo, a fast generative text-to-image model that can synthesize photorealistic images from a text prompt in a single network evaluation. Using only single inference, pix2pix-turbo achieves comparable by quality results with recent works such as ControlNet for Sketch2Photo and Edge2Image for 50 steps.
In this tutorial you will learn how to turn sketches into images using Pix2Pix-Turbo and OpenVINO.
The tutorial consists from following steps:
- Prerequisites
- Load PyTorch Model
- Convert the model to OpenVINO IR
- Select Inference Device
- Compile OpenVINO Model
- Run Model Inference
- Launch Interactive Demo
This is a self-contained example that relies solely on its own code.
We recommend running the notebook in a virtual environment. You only need a Jupyter server to start.
For details, please refer to Installation Guide.
