This notebook demonstrates Fast Neural Style Transfer on ONNX models with OpenVINO. Style Transfer models mix the content of an image with the style of another image.
This notebook uses five pre-trained models, for the following styles: Mosaic, Rain Princess, Candy, Udnie and Pointilism. The models are from the ONNX Model Repository and are based on the research paper Perceptual Losses for Real-Time Style Transfer and Super-Resolution by Justin Johnson, Alexandre Alahi and Li Fei-Fei.
This tutorial consists of the following steps:
- Loading an ONNX model in OpenVINO Runtime and doing inference on this model.
- Showing inference results on five neural style transfer models.
- Saving the transformed images and providing a download link.
The ONNX models and a sample image are provided in the notebook. For instructions on how to upload your own images to Jupyter Lab, see this short video.
If you have not installed all required dependencies, follow the Installation Guide.