A few stylization coreML models that I've trained with CreateML

Doron Adler

Last update: Aug 18, 2022

Related tags

Deep Learning python xcode style-transfer image-stylization coreml coreml-models

Overview

CoreML-StyleTransfer

A few stylization coreML models that I've trained with CreateML

You can open and use the .mlmodel files in the "models" folder in Xcode:

You can also use test-all-styles.py as reference for inference using Python.

Here are inference examples for all the styles in this repository:

If you end up using these styles in your own projects, I'd be glad if you let me know :)

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Owner

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A few stylization coreML models that I've trained with CreateML

Related tags

Overview

CoreML-StyleTransfer

You might also like...

A collection of pre-trained StyleGAN2 models trained on different datasets at different resolution.

Annotate datasets with a semi-trained or fully trained YOLOv5 model

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Code for T-Few from "Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learning"

Monocular Depth Estimation - Weighted-average prediction from multiple pre-trained depth estimation models

Source code, datasets and trained models for the paper Learning Advanced Mathematical Computations from Examples (ICLR 2021), by François Charton, Amaury Hayat (ENPC-Rutgers) and Guillaume Lample

Code, Data and Demo for Paper: Controllable Generation from Pre-trained Language Models via Inverse Prompting

《K-Adapter: Infusing Knowledge into Pre-Trained Models with Adapters》(2020)

Owner

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Official pytorch implementation of "Feature Stylization and Domain-aware Contrastive Loss for Domain Generalization" ACMMM 2021 (Oral)

This is the official Pytorch implementation of the paper "Diverse Motion Stylization for Multiple Style Domains via Spatial-Temporal Graph-Based Generative Model"

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