An implementation of "Optimal Textures: Fast and Robust Texture Synthesis and Style Transfer through Optimal Transport"

Overview

Optex

An implementation of Optimal Textures: Fast and Robust Texture Synthesis and Style Transfer through Optimal Transport for TU Delft CS4240.

Simplified diagram of the algorithm

You can find a more in-depth summary of the implementation in this blog post.

Installation

git clone https://github.com/JCBrouwer/OptimalTextures
cd OptimalTextures
pip install -r requirements.txt
python optex.py -h

Texture synthesis

Generate a texture based on an example:

python optex.py --style style/graffiti.jpg --size 512

Style transfer

Supply two images and synthesize one in the style of the other.

python optex.py --style style/lava-small.jpg --content content/rocket.jpg --content_strength 0.2

Texture mixing

Blend two textures together.

python optex.py --style style/zebra.jpg style/pattern-small.jpg --mixing_alpha 0.5  

Color transfer

Perform style transfer but keep the original colors of the content.

python optex.py --style style/green-paint-large.jpg --content content/city.jpg --style_scale 0.5 --content_strength 0.2 --color_transfer opt --size 1024
Owner
Hans Brouwer
Hans Brouwer
Machine learning Bot detection technique, based on United States election dataset

Machine learning Bot detection technique, based on United States election dataset (2020). Current github repo provides implementation described in pap

Alexander Shevtsov 4 Nov 20, 2022
Learning from Guided Play: A Scheduled Hierarchical Approach for Improving Exploration in Adversarial Imitation Learning Source Code

Learning from Guided Play: A Scheduled Hierarchical Approach for Improving Exploration in Adversarial Imitation Learning Trevor Ablett*, Bryan Chan*,

STARS Laboratory 8 Sep 14, 2022
Code accompanying the paper "How Tight Can PAC-Bayes be in the Small Data Regime?"

How Tight Can PAC-Bayes be in the Small Data Regime? This is the code to reproduce all experiments for the following paper: @inproceedings{Foong:2021:

5 Dec 21, 2021
A model which classifies reviews as positive or negative.

SentiMent Analysis In this project I built a model to classify movie reviews fromn the IMDB dataset of 50K reviews. WordtoVec : Neural networks only w

Rishabh Bali 2 Feb 09, 2022
Google Landmark Recogntion and Retrieval 2021 Solutions

Google Landmark Recogntion and Retrieval 2021 Solutions In this repository you can find solution and code for Google Landmark Recognition 2021 and Goo

Vadim Timakin 5 Nov 25, 2022
transfer attack; adversarial examples; black-box attack; unrestricted Adversarial Attacks on ImageNet; CVPR2021 天池黑盒竞赛

transfer_adv CVPR-2021 AIC-VI: unrestricted Adversarial Attacks on ImageNet CVPR2021 安全AI挑战者计划第六期赛道2:ImageNet无限制对抗攻击 介绍 : 深度神经网络已经在各种视觉识别问题上取得了最先进的性能。

25 Dec 08, 2022
Pytorch implementation of "Grad-TTS: A Diffusion Probabilistic Model for Text-to-Speech"

GradTTS Unofficial Pytorch implementation of "Grad-TTS: A Diffusion Probabilistic Model for Text-to-Speech" (arxiv) About this repo This is an unoffic

HeyangXue1997 103 Dec 23, 2022
[ICML 2020] "When Does Self-Supervision Help Graph Convolutional Networks?" by Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen

When Does Self-Supervision Help Graph Convolutional Networks? PyTorch implementation for When Does Self-Supervision Help Graph Convolutional Networks?

Shen Lab at Texas A&M University 106 Nov 11, 2022
Run Effective Large Batch Contrastive Learning on Limited Memory GPU

Gradient Cache Gradient Cache is a simple technique for unlimitedly scaling contrastive learning batch far beyond GPU memory constraint. This means tr

Luyu Gao 198 Dec 29, 2022
Official pytorch implementation of Active Learning for deep object detection via probabilistic modeling (ICCV 2021)

Active Learning for Deep Object Detection via Probabilistic Modeling This repository is the official PyTorch implementation of Active Learning for Dee

NVIDIA Research Projects 130 Jan 06, 2023
Tensorflow implementation of "BEGAN: Boundary Equilibrium Generative Adversarial Networks"

BEGAN in Tensorflow Tensorflow implementation of BEGAN: Boundary Equilibrium Generative Adversarial Networks. Requirements Python 2.7 or 3.x Pillow tq

Taehoon Kim 922 Dec 21, 2022
An open-source outlier detection package by Getcontact Data Team

pyfbad The pyfbad library supports anomaly detection projects. An end-to-end anomaly detection application can be written using the source codes of th

Teknasyon Tech 41 Dec 27, 2022
Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context Code in both PyTorch and TensorFlow

Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context This repository contains the code in both PyTorch and TensorFlow for our paper

Zhilin Yang 3.3k Jan 06, 2023
A 1.3B text-to-image generation model trained on 14 million image-text pairs

minDALL-E on Conceptual Captions minDALL-E, named after minGPT, is a 1.3B text-to-image generation model trained on 14 million image-text pairs for no

Kakao Brain 604 Dec 14, 2022
Learning Saliency Propagation for Semi-supervised Instance Segmentation

Learning Saliency Propagation for Semi-supervised Instance Segmentation PyTorch Implementation This repository contains: the PyTorch implementation of

Berkeley DeepDrive 68 Oct 18, 2022
Object recognition using Azure Custom Vision AI and Azure Functions

Step by Step on how to create an object recognition model using Custom Vision, export the model and run the model in an Azure Function

El Bruno 11 Jul 08, 2022
Code of paper: "DropAttack: A Masked Weight Adversarial Training Method to Improve Generalization of Neural Networks"

DropAttack: A Masked Weight Adversarial Training Method to Improve Generalization of Neural Networks Abstract: Adversarial training has been proven to

倪仕文 (Shiwen Ni) 58 Nov 10, 2022
Implementation of the Swin Transformer in PyTorch.

Swin Transformer - PyTorch Implementation of the Swin Transformer architecture. This paper presents a new vision Transformer, called Swin Transformer,

597 Jan 03, 2023
Pytorch implementation of CVPR2021 paper "MUST-GAN: Multi-level Statistics Transfer for Self-driven Person Image Generation"

MUST-GAN Code | paper The Pytorch implementation of our CVPR2021 paper "MUST-GAN: Multi-level Statistics Transfer for Self-driven Person Image Generat

TianxiangMa 46 Dec 26, 2022
This repo is the official implementation of "L2ight: Enabling On-Chip Learning for Optical Neural Networks via Efficient in-situ Subspace Optimization".

L2ight is a closed-loop ONN on-chip learning framework to enable scalable ONN mapping and efficient in-situ learning. L2ight adopts a three-stage learning flow that first calibrates the complicated p

Jiaqi Gu 9 Jul 14, 2022