A collection of Jupyter notebooks to play with NVIDIA's StyleGAN3 and OpenAI's CLIP for a text-based guided image generation.

Last update: Dec 30, 2022

Overview

StyleGAN3 CLIP-based guidance

StyleGAN3 + CLIP

StyleGAN3 + inversion + CLIP

This repo is a collection of Jupyter notebooks made to easily play with StyleGAN3¹ and CLIP² for a text-based guided image generation.

Both notebooks are heavily based on this notebook, created by nshepperd (thank you!).

Special thanks too to Katherine Crowson for coming up with many improved sampling tricks, as well as some of the code.

Feel free to suggest any changes! If anyone has any idea what license should this repo use, please let me know.

StyleGAN3 was created by NVIDIA. Here is the original repo. ↩
CLIP (Contrastive Language-Image Pre-Training) is a multimodal model made by OpenAI. For more information head over here. ↩

Owner

Eugenio Herrera

Data Scientist, Full-Stack Engineer, and aspiring Researcher.

GitHub Repository

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A collection of Jupyter notebooks to play with NVIDIA's StyleGAN3 and OpenAI's CLIP for a text-based guided image generation.

Related tags

Overview

StyleGAN3 CLIP-based guidance

StyleGAN3 + CLIP

StyleGAN3 + inversion + CLIP

Owner

Eugenio Herrera

Code for paper "A Critical Assessment of State-of-the-Art in Entity Alignment" (https://arxiv.org/abs/2010.16314)

Pytorch implementation of the paper "Class-Balanced Loss Based on Effective Number of Samples"

Hcpy - Interface with Home Connect appliances in Python

Official pytorch code for SSAT: A Symmetric Semantic-Aware Transformer Network for Makeup Transfer and Removal

DeRF: Decomposed Radiance Fields

My coursework for Machine Learning (2021 Spring) at National Taiwan University (NTU)

The Medical Detection Toolkit contains 2D + 3D implementations of prevalent object detectors such as Mask R-CNN, Retina Net, Retina U-Net, as well as a training and inference framework focused on dealing with medical images.

[SIGGRAPH'22] StyleGAN-XL: Scaling StyleGAN to Large Diverse Datasets

机器学习、深度学习、自然语言处理等人工智能基础知识总结。

The codebase for our paper "Generative Occupancy Fields for 3D Surface-Aware Image Synthesis" (NeurIPS 2021)

A sequence of Jupyter notebooks featuring the 12 Steps to Navier-Stokes

Accommodating supervised learning algorithms for the historical prices of the world's favorite cryptocurrency and boosting it through LightGBM.

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A collection of Jupyter notebooks to play with NVIDIA's StyleGAN3 and OpenAI's CLIP for a text-based guided image generation.

Related tags

Overview

StyleGAN3 CLIP-based guidance

StyleGAN3 + CLIP

StyleGAN3 + inversion + CLIP

Footnotes

Owner

Eugenio Herrera

Code for paper "A Critical Assessment of State-of-the-Art in Entity Alignment" (https://arxiv.org/abs/2010.16314)

Pytorch implementation of the paper "Class-Balanced Loss Based on Effective Number of Samples"

Hcpy - Interface with Home Connect appliances in Python

Official pytorch code for SSAT: A Symmetric Semantic-Aware Transformer Network for Makeup Transfer and Removal

DeRF: Decomposed Radiance Fields

My coursework for Machine Learning (2021 Spring) at National Taiwan University (NTU)

The Medical Detection Toolkit contains 2D + 3D implementations of prevalent object detectors such as Mask R-CNN, Retina Net, Retina U-Net, as well as a training and inference framework focused on dealing with medical images.

[SIGGRAPH'22] StyleGAN-XL: Scaling StyleGAN to Large Diverse Datasets

机器学习、深度学习、自然语言处理等人工智能基础知识总结。

The codebase for our paper "Generative Occupancy Fields for 3D Surface-Aware Image Synthesis" (NeurIPS 2021)

A sequence of Jupyter notebooks featuring the 12 Steps to Navier-Stokes

Accommodating supervised learning algorithms for the historical prices of the world's favorite cryptocurrency and boosting it through LightGBM.

Regularizing Generative Adversarial Networks under Limited Data (CVPR 2021)

Probabilistic Gradient Boosting Machines

History Aware Multimodal Transformer for Vision-and-Language Navigation

This project generates news headlines using a Long Short-Term Memory (LSTM) neural network.

Motion planning environment for Sampling-based Planners

PyTorch implementation of ICLR 2022 paper PiCO: Contrastive Label Disambiguation for Partial Label Learning

RoboDesk A Multi-Task Reinforcement Learning Benchmark

ConE: Cone Embeddings for Multi-Hop Reasoning over Knowledge Graphs