GANfolk: Using AI to create portraits of fictional people to sell as NFTs

Last update: Dec 02, 2022

Overview

GANfolk: Using AI to create portraits of fictional people to sell as NFTs

How to use GPT-3, StyleGAN2, and VQGAN to synthesize diverse characters from open-source images

By Robert. A Gonsalves

You can see my article on Medium and check out the results here, opensea.io/collection/ganfolk

The source code and generated images are released under the CC BY-SA license.

If you use this project to create images, please give attribution like this: This image was created with GANfolk by Robert A. Gonsalves.

Google Colabs

Acknowledgements

StyleGAN 2 by T. Karras, et al., Analyzing and Improving the Image Quality of StyleGAN
StyleGAN 2 implementation by rosinality, https://github.com/rosinality/stylegan2-pytorch
VQGAN by P. Esser, R. Rombach, and B. Ommer, Taming Transformers for High-Resolution Image Synthesis
CLIP by A. Radford, et al., Learning Transferable Visual Models From Natural Language Supervision
GPT-3 by Tom B. Brown, et al., Language Models are Few-Shot Learners
The original VQGAN+Clip notebook was made by Katherine Crowson, with further modifications by Justin John

GANfolk: Using AI to create portraits of fictional people to sell as NFTs

Related tags

Overview

GANfolk: Using AI to create portraits of fictional people to sell as NFTs

How to use GPT-3, StyleGAN2, and VQGAN to synthesize diverse characters from open-source images

Google Colabs

Acknowledgements

Owner

Robert A. Gonsalves

Bunch of different tools which helps visualizing and annotating images for semantic/instance segmentation tasks

Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit

Fine-tuning StyleGAN2 for Cartoon Face Generation

Code for Learning Manifold Patch-Based Representations of Man-Made Shapes, in ICLR 2021.

A collection of random and hastily hacked together scripts for investigating EU-DCC

This program can detect your face and add an Christams hat on the top of your head

SUPERVISED-CONTRASTIVE-LEARNING-FOR-PRE-TRAINED-LANGUAGE-MODEL-FINE-TUNING - The Facebook paper about fine tuning RoBERTa with contrastive loss

Python scripts form performing stereo depth estimation using the HITNET model in ONNX.

Mapping Conditional Distributions for Domain Adaptation Under Generalized Target Shift

Python inverse kinematics for your robot model based on Pinocchio.

Codebase for arXiv preprint "NeRF++: Analyzing and Improving Neural Radiance Fields"

The PASS dataset: pretrained models and how to get the data - PASS: Pictures without humAns for Self-Supervised Pretraining

Semi-Supervised Semantic Segmentation via Adaptive Equalization Learning, NeurIPS 2021 (Spotlight)

🤖 A Python library for learning and evaluating knowledge graph embeddings

Re-TACRED: Addressing Shortcomings of the TACRED Dataset

Source code and data from the RecSys 2020 article "Carousel Personalization in Music Streaming Apps with Contextual Bandits" by W. Bendada, G. Salha and T. Bontempelli

The source code of the paper "Understanding Graph Neural Networks from Graph Signal Denoising Perspectives"

Convolutional Neural Network to detect deforestation in the Amazon Rainforest

This repository contains the source code of our work on designing efficient CNNs for computer vision

A collection of IPython notebooks covering various topics.