# Generative Machine Learning GAN

## GAN

The dataset was web-scraped for an original 20k samples, then a custom MRCNN model was trained for image segmentation and cropping before being fed into the 128 DCGAN, trained on local hardware, 1660

* [Collections of GANs : Pytorch implementation of unsupervised GANs.](https://github.com/w86763777/pytorch-gan-collections)

## Generative Model Course

* [CSE 599](https://courses.cs.washington.edu/courses/cse599i/20au/)
* [deepgenerativemodels](https://deepgenerativemodels.github.io/notes/index.html)

## GAN Course

* [Deep Learning Specialization - DeepLearning.AI](https://www.deeplearning.ai/program/deep-learning-specialization/)
* [Machine Learning for Musicians - Berklee](https://college.berklee.edu/courses/mtec-345)
* [MUSIC DATA MINING - a Music Information Retrieval (MIR) Online Course at Kadenze](https://www.kadenze.com/courses/machine-learning-for-music-information-retrieval/info)
* [Arts and Entertainment Technology - Online Course - Kadenze](https://www.kadenze.com/courses/foundations-of-arts-and-entertainment-technologies-i/info)
* [Introduction to Generative Arts and Computational Creativity - an Online Course at Kadenze](https://www.kadenze.com/courses/generative-art-and-computational-creativity/info)
* [UAL - Apply Creative Machine Learning - Institute of CodingInstitute of Coding](https://instituteofcoding.org/courses/course/ual-apply-creative-machine-learning/)
* [Machine Learning for Musicians and Artists - an Online Machine Art Course at Kadenze](https://www.kadenze.com/courses/machine-learning-for-musicians-and-artists/info)
* [Artificial Images - YouTube](https://www.youtube.com/user/bustbright/playlists)

## GAN Project/Paper

* [NVlabs/stylegan3: Official PyTorch implementation of StyleGAN3](https://github.com/NVlabs/stylegan3)
* [AI Demos - NVIDIA Research](https://www.nvidia.com/en-us/research/ai-demos/) GAN
* [HyperStyle](https://yuval-alaluf.github.io/hyperstyle/) StyleGAN Inversion
* [Pollinations.AI](https://old.pollinations.ai/)

## Style GAN

* [Making Anime Faces With StyleGAN · Gwern.net](https://www.gwern.net/Faces?ref=mlnews#examples)
* [cedricoeldorf/ConditionalStyleGAN: Conditional implementation for NVIDIA's StyleGAN architecture](https://github.com/cedricoeldorf/ConditionalStyleGAN)
* [NVlabs/stylegan: StyleGAN - Official TensorFlow Implementation](https://github.com/NVlabs/stylegan)
  * [P StyleGAN on Oxford Visual Geometry Group Flowers 102 Dataset 💐🌻🌷🥀🌺🌹🌸🌼 : computervision](https://old.reddit.com/r/computervision/comments/bfcnbj/p_stylegan_on_oxford_visual_geometry_group/)
  * [Visual Geometry Group - University of Oxford](https://www.robots.ox.ac.uk/~vgg/data/flowers/)
* [colinrsmall/ehm\_faces](https://github.com/colinrsmall/ehm_faces)
* [StyleGAN versions](https://nvlabs.github.io/stylegan2/versions.html)
* [t04glovern/stylegan-pokemon: Generating Pokemon cards using a mixture of StyleGAN and RNN to create beautiful & vibrant cards ready for battle!](https://github.com/t04glovern/stylegan-pokemon)

## Paper

* [2011.05552End-to-End Chinese Landscape Painting Creation Using Generative Adversarial Networks](https://arxiv.org/abs/2011.05552)
* [1812.04948 A Style-Based Generator Architecture for Generative Adversarial Networks](https://arxiv.org/abs/1812.04948)
* [EditGAN](https://nv-tlabs.github.io/editGAN/)

## GAN Image Superresolution

* [Cupscale](https://github.com/n00mkrad/cupscale)
* [Real-ESRGAN](https://github.com/xinntao/Real-ESRGAN)
* [hi, generate with your photo](https://filter.mot.omg.lol/)

## GAN

* [Making Anime Faces With StyleGAN · Gwern.net](https://www.gwern.net/Faces)

## Style-GAN

* [junyanz/CycleGAN: Software that can generate photos from paintings, turn horses into zebras, perform style transfer, and more.](https://github.com/junyanz/CycleGAN)
* [kaonashi-tyc/zi2zi: Learning Chinese Character style with conditional GAN](https://github.com/kaonashi-tyc/zi2zi)
* [rosinality/style-based-gan-pytorch: Implementation A Style-Based Generator Architecture for Generative Adversarial Networks in PyTorch](https://github.com/rosinality/style-based-gan-pytorch)
* [taki0112/StyleGAN-Tensorflow: Simple & Intuitive Tensorflow implementation of StyleGAN (CVPR 2019 Oral)](https://github.com/taki0112/StyleGAN-Tensorflow)
* [mtobeiyf/sketch-to-art: 🖼 Create artwork from your casual sketch with GAN and style transfer](https://github.com/mtobeiyf/sketch-to-art)
* [taki0112/UGATIT: Official Tensorflow implementation of U-GAT-IT: Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Image Translation (ICLR 2020)](https://github.com/taki0112/UGATIT)
* [zeka-io/selfie-to-anime](https://github.com/zeka-io/selfie-to-anime)
* [boistud/StyleArtGan](https://github.com/boistud/StyleArtGan)
* [heavenstobetsy/ArtGenerationwithStyleGan: Fauvist art generation using StyleGAN](https://github.com/heavenstobetsy/ArtGenerationwithStyleGan)
* [zhenxuan00/triple-gan: See Triple-GAN-V2 in PyTorch: https://github.com/taufikxu/Triple-GAN](https://github.com/zhenxuan00/triple-gan)
* [Mawiszus/TOAD-GAN: Official repository for "TOAD-GAN: Coherent Style Level Generation from a Single Example" by Maren Awiszus, Frederik Schubert and Bodo Rosenhahn.](https://github.com/Mawiszus/TOAD-GAN)
* [schrum2/GameGAN: Interactive GAN evolution of Mario and Zelda levels.](https://github.com/schrum2/GameGAN)
* [changebo/HCCG-CycleGAN: Handwritten Chinese Characters Generation](https://github.com/changebo/HCCG-CycleGAN)

## Research

* [An enhanced 3D model and generative adversarial network for automated generation of horizontal building mask images and cloudless aerial photographs - ScienceDirect](https://www.sciencedirect.com/science/article/pii/S1474034621001336?via%3Dihub)

## Research

* [Realless](https://realless.glitch.me/) Generative webs with blinking eyes

## GAN

* [Gradio demo for GFP-GAN: Towards Real-World Blind Face Restoration with Generative Facial Prior](https://huggingface.co/spaces/akhaliq/GFPGAN)

Stable Diffusion

* [The Illustrated Stable Diffusion–Jay Alammar–Visualizing machine learning one concept at a time.](https://jalammar.github.io/illustrated-stable-diffusion/)


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