Simple SN-GAN to generate CryptoPunks

Overview

CryptoPunks GAN

Simple SN-GAN to generate CryptoPunks. Neural network architecture and training code has been modified from the PyTorch DCGAN example. See Notes for more information.

Punks during training

Linear interpolation between two punks

Usage

Example

Generate 64 punks using pretrained model:

import torch
from torchvision.utils import save_image
from train import Generator

model = Generator()
model.load_state_dict(torch.load("models/net_g_epoch_999.pth"))
z = torch.randn(64, 100, 1, 1)
punks = model(z)
save_image(punks, "punks.png", normalize=True)

Train

On CUDA machine:

python train.py

Check out directory for weights and sample images.

Notes

Using Spectral Normalization created very nice punks, but had a tendency to create very transparent ones:

Using batch normalization seems to negate this, but causes mode collapse

Instead, penalizing the model for a high mean alpha produces very good punks, with no transparency issues:

# minimize criterion + mean of alpha channel
loss_g = criterion(output, label) + fake[:, -1].mean()

In order to encourage more variety in the outputs, we generate a feature matrix of all the punks (using punks.attributes):

    3D Glasses  Bandana  Beanie  Big Beard  Big Shades  ...  Ape  Human  Zombie  Female  Male
id                                                      ...
0            0        0       0          0           0  ...    0      1       0       1     0
1            0        0       0          0           0  ...    0      1       0       0     1
2            0        0       0          0           0  ...    0      1       0       1     0
3            0        0       0          0           0  ...    0      1       0       0     1
4            0        0       0          0           1  ...    0      1       0       0     1

For each image in the batch, randomly select an attribute (column), and then randomly select a punk that has that attribute. This ensures that the discriminator is exposed to all of the attributes in a more balanced manor than running through all the punks.

Owner
Teddy Koker
Machine Learning @mit-ll
Teddy Koker
Code for Contrastive-Geometry Networks for Generalized 3D Pose Transfer

Code for Contrastive-Geometry Networks for Generalized 3D Pose Transfer

18 Jun 28, 2022
RoBERTa Marathi Language model trained from scratch during huggingface 🤗 x flax community week

RoBERTa base model for Marathi Language (मराठी भाषा) Pretrained model on Marathi language using a masked language modeling (MLM) objective. RoBERTa wa

Nipun Sadvilkar 23 Oct 19, 2022
MGFN: Multi-Graph Fusion Networks for Urban Region Embedding was accepted by IJCAI-2022.

Multi-Graph Fusion Networks for Urban Region Embedding (IJCAI-22) This is the implementation of Multi-Graph Fusion Networks for Urban Region Embedding

202 Nov 18, 2022
Convolutional Neural Networks

Darknet Darknet is an open source neural network framework written in C and CUDA. It is fast, easy to install, and supports CPU and GPU computation. D

Joseph Redmon 23.7k Jan 05, 2023
A 10000+ hours dataset for Chinese speech recognition

WenetSpeech Official website | Paper A 10000+ Hours Multi-domain Chinese Corpus for Speech Recognition Download Please visit the official website, rea

310 Jan 03, 2023
Pull sensitive data from users on windows including discord tokens and chrome data.

⭐ For a 🍪 Pegasus Pull sensitive data from users on windows including discord tokens and chrome data. Features 🟩 Discord tokens 🟩 Geolocation data

Addi 44 Dec 31, 2022
Implementation of the SUMO (Slim U-Net trained on MODA) model

SUMO - Slim U-Net trained on MODA Implementation of the SUMO (Slim U-Net trained on MODA) model as described in: TODO: add reference to paper once ava

6 Nov 19, 2022
Tandem Mass Spectrum Prediction with Graph Transformers

MassFormer This is the original implementation of MassFormer, a graph transformer for small molecule MS/MS prediction. Check out the preprint on arxiv

Röst Lab 13 Oct 27, 2022
diablo2 resurrected loot filter

Only For Chinese and Traditional Chinese The filter only for Chinese and Traditional Chinese, i didn't change it for other language.Maybe you could mo

elmagnifico 249 Dec 04, 2022
Yet Another Robotics and Reinforcement (YARR) learning framework for PyTorch.

Yet Another Robotics and Reinforcement (YARR) learning framework for PyTorch.

Stephen James 51 Dec 27, 2022
Pytorch implementation of various High Dynamic Range (HDR) Imaging algorithms

Deep High Dynamic Range Imaging Benchmark This repository is the pytorch impleme

Tianhong Dai 5 Nov 16, 2022
Source code for models described in the paper "AudioCLIP: Extending CLIP to Image, Text and Audio" (https://arxiv.org/abs/2106.13043)

AudioCLIP Extending CLIP to Image, Text and Audio This repository contains implementation of the models described in the paper arXiv:2106.13043. This

458 Jan 02, 2023
Hashformers is a framework for hashtag segmentation with transformers.

Hashtag segmentation is the task of automatically inserting the missing spaces between the words in a hashtag. Hashformers applies Transformer models

Ruan Chaves 41 Nov 09, 2022
The official code repo of "HTS-AT: A Hierarchical Token-Semantic Audio Transformer for Sound Classification and Detection"

Hierarchical Token Semantic Audio Transformer Introduction The Code Repository for "HTS-AT: A Hierarchical Token-Semantic Audio Transformer for Sound

Knut(Ke) Chen 134 Jan 01, 2023
This tool converts a Nondeterministic Finite Automata (NFA) into a Deterministic Finite Automata (DFA)

This tool converts a Nondeterministic Finite Automata (NFA) into a Deterministic Finite Automata (DFA)

Quinn Herden 1 Feb 04, 2022
A PyTorch implementation of Implicit Q-Learning

IQL-PyTorch This repository houses a minimal PyTorch implementation of Implicit Q-Learning (IQL), an offline reinforcement learning algorithm, along w

Garrett Thomas 30 Dec 12, 2022
Unofficial PyTorch Implementation of "DOLG: Single-Stage Image Retrieval with Deep Orthogonal Fusion of Local and Global Features"

Pytorch Implementation of Deep Orthogonal Fusion of Local and Global Features (DOLG) This is the unofficial PyTorch Implementation of "DOLG: Single-St

DK 96 Jan 06, 2023
An image base contains 490 images for learning (400 cars and 90 boats), and another 21 images for testingAn image base contains 490 images for learning (400 cars and 90 boats), and another 21 images for testing

SVM Données Une base d’images contient 490 images pour l’apprentissage (400 voitures et 90 bateaux), et encore 21 images pour fait des tests. Prétrait

Achraf Rahouti 3 Nov 30, 2021
Compare GAN code.

Compare GAN This repository offers TensorFlow implementations for many components related to Generative Adversarial Networks: losses (such non-saturat

Google 1.8k Jan 05, 2023
Repo for paper "Dynamic Placement of Rapidly Deployable Mobile Sensor Robots Using Machine Learning and Expected Value of Information"

Repo for paper "Dynamic Placement of Rapidly Deployable Mobile Sensor Robots Using Machine Learning and Expected Value of Information" Notes I probabl

Berkeley Expert System Technologies Lab 0 Jul 01, 2021