Python Augmentation-corruption Resources

Benchmarking Robustness of 3D Point Cloud Recognition against Common Corruptions This repo contains the dataset and code for the paper Benchmarking Ro

Easy Data Augmentation Implementation This repository contains my Implementation for the paper EDA: Easy Data Augmentation Techniques for Boosting Per

💎A high level pipeline for face landmarks detection, supports training, evaluating, exporting, inference and 100+ data augmentations, compatible with torchvision and albumentations, can easily install with pip.

Understanding Bayesian Classification This repository hosts the code to reproduce the results presented in the paper On Uncertainty, Tempering, and Da

Traffic-Sign-Recognition In this report, we propose a Convolutional Neural Network(CNN) for traffic sign classification that achieves outstanding perf

ZEROGEN This repository contains the code for our paper “ZeroGen: Efficient Zero

anti-corruption-bot Test API (running via Flask) is currently hosted at https://

daaja This repository has a implementations of data augmentation for NLP for Japanese: EDA: Easy Data Augmentation Techniques for Boosting Performance

Image data augmentation is a technique that can be used to artificially expand the size of a training dataset by creating modified versions of images in the dataset.

Data-Augmentation-Using-Keras-and-Python Data augmentation is the process of increasing the number of training dataset. Keras library offers a simple

VocAug It is difficult to find a script which can augment VOC-format dataset, especially the bbox. Or find a script needs complex requirements so it i

You Only Cut Once (YOCO) YOCO is a simple method/strategy of performing augmenta

Dual-Contrastive-Learning A PyTorch implementation for our paper "Dual Contrastive Learning: Text Classification via Label-Aware Data Augmentation". Y

How robust are discriminatively trained zero-shot learning models? This repository contains the PyTorch implementation of our paper How robust are dis

SAS: Self-Augmentation Strategy for Language Model Pre-training This repository

Synthetic data need to preserve the statistical properties of real data in terms of their individual behavior and (inter-)dependences. Copula and functional Principle Component Analysis (fPCA) are statistical models that allow these properties to be simulated (Joe 2014). As such, copula generated data have shown potential to improve the generalization of machine learning (ML) emulators (Meyer et al. 2021) or anonymize real-data datasets (Patki et al. 2016).

Multiview Detection with Shadow Transformer (and View-Coherent Data Augmentation) [arXiv] [paper] @inproceedings{hou2021multiview, title={Multiview

GMAT: Global Memory Augmentation for Transformers This repository contains the accompanying code for the paper: "GMAT: Global Memory Augmentation for

SRAugmentation Augmentation for Single-Image-Super-Resolution Implimentation CutBlur Cutout CutMix Cutup CutMixup Blend RGBPermutation Identity OneOf

DeltaPy⁠⁠ — Tabular Data Augmentation & Feature Engineering Finance Quant Machine Learning ML-Quant.com - Automated Research Repository Introduction T

tsaug tsaug is a Python package for time series augmentation. It offers a set of augmentation methods for time series, as well as a simple API to conn

Time Series Augmentation This is a collection of time series data augmentation methods and an example use using Keras. News 2020/04/16: Repository Cre

AutoAugment - Learning Augmentation Policies from Data Unofficial implementation of the ImageNet, CIFAR10 and SVHN Augmentation Policies learned by Au

SITT The repo contains official PyTorch Implementation of the paper Single Image Texture Translation for Data Augmentation. Authors: Boyi Li Yin Cui T

FPT_data_centric_competition - Team nan solution repository for FPT data-centric competition. Data augmentation, Albumentation, Mosaic, Visualization, KNN application

SpecAugment An implementation of SpecAugment for Pytorch How to use Install pytorch, version=1.9.0 (new feature (torch.Tensor.take_along_dim) is used

Code used for the results in the paper "ClassMix: Segmentation-Based Data Augmentation for Semi-Supervised Learning" Getting started Prerequisites CUD

CCGL: Contrastive Cascade Graph Learning This repo provides a reference implementation of Contrastive Cascade Graph Learning (CCGL) framework as descr

Self-supervised Label Augmentation via Input Transformations Authors: Hankook Lee, Sung Ju Hwang, Jinwoo Shin (KAIST) Accepted to ICML 2020 Install de

Well-formed Limericks and Haikus with GPT2 📜 GPT-2 Rhyming Limerick and Haiku models using data augmentation In collaboration with Matthew Korahais &

Frequency Spectrum Augmentation Consistency for Domain Adaptive Object Detection Main requirements torch = 1.0 torchvision = 0.2.0 Python 3 Environm

Description Data augmentation libarary for Deep Learning, which supports images, segmentation masks, labels and keypoints. Furthermore, SOLT is fast a

Pytorch library for seismic data augmentation

Imagine by Reasoning: A Reasoning-Based Implicit Semantic Data Augmentation for Long-Tailed Classification Prerequisite PyTorch = 1.2.0 Python3 torch

Frequency Spectrum Augmentation Consistency for Domain Adaptive Object Detection Main requirements torch = 1.0 torchvision = 0.2.0 Python 3 Environm

Self-Supervised Learning (SimCLR) with Biological Plausible Image Augmentations Official code base for the poster "On the use of Cortical Magnificatio

BiCAT This is our TensorFlow implementation for the paper: "BiCAT: Sequential Recommendation with Bidirectional Chronological Augmentation of Transfor

Programmatically Build and Manage Training Data Announcement The Snorkel team is now focusing their efforts on Snorkel Flow, an end-to-end AI applicat

Imagine by Reasoning: A Reasoning-Based Implicit Semantic Data Augmentation for Long-Tailed Classification (AAAI 2022) Prerequisite PyTorch = 1.2.0 P

MetaSAug: Meta Semantic Augmentation for Long-Tailed Visual Recognition (CVPR 2021) arXiv Prerequisite PyTorch = 1.2.0 Python3 torchvision PIL argpar

WebDataset WebDataset is a PyTorch Dataset (IterableDataset) implementation providing efficient access to datasets stored in POSIX tar archives and us

Adversarial Differentiable Data Augmentation This repository provides the official PyTorch implementation of the ICRA 2021 paper: Adversarial Differen

Augmentation-Free Self-Supervised Learning on Graphs An official source code for Augmentation-Free Self-Supervised Learning on Graphs paper, accepted

Augmentation-Free Self-Supervised Learning on Graphs An official source code for Augmentation-Free Self-Supervised Learning on Graphs paper, accepted

On Interaction Between Augmentations and Corruptions in Natural Corruption Robustness This repository provides the code for the paper On Interaction B

SentAugment SentAugment is a data augmentation technique for semi-supervised learning in NLP. It uses state-of-the-art sentence embeddings to structur

hey-daug A light weight data augmentation tool for training CNNs and Viola Jones detectors (Haar Cascades). This tool inflates your data by up to six

AugLiChem Welcome to AugLiChem! The augmentation library for chemical systems. This package supports augmentation for both crystaline and molecular sy

StyleGAN2 with adaptive discriminator augmentation (ADA) — Official TensorFlow implementation Training Generative Adversarial Networks with Limited Da

Deceive D: Adaptive Pseudo Augmentation for GAN Training with Limited Data (NeurIPS 2021) This repository provides the official PyTorch implementation

Description The source code and data for my paper titled Linguistic Knowledge in Data Augmentation for Natural Language Processing: An Example on Chin

HyperMix Code for our paper GPT3Mix and conducting classification experiments using GPT-3 prompt-based data augmentation. Getting Started Installing P

SnapMix: Semantically Proportional Mixing for Augmenting Fine-grained Data (AAAI 2021) PyTorch implementation of SnapMix | paper Method Overview Cite

Robust Self-augmentation for NER with Meta-reweighting

Improving Transferability of Representations via Augmentation-Aware Self-Supervision Accepted to NeurIPS 2021 TL;DR: Learning augmentation-aware infor

SATGAN TODO: update the article URL once published. Article about this implemention The self-attentive task generative adversarial network (SATGAN) le

HyperMix Code for our paper GPT3Mix and conducting classification experiments using GPT-3 prompt-based data augmentation. Getting Started Installing P

Deceive D: Adaptive Pseudo Augmentation for GAN Training with Limited Data (NeurIPS 2021) This repository will provide the official PyTorch implementa

FASA: Feature Augmentation and Sampling Adaptation for Long-Tailed Instance Segmentation (ICCV 2021) This repository contains the implementation of th

Social-NCE + CrowdNav Website | Paper | Video | Social NCE + Trajectron | Social NCE + STGCNN This is an official implementation for Social NCE: Contr

Dynamic Data Augmentation with Gating Networks This is an official PyTorch implementation of the paper Dynamic Data Augmentation with Gating Networks

ADGCL : Adversarial Graph Augmentation to Improve Graph Contrastive Learning Introduction This repo contains the Pytorch [1] implementation of Adversa

Corruption Invariant Learning for Re-identification The official repository for Benchmarks for Corruption Invariant Person Re-identification (NeurIPS

Elucidating Robust Learning with Uncertainty-Aware Corruption Pattern Estimation Introduction 📋 Official implementation of Explainable Robust Learnin

FastestCopy The fastest way to copy to (not from) high speed flash storage. This is about 3-6x faster than file copy on explorer.exe to usb flash driv

TAug :: Time Series Data Augmentation using Deep Generative Models Note!!! The package is under development so be careful for using in production! Fea

Deep Illuminator Deep Illuminator is a data augmentation tool designed for image relighting. It can be used to easily and efficiently generate a wide

Albumentations Albumentations is a Python library for image augmentation. Image augmentation is used in deep learning and computer vision tasks to inc

Cut-Thumbnail (Accepted at ACM MULTIMEDIA 2021) Tianshu Xie, Xuan Cheng, Xiaomin Wang, Minghui Liu, Jiali Deng, Tao Zhou, Ming Liu This is the officia

YOLO Dataset Augmentation lib Инструкция по использованию этой библиотеки Запуск всех файлов осуществлять из консоли. GoogleCrawl_to_Dataset.py Это ск

Improving Transferability of Representations via Augmentation-Aware Self-Supervision Accepted to NeurIPS 2021 TL;DR: Learning augmentation-aware infor

A GUI based datamoshing apllication for everyone! Apply this glitch to your videos and gifs. Supports all video formats!

Accelerated DL & RL PyTorch framework for Deep Learning research and development. It was developed with a focus on reproducibility, fast experimentati

Live-human-face-expression-augmentation-by-projection my graduation project is about live human face augmentation by projection mapping by using CNN o

Improving Model Generalization by Agreement of Learned Representations from Data Augmentation (WACV 2022) Paper ArXiv Why it matters? When data augmen

Welcome! I am a computer vision deep learning developer working in Korea. This is my blog, and you can see everything I've studied here. https://www.n

face.evoLVe: High-Performance Face Recognition Library based on PaddlePaddle & PyTorch Evolve to be more comprehensive, effective and efficient for fa

Learning Debiased Representation via Disentangled Feature Augmentation (Neurips 2021, Oral): Official Project Webpage This repository provides the off

Amazon Forest Computer Vision Satellite Image tagging code using PyTorch / Keras Here is a sample of images we had to work with Source: https://www.ka

[ICCV 2021] A Simple Baseline for Semi-supervised Semantic Segmentation with Strong Data Augmentation

Datashredder is a simple data corruption engine written in python. You can corrupt anything text, images and video. You can chose the cha

Benchmarking the robustness of Spatial-Temporal Models This repositery contains the code for the paper Benchmarking the Robustness of Spatial-Temporal

PointWOLF: Point Cloud Augmentation with Weighted Local Transformations This repository is the implementation of PointWOLF(To appear). Sihyeon Kim1*,

Doubly Trained Neural Machine Translation System for Adversarial Attack and Data Augmentation Languages Experimented: Data Overview: Source Target Tra

PASS - Official PyTorch Implementation [CVPR2021 Oral] Prototype Augmentation and Self-Supervision for Incremental Learning Fei Zhu, Xu-Yao Zhang, Chu

Mix3D: Out-of-Context Data Augmentation for 3D Scenes (3DV 2021) Alexey Nekrasov*, Jonas Schult*, Or Litany, Bastian Leibe, Francis Engelmann Mix3D is

This is the official implementation of our neural-network-based fast diffuse room impulse response generator (FAST-RIR) for generating room impulse responses (RIRs) for a given acoustic environment.

Documentation Pyraug This library provides a way to perform Data Augmentation using Variational Autoencoders in a reliable way even in challenging con

EPCDepth EPCDepth is a self-supervised monocular depth estimation model, whose supervision is coming from the other image in a stereo pair. Details ar

face.evoLVe: High-Performance Face Recognition Library based on PaddlePaddle & PyTorch Evolve to be more comprehensive, effective and efficient for fa

GLaRA: Graph-based Labeling Rule Augmentation for Weakly Supervised Named Entity Recognition

TextAttack 🐙 Generating adversarial examples for NLP models [TextAttack Documentation on ReadTheDocs] About • Setup • Usage • Design About TextAttack

Augmenty: The cherry on top of your NLP pipeline Augmenty is an augmentation library based on spaCy for augmenting texts. Besides a wide array of high

Data Augmentation for Cross-Domain Named Entity Recognition Authors: Shuguang Chen, Gustavo Aguilar, Leonardo Neves and Thamar Solorio This repository

Code for EMNLP 2021 main conference paper "Text AutoAugment: Learning Compositional Augmentation Policy for Text Classification"

Text-AutoAugment (TAA) This repository contains the code for our paper Text AutoAugment: Learning Compositional Augmentation Policy for Text Classific

The baseline code is for EDA: Easy Data Augmentation techniques for boosting performance on text classification tasks

AEDA: An Easier Data Augmentation Technique for Text Classification This is the code for the EMNLP 2021 paper AEDA: An Easier Data Augmentation Techni

Medical image preprocessing and augmentation toolkit for deep learning. Part of the PyTorch Ecosystem.

Data Augmentation for Scene Text Recognition (ICCV 2021 Workshop) (Pronounced as "strog") Paper Arxiv Why it matters? Scene Text Recognition (STR) req