This library helps you with augmenting images for your machine learning projects. It converts a set of input images into a new, much larger set of slightly altered images. Many very popular projects have been integrated. New methods like augmix,cutmix，are being tracked. Whether you're a researcher or an engineer, just enjoy it!

• intro: 2019
• github star: 7.8k
• github: https://github.com/aleju/imgaug

Albumentations: fast and flexible image augmentations

• intro: ArXiv 2018
• github star: 4.1k
• arxiv: https://arxiv.org/abs/1809.06839v1
• github: https://github.com/albumentations-team/albumentations

Biomedical image augmentation using Augmentor

• intro: Bioinformatics
• github star: 3.7k
• arxiv: https://github.com/mdbloice/Augmentor
• github: https://github.com/mdbloice/Augmentor
• docs: https://augmentor.readthedocs.io/en/master/

Augmentor is a Python package designed to aid the augmentation and artificial generation of image data for machine learning tasks. It is primarily a data augmentation tool, but will also incorporate basic image pre-processing functionality.

Mixup: BEYOND EMPIRICAL RISK MINIMIZATION

• intro: ICLR2018
• arxiv: https://arxiv.org/abs/1710.09412
• github: https://github.com/facebookresearch/mixup-cifar10

Mixup is a generic and straightforward data augmentation principle. In essence, mixup trains a neural network on convex combinations of pairs of examples and their labels. By doing so, mixup regularizes the neural network to favor simple linear behavior in-between training examples.

Improved Regularization of Convolutional Neural Networks with Cutout

• intro: arXiv 2017
• arxiv: https://arxiv.org/abs/1708.04552
• github: https://github.com/uoguelph-mlrg/Cutout

CutMix:Regularization Strategy to Train Strong Classifiers with Localizable Features

• intro: ICCV 2019 (oral talk)
• arxiv: https://arxiv.org/pdf/1905.04899.pdf
• github: https://github.com/clovaai/CutMix-PyTorch

AUGMIX: A SIMPLE DATA PROCESSING METHOD TO IMPROVE ROBUSTNESS AND UNCERTAINTY

• intro: ICLR 2020
• arxiv: https://arxiv.org/pdf/1912.02781.pdf
• github: https://github.com/google-research/augmix

Simple Copy-Paste is a Strong Data Augmentation Method for Instance Segmentation

• intro: 2020
• provider: google
• arxiv: https://arxiv.org/pdf/2012.07177.pdf
• github: https://github.com/google-research/augmix

Fast AutoAugment

• intro: NeurIPS 2019
• github star: 671
• arxiv: https://arxiv.org/abs/1905.00397
• github: https://github.com/kakaobrain/fast-autoaugment

AutoAugment:Learning Augmentation Strategies from Data

• intro: CVPR 2019
• provider: google
• arxiv: https://arxiv.org/pdf/1805.09501v3.pdf
• github: https://github.com/DeepVoltaire/AutoAugment

RandAugment: Practical automated data augmentation with a reduced search space

• intro: ICLR 2020
• provider: google
• arxiv: https://arxiv.org/pdf/1909.13719.pdf
• github: https://github.com/tensorflow/tpu/tree/master/models/official/efficientnet

Random Erasing Data Augmentation

black	white	random

• intro: AAAI 2020
• arxiv: https://arxiv.org/pdf/1708.04896.pdf
• github: https://github.com/zhunzhong07/Random-Erasing

GridMaskDataAugmentation

• intro: 2020.01
• arxiv: https://arxiv.org/abs/2001.04086
• github: https://github.com/akuxcw/GridMask
• 知乎参考: https://zhuanlan.zhihu.com/p/103992528

A Person Re-identification Data Augmentation Method with Adversarial Defense Effect

• intro: 2021.01
• arxiv: https://arxiv.org/abs/2001.04086
• github: https://github.com/finger-monkey/ReID_Adversarial_Defense

Benchmarking Robustness in Object Detection:Autonomous Driving when Winter is Coming

• intro: arXiv 2019
• arxiv: https://arxiv.org/abs/1807.01697
• github: https://github.com/CrazyVertigo/imagecorruptions

Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networkss

• intro: ICCV 2017
• arxiv: https://arxiv.org/pdf/1912.02781.pdf
• provider: UC Berkeley
• github: https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix
• github: https://github.com/junyanz/CycleGAN

Adversarial Latent Autoencoders

• intro: CVPR 2020
• arxiv: https://arxiv.org/pdf/2004.04467.pdf
• github: https://github.com/podgorskiy/ALAE

Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networkss

• intro: 2017
• arxiv: https://arxiv.org/pdf/1902.07296.pdf
• github: https://github.com/gmayday1997/SmallObjectAugmentation

Real-Time High-Resolution Background Matting

• intro: 2020.12
• arxiv: https://arxiv.org/abs/2012.07810
• github: https://github.com/PeterL1n/BackgroundMattingV2

Deep Image Harmonization via Domain Verification

• intro: CVPR 2020
• provider: SJTU
• arxiv: https://arxiv.org/abs/1911.13239
• github: https://github.com/bcmi/Image_Harmonization_Datasets

InstaBoost: Boosting Instance Segmentation Via Probability Map Guided Copy-Pasting

• intro: ICCV 2019
• provider: SJTU
• arxiv: https://arxiv.org/abs/1908.07801
• github: https://github.com/GothicAi/Instaboost

Unsupervised Hard Example Mining from Videos for Improved Object Detection

• intro: ECCV 2018
• arxiv: http://vis-www.cs.umass.edu/unsupVideo/docs/unsup-video_eccv2018.pdf
• github: https://github.com/adiprasad/unsup-hard-negative-mining-mscoco
• project: http://vis-www.cs.umass.edu/unsupVideo/
• demo video: http://vis-www.cs.umass.edu/unsupVideo/docs/suppVideo.mp4
• 知乎参考: https://zhuanlan.zhihu.com/p/174057800

• intro: 2017
• github star: 9.8k
• github: https://github.com/tzutalin/labelImg

LabelImg is a graphical image annotation tool and label object bounding boxes in images.

• intro: 2017
• github star: 4.2k
• github: https://github.com/wkentaro/labelme

Image Polygonal Annotation with Python (polygon, rectangle, circle, line, point and image-level flag annotation).

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