List of useful data augmentation resources. You will find here some not common techniques, libraries, links to GitHub repos, papers, and others.

Data Augmentation For Object Detection

This is a list of awesome methods about data augmentation.

Image augmentation for object detection, segmentation and classification

This library augments road images to introduce various real world scenarios that pose challenges for training neural networks of Autonomous vehicles. Automold is created to train CNNs in specific weather and road conditions.

Geometric Augmentation for Text Image

A sample code of data augmentation methods for wearable sensor data (time-series data)

An example of time series augmentation methods with Keras

A curated list of graph data augmentation papers.

Data Augmentation for NLP. NLP数据增强

Includes: Learning data augmentation strategies for object detection | GridMask data augmentation | Augmentation for small object detection in Numpy. Use RetinaNet with ResNet-18 to test these methods on VOC and KITTI.

Python implementation of Text-Image-Augmentation

Audio transformations library for PyTorch

Simple implementation of augmentation for small object detection

Contextual augmentation, a text data augmentation using a bidirectional language model.

Fine-tuned pre-trained GPT2 for custom topic specific text generation. Such system can be used for Text Augmentation.

No description available

Data Augmentation for Caffe

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这里面存放了一些目标检测算法的数据增强方法。如mosaic、mixup。

:zap: Caffe real-time data augmentation on-the-fly!!

Image augmentation for randomly rotating, shearing, translating and changing lighting conditions.

Unofficial PyTorch Implementation of Unsupervised Data Augmentation.

Cut and paste augmentation for object detection and instance segmentation

No description available

This package provides TensorFlow Ops for multidimensional volumetric image augmentation.

Code associated with the "Data Augmentation using Pre-trained Transformer Models" paper

本仓库主要包含了针对目标检测数据集的增强手段和源码：图像的旋转，镜像，裁剪，亮度/对比度的变换等

Code for the paper, "Distribution Augmentation for Generative Modeling", ICML 2020.

A collection of awesome things about mixed sample data augmentation