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# Text Image Augmentation
[![Build Status](https://travis-ci.org/Canjie-Luo/Text-Image-Augmentation.svg?branch=master)](https://travis-ci.org/Canjie-Luo/Text-Image-Augmentation)
A general geometric augmentation tool for text images in the CVPR 2020 paper "Learn to Augment: Joint Data Augmentation and Network Optimization for Text Recognition". We provide the tool to avoid overfitting and gain robustness of text recognizers.
Note that this is a general toolkit. Please customize for your specific task. If the repo benefits your work, please cite the papers.
## Requirements
- [Python](https://www.python.org/) 3.6.4
- [Numpy](https://numpy.org/) 1.14.0
## Demo
- Distortion
![](imgs/distort.gif)
- Stretch
![](imgs/stretch.gif)
- Perspective
![](imgs/perspective.gif)
## Speed
To transform an image with size (H:64, W:200), it takes less than 14ms using a 2.5GHz CPU. It is possible to accelerate the process by calling multi-process batch samplers in an on-the-fly manner, such as setting [**\"num_workers\"**](https://pytorch.org/docs/0.3.1/data.html?highlight=dataset#torch.utils.data.DataLoader) in [PyTorch](https://pytorch.org/docs/0.3.1/data.html?highlight=dataset#torch.utils.data.DataLoader).
## Attention
Modify from https://github.com/Canjie-Luo/Text-Image-Augmentation.git.