# Text Image Augmentation

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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.