为训练深度OCR 图像，生成文本图像

https://github.com/Sanster/text_renderer

Generate text images for training deep learning ocr model

在Windows中也可以运行，只需要将Unicode编码 encoding='utf-8' 即可。

说明：

这个开源项目可以根据你提供的语料文字，来生成对应的多变文本图像，这样可以方便OCR在训练时需要大量的训练样本。

运行 python main.py --help 可以看到在生成自己的 文本图像时需要设置的一些参数.

主要参数：

语料模型：curpus_mode  包括：chn，eng，random，list

语料目录：corpus_dir

输出目录：output_dir

图像保存：--tag  在输出目录的一个子目录下面

运行代码如下：

python main.py --corpus_mode chn --corpus_dir MY_corpus --output_dir MY_samples --tag image

一定要有 tag 参数设定 ，否则跑不出结果。

生成新样本如下：

Text Renderer

Generate text images for training deep learning OCR model (e.g. CRNN). Support both latin and non-latin text.

Setup

• Ubuntu 16.04
• python 3.5+

Install dependencies:

pip3 install -r requirements.txt

Demo

By default, simply run python3 main.py will generate 20 text images and a labels.txt file in output/default/.

 

 

Use your own data to generate image

1. Please run python3 main.py --help to see all optional arguments and their meanings. And put your own data in corresponding folder.

2. Config text effects and fraction in configs/default.yaml file(or create a new config file and use it by --config_fileoption), here are some examples:

Effect name	Image
Origin(Font size 25)
Perspective Transform
Random Crop
Curve
Light border
Dark border
Random char space big
Random char space small
Middle line
Table line
Under line
Emboss
Reverse color
Blur

1. Run main.py file.

Strict mode

For no-latin language(e.g Chinese), it's very common that some fonts only support limited chars. In this case, you will get bad results like these:

Select fonts that support all chars in --chars_file is annoying. Run main.py with --strict option, renderer will retry get text from corpus during generate processing until all chars are supported by a font.

Tools

You can use check_font.py script to check how many chars your font not support in --chars_file:

python3 tools/check_font.py

checking font ./data/fonts/eng/Hack-Regular.ttf
chars not supported(4971):
['第', '朱', '广', '沪', '联', '自', '治', '县', '驼', '身', '进', '行', '纳', '税', '防', '火', '墙', '掏', '心', '内', '容', '万', '警','钟', '上', '了', '解'...]
0 fonts support all chars(5071) in ./data/chars/chn.txt:
[]

Generate image using GPU

If you want to use GPU to make generate image faster, first compile opencv with CUDA. Compiling OpenCV with CUDA support

Then build Cython part, and add --gpu option when run main.py

cd libs/gpu
python3 setup.py build_ext --inplace

Debug mode

Run python3 main.py --debug will save images with extract information. You can see how perspectiveTransform works and all bounding/rotated boxes.

Todo

See https://github.com/Sanster/text_renderer/projects/1