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				| @ -1,4 +1,4 @@ | ||||
| ## Style Text | ||||
| English | [简体中文](README_ch.md) | ||||
| 
 | ||||
| ### Contents | ||||
| - [1. Introduction](#Introduction) | ||||
| @ -27,7 +27,7 @@ Different from the commonly used GAN-based data synthesis tools, the main framew | ||||
| * (2) Background extraction module. | ||||
| * (3) Fusion module. | ||||
| 
 | ||||
| After these three steps, you can quickly realize the image text style transfer. The following figure is som results of the data synthesis tool. | ||||
| After these three steps, you can quickly realize the image text style transfer. The following figure is some results of the data synthesis tool. | ||||
| 
 | ||||
| <div align="center"> | ||||
|     <img src="doc/images/2.png" width="1000"> | ||||
| @ -100,7 +100,7 @@ First, you should have the style reference data for synthesis tasks, which are g | ||||
|      * `language`: The language of the corpus. Needed if method is not `EnNumCorpus`. | ||||
|      * `corpus_file`: The corpus file path. Needed if method is not `EnNumCorpus`. | ||||
| 
 | ||||
| We provide a general dataset constaining Chinese, English and Korean (50,000 images in all) for your trial ([download link](https://paddleocr.bj.bcebos.com/dygraph_v2.0/style_text/chkoen_5w.tar)), some examples are given below : | ||||
| We provide a general dataset containing Chinese, English and Korean (50,000 images in all) for your trial ([download link](https://paddleocr.bj.bcebos.com/dygraph_v2.0/style_text/chkoen_5w.tar)), some examples are given below : | ||||
| 
 | ||||
| <div align="center"> | ||||
|      <img src="doc/images/5.png" width="800"> | ||||
|  | ||||
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