Merge branch 'dygraph' of https://github.com/PaddlePaddle/PaddleOCR into update_notice_1215

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grasswolfs 2020-12-16 00:45:42 +08:00
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@ -96,7 +96,7 @@ For a new language request, please refer to [Guideline for new language_requests
- [Benchmark](./doc/doc_en/benchmark_en.md)
- Data Annotation and Synthesis
- [Semi-automatic Annotation Tool: PPOCRLabel](./PPOCRLabel/README.md)
- [Data Synthesis Tool: Style_Edit](./StyleTextRec/README.md)
- [Data Synthesis Tool: Style-Text](./StyleText/README.md)
- [Other Data Annotation Tools](./doc/doc_en/data_annotation_en.md)
- [Other Data Synthesis Tools](./doc/doc_en/data_synthesis_en.md)
- Datasets

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## Style Text
## Style-Text
### 目录
- [一、工具简介](#工具简介)
@ -85,7 +85,7 @@ python3 -m tools.synth_image -c configs/config.yml --style_image examples/style_
</div>
#### 批量合成
在实际应用场景中经常需要批量合成图片补充到训练集中。StyleText可以使用一批风格图片和语料批量合成数据。合成过程如下
在实际应用场景中经常需要批量合成图片补充到训练集中。Style-Text可以使用一批风格图片和语料批量合成数据。合成过程如下
1. 在`configs/dataset_config.yml`中配置目标场景风格图像和语料的路径,具体如下:
@ -100,7 +100,7 @@ python3 -m tools.synth_image -c configs/config.yml --style_image examples/style_
* `language`:语料的语种;
* `corpus_file`: 语料文件路径。
StyleText也提供了一批中英韩5万张通用场景数据用作文本风格图像便于合成场景丰富的文本图像下图给出了一些示例。
Style-Text也提供了一批中英韩5万张通用场景数据用作文本风格图像便于合成场景丰富的文本图像下图给出了一些示例。
中英韩5万张通用场景数据: [下载地址](https://paddleocr.bj.bcebos.com/dygraph_v2.0/style_text/chkoen_5w.tar)
@ -116,7 +116,7 @@ python3 -m tools.synth_image -c configs/config.yml --style_image examples/style_
<a name="应用案例"></a>
### 四、应用案例
下面以金属表面英文数字识别和通用韩语识别两个场景为例说明使用StyleText合成数据来提升文本识别效果的实际案例。下图给出了一些真实场景图像和合成图像的示例
下面以金属表面英文数字识别和通用韩语识别两个场景为例说明使用Style-Text合成数据来提升文本识别效果的实际案例。下图给出了一些真实场景图像和合成图像的示例
<div align="center">
<img src="doc/images/6.png" width="800">
@ -134,38 +134,38 @@ python3 -m tools.synth_image -c configs/config.yml --style_image examples/style_
### 五、代码结构
```
style_text_rec
|-- arch
|-- arch // 网络结构定义文件
| |-- base_module.py
| |-- decoder.py
| |-- encoder.py
| |-- spectral_norm.py
| `-- style_text_rec.py
|-- configs
|-- configs // 配置文件
| |-- config.yml
| `-- dataset_config.yml
|-- engine
| |-- corpus_generators.py
| |-- predictors.py
| |-- style_samplers.py
| |-- synthesisers.py
| |-- text_drawers.py
| `-- writers.py
|-- examples
|-- engine // 数据合成引擎
| |-- corpus_generators.py // 从文本采样或随机生成语料
| |-- predictors.py // 调用网络生成数据
| |-- style_samplers.py // 采样风格图片
| |-- synthesisers.py // 调度各个模块,合成数据
| |-- text_drawers.py // 生成标准文字图片,用作输入
| `-- writers.py // 将合成的图片和标签写入本地目录
|-- examples // 示例文件
| |-- corpus
| | `-- example.txt
| |-- image_list.txt
| `-- style_images
| |-- 1.jpg
| `-- 2.jpg
|-- fonts
|-- fonts // 字体文件
| |-- ch_standard.ttf
| |-- en_standard.ttf
| `-- ko_standard.ttf
|-- tools
|-- tools // 程序入口
| |-- __init__.py
| |-- synth_dataset.py
| `-- synth_image.py
`-- utils
| |-- synth_dataset.py // 批量合成数据
| `-- synth_image.py // 合成单张图片
`-- utils // 其他基础功能模块
|-- config.py
|-- load_params.py
|-- logging.py

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@ -20,7 +20,7 @@ The downloadable models provided by PaddleOCR include `inference model`, `traine
|model name|description|config|model size|download|
| --- | --- | --- | --- | --- |
|ch_ppocr_mobile_slim_v2.0_det|Slim pruned lightweight model, supporting Chinese, English, multilingual text detection|[ch_det_mv3_db_v2.0.yml](../../configs/det/ch_ppocr_v2.0/ch_det_mv3_db_v2.0.yml)| |[inference model (coming soon)](link) / [slim model (coming soon)](link)|
|ch_ppocr_mobile_slim_v2.0_det|Slim pruned lightweight model, supporting Chinese, English, multilingual text detection|[ch_det_mv3_db_v2.0.yml](../../configs/det/ch_ppocr_v2.0/ch_det_mv3_db_v2.0.yml)| |inference model (coming soon) / slim model (coming soon)|
|ch_ppocr_mobile_v2.0_det|Original lightweight model, supporting Chinese, English, multilingual text detection|[ch_det_mv3_db_v2.0.yml](../../configs/det/ch_ppocr_v2.0/ch_det_mv3_db_v2.0.yml)|3M|[inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_infer.tar) / [trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_train.tar)|
|ch_ppocr_server_v2.0_det|General model, which is larger than the lightweight model, but achieved better performance|[ch_det_res18_db_v2.0.yml](../../configs/det/ch_ppocr_v2.0/ch_det_res18_db_v2.0.yml)|47M|[inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_det_infer.tar) / [trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_det_train.tar)|
@ -32,7 +32,7 @@ The downloadable models provided by PaddleOCR include `inference model`, `traine
|model name|description|config|model size|download|
| --- | --- | --- | --- | --- |
|ch_ppocr_mobile_slim_v2.0_rec|Slim pruned and quantized lightweight model, supporting Chinese, English and number recognition|[rec_chinese_lite_train_v2.0.yml](../../configs/rec/ch_ppocr_v2.0/rec_chinese_lite_train_v2.0.yml)| |[inference model (coming soon)](link) / [slim model (coming soon)](link) |
|ch_ppocr_mobile_slim_v2.0_rec|Slim pruned and quantized lightweight model, supporting Chinese, English and number recognition|[rec_chinese_lite_train_v2.0.yml](../../configs/rec/ch_ppocr_v2.0/rec_chinese_lite_train_v2.0.yml)| |inference model (coming soon) / slim model (coming soon) |
|ch_ppocr_mobile_v2.0_rec|Original lightweight model, supporting Chinese, English and number recognition|[rec_chinese_lite_train_v2.0.yml](../../configs/rec/ch_ppocr_v2.0/rec_chinese_lite_train_v2.0.yml)|3.71M|[inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_infer.tar) / [trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_train.tar) / [pre-trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_pre.tar) |
|ch_ppocr_server_v2.0_rec|General model, supporting Chinese, English and number recognition|[rec_chinese_common_train_v2.0.yml](../../configs/rec/ch_ppocr_v2.0/rec_chinese_common_train_v2.0.yml)|94.8M|[inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_rec_infer.tar) / [trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_rec_train.tar) / [pre-trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_rec_pre.tar) |
@ -44,7 +44,7 @@ The downloadable models provided by PaddleOCR include `inference model`, `traine
|model name|description|config|model size|download|
| --- | --- | --- | --- | --- |
|en_number_mobile_slim_v2.0_rec|Slim pruned and quantized lightweight model, supporting English and number recognition|[rec_en_number_lite_train.yml](../../configs/rec/multi_language/rec_en_number_lite_train.yml)| |[inference model (coming soon )](link) / [slim model (coming soon)](link) |
|en_number_mobile_slim_v2.0_rec|Slim pruned and quantized lightweight model, supporting English and number recognition|[rec_en_number_lite_train.yml](../../configs/rec/multi_language/rec_en_number_lite_train.yml)| |inference model (coming soon ) / slim model (coming soon) |
|en_number_mobile_v2.0_rec|Original lightweight model, supporting English and number recognition|[rec_en_number_lite_train.yml](../../configs/rec/multi_language/rec_en_number_lite_train.yml)|2.56M|[inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/en_number_mobile_v2.0_rec_infer.tar) / [trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/en_number_mobile_v2.0_rec_train.tar) |
<a name="Multilingual"></a>
@ -62,6 +62,6 @@ The downloadable models provided by PaddleOCR include `inference model`, `traine
|model name|description|config|model size|download|
| --- | --- | --- | --- | --- |
|ch_ppocr_mobile_slim_v2.0_cls|Slim quantized model|[cls_mv3.yml](../../configs/cls/cls_mv3.yml)| |[inference model (coming soon)](link) / [trained model](link) / [slim model](link) |
|ch_ppocr_mobile_slim_v2.0_cls|Slim quantized model|[cls_mv3.yml](../../configs/cls/cls_mv3.yml)| |inference model (coming soon) / trained model / slim model|
|ch_ppocr_mobile_v2.0_cls|Original model|[cls_mv3.yml](../../configs/cls/cls_mv3.yml)|1.38M|[inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar) / [trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_train.tar) |