update readme and doc

README.md

-# PaddleOCR
-OCR algorithms with PaddlePaddle （still under develop)
+
+# 简介
+PaddleOCR旨在打造一套丰富、领先、且实用的文字检测、识别模型/工具库，助力使用者训练出更好的模型，并应用落地。
+
+【这里加上效果图】
+
+## 文档教程
+- [快速安装](./doc/installation.md)
+- [文本识别模型训练/评估/预测](./doc/detection.md)
+- [文本预测模型训练/评估/预测](./doc/recognition.md)
+
+## 特性：
+- 超轻量级模型
+    -（检测模型4.1M + 识别模型4.5M = 8.6M）
+- 支持竖排文字
+    - (单模型同时支持横排和竖排文字识别)
+- 支持长文本识别
+- 支持中英文数字组合识别
+- 提供训练代码
+- 支持模型部署
+
+## 文本检测算法:
+
+PaddleOCR提供的文本检测算法列表：
+- [EAST](https://arxiv.org/abs/1704.03155)
+- [DB](https://arxiv.org/abs/1911.08947)
+- [SAST](https://arxiv.org/abs/1908.05498)
+
+算法效果：
+|模型|骨干网络|数据集|Hmean|
+|-|-|-|-|
+|EAST|ResNet50_vd|ICDAR2015|85.85%|
+|EAST|MobileNetV3|ICDAR2015|79.08%|
+|DB|ResNet50_vd|ICDAR2015|83.30%|
+|DB|MobileNetV3|ICDAR2015|73.00%|
+
+PaddleOCR文本检测算法的训练与使用请参考[文档](./doc/detection.md)。
+
+## 文本识别算法:
+
+PaddleOCR提供的文本识别算法列表：
+- (CRNN)[https://arxiv.org/abs/1507.05717]
+- [Rosetta](https://arxiv.org/abs/1910.05085)
+- [STAR-Net](http://www.bmva.org/bmvc/2016/papers/paper043/index.html)
+- [RARE](https://arxiv.org/abs/1603.03915v1)
+- [SRN]((https://arxiv.org/abs/2003.12294))(百度自研)
+
+算法效果：
+
+以下指标是在IIIT, SVT, IC03, IC13, IC15, SVTP, CUTE数据集上的评测结果的平均。
+
+|模型|骨干网络|ACC|
+|-|-|-|
+|Rosetta|Resnet34_vd|80.24%|
+|Rosetta|MobileNetV3|78.16%|
+|CRNN|Resnet34_vd|82.20%|
+|CRNN|MobileNetV3|79.37%|
+|STAR-Net|Resnet34_vd|83.93%|
+|STAR-Net|MobileNetV3|81.56%|
+|RARE|Resnet34_vd|84.90%|
+|RARE|MobileNetV3|83.32%|
+
+PaddleOCR文本识别算法的训练与使用请参考[文档](./doc/recognition.md)。
+
+## 端到端算法
+PaddleOCR即将开源百度自研端对端OCR模型[End2End-PSL](https://arxiv.org/abs/1909.07808)，敬请关注。
+- End2End-PSL (comming soon)
+
+
+
+# 参考文献
+```
+EAST:
+@inproceedings{zhou2017east,
+  title={EAST: an efficient and accurate scene text detector},
+  author={Zhou, Xinyu and Yao, Cong and Wen, He and Wang, Yuzhi and Zhou, Shuchang and He, Weiran and Liang, Jiajun},
+  booktitle={Proceedings of the IEEE conference on Computer Vision and Pattern Recognition},
+  pages={5551--5560},
+  year={2017}
+}
+
+DB:
+@article{liao2019real,
+  title={Real-time Scene Text Detection with Differentiable Binarization},
+  author={Liao, Minghui and Wan, Zhaoyi and Yao, Cong and Chen, Kai and Bai, Xiang},
+  journal={arXiv preprint arXiv:1911.08947},
+  year={2019}
+}
+
+DTRB:
+@inproceedings{baek2019wrong,
+  title={What is wrong with scene text recognition model comparisons? dataset and model analysis},
+  author={Baek, Jeonghun and Kim, Geewook and Lee, Junyeop and Park, Sungrae and Han, Dongyoon and Yun, Sangdoo and Oh, Seong Joon and Lee, Hwalsuk},
+  booktitle={Proceedings of the IEEE International Conference on Computer Vision},
+  pages={4715--4723},
+  year={2019}
+}
+
+SAST:
+@inproceedings{wang2019single,
+  title={A Single-Shot Arbitrarily-Shaped Text Detector based on Context Attended Multi-Task Learning},
+  author={Wang, Pengfei and Zhang, Chengquan and Qi, Fei and Huang, Zuming and En, Mengyi and Han, Junyu and Liu, Jingtuo and Ding, Errui and Shi, Guangming},
+  booktitle={Proceedings of the 27th ACM International Conference on Multimedia},
+  pages={1277--1285},
+  year={2019}
+}
+
+SRN:
+@article{yu2020towards,
+  title={Towards Accurate Scene Text Recognition with Semantic Reasoning Networks},
+  author={Yu, Deli and Li, Xuan and Zhang, Chengquan and Han, Junyu and Liu, Jingtuo and Ding, Errui},
+  journal={arXiv preprint arXiv:2003.12294},
+  year={2020}
+}
+
+end2end-psl:
+@inproceedings{sun2019chinese,
+  title={Chinese Street View Text: Large-scale Chinese Text Reading with Partially Supervised Learning},
+  author={Sun, Yipeng and Liu, Jiaming and Liu, Wei and Han, Junyu and Ding, Errui and Liu, Jingtuo},
+  booktitle={Proceedings of the IEEE International Conference on Computer Vision},
+  pages={9086--9095},
+  year={2019}
+}
+```

doc/detection.md

@@ -35,15 +35,15 @@ json.dumps编码前的图像标注信息是包含多个字典的list，字典中
 首先下载pretrain model，PaddleOCR的检测模型目前支持两种backbone，分别是MobileNetV3、ResNet50_vd，
 您可以根据需求使用[PaddleClas](https://github.com/PaddlePaddle/PaddleClas/tree/master/ppcls/modeling/architectures)中的模型更换backbone。
 ```
+cd PaddleOCR/
 # 下载MobileNetV3的预训练模型
-wget -P /PaddleOCR/pretrained_model/ 模型链接
+wget -P /PaddleOCR/pretrain_models/ 模型链接
 # 下载ResNet50的预训练模型
-wget -P /PaddleOCR/pretrained_model/ 模型链接
+wget -P /PaddleOCR/pretrain_models/ 模型链接
 ```
 
 **启动训练**
 ```
-cd PaddleOCR/
 python3 tools/train.py -c configs/det/det_db_mv3.yml
 ```
 

doc/installation.md

-### 2.1 快速安装
+## 快速安装
 
 建议使用我们提供的docker运行PaddleOCR，有关docker使用请参考[链接](https://docs.docker.com/get-started/)。
 1. 准备docker环境。第一次使用这个镜像，会自动下载该镜像，请耐心等待。
 ```
 # 切换到工作目录下
 cd /home/Projects
+# 首次运行需创建一个docker容器，再次运行时不需要运行当前命令
 # 创建一个名字为pdocr的docker容器，并将当前目录映射到容器的/data目录下
 sudo nvidia-docker run --name pdocr -v $PWD:/data --network=host -it  hub.baidubce.com/paddlepaddle/paddle:latest-gpu-cuda9.0-cudnn7-dev  /bin/bash
+
+# ctrl+P+Q可退出docker，重新进入docker使用如下命令
+sudo nvidia-docker container exec -it pdocr /bin/bash
+
 ```
 
 2. 克隆PaddleOCR repo代码
@@ -20,3 +25,10 @@ cd PaddleOCR
 pip3 install --upgrade pip
 pip3 install -r requirements.txt
 ```
+
+## 快速运行
+
+```
+python3 tools/infer/predict_eval.py --image_file="./"
+```
+【可视化运行结果】