未验证 提交 8b2feecb 编写于 作者: M MissPenguin 提交者: GitHub

Merge pull request #1367 from WenmuZhou/update_angle_class_doc

[Dygraph] update quickstart doc, model link uses link as a placeholder
...@@ -5,7 +5,7 @@ ...@@ -5,7 +5,7 @@
请先参考[快速安装](./installation.md)配置PaddleOCR运行环境。 请先参考[快速安装](./installation.md)配置PaddleOCR运行环境。
*注意:也可以通过 whl 包安装使用PaddleOCR,具体参考[Paddleocr Package使用说明](https://github.com/PaddlePaddle/PaddleOCR/blob/develop/doc/doc_ch/whl.md)。* *注意:也可以通过 whl 包安装使用PaddleOCR,具体参考[Paddleocr Package使用说明](./whl.md)。*
## 2.inference模型下载 ## 2.inference模型下载
...@@ -13,8 +13,8 @@ ...@@ -13,8 +13,8 @@
| 模型简介 | 模型名称 |推荐场景 | 检测模型 | 方向分类器 | 识别模型 | | 模型简介 | 模型名称 |推荐场景 | 检测模型 | 方向分类器 | 识别模型 |
| ------------ | --------------- | ----------------|---- | ---------- | -------- | | ------------ | --------------- | ----------------|---- | ---------- | -------- |
| 中英文超轻量OCR模型(8.1M) | ch_ppocr_mobile_v1.1_xx |移动端&服务器端|[推理模型](https://paddleocr.bj.bcebos.com/20-09-22/mobile/det/ch_ppocr_mobile_v1.1_det_infer.tar) / [预训练模型](https://paddleocr.bj.bcebos.com/20-09-22/mobile/det/ch_ppocr_mobile_v1.1_det_train.tar)|[推理模型](https://paddleocr.bj.bcebos.com/20-09-22/cls/ch_ppocr_mobile_v1.1_cls_infer.tar) / [预训练模型](https://paddleocr.bj.bcebos.com/20-09-22/cls/ch_ppocr_mobile_v1.1_cls_train.tar) |[推理模型](https://paddleocr.bj.bcebos.com/20-09-22/mobile/rec/ch_ppocr_mobile_v1.1_rec_infer.tar) / [预训练模型](https://paddleocr.bj.bcebos.com/20-09-22/mobile/rec/ch_ppocr_mobile_v1.1_rec_pre.tar) | | 中英文超轻量OCR模型(xM) | |移动端&服务器端|[推理模型](link) / [预训练模型](link)|[推理模型]({}) / [预训练模型]({}) |[推理模型]({}) / [预训练模型]({}) |
| 中英文通用OCR模型(155.1M) |ch_ppocr_server_v1.1_xx|服务器端 |[推理模型](https://paddleocr.bj.bcebos.com/20-09-22/server/det/ch_ppocr_server_v1.1_det_infer.tar) / [预训练模型](https://paddleocr.bj.bcebos.com/20-09-22/server/det/ch_ppocr_server_v1.1_det_train.tar) |[推理模型](https://paddleocr.bj.bcebos.com/20-09-22/cls/ch_ppocr_mobile_v1.1_cls_infer.tar) / [预训练模型](https://paddleocr.bj.bcebos.com/20-09-22/cls/ch_ppocr_mobile_v1.1_cls_train.tar) |[推理模型](https://paddleocr.bj.bcebos.com/20-09-22/server/rec/ch_ppocr_server_v1.1_rec_infer.tar) / [预训练模型](https://paddleocr.bj.bcebos.com/20-09-22/server/rec/ch_ppocr_server_v1.1_rec_pre.tar) | | 中英文通用OCR模型(xM) | |服务器端 |[推理模型]({}) / [预训练模型]({}) |[推理模型]({}) / [预训练模型]({}) |[推理模型]({}) / [预训练模型]({}}) |
* windows 环境下如果没有安装wget,下载模型时可将链接复制到浏览器中下载,并解压放置在相应目录下 * windows 环境下如果没有安装wget,下载模型时可将链接复制到浏览器中下载,并解压放置在相应目录下
...@@ -37,11 +37,11 @@ cd .. ...@@ -37,11 +37,11 @@ cd ..
``` ```
mkdir inference && cd inference mkdir inference && cd inference
# 下载超轻量级中文OCR模型的检测模型并解压 # 下载超轻量级中文OCR模型的检测模型并解压
wget https://paddleocr.bj.bcebos.com/20-09-22/mobile/det/ch_ppocr_mobile_v1.1_det_infer.tar && tar xf ch_ppocr_mobile_v1.1_det_infer.tar wget {} && tar xf ch_ppocr_mobile_v1.1_det_infer.tar
# 下载超轻量级中文OCR模型的识别模型并解压 # 下载超轻量级中文OCR模型的识别模型并解压
wget https://paddleocr.bj.bcebos.com/20-09-22/mobile/rec/ch_ppocr_mobile_v1.1_rec_infer.tar && tar xf ch_ppocr_mobile_v1.1_rec_infer.tar wget {} && tar xf ch_ppocr_mobile_v1.1_rec_infer.tar
# 下载超轻量级中文OCR模型的文本方向分类器模型并解压 # 下载超轻量级中文OCR模型的文本方向分类器模型并解压
wget https://paddleocr.bj.bcebos.com/20-09-22/cls/ch_ppocr_mobile_v1.1_cls_infer.tar && tar xf ch_ppocr_mobile_v1.1_cls_infer.tar wget {} && tar xf ch_ppocr_mobile_v1.1_cls_infer.tar
cd .. cd ..
``` ```
...@@ -63,7 +63,7 @@ cd .. ...@@ -63,7 +63,7 @@ cd ..
## 3.单张图像或者图像集合预测 ## 3.单张图像或者图像集合预测
以下代码实现了文本检测、识别串联推理,在执行预测时,需要通过参数image_dir指定单张图像或者图像集合的路径、参数`det_model_dir`指定检测inference模型的路径、参数`rec_model_dir`指定识别inference模型的路径、参数`use_angle_cls`指定是否使用方向分类器、参数`cls_model_dir`指定方向分类器inference模型的路径、参数`use_space_char`指定是否预测空格字符。可视化识别结果默认保存到`./inference_results`文件夹里面。 以下代码实现了文本检测、方向分类器和识别串联推理,在执行预测时,需要通过参数image_dir指定单张图像或者图像集合的路径、参数`det_model_dir`指定检测inference模型的路径、参数`rec_model_dir`指定识别inference模型的路径、参数`use_angle_cls`指定是否使用方向分类器、参数`cls_model_dir`指定方向分类器inference模型的路径、参数`use_space_char`指定是否预测空格字符。可视化识别结果默认保存到`./inference_results`文件夹里面。
```bash ```bash
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...@@ -5,7 +5,7 @@ ...@@ -5,7 +5,7 @@
Please refer to [quick installation](./installation_en.md) to configure the PaddleOCR operating environment. Please refer to [quick installation](./installation_en.md) to configure the PaddleOCR operating environment.
* Note: Support the use of PaddleOCR through whl package installation,pelease refer [PaddleOCR Package](https://github.com/PaddlePaddle/PaddleOCR/blob/develop/doc/doc_en/whl_en.md). * Note: Support the use of PaddleOCR through whl package installation,pelease refer [PaddleOCR Package](./whl_en.md).
## 2.inference models ## 2.inference models
...@@ -14,8 +14,8 @@ The detection and recognition models on the mobile and server sides are as follo ...@@ -14,8 +14,8 @@ The detection and recognition models on the mobile and server sides are as follo
| Model introduction | Model name | Recommended scene | Detection model | Direction Classifier | Recognition model | | Model introduction | Model name | Recommended scene | Detection model | Direction Classifier | Recognition model |
| ------------ | --------------- | ----------------|---- | ---------- | -------- | | ------------ | --------------- | ----------------|---- | ---------- | -------- |
| Ultra-lightweight Chinese OCR model(8.1M) | ch_ppocr_mobile_v1.1_xx |Mobile-side/Server-side|[inference model](https://paddleocr.bj.bcebos.com/20-09-22/mobile/det/ch_ppocr_mobile_v1.1_det_infer.tar) / [pretrained model](https://paddleocr.bj.bcebos.com/20-09-22/mobile/det/ch_ppocr_mobile_v1.1_det_train.tar)|[inference model](https://paddleocr.bj.bcebos.com/20-09-22/cls/ch_ppocr_mobile_v1.1_cls_infer.tar) / [pretrained model](https://paddleocr.bj.bcebos.com/20-09-22/cls/ch_ppocr_mobile_v1.1_cls_train.tar) |[inference model](https://paddleocr.bj.bcebos.com/20-09-22/mobile/rec/ch_ppocr_mobile_v1.1_rec_infer.tar) / [pretrained model](https://paddleocr.bj.bcebos.com/20-09-22/mobile/rec/ch_ppocr_mobile_v1.1_rec_pre.tar) | | Ultra-lightweight Chinese OCR model(xM) | ch_ppocr_mobile_v1.1_xx |Mobile-side/Server-side|[inference model](link) / [pretrained model](link)|[inference model](link) / [pretrained model](link) |[inference model](link) / [pretrained model](link) |
| Universal Chinese OCR model(155.1M) |ch_ppocr_server_v1.1_xx|Server-side |[inference model](https://paddleocr.bj.bcebos.com/20-09-22/server/det/ch_ppocr_server_v1.1_det_infer.tar) / [pretrained model](https://paddleocr.bj.bcebos.com/20-09-22/server/det/ch_ppocr_server_v1.1_det_train.tar) |[inference model](https://paddleocr.bj.bcebos.com/20-09-22/cls/ch_ppocr_mobile_v1.1_cls_infer.tar) / [pretrained model](https://paddleocr.bj.bcebos.com/20-09-22/cls/ch_ppocr_mobile_v1.1_cls_train.tar) |[inference model](https://paddleocr.bj.bcebos.com/20-09-22/server/rec/ch_ppocr_server_v1.1_rec_infer.tar) / [pretrained model](https://paddleocr.bj.bcebos.com/20-09-22/server/rec/ch_ppocr_server_v1.1_rec_pre.tar) | | Universal Chinese OCR model(xM) |ch_ppocr_server_v1.1_xx|Server-side |[inference model](link) / [pretrained model](link) |[inference model](link) / [pretrained model](link) |[inference model](link) / [pretrained model](link) |
* If `wget` is not installed in the windows environment, you can copy the link to the browser to download when downloading the model, then uncompress it and place it in the corresponding directory. * If `wget` is not installed in the windows environment, you can copy the link to the browser to download when downloading the model, then uncompress it and place it in the corresponding directory.
...@@ -37,11 +37,11 @@ Take the ultra-lightweight model as an example: ...@@ -37,11 +37,11 @@ Take the ultra-lightweight model as an example:
``` ```
mkdir inference && cd inference mkdir inference && cd inference
# Download the detection model of the ultra-lightweight Chinese OCR model and uncompress it # Download the detection model of the ultra-lightweight Chinese OCR model and uncompress it
wget https://paddleocr.bj.bcebos.com/20-09-22/mobile/det/ch_ppocr_mobile_v1.1_det_infer.tar && tar xf ch_ppocr_mobile_v1.1_det_infer.tar wget link && tar xf ch_ppocr_mobile_v1.1_det_infer.tar
# Download the recognition model of the ultra-lightweight Chinese OCR model and uncompress it # Download the recognition model of the ultra-lightweight Chinese OCR model and uncompress it
wget https://paddleocr.bj.bcebos.com/20-09-22/mobile/rec/ch_ppocr_mobile_v1.1_rec_infer.tar && tar xf ch_ppocr_mobile_v1.1_rec_infer.tar wget link && tar xf ch_ppocr_mobile_v1.1_rec_infer.tar
# Download the direction classifier model of the ultra-lightweight Chinese OCR model and uncompress it # Download the direction classifier model of the ultra-lightweight Chinese OCR model and uncompress it
wget https://paddleocr.bj.bcebos.com/20-09-22/cls/ch_ppocr_mobile_v1.1_cls_infer.tar && tar xf ch_ppocr_mobile_v1.1_cls_infer.tar wget link && tar xf ch_ppocr_mobile_v1.1_cls_infer.tar
cd .. cd ..
``` ```
...@@ -63,7 +63,7 @@ After decompression, the file structure should be as follows: ...@@ -63,7 +63,7 @@ After decompression, the file structure should be as follows:
## 3. Single image or image set prediction ## 3. Single image or image set prediction
* The following code implements text detection and recognition process. When performing prediction, you need to specify the path of a single image or image set through the parameter `image_dir`, the parameter `det_model_dir` specifies the path to detect the inference model, the parameter `rec_model_dir` specifies the path to identify the inference model, the parameter `use_angle_cls` specifies whether to use the direction classifier, the parameter `cls_model_dir` specifies the path to identify the direction classifier model, the parameter `use_space_char` specifies whether to predict the space char. The visual results are saved to the `./inference_results` folder by default. * The following code implements text detection、angle class and recognition process. When performing prediction, you need to specify the path of a single image or image set through the parameter `image_dir`, the parameter `det_model_dir` specifies the path to detect the inference model, the parameter `rec_model_dir` specifies the path to identify the inference model, the parameter `use_angle_cls` specifies whether to use the direction classifier, the parameter `cls_model_dir` specifies the path to identify the direction classifier model, the parameter `use_space_char` specifies whether to predict the space char. The visual results are saved to the `./inference_results` folder by default.
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