diff --git a/deploy/pdserving/README.md b/deploy/pdserving/README.md
index cb2845c581d244e80ca597e0eb485a16ad369f20..c461fd5e54d3a51ad3427f83a1fca35cbe3ab2d8 100644
--- a/deploy/pdserving/README.md
+++ b/deploy/pdserving/README.md
@@ -45,63 +45,67 @@ PaddleOCR operating environment and Paddle Serving operating environment are nee
```
3. Install the client to send requests to the service
- In [download link](https://github.com/PaddlePaddle/Serving/blob/develop/doc/LATEST_PACKAGES.md) find the client installation package corresponding to the python version.
- The python3.7 version is recommended here:
- ```
- wget https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_client-0.0.0-cp37-none-any.whl
- pip3 install paddle_serving_client-0.0.0-cp37-none-any.whl
- ```
-
-4. Install serving-app
- ```
- pip3 install paddle-serving-app==0.6.1
- ```
+```bash
+# 安装serving，用于启动服务
+wget https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_server_gpu-0.7.0.post102-py3-none-any.whl
+pip3 install paddle_serving_server_gpu-0.7.0.post102-py3-none-any.whl
+# 如果是cuda10.1环境，可以使用下面的命令安装paddle-serving-server
+# wget https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_server_gpu-0.7.0.post101-py3-none-any.whl
+# pip3 install paddle_serving_server_gpu-0.7.0.post101-py3-none-any.whl
+
+# 安装client，用于向服务发送请求
+wget https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_client-0.7.0-cp37-none-any.whl
+pip3 install paddle_serving_client-0.7.0-cp37-none-any.whl
+
+# 安装serving-app
+wget https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_app-0.7.0-py3-none-any.whl
+pip3 install paddle_serving_app-0.7.0-py3-none-any.whl
+```
- **note:** If you want to install the latest version of PaddleServing, refer to [link](https://github.com/PaddlePaddle/Serving/blob/develop/doc/LATEST_PACKAGES.md).
+ **note:** If you want to install the latest version of PaddleServing, refer to [link](https://github.com/PaddlePaddle/Serving/blob/v0.7.0/doc/Latest_Packages_CN.md).
## Model conversion
When using PaddleServing for service deployment, you need to convert the saved inference model into a serving model that is easy to deploy.
-Firstly, download the [inference model](https://github.com/PaddlePaddle/PaddleOCR#pp-ocr-20-series-model-listupdate-on-dec-15) of PPOCR
+Firstly, download the [inference model](https://github.com/PaddlePaddle/PaddleOCR/blob/release/2.3/README_ch.md#pp-ocr%E7%B3%BB%E5%88%97%E6%A8%A1%E5%9E%8B%E5%88%97%E8%A1%A8%E6%9B%B4%E6%96%B0%E4%B8%AD) of PPOCR
```
# Download and unzip the OCR text detection model
-wget https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_infer.tar && tar xf ch_ppocr_mobile_v2.0_det_infer.tar
+wget https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_det_infer.tar -O ch_PP-OCRv2_det_infer.tar && tar -xf ch_PP-OCRv2_det_infer.tar
# Download and unzip the OCR text recognition model
-wget https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_infer.tar && tar xf ch_ppocr_mobile_v2.0_rec_infer.tar
-
+wget https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_rec_infer.tar -O ch_PP-OCRv2_rec_infer.tar && tar -xf ch_PP-OCRv2_rec_infer.tar
```
Then, you can use installed paddle_serving_client tool to convert inference model to mobile model.
```
# Detection model conversion
-python3 -m paddle_serving_client.convert --dirname ./ch_ppocr_mobile_v2.0_det_infer/ \
+python3 -m paddle_serving_client.convert --dirname ./ch_PP-OCRv2_det_infer/ \
--model_filename inference.pdmodel \
--params_filename inference.pdiparams \
- --serving_server ./ppocr_det_mobile_2.0_serving/ \
- --serving_client ./ppocr_det_mobile_2.0_client/
+ --serving_server ./ppocrv2_det_serving/ \
+ --serving_client ./ppocrv2_det_client/
# Recognition model conversion
-python3 -m paddle_serving_client.convert --dirname ./ch_ppocr_mobile_v2.0_rec_infer/ \
+python3 -m paddle_serving_client.convert --dirname ./ch_PP-OCRv2_rec_infer/ \
--model_filename inference.pdmodel \
--params_filename inference.pdiparams \
- --serving_server ./ppocr_rec_mobile_2.0_serving/ \
- --serving_client ./ppocr_rec_mobile_2.0_client/
+ --serving_server ./ppocrv2_rec_serving/ \
+ --serving_client ./ppocrv2_rec_client/
```
After the detection model is converted, there will be additional folders of `ppocr_det_mobile_2.0_serving` and `ppocr_det_mobile_2.0_client` in the current folder, with the following format:
```
-|- ppocr_det_mobile_2.0_serving/
- |- __model__
- |- __params__
- |- serving_server_conf.prototxt
- |- serving_server_conf.stream.prototxt
-
-|- ppocr_det_mobile_2.0_client
- |- serving_client_conf.prototxt
- |- serving_client_conf.stream.prototxt
+|- ppocrv2_det_serving/
+ |- __model__
+ |- __params__
+ |- serving_server_conf.prototxt
+ |- serving_server_conf.stream.prototxt
+
+|- ppocrv2_det_client
+ |- serving_client_conf.prototxt
+ |- serving_client_conf.stream.prototxt
```
The recognition model is the same.
diff --git a/deploy/pdserving/README_CN.md b/deploy/pdserving/README_CN.md
index 067be8bbda10d971b709afdf822aea96a979d000..00024639b0b108225a0835499f62174b6618ae47 100644
--- a/deploy/pdserving/README_CN.md
+++ b/deploy/pdserving/README_CN.md
@@ -34,70 +34,66 @@ PaddleOCR提供2种服务部署方式：
- 准备PaddleServing的运行环境，步骤如下
-1. 安装serving，用于启动服务
- ```
- pip3 install paddle-serving-server==0.6.1 # for CPU
- pip3 install paddle-serving-server-gpu==0.6.1 # for GPU
- # 其他GPU环境需要确认环境再选择执行如下命令
- pip3 install paddle-serving-server-gpu==0.6.1.post101 # GPU with CUDA10.1 + TensorRT6
- pip3 install paddle-serving-server-gpu==0.6.1.post11 # GPU with CUDA11 + TensorRT7
- ```
-
-2. 安装client，用于向服务发送请求
- 在[下载链接](https://github.com/PaddlePaddle/Serving/blob/develop/doc/LATEST_PACKAGES.md)中找到对应python版本的client安装包，这里推荐python3.7版本：
-
- ```
- wget https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_client-0.0.0-cp37-none-any.whl
- pip3 install paddle_serving_client-0.0.0-cp37-none-any.whl
- ```
-
-3. 安装serving-app
- ```
- pip3 install paddle-serving-app==0.6.1
- ```
+```bash
+# 安装serving，用于启动服务
+wget https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_server_gpu-0.7.0.post102-py3-none-any.whl
+pip3 install paddle_serving_server_gpu-0.7.0.post102-py3-none-any.whl
+# 如果是cuda10.1环境，可以使用下面的命令安装paddle-serving-server
+# wget https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_server_gpu-0.7.0.post101-py3-none-any.whl
+# pip3 install paddle_serving_server_gpu-0.7.0.post101-py3-none-any.whl
+
+# 安装client，用于向服务发送请求
+wget https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_client-0.7.0-cp37-none-any.whl
+pip3 install paddle_serving_client-0.7.0-cp37-none-any.whl
+
+# 安装serving-app
+wget https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_app-0.7.0-py3-none-any.whl
+pip3 install paddle_serving_app-0.7.0-py3-none-any.whl
+```
- **Note:** 如果要安装最新版本的PaddleServing参考[链接](https://github.com/PaddlePaddle/Serving/blob/develop/doc/LATEST_PACKAGES.md)。
+**Note:** 如果要安装最新版本的PaddleServing参考[链接](https://github.com/PaddlePaddle/Serving/blob/v0.7.0/doc/Latest_Packages_CN.md)。
## 模型转换
使用PaddleServing做服务化部署时，需要将保存的inference模型转换为serving易于部署的模型。
-首先，下载PPOCR的[inference模型](https://github.com/PaddlePaddle/PaddleOCR#pp-ocr-20-series-model-listupdate-on-dec-15)
-```
+首先，下载PPOCR的[inference模型](https://github.com/PaddlePaddle/PaddleOCR#pp-ocr-series-model-listupdate-on-september-8th)
+
+```bash
# 下载并解压 OCR 文本检测模型
-wget https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_infer.tar && tar xf ch_ppocr_mobile_v2.0_det_infer.tar
+wget https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_det_infer.tar -O ch_PP-OCRv2_det_infer.tar && tar -xf ch_PP-OCRv2_det_infer.tar
# 下载并解压 OCR 文本识别模型
-wget https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_infer.tar && tar xf ch_ppocr_mobile_v2.0_rec_infer.tar
+wget https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_rec_infer.tar -O ch_PP-OCRv2_rec_infer.tar && tar -xf ch_PP-OCRv2_rec_infer.tar
```
接下来，用安装的paddle_serving_client把下载的inference模型转换成易于server部署的模型格式。
-```
+```bash
# 转换检测模型
-python3 -m paddle_serving_client.convert --dirname ./ch_ppocr_mobile_v2.0_det_infer/ \
+python3 -m paddle_serving_client.convert --dirname ./ch_PP-OCRv2_det_infer/ \
--model_filename inference.pdmodel \
--params_filename inference.pdiparams \
- --serving_server ./ppocr_det_mobile_2.0_serving/ \
- --serving_client ./ppocr_det_mobile_2.0_client/
+ --serving_server ./ppocrv2_det_serving/ \
+ --serving_client ./ppocrv2_det_client/
# 转换识别模型
-python3 -m paddle_serving_client.convert --dirname ./ch_ppocr_mobile_v2.0_rec_infer/ \
+python3 -m paddle_serving_client.convert --dirname ./ch_PP-OCRv2_rec_infer/ \
--model_filename inference.pdmodel \
--params_filename inference.pdiparams \
- --serving_server ./ppocr_rec_mobile_2.0_serving/ \
- --serving_client ./ppocr_rec_mobile_2.0_client/
+ --serving_server ./ppocrv2_rec_serving/ \
+ --serving_client ./ppocrv2_rec_client/
```
-检测模型转换完成后，会在当前文件夹多出`ppocr_det_mobile_2.0_serving` 和`ppocr_det_mobile_2.0_client`的文件夹，具备如下格式：
+检测模型转换完成后，会在当前文件夹多出`ppocrv2_det_serving` 和`ppocrv2_det_client`的文件夹，具备如下格式：
```
-|- ppocr_det_mobile_2.0_serving/
+|- ppocrv2_det_serving/
|- __model__
|- __params__
|- serving_server_conf.prototxt
|- serving_server_conf.stream.prototxt
-|- ppocr_det_mobile_2.0_client
+|- ppocrv2_det_client
|- serving_client_conf.prototxt
|- serving_client_conf.stream.prototxt
diff --git a/deploy/pdserving/config.yml b/deploy/pdserving/config.yml
index 2aae922dfa12f46d1c0ebd352e8d3a7077065cf8..f3b0f7ec5a47bb9c513ab3d75f7d2d4138f88c4a 100644
--- a/deploy/pdserving/config.yml
+++ b/deploy/pdserving/config.yml
@@ -34,7 +34,7 @@ op:
client_type: local_predictor
#det模型路径
- model_config: ./ppocr_det_mobile_2.0_serving
+ model_config: ./ppocrv2_det_serving
#Fetch结果列表，以client_config中fetch_var的alias_name为准
fetch_list: ["save_infer_model/scale_0.tmp_1"]
@@ -60,7 +60,7 @@ op:
client_type: local_predictor
#rec模型路径
- model_config: ./ppocr_rec_mobile_2.0_serving
+ model_config: ./ppocrv2_rec_serving
#Fetch结果列表，以client_config中fetch_var的alias_name为准
fetch_list: ["save_infer_model/scale_0.tmp_1"]
diff --git a/deploy/pdserving/web_service.py b/deploy/pdserving/web_service.py
index 21db1e1411a8706dbbd9a22ce2ce7db8e16da5ec..b97c6e1f564a61bb9792542b9e9f1e88d782e80d 100644
--- a/deploy/pdserving/web_service.py
+++ b/deploy/pdserving/web_service.py
@@ -54,7 +54,7 @@ class DetOp(Op):
_, self.new_h, self.new_w = det_img.shape
return {"x": det_img[np.newaxis, :].copy()}, False, None, ""
- def postprocess(self, input_dicts, fetch_dict, log_id):
+ def postprocess(self, input_dicts, fetch_dict, data_id, log_id):
det_out = fetch_dict["save_infer_model/scale_0.tmp_1"]
ratio_list = [
float(self.new_h) / self.ori_h, float(self.new_w) / self.ori_w
@@ -129,7 +129,7 @@ class RecOp(Op):
return feed_list, False, None, ""
- def postprocess(self, input_dicts, fetch_data, log_id):
+ def postprocess(self, input_dicts, fetch_data, data_id, log_id):
res_list = []
if isinstance(fetch_data, dict):
if len(fetch_data) > 0:
diff --git a/deploy/pdserving/web_service_det.py b/deploy/pdserving/web_service_det.py
index 25ac2f37dbd3cdf05b3503abaab0c5651867fae9..ee39388425763d789ada76cf0a9db9f812fe8d2a 100644
--- a/deploy/pdserving/web_service_det.py
+++ b/deploy/pdserving/web_service_det.py
@@ -54,7 +54,7 @@ class DetOp(Op):
_, self.new_h, self.new_w = det_img.shape
return {"x": det_img[np.newaxis, :].copy()}, False, None, ""
- def postprocess(self, input_dicts, fetch_dict, log_id):
+ def postprocess(self, input_dicts, fetch_dict, data_id, log_id):
det_out = fetch_dict["save_infer_model/scale_0.tmp_1"]
ratio_list = [
float(self.new_h) / self.ori_h, float(self.new_w) / self.ori_w
diff --git a/deploy/pdserving/web_service_rec.py b/deploy/pdserving/web_service_rec.py
index 6b3cf707f0f19034a0734fd27824feb4fb6cce20..f5cd8bf053c604786fecb9b71749b3c98f2552a2 100644
--- a/deploy/pdserving/web_service_rec.py
+++ b/deploy/pdserving/web_service_rec.py
@@ -56,7 +56,7 @@ class RecOp(Op):
feed_list.append(feed)
return feed_list, False, None, ""
- def postprocess(self, input_dicts, fetch_data, log_id):
+ def postprocess(self, input_dicts, fetch_data, data_id, log_id):
res_list = []
if isinstance(fetch_data, dict):
if len(fetch_data) > 0: