PaddlePaddle · jiangjiajun · Feb 27, 2023 · Feb 21, 2023 · Feb 21, 2023 · Feb 21, 2023
diff --git a/FastDeploy.cmake.in b/FastDeploy.cmake.in
@@ -131,9 +131,9 @@ endif()
 
 if(ENABLE_RKNPU2_BACKEND)
   if(RKNN2_TARGET_SOC STREQUAL "RK356X")
-    set(RKNPU2_LIB ${CMAKE_CURRENT_LIST_DIR}/third_libs/install/rknpu2_runtime/RK356X/lib/librknn_api.so)
+    set(RKNPU2_LIB ${CMAKE_CURRENT_LIST_DIR}/third_libs/install/rknpu2_runtime/lib/librknnrt.so)
   elseif (RKNN2_TARGET_SOC STREQUAL "RK3588")
-    set(RKNPU2_LIB ${CMAKE_CURRENT_LIST_DIR}/third_libs/install/rknpu2_runtime/RK3588/lib/librknn_api.so)
+    set(RKNPU2_LIB ${CMAKE_CURRENT_LIST_DIR}/third_libs/install/rknpu2_runtime/lib/librknnrt.so)
   else ()
     message(FATAL_ERROR "RKNN2_TARGET_SOC is not set, ref value: RK356X or RK3588")
   endif()

diff --git a/cmake/rknpu2.cmake b/cmake/rknpu2.cmake
@@ -1,7 +1,7 @@
 # get RKNPU2_URL
 set(RKNPU2_URL_BASE "https://bj.bcebos.com/fastdeploy/third_libs/")
-set(RKNPU2_VERSION "1.4.0")
-set(RKNPU2_FILE "rknpu2_runtime-linux-x64-${RKNPU2_VERSION}.tgz")
+set(RKNPU2_VERSION "1.4.2b0")
+set(RKNPU2_FILE "rknpu2_runtime-linux-aarch64-${RKNPU2_VERSION}-${RKNN2_TARGET_SOC}.tgz")
 set(RKNPU2_URL "${RKNPU2_URL_BASE}${RKNPU2_FILE}")
 
 # download_and_decompress
@@ -10,11 +10,12 @@ download_and_decompress(${RKNPU2_URL} ${CMAKE_CURRENT_BINARY_DIR}/${RKNPU2_FILE}
 # set path
 set(RKNPU_RUNTIME_PATH ${THIRD_PARTY_PATH}/install/rknpu2_runtime)
 
+# include lib
 if (EXISTS ${RKNPU_RUNTIME_PATH})
-    set(RKNN_RT_LIB ${RKNPU_RUNTIME_PATH}/${RKNN2_TARGET_SOC}/lib/librknnrt.so)
-    include_directories(${RKNPU_RUNTIME_PATH}/${RKNN2_TARGET_SOC}/include)
+    set(RKNN_RT_LIB ${RKNPU_RUNTIME_PATH}/lib/librknnrt.so)
+    include_directories(${RKNPU_RUNTIME_PATH}/include)
 else ()
-    message(FATAL_ERROR "[rknpu2.cmake] download_and_decompress rknpu2_runtime error")
+    message(FATAL_ERROR "[rknpu2.cmake] RKNPU_RUNTIME_PATH does not exist.")
 endif ()
 
 
diff --git a/examples/vision/ocr/PP-OCRv3/rknpu2/README.md b/examples/vision/ocr/PP-OCRv3/rknpu2/README.md
@@ -0,0 +1,77 @@
+# PaddleOCR 模型部署
+
+## PaddleOCR为多个模型组合串联任务，包含如下几个模型构成
+
+* 文本检测 `DBDetector`
+* [可选]方向分类 `Classifer` 用于调整进入文字识别前的图像方向
+* 文字识别 `Recognizer` 用于从图像中识别出文字
+
+根据不同场景, FastDeploy汇总提供如下OCR任务部署, 用户需同时下载3个模型与字典文件（或2个，分类器可选), 完成OCR整个预测流程
+
+## PP-OCR 中英文系列模型
+
+下表中的模型下载链接由PaddleOCR模型库提供, 详见[PP-OCR系列模型列表](https://github.com/PaddlePaddle/PaddleOCR/blob/release/2.6/doc/doc_ch/models_list.md)
+
+| OCR版本              | 文本框检测                                                                                                          | 方向分类模型                                                                                                         | 文字识别                                                                                                           | 字典文件                                                                              | 说明                                                      |
+|:-------------------|:---------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:--------------------------------------------------------|
+| ch_PP-OCRv3[推荐]    | [ch_PP-OCRv3_det](https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_det_infer.tar)                  | [ch_ppocr_mobile_v2.0_cls](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar) | [ch_PP-OCRv3_rec](https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_infer.tar)                  | [ppocr_keys_v1.txt](https://bj.bcebos.com/paddlehub/fastdeploy/ppocr_keys_v1.txt) | OCRv3系列原始超轻量模型，支持中英文、多语种文本检测                            |
+| en_PP-OCRv3[推荐]    | [en_PP-OCRv3_det](https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_det_infer.tar)                  | [ch_ppocr_mobile_v2.0_cls](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar) | [en_PP-OCRv3_rec](https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_rec_infer.tar)                  | [en_dict.txt](https://bj.bcebos.com/paddlehub/fastdeploy/en_dict.txt)             | OCRv3系列原始超轻量模型，支持英文与数字识别，除检测模型和识别模型的训练数据与中文模型不同以外，无其他区别 |
+| ch_PP-OCRv2        | [ch_PP-OCRv2_det](https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_det_infer.tar)                  | [ch_ppocr_mobile_v2.0_cls](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar) | [ch_PP-OCRv2_rec](https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_rec_infer.tar)                  | [ppocr_keys_v1.txt](https://bj.bcebos.com/paddlehub/fastdeploy/ppocr_keys_v1.txt) | OCRv2系列原始超轻量模型，支持中英文、多语种文本检测                            |
+| ch_PP-OCRv2_mobile | [ch_ppocr_mobile_v2.0_det](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_infer.tar) | [ch_ppocr_mobile_v2.0_cls](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar) | [ch_ppocr_mobile_v2.0_rec](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_infer.tar) | [ppocr_keys_v1.txt](https://bj.bcebos.com/paddlehub/fastdeploy/ppocr_keys_v1.txt) | OCRv2系列原始超轻量模型，支持中英文、多语种文本检测,比PPOCRv2更加轻量               |
+| ch_PP-OCRv2_server | [ch_ppocr_server_v2.0_det](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_det_infer.tar) | [ch_ppocr_mobile_v2.0_cls](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar) | [ch_ppocr_server_v2.0_rec](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_rec_infer.tar) | [ppocr_keys_v1.txt](https://bj.bcebos.com/paddlehub/fastdeploy/ppocr_keys_v1.txt) | OCRv2服务器系列模型, 支持中英文、多语种文本检测，比超轻量模型更大，但效果更好              |
+
+## 模型转换
+
+在RKNPU2上使用PPOCR时，我们需要把Paddle静态图模型转为RKNN模型。
+
+### 静态图模型转RKNN格式模型
+
+rknn_toolkit2工具暂不支持直接从Paddle静态图模型直接转换为RKNN模型，因此我们需要先将Paddle静态图模型转为RKNN模型。
+
+```bash
+# 下载模型和字典文件
+wget https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_det_infer.tar
+tar -xvf ch_PP-OCRv3_det_infer.tar
+
+wget https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar
+tar -xvf ch_ppocr_mobile_v2.0_cls_infer.tar
+
+wget https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_infer.tar
+tar -xvf ch_PP-OCRv3_rec_infer.tar
+
+# 转换模型到ONNX格式的模型
+paddle2onnx --model_dir ch_PP-OCRv3_det_infer \
+            --model_filename inference.pdmodel \
+            --params_filename inference.pdiparams \
+            --save_file ch_PP-OCRv3_det_infer/ch_PP-OCRv3_det_infer.onnx \
+            --enable_dev_version True
+paddle2onnx --model_dir ch_ppocr_mobile_v2.0_cls_infer \
+            --model_filename inference.pdmodel \
+            --params_filename inference.pdiparams \
+            --save_file ch_ppocr_mobile_v2.0_cls_infer/ch_ppocr_mobile_v2.0_cls_infer.onnx \
+            --enable_dev_version True
+paddle2onnx --model_dir ch_PP-OCRv3_rec_infer \
+            --model_filename inference.pdmodel \
+            --params_filename inference.pdiparams \
+            --save_file ch_PP-OCRv3_rec_infer/ch_PP-OCRv3_rec_infer.onnx \
+            --enable_dev_version True
+
+# 固定模型的输入shape
+python -m paddle2onnx.optimize --input_model ch_PP-OCRv3_det_infer/ch_PP-OCRv3_det_infer.onnx \
+                               --output_model ch_PP-OCRv3_det_infer/ch_PP-OCRv3_det_infer.onnx \
+                               --input_shape_dict "{'x':[1,3,960,960]}"
+python -m paddle2onnx.optimize --input_model ch_ppocr_mobile_v2.0_cls_infer/ch_ppocr_mobile_v2.0_cls_infer.onnx \
+                               --output_model ch_ppocr_mobile_v2.0_cls_infer/ch_ppocr_mobile_v2.0_cls_infer.onnx \
+                               --input_shape_dict "{'x':[1,3,48,192]}"
+python -m paddle2onnx.optimize --input_model ch_PP-OCRv3_rec_infer/ch_PP-OCRv3_rec_infer.onnx \
+                               --output_model ch_PP-OCRv3_rec_infer/ch_PP-OCRv3_rec_infer.onnx \
+                               --input_shape_dict "{'x':[1,3,48,320]}"
+
+# 转换ONNX模型到RKNN模型
+python tools/rknpu2/export.py --config_path tools/rknpu2/config/ppocrv3_det.yaml \
+                              --target_platform rk3588
+python tools/rknpu2/export.py --config_path tools/rknpu2/config/ppocrv3_rec.yaml \
+                              --target_platform rk3588
+python tools/rknpu2/export.py --config_path tools/rknpu2/config/ppocrv3_cls.yaml \
+                              --target_platform rk3588
+```
diff --git a/examples/vision/ocr/PP-OCRv3/rknpu2/cpp/CMakeLists.txt b/examples/vision/ocr/PP-OCRv3/rknpu2/cpp/CMakeLists.txt
@@ -0,0 +1,14 @@
+PROJECT(infer_demo C CXX)
+CMAKE_MINIMUM_REQUIRED (VERSION 3.10)
+
+# 指定下载解压后的fastdeploy库路径
+option(FASTDEPLOY_INSTALL_DIR "Path of downloaded fastdeploy sdk.")
+
+include(${FASTDEPLOY_INSTALL_DIR}/FastDeploy.cmake)
+
+# 添加FastDeploy依赖头文件
+include_directories(${FASTDEPLOY_INCS})
+
+add_executable(infer_static_shape_demo ${PROJECT_SOURCE_DIR}/infer_static_shape.cc)
+# 添加FastDeploy库依赖
+target_link_libraries(infer_static_shape_demo ${FASTDEPLOY_LIBS})
diff --git a/examples/vision/ocr/PP-OCRv3/rknpu2/cpp/README.md b/examples/vision/ocr/PP-OCRv3/rknpu2/cpp/README.md
@@ -0,0 +1,55 @@
+English | [简体中文](README_CN.md)
+# PPOCRv3 C++ Deployment Example
+
+This directory provides examples that `infer.cc` fast finishes the deployment of PPOCRv3 on CPU/GPU and GPU accelerated by TensorRT.
+
+Two steps before deployment
+
+- 1. Software and hardware should meet the requirements. Please refer to [FastDeploy Environment Requirements](../../../../../docs/en/build_and_install/download_prebuilt_libraries.md)  
+- 2. Download the precompiled deployment library and samples code according to your development environment. Refer to [FastDeploy Precompiled Library](../../../../../docs/en/build_and_install/download_prebuilt_libraries.md)
+
+Taking the CPU inference on Linux as an example, the compilation test can be completed by executing the following command in this directory. FastDeploy version 0.7.0 or above (x.x.x>=0.7.0) is required to support this model.
+
+```
+mkdir build
+cd build
+# Download the FastDeploy precompiled library. Users can choose your appropriate version in the `FastDeploy Precompiled Library` mentioned above
+cmake .. -DFASTDEPLOY_INSTALL_DIR=${PWD}/fastdeploy-linux-x64-x.x.x
+make -j
+
+
+# Download model, image, and dictionary files
+wget https://gitee.com/paddlepaddle/PaddleOCR/raw/release/2.6/doc/imgs/12.jpg
+
+wget https://gitee.com/paddlepaddle/PaddleOCR/raw/release/2.6/ppocr/utils/ppocr_keys_v1.txt
+
+# CPU推理
+./infer_static_shape_demo ./ch_PP-OCRv3_det_infer/ch_PP-OCRv3_det_infer.onnx \
+                          ./ch_ppocr_mobile_v2.0_cls_infer/ch_ppocr_mobile_v2.0_cls_infer.onnx \
+                          ./ch_PP-OCRv3_rec_infer/ch_PP-OCRv3_rec_infer.onnx \
+                          ./ppocr_keys_v1.txt \
+                          ./12.jpg \
+                          0
+# RKNPU推理
+./infer_static_shape_demo ./ch_PP-OCRv3_det_infer/ch_PP-OCRv3_det_infer_rk3588_unquantized.rknn \
+                            ./ch_ppocr_mobile_v2.0_cls_infer/ch_ppocr_mobile_v20_cls_infer_rk3588_unquantized.rknn \
+                             ./ch_PP-OCRv3_rec_infer/ch_PP-OCRv3_rec_infer_rk3588_unquantized.rknn \
+                              ./ppocr_keys_v1.txt \
+                              ./12.jpg \
+                              1
+```
+
+The above command works for Linux or MacOS. For SDK in Windows, refer to:
+- [How to use FastDeploy C++ SDK in Windows](../../../../../docs/cn/faq/use_sdk_on_windows.md)
+
+The visualized result after running is as follows
+
+<img width="640" src="https://user-images.githubusercontent.com/109218879/185826024-f7593a0c-1bd2-4a60-b76c-15588484fa08.jpg">
+
+## Other Documents
+
+- [C++ API Reference](https://baidu-paddle.github.io/fastdeploy-api/cpp/html/)
+- [PPOCR Model Description](../../)
+- [PPOCRv3 Python Deployment](../python)
+- [Model Prediction Results](../../../../../../docs/en/faq/how_to_change_backend.md)
+- [How to switch the model inference backend engine](../../../../../../docs/en/faq/how_to_change_backend.md)
diff --git a/examples/vision/ocr/PP-OCRv3/rknpu2/cpp/README_CN.md b/examples/vision/ocr/PP-OCRv3/rknpu2/cpp/README_CN.md
@@ -0,0 +1,63 @@
+[English](README_CN.md) | 简体中文
+# PPOCRv3 C++部署示例
+
+本目录下提供`infer.cc`快速完成PPOCRv3在CPU/GPU，以及GPU上通过TensorRT加速部署的示例。
+
+在部署前，需确认你已经成功完成以下两个操作:
+
+* [正确编译FastDeploy SDK](../../../../../../docs/cn/faq/rknpu2/build.md).
+* [成功转换模型](../README.md).
+
+在本目录执行如下命令即可完成编译测试，支持此模型需保证FastDeploy版本1.0.3以上(x.x.x>1.0.3), RKNN版本在1.4.1b22以上。
+
+```
+mkdir build
+cd build
+cmake .. -DFASTDEPLOY_INSTALL_DIR=${PWD}/fastdeploy-linux-x64-x.x.x
+make -j
+
+# 下载图片和字典文件
+wget https://gitee.com/paddlepaddle/PaddleOCR/raw/release/2.6/doc/imgs/12.jpg
+wget https://gitee.com/paddlepaddle/PaddleOCR/raw/release/2.6/ppocr/utils/ppocr_keys_v1.txt
+
+
+# 拷贝RKNN模型到build目录
+
+# CPU推理
+./infer_static_shape_demo ./ch_PP-OCRv3_det_infer/ch_PP-OCRv3_det_infer.onnx \
+                          ./ch_ppocr_mobile_v2.0_cls_infer/ch_ppocr_mobile_v2.0_cls_infer.onnx \
+                          ./ch_PP-OCRv3_rec_infer/ch_PP-OCRv3_rec_infer.onnx \
+                          ./ppocr_keys_v1.txt \
+                          ./12.jpg \
+                          0
+# RKNPU推理
+./infer_static_shape_demo ./ch_PP-OCRv3_det_infer/ch_PP-OCRv3_det_infer_rk3588_unquantized.rknn \
+                            ./ch_ppocr_mobile_v2.0_cls_infer/ch_ppocr_mobile_v20_cls_infer_rk3588_unquantized.rknn \
+                             ./ch_PP-OCRv3_rec_infer/ch_PP-OCRv3_rec_infer_rk3588_unquantized.rknn \
+                              ./ppocr_keys_v1.txt \
+                              ./12.jpg \
+                              1
+```
+
+运行完成可视化结果如下图所示:
+
+<img width="640" src="https://user-images.githubusercontent.com/109218879/185826024-f7593a0c-1bd2-4a60-b76c-15588484fa08.jpg">
+
+结果输出如下:
+
+```text
+det boxes: [[276,174],[285,173],[285,178],[276,179]]rec text:  rec score:0.000000 cls label: 1 cls score: 0.766602
+det boxes: [[43,408],[483,390],[483,431],[44,449]]rec text: 上海斯格威铂尔曼大酒店 rec score:0.888450 cls label: 0 cls score: 1.000000
+det boxes: [[186,456],[399,448],[399,480],[186,488]]rec text: 打浦路15号 rec score:0.988769 cls label: 0 cls score: 1.000000
+det boxes: [[18,501],[513,485],[514,537],[18,554]]rec text: 绿洲仕格维花园公寓 rec score:0.992730 cls label: 0 cls score: 1.000000
+det boxes: [[78,553],[404,541],[404,573],[78,585]]rec text: 打浦路252935号 rec score:0.983545 cls label: 0 cls score: 1.000000
+Visualized result saved in ./vis_result.jpg
+```
+
+
+## 其它文档
+
+- [C++ API查阅](https://baidu-paddle.github.io/fastdeploy-api/cpp/html/)
+- [PPOCR 系列模型介绍](../../../README_CN.md)
+- [PPOCRv3 Python部署](../python)
+- [模型预测结果说明](../../../../../../docs/cn/faq/how_to_change_backend.md)
diff --git a/examples/vision/ocr/PP-OCRv3/rknpu2/cpp/infer_static_shape.cc b/examples/vision/ocr/PP-OCRv3/rknpu2/cpp/infer_static_shape.cc
@@ -0,0 +1,126 @@
+// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include "fastdeploy/vision.h"
+
+void InitAndInfer(const std::string &det_model_file,
+                  const std::string &cls_model_file,
+                  const std::string &rec_model_file,
+                  const std::string &rec_label_file,
+                  const std::string &image_file,
+                  const fastdeploy::RuntimeOption &option,
+                  const fastdeploy::ModelFormat &format) {
+  auto det_params_file = "";
+  auto cls_params_file = "";
+  auto rec_params_file = "";
+
+  auto det_option = option;
+  auto cls_option = option;
+  auto rec_option = option;
+
+  if (format == fastdeploy::ONNX) {
+    std::cout << "ONNX Model" << std::endl;
+  }
+
+  auto det_model = fastdeploy::vision::ocr::DBDetector(
+      det_model_file, det_params_file, det_option, format);
+  auto cls_model = fastdeploy::vision::ocr::Classifier(
+      cls_model_file, cls_params_file, cls_option, format);
+  auto rec_model = fastdeploy::vision::ocr::Recognizer(
+      rec_model_file, rec_params_file, rec_label_file, rec_option, format);
+
+  if (format == fastdeploy::RKNN) {
+    cls_model.GetPreprocessor().DisableNormalize();
+    cls_model.GetPreprocessor().DisablePermute();
+
+    det_model.GetPreprocessor().DisableNormalize();
+    det_model.GetPreprocessor().DisablePermute();
+
+    rec_model.GetPreprocessor().DisableNormalize();
+    rec_model.GetPreprocessor().DisablePermute();
+  }
+  det_model.GetPreprocessor().SetStaticShapeInfer(true);
+  rec_model.GetPreprocessor().SetStaticShapeInfer(true);
+
+  assert(det_model.Initialized());
+  assert(cls_model.Initialized());
+  assert(rec_model.Initialized());
+
+  // The classification model is optional, so the PP-OCR can also be connected
+  // in series as follows auto ppocr_v3 =
+  // fastdeploy::pipeline::PPOCRv3(&det_model, &rec_model);
+  auto ppocr_v3 =
+      fastdeploy::pipeline::PPOCRv3(&det_model, &cls_model, &rec_model);
+
+  // When users enable static shape infer for rec model, the batch size of cls
+  // and rec model must to be set to 1.
+  ppocr_v3.SetClsBatchSize(1);
+  ppocr_v3.SetRecBatchSize(1);
+
+  if (!ppocr_v3.Initialized()) {
+    std::cerr << "Failed to initialize PP-OCR." << std::endl;
+    return;
+  }
+
+  auto im = cv::imread(image_file);
+
+  fastdeploy::vision::OCRResult result;
+  if (!ppocr_v3.Predict(im, &result)) {
+    std::cerr << "Failed to predict." << std::endl;
+    return;
+  }
+
+  std::cout << result.Str() << std::endl;
+
+  auto vis_im = fastdeploy::vision::VisOcr(im, result);
+  cv::imwrite("vis_result.jpg", vis_im);
+  std::cout << "Visualized result saved in ./vis_result.jpg" << std::endl;
+}
+
+int main(int argc, char *argv[]) {
+  if (argc < 7) {
+    std::cout << "Usage: infer_demo path/to/det_model path/to/cls_model "
+                 "path/to/rec_model path/to/rec_label_file path/to/image "
+                 "run_option, "
+                 "e.g ./infer_demo ./ch_PP-OCRv3_det_infer "
+                 "./ch_ppocr_mobile_v2.0_cls_infer ./ch_PP-OCRv3_rec_infer "
+                 "./ppocr_keys_v1.txt ./12.jpg 0"
+              << std::endl;
+    std::cout << "The data type of run_option is int, 0: run with cpu; 1: run "
+                 "with ascend."
+              << std::endl;
+    return -1;
+  }
+
+  fastdeploy::RuntimeOption option;
+  fastdeploy::ModelFormat format;
+  int flag = std::atoi(argv[6]);
+
+  if (flag == 0) {
+    option.UseCpu();
+    format = fastdeploy::ONNX;
+  } else if (flag == 1) {
+    option.UseRKNPU2();
+    format = fastdeploy::RKNN;
+  }
+
+  std::string det_model_dir = argv[1];
+  std::string cls_model_dir = argv[2];
+  std::string rec_model_dir = argv[3];
+  std::string rec_label_file = argv[4];
+  std::string test_image = argv[5];
+  InitAndInfer(det_model_dir, cls_model_dir, rec_model_dir, rec_label_file,
+               test_image, option, format);
+  return 0;
+}