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# PaddleDetection C++部署示例
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English | [简体中文](README_CN.md)
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# PaddleDetection Deployment Examples for C++
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本目录下提供`infer_picodet.cc`快速完成PPDetection模型在Rockchip板子上上通过二代NPU加速部署的示例。
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`infer_picodet.cc` in this directory provides an example of quickly completing the PPDetection model on Rockchip boards for accelerated deployment via second-generation NPUs.
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在部署前，需确认以下两个步骤:
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Before deployment, the following two steps need to be confirmed:
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1. 软硬件环境满足要求
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2. 根据开发环境，下载预编译部署库或者从头编译FastDeploy仓库
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1. Hardware and software environment meets the requirements.
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2. Download the pre-compiled deployment repository or compile the FastDeploy repository from scratch according to the development environment.
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以上步骤请参考[RK2代NPU部署库编译](../../../../../../docs/cn/build_and_install/rknpu2.md)实现
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For the above steps, please refer to [How to Build RKNPU2 Deployment Environment](../../../../../../docs/en/build_and_install/rknpu2.md).
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## 生成基本目录文件
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## Generate Basic Directory Files
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该例程由以下几个部分组成
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The routine consists of the following parts:
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```text
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.
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├── CMakeLists.txt
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├── build # 编译文件夹
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├── image # 存放图片的文件夹
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├── build # Compile Folder
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├── image # Folder for images
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├── infer_picodet.cc
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├── model # 存放模型文件的文件夹
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└── thirdpartys # 存放sdk的文件夹
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├── model # Folder for models
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└── thirdpartys # Folder for sdk
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```
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首先需要先生成目录结构
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First, please build a directory structure
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```bash
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mkdir build
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mkdir images
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@@ -30,24 +31,23 @@ mkdir model
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mkdir thirdpartys
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```
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## 编译
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## Compile
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### 编译并拷贝SDK到thirdpartys文件夹
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### Compile and Copy SDK to folder thirdpartys
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请参考[RK2代NPU部署库编译](../../../../../../docs/cn/build_and_install/rknpu2.md)仓库编译SDK，编译完成后，将在build目录下生成
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fastdeploy-0.0.3目录，请移动它至thirdpartys目录下.
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Please refer to [How to Build RKNPU2 Deployment Environment](../../../../../../docs/en/build_and_install/rknpu2.md) to compile SDK.After compiling, the fastdeploy-0.0.3 directory will be created in the build directory, please move it to the thirdpartys directory.
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### 拷贝模型文件，以及配置文件至model文件夹
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在Paddle动态图模型 -> Paddle静态图模型 -> ONNX模型的过程中，将生成ONNX文件以及对应的yaml配置文件，请将配置文件存放到model文件夹内。
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转换为RKNN后的模型文件也需要拷贝至model。
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### Copy model and configuration files to folder Model
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In the process of Paddle dynamic map model -> Paddle static map model -> ONNX mdoel, ONNX file and the corresponding yaml configuration file will be generated. Please move the configuration file to the folder model.
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After converting to RKNN, the model file also needs to be copied to folder model.
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### 准备测试图片至image文件夹
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### Prepare Test Images to folder image
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```bash
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wget https://gitee.com/paddlepaddle/PaddleDetection/raw/release/2.4/demo/000000014439.jpg
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cp 000000014439.jpg ./images
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```
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### 编译example
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### Compile example
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```bash
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cd build
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@@ -56,7 +56,7 @@ make -j8
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make install
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```
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## 运行例程
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## Running Routines
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```bash
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cd ./build/install
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@@ -64,6 +64,6 @@ cd ./build/install
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```
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- [模型介绍](../../)
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- [Python部署](../python)
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- [视觉模型预测结果](../../../../../../docs/api/vision_results/)
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- [Model Description](../../)
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- [Python Deployment](../python)
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- [Vision model prediction results](../../../../../../docs/api/vision_results/)
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@@ -0,0 +1,69 @@
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[English](README.md) | 简体中文
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# PaddleDetection C++部署示例
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本目录下提供`infer_picodet.cc`快速完成PPDetection模型在Rockchip板子上上通过二代NPU加速部署的示例。
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在部署前，需确认以下两个步骤:
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1. 软硬件环境满足要求
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2. 根据开发环境，下载预编译部署库或者从头编译FastDeploy仓库
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以上步骤请参考[RK2代NPU部署库编译](../../../../../../docs/cn/build_and_install/rknpu2.md)实现
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## 生成基本目录文件
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该例程由以下几个部分组成
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```text
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.
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├── CMakeLists.txt
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├── build # 编译文件夹
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├── image # 存放图片的文件夹
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├── infer_picodet.cc
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├── model # 存放模型文件的文件夹
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└── thirdpartys # 存放sdk的文件夹
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```
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首先需要先生成目录结构
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```bash
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mkdir build
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mkdir images
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mkdir model
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mkdir thirdpartys
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```
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## 编译
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### 编译并拷贝SDK到thirdpartys文件夹
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请参考[RK2代NPU部署库编译](../../../../../../docs/cn/build_and_install/rknpu2.md)仓库编译SDK，编译完成后，将在build目录下生成fastdeploy-0.0.3目录，请移动它至thirdpartys目录下.
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### 拷贝模型文件，以及配置文件至model文件夹
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在Paddle动态图模型 -> Paddle静态图模型 -> ONNX模型的过程中，将生成ONNX文件以及对应的yaml配置文件，请将配置文件存放到model文件夹内。
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转换为RKNN后的模型文件也需要拷贝至model。
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### 准备测试图片至image文件夹
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```bash
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wget https://gitee.com/paddlepaddle/PaddleDetection/raw/release/2.4/demo/000000014439.jpg
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cp 000000014439.jpg ./images
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```
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### 编译example
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```bash
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cd build
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cmake ..
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make -j8
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make install
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```
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## 运行例程
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```bash
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cd ./build/install
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./infer_picodet model/picodet_s_416_coco_lcnet images/000000014439.jpg
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```
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- [模型介绍](../../)
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- [Python部署](../python)
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- [视觉模型预测结果](../../../../../../docs/api/vision_results/)
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