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58 lines
1.8 KiB
Markdown
58 lines
1.8 KiB
Markdown
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# PaddleClas C++部署示例
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本目录下提供`infer.cc`快速完成ResNet50_vd模型在SOPHGO BM1684x板子上加速部署的示例。
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## 1. 部署环境准备
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在部署前，需自行编译基于SOPHGO硬件的预测库，参考文档[SOPHGO硬件部署环境](https://github.com/PaddlePaddle/FastDeploy/blob/develop/docs/cn/build_and_install#算能硬件部署环境)
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## 2. 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.cc
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├── preprocess_config.yaml #示例前处理配置文件
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└── model # 存放模型文件的文件夹
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```
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## 3. 部署实例
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### 3.1 编译并拷贝SDK到thirdpartys文件夹
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请参考[SOPHGO部署库编译](https://github.com/PaddlePaddle/FastDeploy/blob/develop/docs/cn/build_and_install/sophgo.md)仓库编译SDK，编译完成后，将在build目录下生成fastdeploy-x.x.x目录.
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### 3.2 拷贝模型文件，以及配置文件至model文件夹
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将Paddle模型转换为SOPHGO bmodel模型，转换步骤参考[文档](../README.md)
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将转换后的SOPHGO bmodel模型文件拷贝至model中
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将前处理配置文件也拷贝到model中
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```bash
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cp preprocess_config.yaml ./model
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```
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### 3.3 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/PaddleClas/raw/release/2.4/deploy/images/ImageNet/ILSVRC2012_val_00000010.jpeg
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cp ILSVRC2012_val_00000010.jpeg ./images
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```
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### 3.4 编译example
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```bash
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cd build
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cmake .. -DFASTDEPLOY_INSTALL_DIR=${PWD}/fastdeploy-x.x.x
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make
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```
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### 3.5 运行例程
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```bash
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./infer_demo model images/ILSVRC2012_val_00000010.jpeg
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```
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## 4. 其它文档
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- [ResNet50_vd python部署](../python)
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- [转换ResNet50_vd SOPHGO模型文档](../README.md)
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