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* Refactor PaddleSeg with preprocessor && postprocessor * Fix bugs * Delete redundancy code * Modify by comments * Refactor according to comments * Add batch evaluation * Add single test script * Add ppliteseg single test script && fix eval(raise) error * fix bug * Fix evaluation segmentation.py batch predict * Fix segmentation evaluation bug * Fix evaluation segmentation bugs * Update segmentation result docs * Update old predict api and DisableNormalizeAndPermute * Update resize segmentation label map with cv::INTER_NEAREST * Add Model Clone function for PaddleClas && PaddleDet && PaddleSeg * Add multi thread demo * Add python model clone function * Add multi thread python && C++ example * Fix bug * Update python && cpp multi_thread examples * Add cpp && python directory * Add README.md for examples * Delete redundant code * Create README_CN.md * Rename README_CN.md to README.md * Update README.md * Update README.md Co-authored-by: Jason <jiangjiajun@baidu.com>
37 lines
1.8 KiB
Markdown
37 lines
1.8 KiB
Markdown
# PaddleClas C++多线程部署示例
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本目录下提供`multi_thread.cc`快速完成PaddleClas系列模型在CPU/GPU，以及GPU上通过TensorRT加速多线程部署的示例。
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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，参考[FastDeploy环境要求](../../../docs/cn/build_and_install/download_prebuilt_libraries.md)
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- 2. 根据开发环境，下载预编译部署库和samples代码，参考[FastDeploy预编译库](../../../docs/cn/build_and_install/download_prebuilt_libraries.md)
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以Linux上ResNet50_vd推理为例，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0.7.0以上(x.x.x>=0.7.0)
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```bash
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mkdir build
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cd build
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# 下载FastDeploy预编译库，用户可在上文提到的`FastDeploy预编译库`中自行选择合适的版本使用
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wget https://bj.bcebos.com/fastdeploy/release/cpp/fastdeploy-linux-x64-x.x.x.tgz
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tar xvf fastdeploy-linux-x64-x.x.x.tgz
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cmake .. -DFASTDEPLOY_INSTALL_DIR=${PWD}/fastdeploy-linux-x64-x.x.x
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make -j
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# 下载ResNet50_vd模型文件和测试图片
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wget https://bj.bcebos.com/paddlehub/fastdeploy/ResNet50_vd_infer.tgz
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tar -xvf ResNet50_vd_infer.tgz
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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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# CPU多线程推理
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./infer_demo ResNet50_vd_infer ILSVRC2012_val_00000010.jpeg 0 1
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# GPU多线程推理
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./infer_demo ResNet50_vd_infer ILSVRC2012_val_00000010.jpeg 1 1
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# GPU上TensorRT多线程推理
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./infer_demo ResNet50_vd_infer ILSVRC2012_val_00000010.jpeg 2 1
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```
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>> **注意**: 最后一位数字表示线程数
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以上命令只适用于Linux或MacOS, Windows下SDK的使用方式请参考:
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- [如何在Windows中使用FastDeploy C++ SDK](../../../docs/cn/faq/use_sdk_on_windows.md) |