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* Add Huawei Ascend NPU deploy through PaddleLite CANN * Add NNAdapter interface for paddlelite * Modify Huawei Ascend Cmake * Update way for compiling Huawei Ascend NPU deployment * remove UseLiteBackend in UseCANN * Support compile python whlee * Change names of nnadapter API * Add nnadapter pybind and remove useless API * Support Python deployment on Huawei Ascend NPU * Add models suppor for ascend * Add PPOCR rec reszie for ascend * fix conflict for ascend * Rename CANN to Ascend * Rename CANN to Ascend * Improve ascend * fix ascend bug * improve ascend docs * improve ascend docs * improve ascend docs * Improve Ascend * Improve Ascend * Move ascend python demo * Imporve ascend * Improve ascend * Improve ascend * Improve ascend * Improve ascend * Imporve ascend * Imporve ascend * Improve ascend * acc eval script * acc eval * remove acc_eval from branch huawei * Add detection and segmentation examples for Ascend deployment * Add detection and segmentation examples for Ascend deployment * Add PPOCR example for ascend deploy * Imporve paddle lite compiliation * Add FlyCV doc * Add FlyCV doc * Add FlyCV doc * Imporve Ascend docs * Imporve Ascend docs
69 lines
2.2 KiB
Markdown
69 lines
2.2 KiB
Markdown
[English](../../en/faq/boost_cv_by_flycv.md) | 中文
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# 使用FlyCV加速端到端推理性能
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[FlyCV](https://github.com/PaddlePaddle/FlyCV) 是一款高性能计算机图像处理库, 针对ARM架构做了很多优化, 相比其他图像处理库性能更为出色.
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FastDeploy现在已经集成FlyCV, 用户可以在支持的硬件平台上使用FlyCV, 实现模型端到端推理性能的加速.
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## 已支持的系统与硬件架构
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| 系统 | 硬件架构 |
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| :-----------| :-------- |
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| Android | armeabi-v7a, arm64-v8a |
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| Linux | aarch64, armhf, x86_64|
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## 使用方式
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使用FlyCV,首先需要在编译时开启FlyCV编译选项,之后在部署时新增一行代码即可开启.
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本文以Linux系统为例,说明如何开启FlyCV编译选项, 之后在部署时, 新增一行代码使用FlyCV.
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用户可以按照如下方式,在编译预测库时,开启FlyCV编译选项.
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```bash
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# 编译C++预测库时, 开启FlyCV编译选项.
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-DENABLE_VISION=ON \
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# 在编译Python预测库时, 开启FlyCV编译选项
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export ENABLE_FLYCV=ON
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```
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用户可以按照如下方式,在部署代码中新增一行代码启用FlyCV.
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```bash
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# C++部署代码.
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# 新增一行代码启用FlyCV
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fastdeploy::vision::EnableFlyCV();
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# 其他部署代码...(以昇腾部署为例)
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fastdeploy::RuntimeOption option;
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option.UseAscend();
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...
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# Python部署代码
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# 新增一行代码启用FlyCV
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fastdeploy.vision.enable_flycv()
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# 其他部署代码...(以昇腾部署为例)
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runtime_option = build_option()
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option.use_ascend()
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...
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```
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## 部分平台FlyCV 端到端性能数据
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鲲鹏920 CPU + Atlas 300I Pro 推理卡.
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| 模型 | OpenCV 端到端性能(ms) | FlyCV 端到端性能(ms) |
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| :-----------| :-------- | :-------- |
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| ResNet50 | 2.78 | 1.63 |
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| PP-LCNetV2 | 2.50 | 1.39 |
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| YOLOv7 | 27.00 | 21.36 |
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| PP_HumanSegV2_Lite | 2.76 | 2.10 |
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瑞芯微RV1126.
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| 模型 | OpenCV 端到端性能(ms) | FlyCV 端到端性能(ms) |
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| :-----------| :-------- | :-------- |
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| ResNet50 | 9.23 | 6.01 |
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| mobilenetv1_ssld_量化模型 | 9.23 | 6.01 |
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| yolov5s_量化模型 | 28.33 | 14.25 |
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| PP_LiteSeg_量化模型 | 132.25 | 60.31 |
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