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100 lines
3.6 KiB
Markdown
100 lines
3.6 KiB
Markdown
# PaddleClas高性能全场景模型部署方案—FastDeploy
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## 目录
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- [FastDeploy介绍](#FastDeploy介绍)
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- [图像分类模型部署](#图像分类模型部署)
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- [常见问题](#常见问题)
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## 1. FastDeploy介绍
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<div id="FastDeploy介绍"></div>
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**[⚡️FastDeploy](https://github.com/PaddlePaddle/FastDeploy)**是一款**全场景**、**易用灵活**、**极致高效**的AI推理部署工具，支持**云边端**部署。使用FastDeploy可以简单高效的在X86 CPU、NVIDIA GPU、飞腾CPU、ARM CPU、Intel GPU、Graphcore IPU、昆仑、昇腾、瑞芯微、晶晨、算能等10+款硬件上对PaddleClas模型进行快速部署，并且支持Paddle Inference、Paddle Lite、TensorRT、OpenVINO、ONNXRuntime、RKNPU2、SOPHGO等多种推理后端。
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<div align="center">
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<img src="https://user-images.githubusercontent.com/31974251/224941235-d5ea4ed0-7626-4c62-8bbd-8e4fad1e72ad.png" >
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</div>
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## 2. 图像分类模型部署
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<div id="图像分类模型部署"></div>
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### 2.1 硬件支持列表
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|硬件类型|该硬件是否支持|使用指南|Python|C++|
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|:---:|:---:|:---:|:---:|:---:|
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|X86 CPU|✅|[链接](./cpu-gpu)|✅|✅|
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|NVIDIA GPU|✅|[链接](./cpu-gpu)|✅|✅|
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|飞腾CPU|✅|[链接](./cpu-gpu)|✅|✅|
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|ARM CPU|✅|[链接](./cpu-gpu)|✅|✅|
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|Intel GPU(集成显卡)|✅|[链接](./cpu-gpu)|✅|✅|
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|Intel GPU(独立显卡)|✅|[链接](./cpu-gpu)|✅|✅|
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|Graphcore IPU|✅|[链接](./graphcore)|✅|✅|
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|昆仑|✅|[链接](./kunlunxin)|✅|✅|
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|昇腾|✅|[链接](./ascend)|✅|✅|
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|瑞芯微|✅|[链接](./rockchip)|✅|✅|
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|晶晨|✅|[链接](./amlogic)|--|✅|✅|
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|算能|✅|[链接](./sophgo)|✅|✅|
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### 2.2. 详细使用文档
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- X86 CPU
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- [部署模型准备](./cpu-gpu)
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- [Python部署示例](./cpu-gpu/python/)
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- [C++部署示例](./cpu-gpu/cpp/)
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- NVIDIA GPU
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- [部署模型准备](./cpu-gpu)
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- [Python部署示例](./cpu-gpu/python/)
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- [C++部署示例](./cpu-gpu/cpp/)
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- 飞腾CPU
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- [部署模型准备](./cpu-gpu)
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- [Python部署示例](./cpu-gpu/python/)
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- [C++部署示例](./cpu-gpu/cpp/)
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- ARM CPU
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- [部署模型准备](./cpu-gpu)
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- [Python部署示例](./cpu-gpu/python/)
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- [C++部署示例](./cpu-gpu/cpp/)
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- Intel GPU
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- [部署模型准备](./cpu-gpu)
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- [Python部署示例](./cpu-gpu/python/)
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- [C++部署示例](./cpu-gpu/cpp/)
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- Graphcore IPU
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- [部署模型准备](./graphcore)
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- [Python部署示例](./graphcore/python/)
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- [C++部署示例](./graphcore/cpp/)
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- 昆仑 XPU
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- [部署模型准备](./kunlunxin)
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- [Python部署示例](./kunlunxin/python/)
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- [C++部署示例](./kunlunxin/cpp/)
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- 昇腾 Ascend
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- [部署模型准备](./ascend)
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- [Python部署示例](./ascend/python/)
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- [C++部署示例](./ascend/cpp/)
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- 瑞芯微 Rockchip
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- [部署模型准备](./rockchip/)
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- [Python部署示例](./rockchip/rknpu2/)
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- [C++部署示例](./rockchip/rknpu2/)
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- 晶晨 Amlogic
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- [部署模型准备](./amlogic/a311d/)
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- [C++部署示例](./amlogic/a311d/cpp/)
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- 算能 Sophgo
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- [部署模型准备](./sophgo/)
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- [Python部署示例](./sophgo/python/)
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- [C++部署示例](./sophgo/cpp/)
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### 2.3 更多部署方式
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- [Android ARM CPU部署](./android)
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- [服务化Serving部署](./serving)
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- [web部署](./web)
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- [模型自动化压缩工具](./quantize)
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## 4. 常见问题
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<div id="常见问题"></div>
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遇到问题可查看常见问题集合，搜索FastDeploy issue，*或给FastDeploy提交[issue](https://github.com/PaddlePaddle/FastDeploy/issues)*:
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[常见问题集合](https://github.com/PaddlePaddle/FastDeploy/tree/develop/docs/cn/faq)
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[FastDeploy issues](https://github.com/PaddlePaddle/FastDeploy/issues)
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