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422 lines
66 KiB
Markdown
Executable File
[English](README_EN.md) | 简体中文 | [हिन्दी](./docs/docs_i18n/README_हिन्दी.md) | [日本語](./docs/docs_i18n/README_日本語.md) | [한국인](./docs/docs_i18n/README_한국인.md) | [Pу́сский язы́к](./docs/docs_i18n/README_Pу́сский_язы́к.md)
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</p>
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<p align="center">
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<a href="./LICENSE"><img src="https://img.shields.io/badge/license-Apache%202-dfd.svg"></a>
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<a href="https://github.com/PaddlePaddle/FastDeploy/releases"><img src="https://img.shields.io/github/v/release/PaddlePaddle/FastDeploy?color=ffa"></a>
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<a href=""><img src="https://img.shields.io/badge/python-3.7+-aff.svg"></a>
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<a href=""><img src="https://img.shields.io/badge/os-linux%2C%20win%2C%20mac-pink.svg"></a>
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<a href="https://github.com/PaddlePaddle/FastDeploy/graphs/contributors"><img src="https://img.shields.io/github/contributors/PaddlePaddle/FastDeploy?color=9ea"></a>
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<a href="https://github.com/PaddlePaddle/FastDeploy/commits"><img src="https://img.shields.io/github/commit-activity/m/PaddlePaddle/FastDeploy?color=3af"></a>
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<a href="https://github.com/PaddlePaddle/FastDeploy/issues"><img src="https://img.shields.io/github/issues/PaddlePaddle/FastDeploy?color=9cc"></a>
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<a href="https://github.com/PaddlePaddle/FastDeploy/stargazers"><img src="https://img.shields.io/github/stars/PaddlePaddle/FastDeploy?color=ccf"></a>
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</p>
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<p align="center">
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<a href="/docs/cn/build_and_install"><b> 安装 </b></a>
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<a href="docs/README_CN.md"><b> 使用文档 </b></a>
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<a href="README_CN.md#fastdeploy-quick-start-python"><b> 快速开始 </b></a>
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<a href="https://baidu-paddle.github.io/fastdeploy-api/"><b> API文档 </b></a>
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<a href="https://github.com/PaddlePaddle/FastDeploy/releases"><b> 更新日志 </b></a>
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</p>
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<div align="center">
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[<img src='https://user-images.githubusercontent.com/54695910/200465949-da478e1b-21ce-43b8-9f3f-287460e786bd.png' height="80px" width="110px">](examples/vision/classification)
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[<img src='https://user-images.githubusercontent.com/54695910/188054680-2f8d1952-c120-4b67-88fc-7d2d7d2378b4.gif' height="80px" width="110px">](examples/vision/detection)
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[<img src='https://user-images.githubusercontent.com/54695910/188054711-6119f0e7-d741-43b1-b273-9493d103d49f.gif' height="80px" width="110px">](examples/vision/segmentation/paddleseg)
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[<img src='https://user-images.githubusercontent.com/54695910/188054718-6395321c-8937-4fa0-881c-5b20deb92aaa.gif' height="80px" width="110px">](examples/vision/segmentation/paddleseg)
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[<img src='https://user-images.githubusercontent.com/54695910/188058231-a5fe1ce1-0a38-460f-9582-e0b881514908.gif' height="80px" width="110px">](examples/vision/matting)
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[<img src='https://user-images.githubusercontent.com/54695910/188054691-e4cb1a70-09fe-4691-bc62-5552d50bd853.gif' height="80px" width="110px">](examples/vision/matting)
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[<img src='https://user-images.githubusercontent.com/54695910/188054669-a85996ba-f7f3-4646-ae1f-3b7e3e353e7d.gif' height="80px" width="110px">](examples/vision/ocr)<br>
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[<img src='https://user-images.githubusercontent.com/54695910/188059460-9845e717-c30a-4252-bd80-b7f6d4cf30cb.png' height="80px" width="110px">](examples/vision/facealign)
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[<img src='https://user-images.githubusercontent.com/54695910/188054671-394db8dd-537c-42b1-9d90-468d7ad1530e.gif' height="80px" width="110px">](examples/vision/keypointdetection)
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[<img src='https://user-images.githubusercontent.com/48054808/173034825-623e4f78-22a5-4f14-9b83-dc47aa868478.gif' height="80px" width="110px">](https://user-images.githubusercontent.com/54695910/200162475-f5d85d70-18fb-4930-8e7e-9ca065c1d618.gif)
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[<img src='https://user-images.githubusercontent.com/54695910/200162475-f5d85d70-18fb-4930-8e7e-9ca065c1d618.gif' height="80px" width="110px">](examples/text)
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[<img src='https://user-images.githubusercontent.com/54695910/212314909-77624bdd-1d12-4431-9cca-7a944ec705d3.png' height="80px" width="110px">](https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/parakeet/001.wav)
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</div>
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**⚡️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。提供超过 🔥160+ **Text**，**Vision**， **Speech**和**跨模态**模型📦**开箱即用**的部署体验，并实现🔚**端到端**的推理性能优化。包括 [物体检测](./examples/vision/detection)、[字符识别（OCR）](./examples/vision/ocr)、[人脸](./examples/vision/facedet)、[人像扣图](./examples/vision/matting)、[多目标跟踪系统](./examples/vision/tracking/pptracking)、[NLP](./examples/text)、[Stable Diffusion文图生成](./examples/multimodal/stable_diffusion)、[TTS](./examples/audio/pp-tts) 等几十种任务场景，满足开发者**多场景、多硬件、多平台**的产业部署需求。
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<div align="center">
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<img src="https://user-images.githubusercontent.com/54695910/213087733-7f2ea97b-baa4-4b0d-9b71-202ff6032a30.png" >
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</div>
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## 🌠 近期更新
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- FastDeploy系列[**直播课程回放**](https://aistudio.baidu.com/aistudio/education/group/info/27800)
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- **2023.01.17** 发布 [**YOLOv8**](./examples/vision/detection/paddledetection/) 在FastDeploy系列硬件的部署支持。 其中包括 [**Paddle YOLOv8**](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov8) 以及 [**社区 ultralytics YOLOv8**](https://github.com/ultralytics/ultralytics)
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- [**Paddle YOLOv8**](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov8) 可以部署的硬件：[**Intel CPU**](./examples/vision/detection/paddledetection/python/infer_yolov8.py)、[**NVIDIA GPU**](./examples/vision/detection/paddledetection/python/infer_yolov8.py)、[**Jetson**](./examples/vision/detection/paddledetection/python/infer_yolov8.py)、[**飞腾**](./examples/vision/detection/paddledetection/python/infer_yolov8.py)、[**昆仑芯**](./examples/vision/detection/paddledetection/python/infer_yolov8.py)、[**昇腾**](./examples/vision/detection/paddledetection/python/infer_yolov8.py)、[**ARM CPU**](./examples/vision/detection/paddledetection/cpp/infer_yolov8.cc)、[**RK3588**](./examples/vision/detection/paddledetection/rknpu2) 和 [**Sophgo TPU**](./examples/vision/detection/paddledetection/sophgo), 部分硬件包含 **Python** 部署和 **C++** 部署；
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- [**社区 ultralytics YOLOv8**](https://github.com/ultralytics/ultralytics) 可以部署的硬件：[**Intel CPU**](./examples/vision/detection/yolov8)、[**NVIDIA GPU**](./examples/vision/detection/yolov8)、[**Jetson**](./examples/vision/detection/yolov8)，均包含 **Python** 部署和 **C++** 部署；
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- FastDeploy 一行模型API切换，可以实现**YOLOv8**、 **PP-YOLOE+**、**YOLOv5** 等模型性能对比。
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- 服务化部署结合VisualDL新增支持可视化部署。在FastDeploy容器中启动VDL服务后，即可在VDL界面修改模型配置、启动/管理模型服务、查看性能数据、发送请求等，详细操作可参考相关文档
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- [Serving可视化部署](https://github.com/PaddlePaddle/FastDeploy/blob/develop/serving/docs/zh_CN/vdl_management.md)
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- [Serving可视化请求](https://github.com/PaddlePaddle/FastDeploy/blob/develop/serving/docs/zh_CN/client.md#%E4%BD%BF%E7%94%A8fastdeploy-client%E8%BF%9B%E8%A1%8C%E5%8F%AF%E8%A7%86%E5%8C%96%E8%AF%B7%E6%B1%82)
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- **✨👥✨ 社区交流**
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- **Slack**：Join our [Slack community](https://join.slack.com/t/fastdeployworkspace/shared_invite/zt-1o50e4voz-zbiIneCNRf_eH99eS2NVLg) and chat with other community members about ideas
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- **微信**：扫描二维码，填写问卷加入技术社区，与社区开发者交流部署产业落地痛点问题
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<div align="center">
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<img src="https://user-images.githubusercontent.com/54695910/216615983-bbb78319-0231-4635-86d1-f2ebf9eac85d.jpg" width = "150" height = "150" />
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</div>
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<div id="fastdeploy-acknowledge"></div>
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## 🌌 推理后端及能力
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<font size=0.5em>
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| | <img src="https://user-images.githubusercontent.com/54695910/212475832-f32502e2-4be2-42fc-a380-2ae265417938.png" height = "26" /> | <img src="https://user-images.githubusercontent.com/54695910/212475828-240036b0-f06c-4c44-830a-d8b136099b09.png" height = "27" /> |<img src="https://user-images.githubusercontent.com/54695910/212475827-b73a1191-b3a8-4ad5-b6f6-855b3d1ffc09.png" height = "26" />| <img src="https://user-images.githubusercontent.com/54695910/212475826-f52b0ef3-e512-49fe-9b52-e1b9d1e8b6c2.png" height = "30" /> | <img src="https://user-images.githubusercontent.com/54695910/212475825-9686ae78-bad9-4be9-852e-6ad23be209da.png" height = "30" /> | <img src="https://user-images.githubusercontent.com/54695910/212475822-067349d2-8c4a-4431-bf02-05387e2962a8.png" height = "30" /> |<img src="https://user-images.githubusercontent.com/54695910/212475820-5210efe0-3e9a-429a-ad9d-48e8da2ffd0b.png" height = "30" /> |
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| X86_64 CPU | | <img src="https://user-images.githubusercontent.com/54695910/212545467-e64ee45d-bf12-492c-b263-b860cb1e172b.png" height = "25"/> | <img src="https://user-images.githubusercontent.com/54695910/212474104-d82f3545-04d4-4ddd-b240-ffac34d8a920.svg" height = "17"/> | <img src="https://user-images.githubusercontent.com/54695910/212473391-92c9f289-a81a-4927-9f31-1ab3fa3c2971.svg" height = "17"/><br><img src="https://user-images.githubusercontent.com/54695910/212473392-9df374d4-5daa-4e2b-856b-6e50ff1e4282.svg" height = "17"/><br><img src="https://user-images.githubusercontent.com/54695910/212473190-fdf3cee2-5670-47b5-85e7-6853a8dd200a.svg" height = "17"/> | <img src="https://user-images.githubusercontent.com/54695910/212473391-92c9f289-a81a-4927-9f31-1ab3fa3c2971.svg" height = "17"/><br><img src="https://user-images.githubusercontent.com/54695910/212473392-9df374d4-5daa-4e2b-856b-6e50ff1e4282.svg" height = "17"/><br><img src="https://user-images.githubusercontent.com/54695910/212473190-fdf3cee2-5670-47b5-85e7-6853a8dd200a.svg" height = "17"/> | | <img src="https://user-images.githubusercontent.com/54695910/212473391-92c9f289-a81a-4927-9f31-1ab3fa3c2971.svg" height = "17"/><br><img src="https://user-images.githubusercontent.com/54695910/212473392-9df374d4-5daa-4e2b-856b-6e50ff1e4282.svg" height = "17"/><br><img src="https://user-images.githubusercontent.com/54695910/212473190-fdf3cee2-5670-47b5-85e7-6853a8dd200a.svg" height = "17"/> |
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| NVDIA GPU | <img src="https://user-images.githubusercontent.com/54695910/212545467-e64ee45d-bf12-492c-b263-b860cb1e172b.png" height = "25"/> | <img src="https://user-images.githubusercontent.com/54695910/212545467-e64ee45d-bf12-492c-b263-b860cb1e172b.png" height = "25"/> | <img src="https://user-images.githubusercontent.com/54695910/212474106-a297aa0d-9225-458e-b5b7-e31aec7cfa79.svg" height = "17"/><br><img src="https://user-images.githubusercontent.com/54695910/212474104-d82f3545-04d4-4ddd-b240-ffac34d8a920.svg" height = "17"/> | <img src="https://user-images.githubusercontent.com/54695910/212473391-92c9f289-a81a-4927-9f31-1ab3fa3c2971.svg" height = "17"/><br><img src="https://user-images.githubusercontent.com/54695910/212473556-d2ebb7cc-e72b-4b49-896b-83f95ae1fe63.svg" height = "17"/><br><img src="https://user-images.githubusercontent.com/54695910/212473190-fdf3cee2-5670-47b5-85e7-6853a8dd200a.svg" height = "17"/> |<img src="https://user-images.githubusercontent.com/54695910/212473391-92c9f289-a81a-4927-9f31-1ab3fa3c2971.svg" height = "17"/><br><img src="https://user-images.githubusercontent.com/54695910/212473556-d2ebb7cc-e72b-4b49-896b-83f95ae1fe63.svg" height = "17"/><br><img src="https://user-images.githubusercontent.com/54695910/212473190-fdf3cee2-5670-47b5-85e7-6853a8dd200a.svg" height = "17"/> | | |
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|飞腾 CPU | | | <img src="https://user-images.githubusercontent.com/54695910/212474105-38051192-9a1c-4b24-8ad1-f842fb0bf39d.svg" height = "17"/> | <img src="https://user-images.githubusercontent.com/54695910/212473389-8c341bbe-30d4-4a28-b50a-074be4e98ce6.svg" height = "17"/><br><img src="https://user-images.githubusercontent.com/54695910/212473393-ae1958bd-ab7d-4863-94b9-32863e600ba1.svg" height = "17"/> | | | |
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| 昆仑芯 XPU | | | <img src="https://user-images.githubusercontent.com/54695910/212474104-d82f3545-04d4-4ddd-b240-ffac34d8a920.svg" height = "17"/> |<img src="https://user-images.githubusercontent.com/54695910/212473389-8c341bbe-30d4-4a28-b50a-074be4e98ce6.svg" height = "17"/> | | | |
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| 华为昇腾 NPU | | | <img src="https://user-images.githubusercontent.com/54695910/212474105-38051192-9a1c-4b24-8ad1-f842fb0bf39d.svg" height = "17"/><br><img src="https://user-images.githubusercontent.com/54695910/212474104-d82f3545-04d4-4ddd-b240-ffac34d8a920.svg" height = "17"/>| <img src="https://user-images.githubusercontent.com/54695910/212473389-8c341bbe-30d4-4a28-b50a-074be4e98ce6.svg" height = "17"/> | | | |
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|Graphcore IPU | | <img src="https://user-images.githubusercontent.com/54695910/212545467-e64ee45d-bf12-492c-b263-b860cb1e172b.png" height = "25"/> | | <img src="https://user-images.githubusercontent.com/54695910/212473391-92c9f289-a81a-4927-9f31-1ab3fa3c2971.svg" height = "17"/> | | | |
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| 算能 | | | | <img src="https://user-images.githubusercontent.com/54695910/212473382-e3e9063f-c298-4b61-ad35-a114aa6e6555.svg" height = "17"/> | | | |
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|Intel 显卡 | | | | <img src="https://user-images.githubusercontent.com/54695910/212473392-9df374d4-5daa-4e2b-856b-6e50ff1e4282.svg" height = "17"/> | | | |
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|Jetson | <img src="https://user-images.githubusercontent.com/54695910/212545467-e64ee45d-bf12-492c-b263-b860cb1e172b.png" height = "25"/> | <img src="https://user-images.githubusercontent.com/54695910/212545467-e64ee45d-bf12-492c-b263-b860cb1e172b.png" height = "25"/> |<img src="https://user-images.githubusercontent.com/54695910/212474105-38051192-9a1c-4b24-8ad1-f842fb0bf39d.svg" height = "17"/><br><img src="https://user-images.githubusercontent.com/54695910/212474106-a297aa0d-9225-458e-b5b7-e31aec7cfa79.svg" height = "17"/> | <img src="https://user-images.githubusercontent.com/54695910/212473391-92c9f289-a81a-4927-9f31-1ab3fa3c2971.svg" height = "17"/><br><img src="https://user-images.githubusercontent.com/54695910/212473556-d2ebb7cc-e72b-4b49-896b-83f95ae1fe63.svg" height = "17"/><br><img src="https://user-images.githubusercontent.com/54695910/212473190-fdf3cee2-5670-47b5-85e7-6853a8dd200a.svg" height = "17"/> |<img src="https://user-images.githubusercontent.com/54695910/212473391-92c9f289-a81a-4927-9f31-1ab3fa3c2971.svg" height = "17"/><br><img src="https://user-images.githubusercontent.com/54695910/212473556-d2ebb7cc-e72b-4b49-896b-83f95ae1fe63.svg" height = "17"/><br><img src="https://user-images.githubusercontent.com/54695910/212473190-fdf3cee2-5670-47b5-85e7-6853a8dd200a.svg" height = "17"/> | | |
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|ARM CPU | | | <img src="https://user-images.githubusercontent.com/54695910/212474105-38051192-9a1c-4b24-8ad1-f842fb0bf39d.svg" height = "17"/><br><img src="https://user-images.githubusercontent.com/54695910/212474104-d82f3545-04d4-4ddd-b240-ffac34d8a920.svg" height = "17"/>| <img src="https://user-images.githubusercontent.com/54695910/212473389-8c341bbe-30d4-4a28-b50a-074be4e98ce6.svg" height = "17"/><br><img src="https://user-images.githubusercontent.com/54695910/212473393-ae1958bd-ab7d-4863-94b9-32863e600ba1.svg" height = "17"/> | | <img src="https://user-images.githubusercontent.com/54695910/212473389-8c341bbe-30d4-4a28-b50a-074be4e98ce6.svg" height = "17"/> | <img src="https://user-images.githubusercontent.com/54695910/212473393-ae1958bd-ab7d-4863-94b9-32863e600ba1.svg" height = "17"/> |
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|RK3588等 | | | <img src="https://user-images.githubusercontent.com/54695910/212474105-38051192-9a1c-4b24-8ad1-f842fb0bf39d.svg" height = "17"/> | <img src="https://user-images.githubusercontent.com/54695910/212473387-2559cc2a-024b-4452-806c-6105d8eb2339.svg" height = "17"/> | | | |
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|RV1126等 | | | <img src="https://user-images.githubusercontent.com/54695910/212474105-38051192-9a1c-4b24-8ad1-f842fb0bf39d.svg" height = "17"/> | <img src="https://user-images.githubusercontent.com/54695910/212473389-8c341bbe-30d4-4a28-b50a-074be4e98ce6.svg" height = "17"/> | | | |
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| 晶晨 | | | <img src="https://user-images.githubusercontent.com/54695910/212474105-38051192-9a1c-4b24-8ad1-f842fb0bf39d.svg" height = "17"/> | <img src="https://user-images.githubusercontent.com/54695910/212473389-8c341bbe-30d4-4a28-b50a-074be4e98ce6.svg" height = "17"/> | | | |
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| 恩智浦 | | | <img src="https://user-images.githubusercontent.com/54695910/212474105-38051192-9a1c-4b24-8ad1-f842fb0bf39d.svg" height = "17"/> |<img src="https://user-images.githubusercontent.com/54695910/212473389-8c341bbe-30d4-4a28-b50a-074be4e98ce6.svg" height = "17"/> | | | |
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</font>
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## 🔮 文档教程
|
||
- [✴️ Python SDK快速开始](#fastdeploy-quick-start-python)
|
||
- [✴️ C++ SDK快速开始](#fastdeploy-quick-start-cpp)
|
||
- **安装文档**
|
||
- [预编译库下载安装](docs/cn/build_and_install/download_prebuilt_libraries.md)
|
||
- [GPU部署环境编译安装](docs/cn/build_and_install/gpu.md)
|
||
- [CPU部署环境编译安装](docs/cn/build_and_install/cpu.md)
|
||
- [IPU部署环境编译安装](docs/cn/build_and_install/ipu.md)
|
||
- [昆仑芯XPU部署环境编译安装](docs/cn/build_and_install/kunlunxin.md)
|
||
- [瑞芯微RV1126部署环境编译安装](docs/cn/build_and_install/rv1126.md)
|
||
- [瑞芯微RK3588部署环境编译安装](docs/cn/build_and_install/rknpu2.md)
|
||
- [晶晨A311D部署环境编译安装](docs/cn/build_and_install/a311d.md)
|
||
- [华为昇腾部署环境编译安装](docs/cn/build_and_install/huawei_ascend.md)
|
||
- [Jetson部署环境编译安装](docs/cn/build_and_install/jetson.md)
|
||
- [Android平台部署环境编译安装](docs/cn/build_and_install/android.md)
|
||
- **快速使用**
|
||
- [PP-YOLOE Python部署示例](docs/cn/quick_start/models/python.md)
|
||
- [PP-YOLOE C++部署示例](docs/cn/quick_start/models/cpp.md)
|
||
- **不同后端使用**
|
||
- [Runtime Python使用示例](docs/cn/quick_start/runtime/python.md)
|
||
- [Runtime C++使用示例](docs/cn/quick_start/runtime/cpp.md)
|
||
- [如何配置模型部署的推理后端](docs/cn/faq/how_to_change_backend.md)
|
||
- **服务化部署**
|
||
- [服务化部署镜像编译安装](serving/docs/zh_CN/compile.md)
|
||
- [服务化部署](serving)
|
||
- **API文档**
|
||
- [Python API文档](https://www.paddlepaddle.org.cn/fastdeploy-api-doc/python/html/)
|
||
- [C++ API文档](https://www.paddlepaddle.org.cn/fastdeploy-api-doc/cpp/html/)
|
||
- [Android Java API文档](java/android)
|
||
- **性能调优**
|
||
- [量化加速](docs/cn/quantize.md)
|
||
- [多线程多进程使用](/tutorials/multi_thread)
|
||
- **常见问题**
|
||
- [1. Windows上C++ SDK如何使用](docs/cn/faq/use_sdk_on_windows.md)
|
||
- [2. Android上如何使用FastDeploy C++ SDK](docs/cn/faq/use_cpp_sdk_on_android.md)
|
||
- [3. TensorRT使用中的一些技巧](docs/cn/faq/tensorrt_tricks.md)
|
||
- **更多FastDeploy部署模块**
|
||
- [Benchmark测试](benchmark)
|
||
- **模型支持列表**
|
||
- [🖥️ 服务端 模型支持列表](#fastdeploy-server-models)
|
||
- [📳 移动端和端侧 模型支持列表](#fastdeploy-edge-models)
|
||
- [⚛️ Web和小程序 模型支持列表](#fastdeploy-web-models)
|
||
- **💕开发者贡献**
|
||
- [增加新模型](docs/cn/faq/develop_a_new_model.md)
|
||
|
||
|
||
|
||
<div id="fastdeploy-quick-start-python"></div>
|
||
|
||
## 快速开始💨
|
||
|
||
<details Open>
|
||
|
||
<summary><b>Python SDK快速开始（点开收缩）</b></summary><div>
|
||
|
||
### 🎆 快速安装
|
||
|
||
#### 🔸 前置依赖
|
||
|
||
- CUDA >= 11.2、cuDNN >= 8.0、Python >= 3.6
|
||
- OS: Linux x86_64/macOS/Windows 10
|
||
|
||
#### 🔸 安装GPU版本
|
||
|
||
```bash
|
||
pip install numpy opencv-python fastdeploy-gpu-python -f https://www.paddlepaddle.org.cn/whl/fastdeploy.html
|
||
```
|
||
|
||
#### [🔸 Conda安装(推荐✨)](docs/cn/build_and_install/download_prebuilt_libraries.md)
|
||
|
||
```bash
|
||
conda config --add channels conda-forge && conda install cudatoolkit=11.2 cudnn=8.2
|
||
```
|
||
|
||
#### 🔸 安装CPU版本
|
||
|
||
```bash
|
||
pip install numpy opencv-python fastdeploy-python -f https://www.paddlepaddle.org.cn/whl/fastdeploy.html
|
||
```
|
||
|
||
### 🎇 Python 推理示例
|
||
|
||
* 准备模型和图片
|
||
|
||
```bash
|
||
wget https://bj.bcebos.com/paddlehub/fastdeploy/ppyoloe_crn_l_300e_coco.tgz
|
||
tar xvf ppyoloe_crn_l_300e_coco.tgz
|
||
wget https://gitee.com/paddlepaddle/PaddleDetection/raw/release/2.4/demo/000000014439.jpg
|
||
```
|
||
|
||
* 测试推理结果
|
||
|
||
```python
|
||
# GPU/TensorRT部署参考 examples/vision/detection/paddledetection/python
|
||
import cv2
|
||
import fastdeploy.vision as vision
|
||
|
||
model = vision.detection.PPYOLOE("ppyoloe_crn_l_300e_coco/model.pdmodel",
|
||
"ppyoloe_crn_l_300e_coco/model.pdiparams",
|
||
"ppyoloe_crn_l_300e_coco/infer_cfg.yml")
|
||
im = cv2.imread("000000014439.jpg")
|
||
result = model.predict(im)
|
||
print(result)
|
||
|
||
vis_im = vision.vis_detection(im, result, score_threshold=0.5)
|
||
cv2.imwrite("vis_image.jpg", vis_im)
|
||
|
||
```
|
||
|
||
</div></details>
|
||
|
||
<div id="fastdeploy-quick-start-cpp"></div>
|
||
|
||
<details close>
|
||
|
||
<summary><b>C++ SDK快速开始（点开查看详情）</b></summary><div>
|
||
|
||
|
||
### 🎆 安装
|
||
|
||
- 参考[C++预编译库下载](docs/cn/build_and_install/download_prebuilt_libraries.md)文档
|
||
|
||
#### 🎇 C++ 推理示例
|
||
|
||
* 准备模型和图片
|
||
|
||
```bash
|
||
wget https://bj.bcebos.com/paddlehub/fastdeploy/ppyoloe_crn_l_300e_coco.tgz
|
||
tar xvf ppyoloe_crn_l_300e_coco.tgz
|
||
wget https://gitee.com/paddlepaddle/PaddleDetection/raw/release/2.4/demo/000000014439.jpg
|
||
```
|
||
|
||
* 测试推理结果
|
||
|
||
```C++
|
||
// GPU/TensorRT部署参考 examples/vision/detection/paddledetection/cpp
|
||
#include "fastdeploy/vision.h"
|
||
|
||
int main(int argc, char* argv[]) {
|
||
namespace vision = fastdeploy::vision;
|
||
auto model = vision::detection::PPYOLOE("ppyoloe_crn_l_300e_coco/model.pdmodel",
|
||
"ppyoloe_crn_l_300e_coco/model.pdiparams",
|
||
"ppyoloe_crn_l_300e_coco/infer_cfg.yml");
|
||
auto im = cv::imread("000000014439.jpg");
|
||
|
||
vision::DetectionResult res;
|
||
model.Predict(im, &res);
|
||
|
||
auto vis_im = vision::VisDetection(im, res, 0.5);
|
||
cv::imwrite("vis_image.jpg", vis_im);
|
||
return 0;
|
||
}
|
||
```
|
||
|
||
</div></details>
|
||
|
||
更多部署案例请参考[模型部署示例](examples) .
|
||
|
||
|
||
<div id="fastdeploy-server-models"></div>
|
||
|
||
|
||
## ✴️ ✴️ 服务端模型支持列表 ✴️ ✴️
|
||
|
||
符号说明: (1) ✅ : 已经支持; (2) ❔: 正在进行中; (3) N/A : 暂不支持. <br>
|
||
|
||
<details open><summary><b> 服务端模型支持列表（点击可收缩）</b></summary><div>
|
||
|
||
<div align="center">
|
||
<img src="https://user-images.githubusercontent.com/115439700/212800663-894e9a7a-6d68-4b0b-bcd2-045732d08887.png" height ="40"/>
|
||
</div>
|
||
|
||
| 任务场景 | 模型 | Linux | Linux | Win | Win | Mac | Mac | Linux | Linux | Linux | Linux | Linux | Linux | Linux |
|
||
|:----------------------:|:--------------------------------------------------------------------------------------------:|:------------------------------------------------:|:----------:|:-------:|:----------:|:-------:|:-------:|:-----------:|:---------------:|:-------------:|:-------------:|:-------:|:-------:|:-------:|
|
||
| --- | --- | X86 CPU | NVIDIA GPU | X86 CPU | NVIDIA GPU | X86 CPU | Arm CPU | AArch64 CPU | 飞腾D2000 aarch64 | [NVIDIA Jetson](./docs/cn/build_and_install/jetson.md) | [Graphcore IPU](./docs/cn/build_and_install/ipu.md) | [昆仑芯 XPU](./docs/cn/build_and_install/kunlunxin.md) |[华为 昇腾](./docs/cn/build_and_install/huawei_ascend.md) | [Serving](./serving) |
|
||
| Classification | [PaddleClas/ResNet50](./examples/vision/classification/paddleclas) | [✅](./examples/vision/classification/paddleclas) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |✅ |
|
||
| Classification | [TorchVison/ResNet](examples/vision/classification/resnet) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ |✅ | ❔ |
|
||
| Classification | [ultralytics/YOLOv5Cls](examples/vision/classification/yolov5cls) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ |❔ |
|
||
| Classification | [PaddleClas/PP-LCNet](./examples/vision/classification/paddleclas) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |✅ | ✅ |
|
||
| Classification | [PaddleClas/PP-LCNetv2](./examples/vision/classification/paddleclas) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |✅ | ✅ |
|
||
| Classification | [PaddleClas/EfficientNet](./examples/vision/classification/paddleclas) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |✅ | ✅ |
|
||
| Classification | [PaddleClas/GhostNet](./examples/vision/classification/paddleclas) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |✅ | ✅ |
|
||
| Classification | [PaddleClas/MobileNetV1](./examples/vision/classification/paddleclas) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |✅ | ✅ |
|
||
| Classification | [PaddleClas/MobileNetV2](./examples/vision/classification/paddleclas) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |✅ | ✅ |
|
||
| Classification | [PaddleClas/MobileNetV3](./examples/vision/classification/paddleclas) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |✅ | ✅ |
|
||
| Classification | [PaddleClas/ShuffleNetV2](./examples/vision/classification/paddleclas) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |✅ | ✅ |
|
||
| Classification | [PaddleClas/SqueeezeNetV1.1](./examples/vision/classification/paddleclas) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |✅ | ✅ |
|
||
| Classification | [PaddleClas/Inceptionv3](./examples/vision/classification/paddleclas) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ |✅ | ✅ |
|
||
| Classification | [PaddleClas/PP-HGNet](./examples/vision/classification/paddleclas) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |✅ | ✅ |
|
||
| Detection | 🔥🔥[PaddleDetection/PP-YOLOE+](./examples/vision/detection/paddledetection) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ |✅ | ✅ |
|
||
| Detection | [🔥PaddleDetection/YOLOv8](./examples/vision/detection/paddledetection) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ |✅ | ❔ |
|
||
| Detection | [🔥ultralytics/YOLOv8](./examples/vision/detection/yolov8) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ |❔ | ❔ |
|
||
| Detection | [PaddleDetection/PicoDet](./examples/vision/detection/paddledetection) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ✅ |
|
||
| Detection | [PaddleDetection/YOLOX](./examples/vision/detection/paddledetection) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ✅ | ✅ |
|
||
| Detection | [PaddleDetection/YOLOv3](./examples/vision/detection/paddledetection) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ✅ | ✅ |
|
||
| Detection | [PaddleDetection/PP-YOLO](./examples/vision/detection/paddledetection) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ✅ | ✅ |
|
||
| Detection | [PaddleDetection/PP-YOLOv2](./examples/vision/detection/paddledetection) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ✅ | ✅ |
|
||
| Detection | [PaddleDetection/Faster-RCNN](./examples/vision/detection/paddledetection) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ |❔ | ✅ |
|
||
| Detection | [PaddleDetection/Mask-RCNN](./examples/vision/detection/paddledetection) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ |❔ | ✅ |
|
||
| Detection | [Megvii-BaseDetection/YOLOX](./examples/vision/detection/yolox) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ |✅ | ❔ |
|
||
| Detection | [WongKinYiu/YOLOv7](./examples/vision/detection/yolov7) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ |✅ | ❔ |
|
||
| Detection | [WongKinYiu/YOLOv7end2end_trt](./examples/vision/detection/yolov7end2end_trt) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ |❔ | ❔ |
|
||
| Detection | [WongKinYiu/YOLOv7end2end_ort](./examples/vision/detection/yolov7end2end_ort) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |❔ | ❔ |
|
||
| Detection | [meituan/YOLOv6](./examples/vision/detection/yolov6) | ✅ | ✅ | ✅ |✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ |
|
||
| Detection | [ultralytics/YOLOv5](./examples/vision/detection/yolov5) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ✅ |✅ |
|
||
| Detection | [WongKinYiu/YOLOR](./examples/vision/detection/yolor) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ | ✅ | ❔ |
|
||
| Detection | [WongKinYiu/ScaledYOLOv4](./examples/vision/detection/scaledyolov4) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |❔ | ❔ |
|
||
| Detection | [ppogg/YOLOv5Lite](./examples/vision/detection/yolov5lite) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ? | ❔ |❔ |❔ |
|
||
| Detection | [RangiLyu/NanoDetPlus](./examples/vision/detection/nanodet_plus) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |❔ | ❔ |
|
||
| Perception | [Paddle3D/Smoke](./examples/vision/perception/paddle3d/smoke) | ❔ | ✅ | ❔ | ✅ | ❔ | ❔ | ❔ | ❔ | ❔ | ❔ | ❔ |❔ | ✅ |
|
||
| KeyPoint | [PaddleDetection/TinyPose](./examples/vision/keypointdetection/tiny_pose) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ |❔ | ❔ |
|
||
| KeyPoint | [PaddleDetection/PicoDet + TinyPose](./examples/vision/keypointdetection/det_keypoint_unite) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ |❔ |
|
||
| HeadPose | [omasaht/headpose](examples/vision/headpose) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ | ❔ |❔ |
|
||
| Tracking | [PaddleDetection/PP-Tracking](examples/vision/tracking/pptracking) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ | ❔ |❔ |
|
||
| OCR | [PaddleOCR/PP-OCRv2](./examples/vision/ocr) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ✅ |✅ | ❔ |
|
||
| OCR | [PaddleOCR/PP-OCRv3](./examples/vision/ocr) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ |✅ | ✅ |
|
||
| Segmentation | [PaddleSeg/PP-LiteSeg](./examples/vision/segmentation/paddleseg) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ✅ |❔ | ❔ |
|
||
| Segmentation | [PaddleSeg/PP-HumanSegLite](./examples/vision/segmentation/paddleseg) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ✅ |✅ | ❔ |
|
||
| Segmentation | [PaddleSeg/HRNet](./examples/vision/segmentation/paddleseg) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ✅ | ✅ |❔ |
|
||
| Segmentation | [PaddleSeg/PP-HumanSegServer](./examples/vision/segmentation/paddleseg) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ✅ | ✅ |❔ |
|
||
| Segmentation | [PaddleSeg/Unet](./examples/vision/segmentation/paddleseg) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ✅ | ✅ | ✅ |❔ |
|
||
| Segmentation | [PaddleSeg/Deeplabv3](./examples/vision/segmentation/paddleseg) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ✅ | ✅ |❔ |
|
||
| FaceDetection | [biubug6/RetinaFace](./examples/vision/facedet/retinaface) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ | ❔ | ❔ |
|
||
| FaceDetection | [Linzaer/UltraFace](./examples/vision/facedet/ultraface) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ | ❔ |❔ |
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| FaceDetection | [deepcam-cn/YOLOv5Face](./examples/vision/facedet/yolov5face) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ | ❔ |❔ |
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| FaceDetection | [insightface/SCRFD](./examples/vision/facedet/scrfd) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ | ❔ |❔ |
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| FaceAlign | [Hsintao/PFLD](examples/vision/facealign/pfld) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ | ❔ |❔ |
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| FaceAlign | [Single430/FaceLandmark1000](./examples/vision/facealign/face_landmark_1000) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ | ❔ | ❔ |
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| FaceAlign | [jhb86253817/PIPNet](./examples/vision/facealign) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ | ❔ |❔ |
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| FaceRecognition | [insightface/ArcFace](./examples/vision/faceid/insightface) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ | ❔ |❔ |
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| FaceRecognition | [insightface/CosFace](./examples/vision/faceid/insightface) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ | ❔ |❔ |
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| FaceRecognition | [insightface/PartialFC](./examples/vision/faceid/insightface) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ | ❔ | ❔ |
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| FaceRecognition | [insightface/VPL](./examples/vision/faceid/insightface) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ | ❔ | ❔ |
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| Matting | [ZHKKKe/MODNet](./examples/vision/matting/modnet) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ | ❔ |❔ |
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| Matting | [PeterL1n/RobustVideoMatting]() | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ | ❔ | ❔ |
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| Matting | [PaddleSeg/PP-Matting](./examples/vision/matting/ppmatting) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ |✅ | ❔ |
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| Matting | [PaddleSeg/PP-HumanMatting](./examples/vision/matting/modnet) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ |✅ |❔ |
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| Matting | [PaddleSeg/ModNet](./examples/vision/matting/modnet) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |❔ | ❔ |
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| Video Super-Resolution | [PaddleGAN/BasicVSR](./) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ | ❔ |❔ |
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| Video Super-Resolution | [PaddleGAN/EDVR](./examples/vision/sr/edvr) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ |❔ | ❔ |
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| Video Super-Resolution | [PaddleGAN/PP-MSVSR](./examples/vision/sr/ppmsvsr) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ |❔ | ❔ |
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| Information Extraction | [PaddleNLP/UIE](./examples/text/uie) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ |❔ | |
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| NLP | [PaddleNLP/ERNIE-3.0](./examples/text/ernie-3.0) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ | ❔ | ✅ |❔ | ✅ |
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| Speech | [PaddleSpeech/PP-TTS](./examples/audio/pp-tts) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ | -- |❔ |❔ | ✅ |
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</div></details>
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||
|
||
<div id="fastdeploy-edge-models"></div>
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|
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## 📳 移动端和端侧 模型支持列表
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|
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<details open><summary><b> 端侧模型支持列表（点击可收缩）</b></summary><div>
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|
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<div align="center">
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<img src="https://user-images.githubusercontent.com/115439700/212800663-894e9a7a-6d68-4b0b-bcd2-045732d08887.png" height ="40"/>
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</div>
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|
||
| 任务场景 | 模型 | 大小(MB) | Linux | Android | Linux | Linux | Linux | Linux | Linux | 更新中... |
|
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|:------------------:|:-----------------------------------------------------------------------------------------:|:--------:|:-------:|:-------:|:-------:|:-----------------------:|:------------------------------:|:---------------------------:|:--------------------------------:|:-------:|
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| --- | --- | --- | ARM CPU | [ARM CPU](./java/android) | [瑞芯微NPU<br>RK3588/RK3568/RK3566](./docs/cn/build_and_install/rknpu2.md) | [瑞芯微NPU<br>RV1109/RV1126/RK1808](./docs/cn/build_and_install/rv1126.md) | [晶晨NPU <br>A311D/S905D/C308X](./docs/cn/build_and_install/a311d.md) | 恩智浦NPU<br>i.MX 8M Plus | 更新中... |
|
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| Classification | [PaddleClas/ResNet50](examples/vision/classification/paddleclas) | 98 | ✅ | ✅ | [✅](./examples/vision/classification/paddleclas/rknpu2) | ✅ | | | |
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| Classification | [PaddleClas/PP-LCNet](examples/vision/classification/paddleclas) | 11.9 | ✅ | ✅ | ❔ | ✅ | -- | -- | -- |
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| Classification | [PaddleClas/PP-LCNetv2](examples/vision/classification/paddleclas) | 26.6 | ✅ | ✅ | ❔ | ✅ | -- | -- | -- |
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| Classification | [PaddleClas/EfficientNet](examples/vision/classification/paddleclas) | 31.4 | ✅ | ✅ | ❔ | ✅ | -- | -- | -- |
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| Classification | [PaddleClas/GhostNet](examples/vision/classification/paddleclas) | 20.8 | ✅ | ✅ | ❔ | ✅ | -- | -- | -- |
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| Classification | [PaddleClas/MobileNetV1](examples/vision/classification/paddleclas) | 17 | ✅ | ✅ | ❔ | ✅ | -- | -- | -- |
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| Classification | [PaddleClas/MobileNetV2](examples/vision/classification/paddleclas) | 14.2 | ✅ | ✅ | ❔ | ✅ | -- | -- | -- |
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| Classification | [PaddleClas/MobileNetV3](examples/vision/classification/paddleclas) | 22 | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ | -- |
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| Classification | [PaddleClas/ShuffleNetV2](examples/vision/classification/paddleclas) | 9.2 | ✅ | ✅ | ❔ | ✅ | -- | -- | -- |
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| Classification | [PaddleClas/SqueezeNetV1.1](examples/vision/classification/paddleclas) | 5 | ✅ | ✅ | ❔ | ✅ | -- | -- | -- |
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| Classification | [PaddleClas/Inceptionv3](examples/vision/classification/paddleclas) | 95.5 | ✅ | ✅ | ❔ | ✅ | -- | -- | -- |
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| Classification | [PaddleClas/PP-HGNet](examples/vision/classification/paddleclas) | 59 | ✅ | ✅ | ❔ | ✅ | -- | -- | -- |
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| Detection | [PaddleDetection/PicoDet_s](examples/vision/detection/paddledetection) | 4.9 | ✅ | ✅ | [✅](./examples/vision/detection/paddledetection/rknpu2) | ✅ | ✅ | ✅ | -- |
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| Detection | [YOLOv5](./examples/vision/detection/rkyolo) | | ❔ | ❔ | [✅](./examples/vision/detection/rkyolo) | ❔ | ❔ | ❔ | -- |
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| Face Detection | [deepinsight/SCRFD](./examples/vision/facedet/scrfd) | 2.5 | ✅ | ✅ | [✅](./examples/vision/facedet/scrfd/rknpu2) | -- | -- | -- | -- |
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| Keypoint Detection | [PaddleDetection/PP-TinyPose](examples/vision/keypointdetection/tiny_pose) | 5.5 | ✅ | ✅ | ❔ | ❔ | ❔ | ❔ | -- |
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| Segmentation | [PaddleSeg/PP-LiteSeg(STDC1)](examples/vision/segmentation/paddleseg) | 32.2 | ✅ | ✅ | [✅](./examples/vision/segmentation/paddleseg/rknpu2) | -- | -- | -- | -- |
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| Segmentation | [PaddleSeg/PP-HumanSeg-Lite](examples/vision/segmentation/paddleseg) | 0.556 | ✅ | ✅ | [✅](./examples/vision/segmentation/paddleseg/rknpu2) | -- | -- | -- | -- |
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| Segmentation | [PaddleSeg/HRNet-w18](examples/vision/segmentation/paddleseg) | 38.7 | ✅ | ✅ | [✅](./examples/vision/segmentation/paddleseg/rknpu2) | -- | -- | -- | -- |
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| Segmentation | [PaddleSeg/PP-HumanSeg](examples/vision/segmentation/paddleseg) | 107.2 | ✅ | ✅ | [✅](./examples/vision/segmentation/paddleseg/rknpu2) | -- | -- | -- | -- |
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| Segmentation | [PaddleSeg/Unet](examples/vision/segmentation/paddleseg) | 53.7 | ✅ | ✅ | [✅](./examples/vision/segmentation/paddleseg/rknpu2) | -- | -- | -- | -- |
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| Segmentation | [PaddleSeg/Deeplabv3](examples/vision/segmentation/paddleseg) | 150 | ❔ | ✅ | [✅](./examples/vision/segmentation/paddleseg/rknpu2) | | | | |
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| OCR | [PaddleOCR/PP-OCRv2](examples/vision/ocr/PP-OCRv2) | 2.3+4.4 | ✅ | ✅ | ❔ | -- | -- | -- | -- |
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| OCR | [PaddleOCR/PP-OCRv3](examples/vision/ocr/PP-OCRv3) | 2.4+10.6 | ✅ | ❔ | ❔ | ❔ | ❔ | ❔ | -- |
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||
|
||
</div></details>
|
||
|
||
## ⚛️ Web和小程序 模型支持列表
|
||
|
||
<div id="fastdeploy-web-models"></div>
|
||
|
||
<details open><summary><b> Web和小程序部署支持列表（点击可收缩）</b></summary><div>
|
||
|
||
| 任务场景 | 模型 | [web_demo](examples/application/js/web_demo) |
|
||
|:------------------:|:-------------------------------------------------------------------------------------------:|:--------------------------------------------:|
|
||
| --- | --- | [Paddle.js](examples/application/js) |
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| Detection | [FaceDetection](examples/application/js/web_demo/src/pages/cv/detection) | ✅ |
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| Detection | [ScrewDetection](examples/application/js/web_demo/src/pages/cv/detection) | ✅ |
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| Segmentation | [PaddleSeg/HumanSeg](./examples/application/js/web_demo/src/pages/cv/segmentation/HumanSeg) | ✅ |
|
||
| Object Recognition | [GestureRecognition](examples/application/js/web_demo/src/pages/cv/recognition) | ✅ |
|
||
| Object Recognition | [ItemIdentification](examples/application/js/web_demo/src/pages/cv/recognition) | ✅ |
|
||
| OCR | [PaddleOCR/PP-OCRv3](./examples/application/js/web_demo/src/pages/cv/ocr) | ✅ |
|
||
|
||
</div></details>
|
||
|
||
|
||
## 💐 Acknowledge
|
||
|
||
本项目中SDK生成和下载使用了[EasyEdge](https://ai.baidu.com/easyedge/app/openSource)中的免费开放能力，在此表示感谢。
|
||
|
||
## ©️ License
|
||
|
||
<div id="fastdeploy-license"></div>
|
||
|
||
FastDeploy遵循[Apache-2.0开源协议](./LICENSE)。
|