⚡️FastDeploy是一款全场景、易用灵活、极致高效的AI推理部署工具。提供📦开箱即用的云边端部署体验, 支持超过 🔥150+ Text, Vision, Speech和跨模态模型，并实现🔚端到端的推理性能优化。包括图像分类、物体检测、图像分割、人脸检测、人脸识别、关键点检测、抠图、OCR、NLP、TTS等任务，满足开发者多场景、多硬件、多平台的产业部署需求。

Image Classification	Object Detection	Semantic Segmentation	Potrait Segmentation

Image Matting	Real-Time Matting	OCR	Face Alignment

Pose Estimation	Behavior Recognition	NLP	Speech
			input ：早上好今天是2020 /10/29，最低温度是-3°C。 output:

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🖥️ 服务端部署

Python SDK快速开始（点开查看详情）

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

pip install numpy opencv-python fastdeploy-gpu-python -f https://www.paddlepaddle.org.cn/whl/fastdeploy.html

Conda安装(推荐)

conda config --add channels conda-forge && conda install cudatoolkit=11.2 cudnn=8.2

安装CPU版本

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

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

# 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)

C++ SDK快速开始（点开查看详情）

安装

参考C++预编译库下载文档

C++ 推理示例

准备模型和图片

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

// 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;
}

更多部署案例请参考模型部署示例 .

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;

服务端模型支持列表（点击可收缩）

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	Graphcore IPU	昆仑芯 XPU	华为昇腾	Serving
Classification	PaddleClas/ResNet50	✅	✅	✅	✅	✅	✅	✅	✅	✅	✅	✅	✅	✅
Classification	TorchVison/ResNet	✅	✅	✅	✅	✅	✅	✅	✅	✅	❔	✅	✅	❔
Classification	ltralytics/YOLOv5Cls	✅	✅	✅	✅	✅	✅	✅	✅	✅	❔	✅	❔	❔
Classification	PaddleClas/PP-LCNet	✅	✅	✅	✅	✅	✅	✅	✅	✅	✅	✅	✅	✅
Classification	PaddleClas/PP-LCNetv2	✅	✅	✅	✅	✅	✅	✅	✅	✅	✅	✅	✅	✅
Classification	PaddleClas/EfficientNet	✅	✅	✅	✅	✅	✅	✅	✅	✅	✅	✅	✅	✅
Classification	PaddleClas/GhostNet	✅	✅	✅	✅	✅	✅	✅	✅	✅	✅	✅	✅	✅
Classification	PaddleClas/MobileNetV1	✅	✅	✅	✅	✅	✅	✅	✅	✅	✅	✅	✅	✅
Classification	PaddleClas/MobileNetV2	✅	✅	✅	✅	✅	✅	✅	✅	✅	✅	✅	✅	✅
Classification	PaddleClas/MobileNetV3	✅	✅	✅	✅	✅	✅	✅	✅	✅	✅	✅	✅	✅
Classification	PaddleClas/ShuffleNetV2	✅	✅	✅	✅	✅	✅	✅	✅	✅	✅	✅	✅	✅
Classification	PaddleClas/SqueeezeNetV1.1	✅	✅	✅	✅	✅	✅	✅	✅	✅	✅	✅	✅	✅
Classification	PaddleClas/Inceptionv3	✅	✅	✅	✅	✅	✅	✅	✅	✅	❔	✅	✅	✅
Classification	PaddleClas/PP-HGNet	✅	✅	✅	✅	✅	✅	✅	✅	✅	✅	✅	✅	✅
Detection	PaddleDetection/PP-YOLOE	✅	✅	✅	✅	✅	✅	✅	✅	✅	❔	✅	✅	✅
Detection	PaddleDetection/PicoDet	✅	✅	✅	✅	✅	✅	✅	✅	✅	❔	✅	❔	✅
Detection	PaddleDetection/YOLOX	✅	✅	✅	✅	✅	✅	✅	✅	✅	❔	✅	✅	✅
Detection	PaddleDetection/YOLOv3	✅	✅	✅	✅	✅	✅	✅	✅	✅	❔	✅	✅	✅
Detection	PaddleDetection/PP-YOLO	✅	✅	✅	✅	✅	✅	✅	✅	✅	❔	✅	✅	✅
Detection	PaddleDetection/PP-YOLOv2	✅	✅	✅	✅	✅	✅	✅	✅	✅	❔	✅	✅	✅
Detection	PaddleDetection/Faster-RCNN	✅	✅	✅	✅	✅	✅	✅	✅	✅	❔	✅	❔	✅
Detection	PaddleDetection/Mask-RCNN	✅	✅	✅	✅	✅	✅	✅	✅	✅	❔	✅	❔	✅
Detection	Megvii-BaseDetection/YOLOX	✅	✅	✅	✅	✅	✅	✅	✅	✅	❔	✅	✅	❔
Detection	WongKinYiu/YOLOv7	✅	✅	✅	✅	✅	✅	✅	✅	✅	❔	✅	✅	❔
Detection	WongKinYiu/YOLOv7end2end_trt	✅	✅	✅	✅	✅	✅	✅	❔	✅	❔	❔	❔	❔
Detection	WongKinYiu/YOLOv7end2end_ort_	✅	✅	✅	✅	✅	✅	✅	✅	✅	❔	❔	❔	❔
Detection	meituan/YOLOv6	✅	✅	✅	✅	✅	✅	✅	✅	✅	✅	❔	✅	❔
Detection	ultralytics/YOLOv5	✅	✅	✅	✅	✅	✅	✅	✅	✅	❔	✅	✅	✅
Detection	WongKinYiu/YOLOR	✅	✅	✅	✅	✅	✅	✅	❔	✅	❔	❔	✅	❔
Detection	WongKinYiu/ScaledYOLOv4	✅	✅	✅	✅	✅	✅	✅	✅	✅	❔	❔	❔	❔
Detection	ppogg/YOLOv5Lite	✅	✅	✅	✅	✅	✅	✅	✅	✅	?	❔	❔	❔
Detection	RangiLyu/NanoDetPlus	✅	✅	✅	✅	✅	✅	✅	✅	✅	❔	❔	❔	❔
KeyPoint	PaddleDetection/TinyPose	✅	✅	✅	✅	✅	✅	✅	✅	✅	❔	✅	❔	❔
KeyPoint	PaddleDetection/PicoDet + TinyPose	✅	✅	✅	✅	✅	✅	✅	✅	✅	❔	✅	❔	❔
HeadPose	omasaht/headpose	✅	✅	✅	✅	✅	✅	✅	❔	✅	❔	❔	❔	❔
Tracking	PaddleDetection/PP-Tracking	✅	✅	✅	✅	✅	✅	✅	✅	✅	❔	❔	❔	❔
OCR	PaddleOCR/PP-OCRv2	✅	✅	✅	✅	✅	✅	✅	❔	✅	❔	✅	✅	❔
OCR	PaddleOCR/PP-OCRv3	✅	✅	✅	✅	✅	✅	✅	✅	✅	❔	✅	✅	✅
Segmentation	PaddleSeg/PP-LiteSeg	✅	✅	✅	✅	✅	✅	✅	❔	✅	❔	✅	❔	❔
Segmentation	PaddleSeg/PP-HumanSegLite	✅	✅	✅	✅	✅	✅	✅	❔	✅	❔	✅	✅	❔
Segmentation	PaddleSeg/HRNet	✅	✅	✅	✅	✅	✅	✅	❔	✅	❔	✅	✅	❔
Segmentation	PaddleSeg/PP-HumanSegServer	✅	✅	✅	✅	✅	✅	✅	❔	✅	❔	✅	✅	❔
Segmentation	PaddleSeg/Unet	✅	✅	✅	✅	✅	✅	✅	❔	✅	✅	✅	✅	❔
Segmentation	PaddleSeg/Deeplabv3	✅	✅	✅	✅	✅	✅	✅	❔	✅	❔	✅	✅	❔
FaceDetection	biubug6/RetinaFace	✅	✅	✅	✅	✅	✅	✅	✅	✅	❔	❔	❔	❔
FaceDetection	Linzaer/UltraFace	✅	✅	✅	✅	✅	✅	✅	✅	✅	❔	❔	❔	❔
FaceDetection	deepcam-cn/YOLOv5Face	✅	✅	✅	✅	✅	✅	✅	✅	✅	❔	❔	❔	❔
FaceDetection	insightface/SCRFD	✅	✅	✅	✅	✅	✅	✅	✅	✅	❔	❔	❔	❔
FaceAlign	Hsintao/PFLD	✅	✅	✅	✅	✅	✅	✅	✅	✅	❔	❔	❔	❔
FaceAlign	Single430/FaceLandmark1000	✅	✅	✅	✅	✅	✅	✅	❔	✅	❔	❔	❔	❔
FaceAlign	jhb86253817/PIPNet	✅	✅	✅	✅	✅	✅	✅	❔	✅	❔	❔	❔	❔
FaceRecognition	insightface/ArcFace	✅	✅	✅	✅	✅	✅	✅	✅	✅	❔	❔	❔	❔
FaceRecognition	insightface/CosFace	✅	✅	✅	✅	✅	✅	✅	✅	✅	❔	❔	❔	❔
FaceRecognition	insightface/PartialFC	✅	✅	✅	✅	✅	✅	✅	✅	✅	❔	❔	❔	❔
FaceRecognition	insightface/VPL	✅	✅	✅	✅	✅	✅	✅	✅	✅	❔	❔	❔	❔
Matting	ZHKKKe/MODNet	✅	✅	✅	✅	✅	✅	✅	❔	✅	❔	❔	❔	❔
Matting	PeterL1n/RobustVideoMatting	✅	✅	✅	✅	✅	✅	✅	❔	✅	❔	❔	❔	❔
Matting	PaddleSeg/PP-Matting	✅	✅	✅	✅	✅	✅	✅	✅	✅	❔	✅	✅	❔
Matting	PaddleSeg/PP-HumanMatting	✅	✅	✅	✅	✅	✅	✅	✅	✅	❔	✅	✅	❔
Matting	PaddleSeg/ModNet	✅	✅	✅	✅	✅	✅	✅	✅	✅	❔	❔	❔	❔
Video Super-Resolution	PaddleGAN/BasicVSR	✅	✅	✅	✅	✅	✅	✅	❔	✅	❔	❔	❔	❔
Video Super-Resolution	PaddleGAN/EDVR	✅	✅	✅	✅	✅	✅	✅	❔	✅	❔	❔	❔	❔
Video Super-Resolution	PaddleGAN/PP-MSVSR	✅	✅	✅	✅	✅	✅	✅	❔	✅	❔	❔	❔	❔
Information Extraction	PaddleNLP/UIE	✅	✅	✅	✅	✅	✅	✅	❔	✅	❔	❔	❔
NLP	PaddleNLP/ERNIE-3.0	✅	✅	✅	✅	✅	✅	✅	❔	❔	❔	✅	❔	✅
Speech	PaddleSpeech/PP-TTS	✅	✅	✅	✅	✅	✅	✅	❔	❔	--	❔	❔	✅

📲 移动端和端侧部署 🔥🔥🔥🔥

端侧模型支持列表

端侧模型支持列表（点击可收缩）

任务场景	模型	大小(MB)	Linux	Android	Linux	Linux	Linux	Linux	Linux
---	---	---	ARM CPU	ARM CPU	瑞芯微NPU RK3568/RK3588	瑞芯微NPU RV1109/RV1126/RK1808	晶晨NPU A311D/S905D/C308X	恩智浦NPU i.MX 8M Plus	更新中...｜
Classification	PaddleClas/ResNet50	98	✅	✅	✅	✅
Classification	PaddleClas/PP-LCNet	11.9	✅	✅	❔	✅	--	--	--
Classification	PaddleClas/PP-LCNetv2	26.6	✅	✅	❔	✅	--	--	--
Classification	PaddleClas/EfficientNet	31.4	✅	✅	❔	✅	--	--	--
Classification	PaddleClas/GhostNet	20.8	✅	✅	❔	✅	--	--	--
Classification	PaddleClas/MobileNetV1	17	✅	✅	❔	✅	--	--	--
Classification	PaddleClas/MobileNetV2	14.2	✅	✅	❔	✅	--	--	--
Classification	PaddleClas/MobileNetV3	22	✅	✅	❔	✅	❔	❔	--
Classification	PaddleClas/ShuffleNetV2	9.2	✅	✅	❔	✅	--	--	--
Classification	PaddleClas/SqueezeNetV1.1	5	✅	✅	❔	✅	--	--	--
Classification	PaddleClas/Inceptionv3	95.5	✅	✅	❔	✅	--	--	--
Classification	PaddleClas/PP-HGNet	59	✅	✅	❔	✅	--	--	--
Detection	PaddleDetection/PicoDet_s	4.9	✅	✅	✅	✅	✅	✅	--
Detection	YOLOv5		❔	❔	✅	❔	❔	❔	--
Face Detection	deepinsight/SCRFD	2.5	✅	✅	✅	--	--	--	--
Keypoint Detection	PaddleDetection/PP-TinyPose	5.5	✅	✅	❔	❔	❔	❔	--
Segmentation	PaddleSeg/PP-LiteSeg(STDC1)	32.2	✅	✅	✅	--	--	--	--
Segmentation	PaddleSeg/PP-HumanSeg-Lite	0.556	✅	✅	✅	--	--	--	--
Segmentation	PaddleSeg/HRNet-w18	38.7	✅	✅	✅	--	--	--	--
Segmentation	PaddleSeg/PP-HumanSeg	107.2	✅	✅	✅	--	--	--	--
Segmentation	PaddleSeg/Unet	53.7	✅	✅	✅	--	--	--	--
Segmentation	PaddleSeg/Deeplabv3	150	❔	✅	✅
OCR	PaddleOCR/PP-OCRv2	2.3+4.4	✅	✅	❔	--	--	--	--
OCR	PaddleOCR/PP-OCRv3	2.4+10.6	✅	❔	❔	❔	❔	❔	--

🌐 Web和小程序部署

Web和小程序部署支持列表（点击可收缩）

任务场景	模型	web_demo
---	---	Paddle.js
Detection	FaceDetection	✅
Detection	ScrewDetection	✅
Segmentation	PaddleSeg/HumanSeg	✅
Object Recognition	GestureRecognition	✅
Object Recognition	ItemIdentification	✅
OCR	PaddleOCR/PP-OCRv3	✅

社区交流

Slack：Join our Slack community and chat with other community members about ideas
微信：扫描二维码，填写问卷加入技术社区，与社区开发者探讨部署的痛点与方案

Acknowledge

本项目中SDK生成和下载使用了EasyEdge中的免费开放能力，在此表示感谢。

License

FastDeploy遵循Apache-2.0开源协议。

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README_CN.md

README_CN.md

📣 最新消息

目录

🖥️ 服务端部署

快速安装

前置依赖

安装GPU版本

Conda安装(推荐)

安装CPU版本

Python 推理示例

安装

C++ 推理示例

服务端模型支持列表 🔥🔥🔥🔥🔥

📲 移动端和端侧部署 🔥🔥🔥🔥

端侧模型支持列表

🌐 Web和小程序部署

社区交流

Acknowledge

License

Files

README_CN.md

Latest commit

History

README_CN.md

File metadata and controls

📣 最新消息

目录

🖥️ 服务端部署

快速安装

前置依赖

安装GPU版本

Conda安装(推荐)

安装CPU版本

Python 推理示例

安装

C++ 推理示例

服务端模型支持列表 🔥🔥🔥🔥🔥

📲 移动端和端侧部署 🔥🔥🔥🔥

端侧模型支持列表

🌐 Web和小程序部署

社区交流

Acknowledge

License