English | 简体中文

Installation | Documents | API Docs | Release Notes

⚡️FastDeploy is an Easy-to-use and High Performance AI model deployment toolkit for Cloud, Mobile and Edge with 📦out-of-the-box and unified experience, 🔚end-to-end optimization for over 🔥150+ Text, Vision, Speech and Cross-modal AI models. Including image classification, object detection, image segmentation, face detection, face recognition, keypoint detection, matting, OCR, NLP, TTS and other tasks to meet developers' industrial deployment needs for multi-scenario, multi-hardware and multi-platform.

Image Classification	Object Detection	Semantic Segmentation	Potrait Segmentation
Image Matting	Real-Time Matting	OCR	Face Alignment
Pose Estimation	Behavior Recognition	NLP	Speech
			input:Life was like a box of chocolates, you never know what you're gonna get. output:

📣 Recent Updates

• Community

  • Slack：Join our Slack community and chat with other community members about ideas.

  • WeChat：Scan the QR code below using WeChat, follow the PaddlePaddle official account and fill out the questionnaire to join the WeChat group.

    

• 🔥 2022.11.23：Release FastDeploy release v0.8.0
  

  • 🖥️ Server-side and Cloud Deployment: Support more CV models, improve deployment performance

    • Support PIPNet, FaceLandmark1000 face alignment models deployment;
    • Support Video Super-Resolution series model PP-MSVSR、EDVR、BasicVSR;
    • Upgrade YOLOv7 deployment code to add batch_predict deployment;
    • Support UIE service-based deployment;
    • Add Python API to_dlpack interface for FDTensor to support copyless transfer of FDTensor between frameworks.

  • 📱 Mobile and Edge Device Deployment: support more CV model

    • Support Android image classification, target detection, semantic segmentation, OCR, face detection APK projects and examples.

    Image Classification	Object Detection	Semantic Segmentation	OCR	Face Detection
    Project Code	Project Code	Project Code	Project Code	Project Code
    Scan the code or click on the link to install	Scan the code or click on the link to install	Scan the code or click on the link to install	Scan the code or click on the link to install	Scan the code or click on the link to install

• more releases information

Contents

• 📖 Tutorials（click to fold）

  • Install

    • How to Install FastDeploy Prebuilt Libraries
    • How to Build and Install FastDeploy Library on GPU Platform
    • How to Build and Install FastDeploy Library on CPU Platform
    • How to Build and Install FastDeploy Library on IPU Platform
    • How to Build and Install FastDeploy Library on Nvidia Jetson Platform
    • How to Build and Install FastDeploy Library on Android Platform
    • How to Install FastDeploy Images on Serving Deployment

  • A Quick Start - Demos

    • Python Deployment Demo
    • C++ Deployment Demo
    • A Quick Start on Runtime Python
    • A Quick Start on Runtime C++

  • API (To be continued)

    • Python API
    • C++ API

  • Performance Optimization

    • Quantization Acceleration

  • Frequent Q&As

    • 1. How to Change Inference Backends
    • 2. How to Use FastDeploy C++ SDK on Windows Platform
    • 3. How to Use FastDeploy C++ SDK on Android Platform(To be Continued)
    • 4. Tricks of TensorRT
    • 5. How to Develop a New Model(To be Continued)

  • More FastDeploy Deployment Module

    • deployment AI Model as a Service

    • Benchmark Testing

• 🖥️ Server-side and Cloud Deployment

  • A Quick Start for Python SDK
  • A Quick Start for C++ SDK
  • Supported Server-side and Cloud Model List

• 📱 Mobile and Edge Device Deployment

  • Supported Mobile and Edge Model List

• 🌐 Browser and Mini Program Deployment

  • Supported Web and Mini Program Model List

• Community

• Acknowledge

• License

🖥️ Server-side and Cloud Deployment

A Quick Start for Python SDK（click to expand）

Installation

Prerequisites

• CUDA >= 11.2 、cuDNN >= 8.0 、 Python >= 3.6
• OS: Linux x86_64/macOS/Windows 10

Install FastDeploy SDK with both CPU and GPU support

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

Conda Installation (Recommended)

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

Install FastDeploy SDK with only CPU support

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

Python Inference Example

• Prepare model and picture

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

• Test inference results

# For deployment of GPU/TensorRT, please refer to examples/vision/detection/paddledetection/python
import cv2
import fastdeploy.vision as vision

im = cv2.imread("000000014439.jpg")
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")

result = model.predict(im)
print(result)

vis_im = vision.vis_detection(im, result, score_threshold=0.5)
cv2.imwrite("vis_image.jpg", vis_im)

A Quick Start for C++ SDK（click to expand）

Installation

• Please refer to C++ Prebuilt Libraries Download

C++ Inference Example

• Prepare models and pictures

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

• Test inference results

// For GPU/TensorRT deployment, please refer to examples/vision/detection/paddledetection/cpp
#include "fastdeploy/vision.h"

int main(int argc, char* argv[]) {
  namespace vision = fastdeploy::vision;
  auto im = cv::imread("000000014439.jpg");
  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");

  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;
 }

For more deployment models, please refer to Vision Model Deployment Examples .

Server-side and Cloud Model List🔥🔥🔥🔥🔥

Notes: ✅: already supported; ❔: to be supported in the future; N/A: Not Available;

Server-side and Cloud Model List（click to fold）

Task	Model	Linux	Linux	Win	Win	Mac	Mac	Linux	Linux	Linux	Linux
---	---	X86 CPU	NVIDIA GPU	Intel CPU	NVIDIA GPU	Intel CPU	Arm CPU	AArch64 CPU	NVIDIA Jetson	Graphcore IPU	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	✅	✅	✅	✅	✅	✅	✅	✅	✅	✅
Classification	PaddleClas/SwinTransformer	✅	✅	✅	✅	✅	✅	✅	✅	❔	✅
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	Single430FaceLandmark1000	✅	✅	✅	✅	✅	✅	✅	✅	❔	❔
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	✅	✅	✅	✅	✅	✅	✅	❔	--	✅

📱 Mobile and Edge Device Deployment

Mobile and Edge Model List 🔥🔥🔥🔥

Mobile and Edge Model List（click to fold）

Task	Model	Size (MB)	Linux	Android	iOS	Linux	Linux	Linux	Linux	TBD...
---	---	---	ARM CPU	ARM CPU	ARM CPU	Rockchip-NPU RK3568/RK3588	Rockchip-NPU RV1109/RV1126/RK1808	Amlogic-NPU A311D/S905D/C308X	NXP-NPU i.MX 8M Plus	TBD...｜
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	✅	✅	❔	❔	--	--	--	--
Classification	PaddleClas/SwinTransformer_224_win7	352.7	✅	✅	❔	❔	--	--	--	--
Detection	PaddleDetection/PP-PicoDet_s_320_coco	4.1	✅	✅	❔	❔	--	--	--	--
Detection	PaddleDetection/PP-PicoDet_s_320_lcnet	4.9	✅	✅	❔	❔	✅	✅	✅	--
Detection	PaddleDetection/CenterNet	4.8	✅	❔	❔	❔	--	--	--	--
Detection	PaddleDetection/YOLOv3_MobileNetV3	94.6	✅	❔	❔	❔	--	--	--	--
Detection	PaddleDetection/PP-YOLO_tiny_650e_coco	4.4	✅	❔	❔	❔	--	--	--	--
Detection	PaddleDetection/SSD_MobileNetV1_300_120e_voc	23.3	✅	❔	❔	❔	--	--	--	--
Detection	PaddleDetection/PP-YOLO_ResNet50vd	188.5	✅	❔	❔	❔	--	--	--	--
Detection	PaddleDetection/PP-YOLOv2_ResNet50vd	218.7	✅	❔	❔	❔	--	--	--	--
Detection	PaddleDetection/PP-YOLO_crn_l_300e_coco	209.1	✅	❔	❔	❔	--	--	--	--
Detection	YOLOv5s	29.3	❔	❔	❔	❔	--	--	--	--
Face Detection	BlazeFace	1.5	❔	❔	❔	❔	--	--	--	--
Face Detection	RetinaFace	1.7	❔	❔	❔	❔	--	--	--	--
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-OCRv1	2.3+4.4	❔	❔	❔	❔	--	--	--	--
OCR	PaddleOCR/PP-OCRv2	2.3+4.4	✅	❔	❔	❔	--	--	--	--
OCR	PaddleOCR/PP-OCRv3	2.4+10.6	✅	❔	❔	❔	❔	❔	❔	--
OCR	PaddleOCR/PP-OCRv3-tiny	2.4+10.7	❔	❔	❔	❔	--	--	--	--

🌐 Browser-based Model List

Browser-based Model List（click to fold）

Task	Model	web_demo
---	---	Paddle.js
Detection	FaceDetection	✅
Detection	ScrewDetection	✅
Segmentation	PaddleSeg/HumanSeg	✅
Object Recognition	GestureRecognition	✅
Object Recognition	ItemIdentification	✅
OCR	PaddleOCR/PP-OCRv3	✅

Community

• If you have any question or suggestion, please give us your valuable input via GitHub Issues
• Join Us👬：
  • Slack：Join our Slack community and chat with other community members about ideas
  • WeChat：join our WeChat community and chat with other community members about ideas

Acknowledge

We sincerely appreciate the open-sourced capabilities in EasyEdge as we adopt it for the SDK generation and download in this project.

License

FastDeploy is provided under the Apache-2.0.