Skip to content

⚡️An Easy-to-use and Fast Deep Learning Model Deployment Toolkit for ☁️Cloud 📱Mobile and 📹Edge. Including Image, Video, Text and Audio 20+ main stream scenarios and 150+ SOTA models with end-to-end optimization, multi-platform and multi-framework support.

License

Notifications You must be signed in to change notification settings

ikingye/FastDeploy

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

English | 简体中文 | हिन्दी | 日本語 | 한국인 | Pу́сский язы́к

⚡️FastDeploy

Installation | Documents | Quick Start | 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 🔥160+ Text, Vision, Speech and Cross-modal AI models. Including image classification, object detection, OCR, face detection, matting, pp-tracking, NLP, stable difussion, TTS and other tasks to meet developers' industrial deployment needs for multi-scenario, multi-hardware and multi-platform.

🌠 Recent updates

🌌 Inference Backend and Abilities

X86_64 CPU       





NVDIA GPU




Phytium CPU
KunlunXin XPU
Huawei Ascend NPU
Graphcore IPU
Sophgo
Intel graphics card
Jetson




ARM CPU

RK3588 etc.
RV1126 etc.
Amlogic
NXP

🔮 Contents

Quick Start💨

A Quick Start for Python SDK(click to fold)

🎆 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 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

🎇 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 Linux Linux Linux
--- --- X86 CPU NVIDIA GPU X86 CPU NVIDIA GPU X86 CPU Arm CPU AArch64 CPU Phytium D2000 aarch64 NVIDIA Jetson Graphcore IPU kunlunxin XPU Huawei Ascend 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/YOLOv8
Detection 🔥ultralytics/YOLOv8
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 --

📳 Mobile and Edge Device Deployment

Mobile and Edge Model List(click to fold)
Task Model Size(MB) Linux Android Linux Linux Linux Linux Linux TBD ...
--- --- --- ARM CPU ARM CPU Rockchip NPU
RK3588/RK3568/RK3566
Rockchip NPU
RV1109/RV1126/RK1808
Amlogic NPU
A311D/S905D/C308X
NXP NPU
i.MX 8M Plus
TBD...
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 and Mini Program Model List

Web and mini program 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

💐 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.

About

⚡️An Easy-to-use and Fast Deep Learning Model Deployment Toolkit for ☁️Cloud 📱Mobile and 📹Edge. Including Image, Video, Text and Audio 20+ main stream scenarios and 150+ SOTA models with end-to-end optimization, multi-platform and multi-framework support.

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • C++ 74.4%
  • Python 13.5%
  • Java 7.0%
  • CMake 3.1%
  • Shell 1.2%
  • Batchfile 0.3%
  • Other 0.5%