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README
Apache-2.0

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⚡️FastDeploy

⚡️FastDeploy是一款易用高效的推理部署开发套件。覆盖业界🔥热门AI模型并提供📦开箱即用的部署体验,包括图像分类、目标检测、图像分割、人脸检测、人脸识别、人体关键点识别、文字识别、语义理解等多任务,满足开发者多场景多硬件多平台的产业部署需求。

Potrait Segmentation Image Matting Semantic Segmentation Real-Time Matting
OCR Behavior Recognition Object Detection Pose Estimation
Face Alignment 3D Object Detection Face Editing Image Animation

近期更新

  • 🔥 2022.10.15:Release FastDeploy release v0.3.0

    • New server-side deployment upgrade:更快的推理性能,一键量化,更多的视觉和NLP模型
      • 集成 OpenVINO 推理引擎,并且保证了使用 OpenVINO 与 使用 TensorRT、ONNX Runtime、 Paddle Inference一致的开发体验;
      • 提供一键模型量化工具,支持YOLOv7、YOLOv6、YOLOv5等视觉模型,在CPU和GPU推理速度可提升1.5~2倍;
      • 新增加 PP-OCRv3, PP-OCRv2, PP-Matting, PP-HumanMatting, ModNet 等视觉模型并提供端到端部署示例
      • 新增加NLP信息抽取模型 UIE 并提供端到端部署示例.
  • 🔥 2022.8.18:发布FastDeploy release v0.2.0

    • 服务端部署全新升级:更快的推理性能,更多的视觉模型支持
      • 发布基于x86 CPU、NVIDIA GPU的高性能推理引擎SDK,推理速度大幅提升
      • 集成Paddle Inference、ONNX Runtime、TensorRT等推理引擎并提供统一的部署体验
      • 支持YOLOv7、YOLOv6、YOLOv5、PP-YOLOE等全系列目标检测模型并提供端到端部署示例
      • 支持人脸检测、人脸识别、实时人像抠图、图像分割等40+重点模型及Demo示例
      • 支持Python和C++两种语言部署
    • 边缘移动端部署新增瑞芯微、晶晨、恩智浦等NPU芯片部署能力

目录

服务端部署

Python SDK快速开始

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.copy())
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

C++ SDK快速开始

安装

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::Visualize::VisDetection(im, res, 0.5);
  cv::imwrite("vis_image.jpg", vis_im);
  return 0;
}

更多部署案例请参考视觉模型部署示例 .

服务端和web模型支持列表 🔥🔥🔥

符号说明: (1) ✅: 已经支持; (2) ❔: 未来支持; (3) ❌: 暂不支持; (4) --: 暂不考虑;
链接说明:「模型列」会跳转到模型推理Demo代码

任务场景 模型 API Linux Linux Win Win Mac Mac Linux Linux web_demo mini_program
--- --- --- X86 CPU NVIDIA GPU Intel CPU NVIDIA GPU Intel CPU Arm CPU AArch64 CPU NVIDIA Jetson Paddle.js Paddle.js
Classification PaddleClas/ResNet50 Python/C++
Classification PaddleClas/PP-LCNet Python/C++
Classification PaddleClas/PP-LCNetv2 Python/C++
Classification PaddleClas/EfficientNet Python/C++
Classification PaddleClas/GhostNet Python/C++
Classification PaddleClas/MobileNetV1 Python/C++
Classification PaddleClas/MobileNetV2 Python/C++
Classification PaddleClas/MobileNetV3 Python/C++
Classification PaddleClas/ShuffleNetV2 Python/C++
Classification PaddleClas/SqueeezeNetV1.1 Python/C++
Classification PaddleClas/Inceptionv3 Python/C++
Classification PaddleClas/PP-HGNet Python/C++
Classification PaddleClas/SwinTransformer Python/C++
Detection PaddleDetection/PP-YOLOE Python/C++
Detection PaddleDetection/PicoDet Python/C++
Detection PaddleDetection/YOLOX Python/C++
Detection PaddleDetection/YOLOv3 Python/C++
Detection PaddleDetection/PP-YOLO Python/C++
Detection PaddleDetection/PP-YOLOv2 Python/C++
Detection PaddleDetection/FasterRCNN Python/C++
Detection Megvii-BaseDetection/YOLOX Python/C++
Detection WongKinYiu/YOLOv7 Python/C++
Detection meituan/YOLOv6 Python/C++
Detection ultralytics/YOLOv5 Python/C++
Detection WongKinYiu/YOLOR Python/C++
Detection WongKinYiu/ScaledYOLOv4 Python/C++
Detection ppogg/YOLOv5Lite Python/C++
Detection RangiLyu/NanoDetPlus Python/C++
OCR PaddleOCR/PP-OCRv2 Python/C++
OCR PaddleOCR/PP-OCRv3 Python/C++
Segmentation PaddleSeg/PP-LiteSeg Python/C++
Segmentation PaddleSeg/PP-HumanSegLite Python/C++
Segmentation PaddleSeg/HRNet Python/C++
Segmentation PaddleSeg/PP-HumanSegServer Python/C++
Segmentation PaddleSeg/Unet Python/C++
Segmentation PaddleSeg/Deeplabv3 Python/C++
Face Detection biubug6/RetinaFace Python/C++
Face Detection Linzaer/UltraFace Python/C++
FaceDetection deepcam-cn/YOLOv5Face Python/C++
Face Detection insightface/SCRFD Python/C++
Face Recognition insightface/ArcFace Python/C++
Face Recognition insightface/CosFace Python/C++
Face Recognition insightface/PartialFC Python/C++
Face Recognition insightface/VPL Python/C++
Matting ZHKKKe/MODNet Python/C++
Matting PaddleSeg/PP-Matting Python/C++
Matting PaddleSeg/PP-HumanMatting Python/C++
Matting PaddleSeg/ModNet Python/C++
Information Extraction PaddleNLP/UIE Python/C++

端侧部署

EasyEdge边缘端部署

EasyEdge移动端部署

EasyEdge自定义模型部署

Paddle Lite NPU部署

端侧模型支持列表

任务场景 模型 大小(MB) Linux Android iOS Linux Linux Linux 更新中...
--- --- --- ARM CPU ARM CPU ARM CPU 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 PP-LCNet 11.9 -- -- -- --
Classification PP-LCNetv2 26.6 -- -- -- --
Classification EfficientNet 31.4 -- -- -- --
Classification GhostNet 20.8 -- -- -- --
Classification MobileNetV1 17 -- -- -- --
Classification MobileNetV2 14.2 -- -- -- --
Classification MobileNetV3 22
Classification ShuffleNetV2 9.2 -- -- -- --
Classification SqueezeNetV1.1 5
Classification Inceptionv3 95.5 -- -- -- --
Classification PP-HGNet 59 -- -- -- --
Classification SwinTransformer_224_win7 352.7 -- -- -- --
Detection PP-PicoDet_s_320_coco 4.1 -- -- -- --
Detection PP-PicoDet_s_320_lcnet 4.9
Detection CenterNet 4.8 -- -- -- --
Detection YOLOv3_MobileNetV3 94.6 -- -- -- --
Detection PP-YOLO_tiny_650e_coco 4.4 -- -- -- --
Detection SSD_MobileNetV1_300_120e_voc 23.3 -- -- -- --
Detection PP-YOLO_ResNet50vd 188.5 -- -- -- --
Detection PP-YOLOv2_ResNet50vd 218.7 -- -- -- --
Detection PP-YOLO_crn_l_300e_coco 209.1 -- -- -- --
Detection YOLOv5s 29.3 -- -- -- --
Face Detection BlazeFace 1.5 -- -- -- --
Face Detection RetinaFace 1.7 -- -- -- --
Keypoint Detection PP-TinyPose 5.5
Segmentation PP-LiteSeg(STDC1) 32.2 -- -- -- --
Segmentation PP-HumanSeg-Lite 0.556 -- -- -- --
Segmentation HRNet-w18 38.7 -- -- -- --
Segmentation PP-HumanSeg-Server 107.2 -- -- -- --
Segmentation Unet 53.7 -- -- -- --
OCR PP-OCRv1 2.3+4.4 -- -- -- --
OCR PP-OCRv2 2.3+4.4 -- -- -- --
OCR PP-OCRv3 2.4+10.6
OCR PP-OCRv3-tiny 2.4+10.7 -- -- -- --

社区交流

  • 加入社区👬: 微信扫描二维码,进入FastDeploy技术交流群

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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