Files
FastDeploy/examples/vision
yunyaoXYY b0663209f6 Add Examples to deploy quantized models (#342)
* Add PaddleOCR Support

* Add PaddleOCR Support

* Add PaddleOCRv3 Support

* Add PaddleOCRv3 Support

* Update README.md

* Update README.md

* Update README.md

* Update README.md

* Add PaddleOCRv3 Support

* Add PaddleOCRv3 Supports

* Add PaddleOCRv3 Suport

* Fix Rec diff

* Remove useless functions

* Remove useless comments

* Add PaddleOCRv2 Support

* Add PaddleOCRv3 & PaddleOCRv2 Support

* remove useless parameters

* Add utils of sorting det boxes

* Fix code naming convention

* Fix code naming convention

* Fix code naming convention

* Fix bug in the Classify process

* Imporve OCR Readme

* Fix diff in Cls model

* Update Model Download Link in Readme

* Fix diff in PPOCRv2

* Improve OCR readme

* Imporve OCR readme

* Improve OCR readme

* Improve OCR readme

* Imporve OCR readme

* Improve OCR readme

* Fix conflict

* Add readme for OCRResult

* Improve OCR readme

* Add OCRResult readme

* Improve OCR readme

* Improve OCR readme

* Add Model Quantization Demo

* Fix Model Quantization Readme

* Fix Model Quantization Readme

* Add the function to do PTQ quantization

* Improve quant tools readme

* Improve quant tool readme

* Improve quant tool readme

* Add PaddleInference-GPU for OCR Rec model

* Add QAT method to fastdeploy-quantization tool

* Remove examples/slim for now

* Move configs folder

* Add Quantization Support for Classification Model

* Imporve ways of importing preprocess

* Upload YOLO Benchmark on readme

* Upload YOLO Benchmark on readme

* Upload YOLO Benchmark on readme

* Improve Quantization configs and readme

* Add support for multi-inputs model

* Add backends and params file for YOLOv7

* Add quantized model deployment support for YOLO series

* Fix YOLOv5 quantize readme

* Fix YOLO quantize readme

* Fix YOLO quantize readme

* Improve quantize YOLO readme

* Improve quantize YOLO readme

* Improve quantize YOLO readme

* Improve quantize YOLO readme

* Improve quantize YOLO readme

* Fix bug, change Fronted to ModelFormat

* Change Fronted to ModelFormat

* Add examples to deploy quantized paddleclas models

* Fix readme

* Add quantize Readme

* Add quantize Readme

* Add quantize Readme

* Modify readme of quantization tools

* Modify readme of quantization tools

* Improve quantization tools readme

* Improve quantization readme

* Improve PaddleClas quantized model deployment  readme

* Add PPYOLOE-l quantized deployment examples

* Improve quantization tools readme
2022-10-14 13:35:45 +08:00
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2022-09-28 17:45:02 +08:00
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2022-09-22 12:17:35 +08:00

视觉模型部署

本目录下提供了各类视觉模型的部署,主要涵盖以下任务类型

任务类型 说明 预测结果结构体
Detection 目标检测,输入图像,检测图像中物体位置,并返回检测框坐标及类别和置信度 DetectionResult
Segmentation 语义分割,输入图像,给出图像中每个像素的分类及置信度 SegmentationResult
Classification 图像分类,输入图像,给出图像的分类结果和置信度 ClassifyResult
FaceDetection 人脸检测,输入图像,检测图像中人脸位置,并返回检测框坐标及人脸关键点 FaceDetectionResult
FaceRecognition 人脸识别,输入图像,返回可用于相似度计算的人脸特征的embedding FaceRecognitionResult
Matting 抠图,输入图像,返回图片的前景每个像素点的Alpha值 MattingResult
OCR 文本框检测,分类,文本框内容识别,输入图像,返回文本框坐标,文本框的方向类别以及框内的文本内容 OCRResult

FastDeploy API设计

视觉模型具有较有统一任务范式,在设计API时(包括C++/Python),FastDeploy将视觉模型的部署拆分为四个步骤

  • 模型加载
  • 图像预处理
  • 模型推理
  • 推理结果后处理

FastDeploy针对飞桨的视觉套件,以及外部热门模型,提供端到端的部署服务,用户只需准备模型,按以下步骤即可完成整个模型的部署

  • 加载模型
  • 调用predict接口

FastDeploy在各视觉模型部署时,也支持一键切换后端推理引擎,详情参阅如何切换模型推理引擎