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FastDeploy/examples/vision/detection/paddledetection
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yunyaoXYY a231c9e7f3 [Quantization] Update quantized model deployment examples and update readme. (#377) 
* 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

* Improve Quantize Readme

* Fix conflicts

* Fix conflicts

* improve readme

* Improve quantization tools and readme

* Improve quantization tools and readme

* Add quantized deployment examples for PaddleSeg model

* Fix cpp readme

* Fix memory leak of reader_wrapper function

* Fix model file name in PaddleClas quantization examples

* Update Runtime and E2E benchmark

* Update Runtime and E2E benchmark

* Rename quantization tools to auto compression tools

* Remove PPYOLOE data when deployed on MKLDNN

* Fix readme

* Support PPYOLOE with OR without NMS and update readme

* Update Readme

* Update configs and readme

* Update configs and readme

* Add Paddle-TensorRT backend in quantized model deploy examples

* Support PPYOLOE+ series
2022-11-02 20:29:29 +08:00
..
android
[Doc] Add PicoDet & PaddleClas Android demo docs (#412)
2022-10-23 14:06:09 +08:00
cpp
[Doc] Update 0.3.0 to 0.4.0 in all docs (#443)
2022-10-27 14:33:05 +08:00
python
Bump up to version 0.3.0 (#371)
2022-10-15 22:01:27 +08:00
quantize
[Quantization] Update quantized model deployment examples and update readme. (#377)
2022-11-02 20:29:29 +08:00
README.md
Correct PP-Series models' name
2022-10-09 02:49:58 +00:00

README.md

PaddleDetection模型部署

模型版本说明

支持模型列表

目前FastDeploy支持如下模型的部署

导出部署模型

在部署前，需要先将PaddleDetection导出成部署模型，导出步骤参考文档导出模型

注意

  • 在导出模型时不要进行NMS的去除操作，正常导出即可
  • 导出模型时，不要添加fuse_normalize=True参数

下载预训练模型

为了方便开发者的测试，下面提供了PaddleDetection导出的各系列模型，开发者可直接下载使用。

其中精度指标来源于PaddleDetection中对各模型的介绍，详情各参考PaddleDetection中的说明。

模型 参数大小 精度 备注
picodet_l_320_coco_lcnet 23MB Box AP 42.6%
ppyoloe_crn_l_300e_coco 200MB Box AP 51.4%
ppyolo_r50vd_dcn_1x_coco 180MB Box AP 44.8% 暂不支持TensorRT
ppyolov2_r101vd_dcn_365e_coco 282MB Box AP 49.7% 暂不支持TensorRT
yolov3_darknet53_270e_coco 237MB Box AP 39.1%
yolox_s_300e_coco 35MB Box AP 40.4%
faster_rcnn_r50_vd_fpn_2x_coco 160MB Box AP 40.8% 暂不支持TensorRT
mask_rcnn_r50_1x_coco 128M Box AP 37.4%, Mask AP 32.8% 暂不支持TensorRT、ORT

详细部署文档