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FastDeploy/tutorials/multi_thread/python/pipeline/README_CN.md
huangjianhui 6c4a08e416 [Other] PPOCR models support model clone function (#1072) 
* Refactor PaddleSeg with preprocessor && postprocessor

* Fix bugs

* Delete redundancy code

* Modify by comments

* Refactor according to comments

* Add batch evaluation

* Add single test script

* Add ppliteseg single test script && fix eval(raise) error

* fix bug

* Fix evaluation segmentation.py batch predict

* Fix segmentation evaluation bug

* Fix evaluation segmentation bugs

* Update segmentation result docs

* Update old predict api and DisableNormalizeAndPermute

* Update resize segmentation label map with cv::INTER_NEAREST

* Add Model Clone function for PaddleClas && PaddleDet && PaddleSeg

* Add multi thread demo

* Add python model clone function

* Add multi thread python && C++ example

* Fix bug

* Update python && cpp multi_thread examples

* Add cpp && python directory

* Add README.md for examples

* Delete redundant code

* Create README_CN.md

* Rename README_CN.md to README.md

* Update README.md

* Update README.md

* Update VERSION_NUMBER

* Update requirements.txt

* Update README.md

* update version in doc:

* [Serving]Update Dockerfile (#1037)

Update Dockerfile

* Add license notice for RVM onnx model file (#1060)

* [Model] Add GPL-3.0 license (#1065)

Add GPL-3.0 license

* PPOCR model support model clone

* Update README.md

* Update PPOCRv2 && PPOCRv3 clone code

* Update PPOCR python __init__

* Add multi thread ocr example code

* Update README.md

* Update README.md

* Update ResNet50_vd_infer multi process code

* Add PPOCR multi process && thread example

* Update README.md

* Update README.md

* Update multi-thread docs

Co-authored-by: Jason <jiangjiajun@baidu.com>
Co-authored-by: leiqing <54695910+leiqing1@users.noreply.github.com>
Co-authored-by: heliqi <1101791222@qq.com>
Co-authored-by: WJJ1995 <wjjisloser@163.com>
2023-01-17 15:16:41 +08:00

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English | 简体中文

PPOCR模型 Python多线程/进程部署示例

在部署前，需确认以下两个步骤

本目录下提供multi_thread_process_ocr.py快速完成PPOCRv3在CPU/GPU，以及GPU上通过TensorRT加速部署的多线程/进程示例。执行如下脚本即可完成

#下载部署示例代码
git clone https://github.com/PaddlePaddle/FastDeploy.git
cd  FastDeploy/tutorials/multi_thread/python/pipeline

# 下载模型,图片和字典文件
wget https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_det_infer.tar
tar xvf ch_PP-OCRv3_det_infer.tar

wget https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar
tar -xvf ch_ppocr_mobile_v2.0_cls_infer.tar

wget https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_infer.tar
tar xvf ch_PP-OCRv3_rec_infer.tar

wget https://gitee.com/paddlepaddle/PaddleOCR/raw/release/2.6/doc/imgs/12.jpg

wget https://gitee.com/paddlepaddle/PaddleOCR/raw/release/2.6/ppocr/utils/ppocr_keys_v1.txt

# CPU多线程推理
python multi_thread_process_ocr.py --det_model ch_PP-OCRv3_det_infer --cls_model ch_ppocr_mobile_v2.0_cls_infer --rec_model ch_PP-OCRv3_rec_infer --rec_label_file ppocr_keys_v1.txt --image_path 12.jpg --device cpu --thread_num 1
# CPU多进程推理
python multi_thread_process_ocr.py --det_model ch_PP-OCRv3_det_infer --cls_model ch_ppocr_mobile_v2.0_cls_infer --rec_model ch_PP-OCRv3_rec_infer --rec_label_file ppocr_keys_v1.txt --image_path 12.jpg --device cpu --use_multi_process True --process_num 1

# GPU多线程推理
python multi_thread_process_ocr.py --det_model ch_PP-OCRv3_det_infer --cls_model ch_ppocr_mobile_v2.0_cls_infer --rec_model ch_PP-OCRv3_rec_infer --rec_label_file ppocr_keys_v1.txt --image_path 12.jpg --device gpu --thread_num 1
# GPU多进程推理
python multi_thread_process_ocr.py --det_model ch_PP-OCRv3_det_infer --cls_model ch_ppocr_mobile_v2.0_cls_infer --rec_model ch_PP-OCRv3_rec_infer --rec_label_file ppocr_keys_v1.txt --image_path 12.jpg --device gpu --use_multi_process True --process_num 1

# GPU上使用TensorRT多线程推理
python multi_thread_process_ocr.py --det_model ch_PP-OCRv3_det_infer --cls_model ch_ppocr_mobile_v2.0_cls_infer --rec_model ch_PP-OCRv3_rec_infer --rec_label_file ppocr_keys_v1.txt --image_path 12.jpg --device gpu --backend trt --thread_num 1
# GPU上使用TensorRT多进程推理
python multi_thread_process_ocr.py --det_model ch_PP-OCRv3_det_infer --cls_model ch_ppocr_mobile_v2.0_cls_infer --rec_model ch_PP-OCRv3_rec_infer --rec_label_file ppocr_keys_v1.txt --image_path 12.jpg --device gpu --backend trt --use_multi_process True --process_num 1

# 昆仑芯XPU多线程推理
python multi_thread_process_ocr.py --det_model ch_PP-OCRv3_det_infer --cls_model ch_ppocr_mobile_v2.0_cls_infer --rec_model ch_PP-OCRv3_rec_infer --rec_label_file ppocr_keys_v1.txt --image_path 12.jpg --device kunlunxin --thread_num 1
# 昆仑芯XPU多进程推理
python multi_thread_process_ocr.py --det_model ch_PP-OCRv3_det_infer --cls_model ch_ppocr_mobile_v2.0_cls_infer --rec_model ch_PP-OCRv3_rec_infer --rec_label_file ppocr_keys_v1.txt --image_path 12.jpg --device kunlunxin --use_multi_process True --process_num 1

注意: --image_path 可以输入图片文件夹的路径

运行完成后返回结果如下所示

thread: 0 , result:  det boxes: [[42,413],[483,391],[484,428],[43,450]]rec text: 上海斯格威铂尔大酒店 rec score:0.949773 cls label: 0 cls score: 1.000000
det boxes: [[187,456],[399,448],[400,480],[188,488]]rec text: 打浦路15号 rec score:0.910265 cls label: 0 cls score: 1.000000
det boxes: [[23,507],[513,488],[515,529],[24,548]]rec text: 绿洲仕格维花园公寓 rec score:0.934239 cls label: 0 cls score: 1.000000
det boxes: [[74,553],[427,542],[428,571],[75,582]]rec text: 打浦路252935号 rec score:0.872207 cls label: 0 cls score: 1.000000