mirror of
https://github.com/PaddlePaddle/FastDeploy.git
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6c4a08e416
* 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>
84 lines
3.4 KiB
C++
Executable File
84 lines
3.4 KiB
C++
Executable File
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#include <pybind11/stl.h>
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#include "fastdeploy/pybind/main.h"
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namespace fastdeploy {
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void BindPPOCRv3(pybind11::module& m) {
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// PPOCRv3
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pybind11::class_<pipeline::PPOCRv3, FastDeployModel>(
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m, "PPOCRv3")
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.def(pybind11::init<fastdeploy::vision::ocr::DBDetector*,
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fastdeploy::vision::ocr::Classifier*,
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fastdeploy::vision::ocr::Recognizer*>())
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.def(pybind11::init<fastdeploy::vision::ocr::DBDetector*,
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fastdeploy::vision::ocr::Recognizer*>())
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.def_property("cls_batch_size", &pipeline::PPOCRv3::GetClsBatchSize, &pipeline::PPOCRv3::SetClsBatchSize)
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.def_property("rec_batch_size", &pipeline::PPOCRv3::GetRecBatchSize, &pipeline::PPOCRv3::SetRecBatchSize)
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.def("clone", [](pipeline::PPOCRv3& self) {
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return self.Clone();
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})
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.def("predict", [](pipeline::PPOCRv3& self,
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pybind11::array& data) {
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auto mat = PyArrayToCvMat(data);
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vision::OCRResult res;
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self.Predict(&mat, &res);
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return res;
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})
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.def("batch_predict", [](pipeline::PPOCRv3& self, std::vector<pybind11::array>& data) {
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std::vector<cv::Mat> images;
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for (size_t i = 0; i < data.size(); ++i) {
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images.push_back(PyArrayToCvMat(data[i]));
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}
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std::vector<vision::OCRResult> results;
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self.BatchPredict(images, &results);
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return results;
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});
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}
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void BindPPOCRv2(pybind11::module& m) {
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// PPOCRv2
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pybind11::class_<pipeline::PPOCRv2, FastDeployModel>(
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m, "PPOCRv2")
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.def(pybind11::init<fastdeploy::vision::ocr::DBDetector*,
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fastdeploy::vision::ocr::Classifier*,
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fastdeploy::vision::ocr::Recognizer*>())
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.def(pybind11::init<fastdeploy::vision::ocr::DBDetector*,
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fastdeploy::vision::ocr::Recognizer*>())
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.def_property("cls_batch_size", &pipeline::PPOCRv2::GetClsBatchSize, &pipeline::PPOCRv2::SetClsBatchSize)
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.def_property("rec_batch_size", &pipeline::PPOCRv2::GetRecBatchSize, &pipeline::PPOCRv2::SetRecBatchSize)
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.def("clone", [](pipeline::PPOCRv2& self) {
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return self.Clone();
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})
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.def("predict", [](pipeline::PPOCRv2& self,
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pybind11::array& data) {
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auto mat = PyArrayToCvMat(data);
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vision::OCRResult res;
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self.Predict(&mat, &res);
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return res;
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})
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.def("batch_predict", [](pipeline::PPOCRv2& self, std::vector<pybind11::array>& data) {
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std::vector<cv::Mat> images;
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for (size_t i = 0; i < data.size(); ++i) {
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images.push_back(PyArrayToCvMat(data[i]));
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}
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std::vector<vision::OCRResult> results;
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self.BatchPredict(images, &results);
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return results;
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});
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}
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} // namespace fastdeploy
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