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https://github.com/PaddlePaddle/FastDeploy.git
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ed19c759df
* add cvcuda support in ppseg * python and pybind * add resize op, remove concat,std::move * define resize op
93 lines
3.3 KiB
C++
93 lines
3.3 KiB
C++
// 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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#pragma once
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#include "fastdeploy/vision/common/processors/manager.h"
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#include "fastdeploy/vision/common/processors/transform.h"
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#include "fastdeploy/vision/common/result.h"
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namespace fastdeploy {
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namespace vision {
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namespace segmentation {
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/*! @brief Preprocessor object for PaddleSeg serials model.
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*/
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class FASTDEPLOY_DECL PaddleSegPreprocessor : public ProcessorManager {
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public:
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/** \brief Create a preprocessor instance for PaddleSeg serials model
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*
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* \param[in] config_file Path of configuration file for deployment, e.g ppliteseg/deploy.yaml
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*/
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explicit PaddleSegPreprocessor(const std::string& config_file);
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/** \brief Implement the virtual function of ProcessorManager, Apply() is the
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* body of Run(). Apply() contains the main logic of preprocessing, Run() is
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* called by users to execute preprocessing
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*
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* \param[in] image_batch The input image batch
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* \param[in] outputs The output tensors which will feed in runtime
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* \return true if the preprocess successed, otherwise false
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*/
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virtual bool Apply(FDMatBatch* image_batch,
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std::vector<FDTensor>* outputs);
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/// Get is_vertical_screen property of PP-HumanSeg model, default is false
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bool GetIsVerticalScreen() const {
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return is_vertical_screen_;
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}
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/// Set is_vertical_screen value, bool type required
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void SetIsVerticalScreen(bool value) {
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is_vertical_screen_ = value;
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}
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/// This function will disable normalize in preprocessing step.
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void DisableNormalize();
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/// This function will disable hwc2chw in preprocessing step.
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void DisablePermute();
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/// This function will set imgs_info_ in PaddleSegPreprocessor
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void SetImgsInfo(
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std::map<std::string, std::vector<std::array<int, 2>>>* imgs_info) {
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imgs_info_ = imgs_info;
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}
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/// This function will get imgs_info_ in PaddleSegPreprocessor
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std::map<std::string, std::vector<std::array<int, 2>>>* GetImgsInfo() {
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return imgs_info_;
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}
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private:
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virtual bool BuildPreprocessPipelineFromConfig();
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std::vector<std::shared_ptr<Processor>> processors_;
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std::string config_file_;
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/** \brief For PP-HumanSeg model, set true if the input image is vertical image(height > width), default value is false
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*/
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bool is_vertical_screen_ = false;
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// for recording the switch of hwc2chw
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bool disable_permute_ = false;
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// for recording the switch of normalize
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bool disable_normalize_ = false;
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bool is_contain_resize_op_ = false;
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bool initialized_ = false;
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std::map<std::string, std::vector<std::array<int, 2>>>* imgs_info_;
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std::shared_ptr<Resize> pre_resize_op_ =
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std::make_shared<Resize>(0, 0);
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};
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} // namespace segmentation
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} // namespace vision
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} // namespace fastdeploy
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