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044ab993d2
* ppocr cls preprocessor use manager * hwc2chw cvcuda * ppocr rec preproc use manager * ocr rec preproc cvcuda * fix rec preproc bug * ppocr cls&rec preproc set normalize * fix pybind * address comment
103 lines
4.1 KiB
C++
103 lines
4.1 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/transform.h"
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#include "fastdeploy/vision/common/processors/manager.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 ocr {
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/*! @brief Preprocessor object for PaddleClas serials model.
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*/
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class FASTDEPLOY_DECL RecognizerPreprocessor : public ProcessorManager {
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public:
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RecognizerPreprocessor();
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using ProcessorManager::Run;
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/** \brief Process the input image and prepare input tensors for runtime
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*
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* \param[in] images The input data list, all the elements are FDMat
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* \param[in] outputs The output tensors which will be fed into runtime
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* \return true if the preprocess successed, otherwise false
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*/
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bool Run(std::vector<FDMat>* images, std::vector<FDTensor>* outputs,
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size_t start_index, size_t end_index,
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const std::vector<int>& indices);
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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, std::vector<FDTensor>* outputs);
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/// Set static_shape_infer is true or not. When deploy PP-OCR
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/// on hardware which can not support dynamic input shape very well,
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/// like Huawei Ascned, static_shape_infer needs to to be true.
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void SetStaticShapeInfer(bool static_shape_infer) {
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static_shape_infer_ = static_shape_infer;
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}
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/// Get static_shape_infer of the recognition preprocess
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bool GetStaticShapeInfer() const { return static_shape_infer_; }
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/// Set preprocess normalize parameters, please call this API to customize
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/// the normalize parameters, otherwise it will use the default normalize
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/// parameters.
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void SetNormalize(const std::vector<float>& mean,
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const std::vector<float>& std,
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bool is_scale) {
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normalize_permute_op_ =
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std::make_shared<NormalizeAndPermute>(mean, std, is_scale);
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normalize_op_ = std::make_shared<Normalize>(mean, std, is_scale);
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}
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/// Set rec_image_shape for the recognition preprocess
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void SetRecImageShape(const std::vector<int>& rec_image_shape) {
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rec_image_shape_ = rec_image_shape;
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}
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/// Get rec_image_shape for the recognition preprocess
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std::vector<int> GetRecImageShape() { return rec_image_shape_; }
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/// This function will disable normalize in preprocessing step.
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void DisableNormalize() { disable_permute_ = true; }
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/// This function will disable hwc2chw in preprocessing step.
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void DisablePermute() { disable_normalize_ = true; }
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private:
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void OcrRecognizerResizeImage(FDMat* mat, float max_wh_ratio,
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const std::vector<int>& rec_image_shape,
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bool static_shape_infer);
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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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std::vector<int> rec_image_shape_ = {3, 48, 320};
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bool static_shape_infer_ = false;
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std::shared_ptr<Resize> resize_op_;
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std::shared_ptr<Pad> pad_op_;
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std::shared_ptr<NormalizeAndPermute> normalize_permute_op_;
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std::shared_ptr<Normalize> normalize_op_;
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std::shared_ptr<HWC2CHW> hwc2chw_op_;
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std::shared_ptr<Cast> cast_op_;
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};
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} // namespace ocr
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} // namespace vision
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} // namespace fastdeploy
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