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- // Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
- //
- // Licensed under the Apache License, Version 2.0 (the "License");
- // you may not use this file except in compliance with the License.
- // You may obtain a copy of the License at
- //
- // http://www.apache.org/licenses/LICENSE-2.0
- //
- // Unless required by applicable law or agreed to in writing, software
- // distributed under the License is distributed on an "AS IS" BASIS,
- // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- // See the License for the specific language governing permissions and
- // limitations under the License.
- #pragma once
- #include "ultra_infer/vision/common/processors/manager.h"
- #include "ultra_infer/vision/common/processors/transform.h"
- #include "ultra_infer/vision/common/result.h"
- namespace ultra_infer {
- namespace vision {
- namespace ocr {
- /*! @brief Preprocessor object for PaddleClas serials model.
- */
- class ULTRAINFER_DECL RecognizerPreprocessor : public ProcessorManager {
- public:
- RecognizerPreprocessor();
- using ProcessorManager::Run;
- /** \brief Process the input image and prepare input tensors for runtime
- *
- * \param[in] images The input data list, all the elements are FDMat
- * \param[in] outputs The output tensors which will be fed into runtime
- * \return true if the preprocess succeeded, otherwise false
- */
- bool Run(std::vector<FDMat> *images, std::vector<FDTensor> *outputs,
- size_t start_index, size_t end_index,
- const std::vector<int> &indices);
- /** \brief Implement the virtual function of ProcessorManager, Apply() is the
- * body of Run(). Apply() contains the main logic of preprocessing, Run() is
- * called by users to execute preprocessing
- *
- * \param[in] image_batch The input image batch
- * \param[in] outputs The output tensors which will feed in runtime
- * \return true if the preprocess succeeded, otherwise false
- */
- virtual bool Apply(FDMatBatch *image_batch, std::vector<FDTensor> *outputs);
- /// Set static_shape_infer is true or not. When deploy PP-OCR
- /// on hardware which can not support dynamic input shape very well,
- /// like Huawei Ascned, static_shape_infer needs to to be true.
- void SetStaticShapeInfer(bool static_shape_infer) {
- static_shape_infer_ = static_shape_infer;
- }
- /// Get static_shape_infer of the recognition preprocess
- bool GetStaticShapeInfer() const { return static_shape_infer_; }
- /// Set preprocess normalize parameters, please call this API to customize
- /// the normalize parameters, otherwise it will use the default normalize
- /// parameters.
- void SetNormalize(const std::vector<float> &mean,
- const std::vector<float> &std, bool is_scale) {
- normalize_permute_op_ =
- std::make_shared<NormalizeAndPermute>(mean, std, is_scale);
- normalize_op_ = std::make_shared<Normalize>(mean, std, is_scale);
- }
- /// Set rec_image_shape for the recognition preprocess
- void SetRecImageShape(const std::vector<int> &rec_image_shape) {
- rec_image_shape_ = rec_image_shape;
- }
- /// Get rec_image_shape for the recognition preprocess
- std::vector<int> GetRecImageShape() { return rec_image_shape_; }
- /// This function will disable normalize in preprocessing step.
- void DisableNormalize() { disable_permute_ = true; }
- /// This function will disable hwc2chw in preprocessing step.
- void DisablePermute() { disable_normalize_ = true; }
- private:
- void OcrRecognizerResizeImage(FDMat *mat, float max_wh_ratio,
- const std::vector<int> &rec_image_shape,
- bool static_shape_infer);
- // for recording the switch of hwc2chw
- bool disable_permute_ = false;
- // for recording the switch of normalize
- bool disable_normalize_ = false;
- std::vector<int> rec_image_shape_ = {3, 48, 320};
- bool static_shape_infer_ = false;
- std::shared_ptr<Resize> resize_op_;
- std::shared_ptr<Pad> pad_op_;
- std::shared_ptr<NormalizeAndPermute> normalize_permute_op_;
- std::shared_ptr<Normalize> normalize_op_;
- std::shared_ptr<HWC2CHW> hwc2chw_op_;
- std::shared_ptr<Cast> cast_op_;
- };
- } // namespace ocr
- } // namespace vision
- } // namespace ultra_infer
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