// 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 "fastdeploy/vision/common/processors/manager.h" #include "fastdeploy/vision/common/processors/resize.h" #include "fastdeploy/vision/common/processors/pad.h" #include "fastdeploy/vision/common/processors/normalize_and_permute.h" #include "fastdeploy/vision/common/result.h" namespace fastdeploy { namespace vision { namespace ocr { /*! @brief Preprocessor object for DBDetector serials model. */ class FASTDEPLOY_DECL DBDetectorPreprocessor : public ProcessorManager { public: DBDetectorPreprocessor(); /** \brief Process the input image and prepare input tensors for runtime * * \param[in] image_batch The input image batch * \param[in] outputs The output tensors which will feed in runtime * \return true if the preprocess successed, otherwise false */ virtual bool Apply(FDMatBatch* image_batch, std::vector* outputs); /// Set max_side_len for the detection preprocess, default is 960 void SetMaxSideLen(int max_side_len) { max_side_len_ = max_side_len; } /// Get max_side_len of the detection preprocess int GetMaxSideLen() const { return max_side_len_; } /// 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& mean = {0.485f, 0.456f, 0.406f}, const std::vector& std = {0.229f, 0.224f, 0.225f}, bool is_scale = true) { normalize_permute_op_ = std::make_shared(mean, std, is_scale); } /// Get the image info of the last batch, return a list of array /// {image width, image height, resize width, resize height} const std::vector>* GetBatchImgInfo() { return &batch_det_img_info_; } /// 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; } /// Set det_image_shape for the detection preprocess. /// This api is usually used when you retrain the model. /// Generally, you do not need to use it. void SetDetImageShape(const std::vector& det_image_shape) { det_image_shape_ = det_image_shape; } /// Get cls_image_shape for the classification preprocess std::vector GetDetImageShape() const { return det_image_shape_; } /// 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_; } private: bool ResizeImage(FDMat* img, int resize_w, int resize_h, int max_resize_w, int max_resize_h); // for recording the switch of hwc2chw bool disable_permute_ = false; // for recording the switch of normalize bool disable_normalize_ = false; int max_side_len_ = 960; std::vector> batch_det_img_info_; std::shared_ptr resize_op_; std::shared_ptr pad_op_; std::shared_ptr normalize_permute_op_; std::vector det_image_shape_ = {3, 960, 960}; bool static_shape_infer_ = false; std::array OcrDetectorGetInfo(FDMat* img, int max_size_len); }; } // namespace ocr } // namespace vision } // namespace fastdeploy