// 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/fastdeploy_model.h" #include "fastdeploy/vision/common/processors/transform.h" #include "fastdeploy/vision/common/result.h" #include "fastdeploy/vision/ocr/ppocr/utils/ocr_postprocess_op.h" #include "fastdeploy/vision/ocr/ppocr/rec_preprocessor.h" #include "fastdeploy/vision/ocr/ppocr/rec_postprocessor.h" namespace fastdeploy { namespace vision { /** \brief All OCR series model APIs are defined inside this namespace * */ namespace ocr { /*! @brief Recognizer object is used to load the recognition model provided by PaddleOCR. */ class FASTDEPLOY_DECL Recognizer : public FastDeployModel { public: Recognizer(); /** \brief Set path of model file, and the configuration of runtime * * \param[in] model_file Path of model file, e.g ./ch_PP-OCRv3_rec_infer/model.pdmodel. * \param[in] params_file Path of parameter file, e.g ./ch_PP-OCRv3_rec_infer/model.pdiparams, if the model format is ONNX, this parameter will be ignored. * \param[in] label_path Path of label file used by OCR recognition model. e.g ./ppocr_keys_v1.txt * \param[in] custom_option RuntimeOption for inference, the default will use cpu, and choose the backend defined in `valid_cpu_backends`. * \param[in] model_format Model format of the loaded model, default is Paddle format. */ Recognizer(const std::string& model_file, const std::string& params_file = "", const std::string& label_path = "", const RuntimeOption& custom_option = RuntimeOption(), const ModelFormat& model_format = ModelFormat::PADDLE); /// Get model's name std::string ModelName() const { return "ppocr/ocr_rec"; } /** \brief Predict the input image and get OCR recognition model result. * * \param[in] img The input image data, comes from cv::imread(), is a 3-D array with layout HWC, BGR format. * \param[in] text The text result of rec model will be written into this parameter. * \param[in] rec_score The sccore result of rec model will be written into this parameter. * \return true if the prediction is successed, otherwise false. */ virtual bool Predict(const cv::Mat& img, std::string* text, float* rec_score); /** \brief BatchPredict the input image and get OCR recognition model result. * * \param[in] images The list of input image data, comes from cv::imread(), is a 3-D array with layout HWC, BGR format. * \param[in] texts The list of text results of rec model will be written into this vector. * \param[in] rec_scores The list of sccore result of rec model will be written into this vector. * \return true if the prediction is successed, otherwise false. */ virtual bool BatchPredict(const std::vector& images, std::vector* texts, std::vector* rec_scores); virtual bool BatchPredict(const std::vector& images, std::vector* texts, std::vector* rec_scores, size_t start_index, size_t end_index, const std::vector& indices); /// Get preprocessor reference of DBDetectorPreprocessor virtual RecognizerPreprocessor& GetPreprocessor() { return preprocessor_; } /// Get postprocessor reference of DBDetectorPostprocessor virtual RecognizerPostprocessor& GetPostprocessor() { return postprocessor_; } private: bool Initialize(); RecognizerPreprocessor preprocessor_; RecognizerPostprocessor postprocessor_; }; } // namespace ocr } // namespace vision } // namespace fastdeploy