// Copyright (c) 2020 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 #include #include #include #include #include #include #include #include #include #include #include #include #include "postprocess_op.h" #include "preprocess_op.h" using namespace paddle_infer; namespace PaddleOCR { class DBDetector { public: explicit DBDetector(const std::string &model_dir) { LoadModel(model_dir); } // Load Paddle inference model void LoadModel(const std::string &model_dir); // Run predictor void Run(cv::Mat &img, std::vector>> &boxes, std::vector ×); private: std::shared_ptr predictor_; bool use_gpu_ = true; int gpu_id_ = 0; int gpu_mem_ = 4000; int cpu_math_library_num_threads_ = 4; bool use_mkldnn_ = false; string limit_type_ = "max"; int limit_side_len_ = 960; double det_db_thresh_ = 0.3; double det_db_box_thresh_ = 0.5; double det_db_unclip_ratio_ = 2.0; std::string det_db_score_mode_ = "slow"; bool use_dilation_ = false; bool visualize_ = true; bool use_tensorrt_ = false; std::string precision_ = "fp32"; std::vector mean_ = {0.485f, 0.456f, 0.406f}; std::vector scale_ = {1 / 0.229f, 1 / 0.224f, 1 / 0.225f}; bool is_scale_ = true; // pre-process ResizeImgType0 resize_op_; Normalize normalize_op_; Permute permute_op_; // post-process DBPostProcessor post_processor_; }; } // namespace PaddleOCR