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https://github.com/PaddlePaddle/PaddleOCR.git
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97d9728a1d
* cpp_infer support PP-OCRv5 models * python_infer support PP-OCRv5 models * update version2.x model_list * rollback version2.x model_list * update * update
127 lines
4.0 KiB
C++
127 lines
4.0 KiB
C++
// Copyright (c) 2020 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 <fstream>
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#include <include/postprocess_op.h>
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#include <include/preprocess_op.h>
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#include <iostream>
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#include <memory>
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#include <yaml-cpp/yaml.h>
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namespace paddle_infer {
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class Predictor;
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}
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namespace PaddleOCR {
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class DBDetector {
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public:
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explicit DBDetector(const std::string &model_dir, const bool &use_gpu,
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const int &gpu_id, const int &gpu_mem,
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const int &cpu_math_library_num_threads,
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const bool &use_mkldnn, const std::string &limit_type,
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const int &limit_side_len, const double &det_db_thresh,
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const double &det_db_box_thresh,
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const double &det_db_unclip_ratio,
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const std::string &det_db_score_mode,
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const bool &use_dilation, const bool &use_tensorrt,
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const std::string &precision) noexcept {
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this->use_gpu_ = use_gpu;
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this->gpu_id_ = gpu_id;
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this->gpu_mem_ = gpu_mem;
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this->cpu_math_library_num_threads_ = cpu_math_library_num_threads;
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this->use_mkldnn_ = use_mkldnn;
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this->limit_type_ = limit_type;
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this->limit_side_len_ = limit_side_len;
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this->det_db_thresh_ = det_db_thresh;
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this->det_db_box_thresh_ = det_db_box_thresh;
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this->det_db_unclip_ratio_ = det_db_unclip_ratio;
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this->det_db_score_mode_ = det_db_score_mode;
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this->use_dilation_ = use_dilation;
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this->use_tensorrt_ = use_tensorrt;
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this->precision_ = precision;
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std::string yaml_file_path = model_dir + "/inference.yml";
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std::ifstream yaml_file(yaml_file_path);
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if (yaml_file.is_open()) {
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std::string model_name;
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try {
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YAML::Node config = YAML::LoadFile(yaml_file_path);
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if (config["Global"] && config["Global"]["model_name"]) {
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model_name = config["Global"]["model_name"].as<std::string>();
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}
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if (!model_name.empty() && model_name != "PP-OCRv5_mobile_det" &&
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model_name != "PP-OCRv5_server_det") {
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std::cerr << "Error: " << model_name << " is currently not supported."
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<< std::endl;
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std::exit(EXIT_FAILURE);
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}
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} catch (const YAML::Exception &e) {
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std::cerr << "Failed to load YAML file: " << e.what() << std::endl;
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}
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}
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LoadModel(model_dir);
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}
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// Load Paddle inference model
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void LoadModel(const std::string &model_dir) noexcept;
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// Run predictor
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void Run(const cv::Mat &img,
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std::vector<std::vector<std::vector<int>>> &boxes,
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std::vector<double> ×) noexcept;
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private:
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std::shared_ptr<paddle_infer::Predictor> predictor_;
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bool use_gpu_ = false;
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int gpu_id_ = 0;
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int gpu_mem_ = 4000;
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int cpu_math_library_num_threads_ = 4;
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bool use_mkldnn_ = false;
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std::string limit_type_ = "max";
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int limit_side_len_ = 960;
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double det_db_thresh_ = 0.3;
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double det_db_box_thresh_ = 0.5;
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double det_db_unclip_ratio_ = 2.0;
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std::string det_db_score_mode_ = "slow";
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bool use_dilation_ = false;
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bool visualize_ = true;
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bool use_tensorrt_ = false;
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std::string precision_ = "fp32";
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std::vector<float> mean_ = {0.485f, 0.456f, 0.406f};
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std::vector<float> scale_ = {1 / 0.229f, 1 / 0.224f, 1 / 0.225f};
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bool is_scale_ = true;
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// pre-process
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ResizeImgType0 resize_op_;
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Normalize normalize_op_;
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Permute permute_op_;
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// post-process
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DBPostProcessor post_processor_;
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};
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} // namespace PaddleOCR
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