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			109 lines
		
	
	
		
			3.2 KiB
		
	
	
	
		
			C++
		
	
	
	
	
	
			
		
		
	
	
			109 lines
		
	
	
		
			3.2 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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| 
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| #pragma once
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| 
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| #include "opencv2/core.hpp"
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| #include "opencv2/imgcodecs.hpp"
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| #include "opencv2/imgproc.hpp"
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| #include "paddle_api.h"
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| #include "paddle_inference_api.h"
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| #include <chrono>
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| #include <iomanip>
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| #include <iostream>
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| #include <ostream>
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| #include <vector>
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| 
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| #include <cstring>
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| #include <fstream>
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| #include <numeric>
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| 
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| #include <include/postprocess_op.h>
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| #include <include/preprocess_op.h>
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| 
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| using namespace paddle_infer;
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| 
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| namespace PaddleOCR {
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| 
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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 int &max_side_len,
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|                       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 bool &use_polygon_score, const bool &visualize,
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|                       const bool &use_tensorrt, const std::string &precision) {
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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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| 
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|     this->max_side_len_ = max_side_len;
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| 
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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->use_polygon_score_ = use_polygon_score;
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| 
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|     this->visualize_ = visualize;
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|     this->use_tensorrt_ = use_tensorrt;
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|     this->precision_ = precision;
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| 
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|     LoadModel(model_dir);
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|   }
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| 
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|   // Load Paddle inference model
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|   void LoadModel(const std::string &model_dir);
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| 
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|   // Run predictor
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|   void Run(cv::Mat &img, std::vector<std::vector<std::vector<int>>> &boxes, std::vector<double> *times);
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| 
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| private:
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|   std::shared_ptr<Predictor> predictor_;
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| 
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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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| 
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|   int max_side_len_ = 960;
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| 
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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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|   bool use_polygon_score_ = false;
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| 
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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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| 
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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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| 
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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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| 
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|   // post-process
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|   PostProcessor post_processor_;
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| };
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| 
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| } // namespace PaddleOCR
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