PaddleOCR/deploy/cpp_infer/include/ocr_det.h

106 lines
3.0 KiB
C++

// 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 "opencv2/core.hpp"
#include "opencv2/imgcodecs.hpp"
#include "opencv2/imgproc.hpp"
#include "paddle_api.h"
#include "paddle_inference_api.h"
#include <chrono>
#include <iomanip>
#include <iostream>
#include <ostream>
#include <vector>
#include <cstring>
#include <fstream>
#include <numeric>
#include <include/postprocess_op.h>
#include <include/preprocess_op.h>
using namespace paddle_infer;
namespace PaddleOCR {
class DBDetector {
public:
explicit DBDetector(const std::string &model_dir, const bool &use_gpu,
const int &gpu_id, const int &gpu_mem,
const int &cpu_math_library_num_threads,
const bool &use_mkldnn, const int &max_side_len,
const double &det_db_thresh,
const double &det_db_box_thresh,
const double &det_db_unclip_ratio, const bool &visualize,
const bool &use_tensorrt, const bool &use_fp16) {
this->use_gpu_ = use_gpu;
this->gpu_id_ = gpu_id;
this->gpu_mem_ = gpu_mem;
this->cpu_math_library_num_threads_ = cpu_math_library_num_threads;
this->use_mkldnn_ = use_mkldnn;
this->max_side_len_ = max_side_len;
this->det_db_thresh_ = det_db_thresh;
this->det_db_box_thresh_ = det_db_box_thresh;
this->det_db_unclip_ratio_ = det_db_unclip_ratio;
this->visualize_ = visualize;
this->use_tensorrt_ = use_tensorrt;
this->use_fp16_ = use_fp16;
LoadModel(model_dir);
}
// Load Paddle inference model
void LoadModel(const std::string &model_dir);
// Run predictor
void Run(cv::Mat &img, std::vector<std::vector<std::vector<int>>> &boxes);
private:
std::shared_ptr<Predictor> predictor_;
bool use_gpu_ = false;
int gpu_id_ = 0;
int gpu_mem_ = 4000;
int cpu_math_library_num_threads_ = 4;
bool use_mkldnn_ = false;
int max_side_len_ = 960;
double det_db_thresh_ = 0.3;
double det_db_box_thresh_ = 0.5;
double det_db_unclip_ratio_ = 2.0;
bool visualize_ = true;
bool use_tensorrt_ = false;
bool use_fp16_ = false;
std::vector<float> mean_ = {0.485f, 0.456f, 0.406f};
std::vector<float> 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
PostProcessor post_processor_;
};
} // namespace PaddleOCR