Win10 + C++ + Paddle编译成DLL C++调用OCR文字识别

继续上一篇

1，打开CMAKE3.23.3

第二个输出目录，如果没有相应文件夹创建一个

这里时CPU版本所以不要添加CUDA目录

依次点击configure、Generate、Open Project

2，生成dll

2.1，1、打开ppocr的项目属性并更改两个地方从exe改到dll


2.2.2、添加一个头文件ppocr.h
1，新建筛选器，命名为 头文件

2，右键筛选器，添加-》新建项

3，复制代码

#pragma once
///c+ +
#pragma once
#ifndef IMAGE_API
#define IMAGE_API

extern "C"
{
	// 图像推理
	__declspec(dllexport) char* ImageProcess(char* image_dir);
}
#endif
///

2.3.3、先注释掉main.cpp中的所有代码
2.4.4、添加以下代码

#include <string>
#include <iostream>
#include <vector>
#include <include/paddleocr.h>
#include <include/args.h>
#include "ppocr.h"
//#include <include/ppocr.h>

using namespace PaddleOCR;

PPOCR ocr; //PPOCR的对象

//处理图片的函数
char* ImageProcess(char* image_dir)
{
    std::vector<cv::String> cv_all_img_names;
    cv::glob(image_dir, cv_all_img_names);
    if (cv_all_img_names.size() > 1)
    {
        return "只支持单独图片识别！";
    }


    std::vector<std::vector<OCRPredictResult>> ocr_results =
        ocr.ocr(cv_all_img_names, FLAGS_det, FLAGS_rec, FLAGS_cls);
    auto ocr_result = ocr_results[0];
    std::string ret_str;
    for (int i = 0; i < ocr_result.size(); i++)
    {
        if (ocr_result[i].score != -1.0) {
            ret_str.append(ocr_result[i].text + "n");
        }
    }
    return const_cast<char*>(ret_str.c_str());
}

2.5.5、在args.cpp下更改一下默认参数，这里我将模型文件改成了和dll同目录下，这里也可以改成参数传入dll。

#include <gflags/gflags.h>

// common args
DEFINE_bool(use_gpu, false, "Infering with GPU or CPU.");
DEFINE_bool(use_tensorrt, false, "Whether use tensorrt.");
DEFINE_int32(gpu_id, 0, "Device id of GPU to execute.");
DEFINE_int32(gpu_mem, 4000, "GPU id when infering with GPU.");
DEFINE_int32(cpu_threads, 10, "Num of threads with CPU.");
DEFINE_bool(enable_mkldnn, false, "Whether use mkldnn with CPU.");
DEFINE_string(precision, "fp32", "Precision be one of fp32/fp16/int8");
DEFINE_bool(benchmark, false, "Whether use benchmark.");
DEFINE_string(output, "./output/", "Save benchmark log path.");
DEFINE_string(image_dir, "", "Dir of input image.");
DEFINE_string(
    type, "ocr",
    "Perform ocr or structure, the value is selected in ['ocr','structure'].");
// detection related
DEFINE_string(det_model_dir, "./models/ch_PP-OCRv3_det_infer", "Path of det inference model.");
DEFINE_int32(max_side_len, 960, "max_side_len of input image.");
DEFINE_double(det_db_thresh, 0.3, "Threshold of det_db_thresh.");
DEFINE_double(det_db_box_thresh, 0.6, "Threshold of det_db_box_thresh.");
DEFINE_double(det_db_unclip_ratio, 1.5, "Threshold of det_db_unclip_ratio.");
DEFINE_bool(use_dilation, false, "Whether use the dilation on output map.");
DEFINE_string(det_db_score_mode, "slow", "Whether use polygon score.");
DEFINE_bool(visualize, true, "Whether show the detection results.");
// classification related
DEFINE_bool(use_angle_cls, false, "Whether use use_angle_cls.");
DEFINE_string(cls_model_dir, "", "Path of cls inference model.");
DEFINE_double(cls_thresh, 0.9, "Threshold of cls_thresh.");
DEFINE_int32(cls_batch_num, 1, "cls_batch_num.");
// recognition related
DEFINE_string(rec_model_dir, "./models/ch_PP-OCRv3_rec_infer", "Path of rec inference model.");
DEFINE_int32(rec_batch_num, 6, "rec_batch_num.");
DEFINE_string(rec_char_dict_path, "./models/ppocr_keys_v1.txt",
              "Path of dictionary.");
DEFINE_int32(rec_img_h, 48, "rec image height");
DEFINE_int32(rec_img_w, 320, "rec image width");

// ocr forward related
DEFINE_bool(det, true, "Whether use det in forward.");
DEFINE_bool(rec, true, "Whether use rec in forward.");
DEFINE_bool(cls, false, "Whether use cls in forward.");

2.6.6、生成项目，一切顺利的话会得到一个ppocr.dll

3，测试DLL

3.1.编写一个测试的exe,把模型文件和DLL文件放在项目目录

#include <iostream>
#include <windows.h>

using namespace std;

int main()
{
	system("chcp 65001");
	HINSTANCE hDll = LoadLibrary(L"ppocr.dll");// 加载DLL库文件，DLL名称和路径用自己的
	if (hDll == NULL)
	{
		std::cout << "load dll fail n";
		return -1;
	}

	const auto ImageProcess{ reinterpret_cast<char* (*)(const char* image_dir)>(GetProcAddress(hDll, "ImageProcess")) };
	for (int xxd=0; xxd < 10; xxd++) {
		char* result2 = ImageProcess("./images/12.png");
		std::cout << result2;
		cout << "---------------------------------------------------------------" << endl;
	}
	

}

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