将mnist训练的caffemodel生成动态链接库DLL

在项目程序中经常看到动态链接库，非常好奇，想自己实现一下，于是乎尝试一波。就因为这种好奇，每天都被bug所困扰。。。

1. 训练caffemodel

在windows环境下搭建caffe无果，转投Ubuntu。。。

用的caffe--example--mnist中的文件，新建文件夹的话注意改路径，下面为train.sh

#!/usr/bin/env sh
set -e

/home/fish/caffe/build/tools/caffe train --solver=/home/fish/STUDY/lenet_solver.prototxt

训练好后把lenet_train_test.prototxt和训练好的模型lenet_iter_10000.caffemodel拿出来。

2. 使用cv::dnn里的API加载model，输入图片，进行测试（可跳过）

根据文章https://blog.csdn.net/sushiqian/article/details/78555891，修改模型文件。若图片为白底黑字，bitwise_not一下。

#include
#include <opencv2/opencv.hpp>
#include <opencv2/dnn.hpp>

using namespace std;
using namespace cv;
using namespace cv::dnn;

/* Find best class for the blob (i. e. class with maximal probability) */
static void getMaxClass(const Mat& probBlob, int* classId, double* classProb)
{
    Mat probMat = probBlob.reshape(1, 1);
    Point classNumber;
    minMaxLoc(probMat, NULL, classProb, NULL, &classNumber);
    *classId = classNumber.x;
}

int main(int argc, char* argv[])
{
    string modelTxt = "C:\\Users\\ATWER\\Desktop\\lenet_train_test.prototxt";
    string modelBin = "C:\\Users\\ATWER\\Desktop\\lenet_iter_10000.caffemodel";
    string imgFileName = "C:\\Users\\ATWER\\Desktop\\9.png";
    //read image
    Mat imgSrc = imread(imgFileName);
    if (imgSrc.empty()) {
        cout << "Failed to read image " << imgFileName << endl;
        exit(-1);
    }
    Mat img;
    cvtColor(imgSrc, img, COLOR_BGR2GRAY);
    //LeNet accepts 28*28 gray image
    resize(img, img, Size(28, 28));
    bitwise_not(img, img);
    img /= 255;

    //transfer image(1*28*28) to blob data with 4 dimensions(1*1*28*28)
    Mat inputBlob = dnn::blobFromImage(img);
    dnn::Net net;
    try {
        net = dnn::readNetFromCaffe(modelTxt, modelBin);
    }
    catch (cv::Exception& ee) {
        cerr << "Exception: " << ee.what() << endl;
        if (net.empty()) {
            cout << "Can't load the network by using the flowing files:" << endl;
            cout << "modelTxt: " << modelTxt << endl;
            cout << "modelBin: " << modelBin << endl; exit(-1);
        }
    }
    Mat pred;
    net.setInput(inputBlob, "data");//set the network input, "data" is the name of the input layer
    pred = net.forward("prob");//compute output, "prob" is the name of the output layer
    cout << pred << endl; int classId; double classProb; getMaxClass(pred, &classId, &classProb);
    cout << "Best Class: " << classId << endl;
    cout << "Probability: " << classProb * 100 << "%" << endl;
}

3. 创建动态链接库

参考https://blog.csdn.net/qq_30139555/article/details/103621955

class.h

#include
#include <opencv2/opencv.hpp>
#include <opencv2/dnn/dnn.hpp>

using namespace std;
using namespace cv;
using namespace cv::dnn;

extern "C" _declspec(dllexport) void Classfication(char* imgpath, char* result);

在此处卡的最久，原本我写的是Classfication(string imgpath, string result)，生成dll时没问题，调用时总是System.AccessViolationException: 尝试读取或写入受保护的内存。后来发现要写成指针的形式。

class.cpp

#include
#include <opencv2/opencv.hpp>
#include <opencv2/dnn/dnn.hpp>
#include "class.h"
using namespace std;
using namespace cv;
using namespace cv::dnn;

/* Find best class for the blob (i. e. class with maximal probability) */
static void getMaxClass(const Mat& probBlob, int* classId, double* classProb)
{
    Mat probMat = probBlob.reshape(1, 1);
    Point classNumber;
    minMaxLoc(probMat, NULL, classProb, NULL, &classNumber);
    *classId = classNumber.x;
}

void Classfication(char* imgpath, char* result)
{
    string res = "";
    string modelTxt = "C:\\Users\\ATWER\\Desktop\\lenet_train_test.prototxt";
    string modelBin = "C:\\Users\\ATWER\\Desktop\\lenet_iter_10000.caffemodel";
    //string imgFileName = "C:\\Users\\ATWER\\Desktop\\9.png";
    string imgFileName = imgpath;
    //read image
    Mat imgSrc = imread(imgFileName);
    if (imgSrc.empty()) {
        cout << "Failed to read image " << imgFileName << endl;
        exit(-1);
    }
    Mat img;
    cvtColor(imgSrc, img, COLOR_BGR2GRAY);
    //LeNet accepts 28*28 gray image
    resize(img, img, Size(28, 28));
    bitwise_not(img, img);
    img /= 255;

    //transfer image(1*28*28) to blob data with 4 dimensions(1*1*28*28)
    Mat inputBlob = dnn::blobFromImage(img);
    dnn::Net net;
    try {
        net = dnn::readNetFromCaffe(modelTxt, modelBin);
    }
    catch (cv::Exception& ee) {
        cerr << "Exception: " << ee.what() << endl;
        if (net.empty()) {
            cout << "Can't load the network by using the flowing files:" << endl;
            cout << "modelTxt: " << modelTxt << endl;
            cout << "modelBin: " << modelBin << endl; exit(-1);
        }
    }
    Mat pred;
    net.setInput(inputBlob, "data");//set the network input, "data" is the name of the input layer
    pred = net.forward("prob");//compute output, "prob" is the name of the output layer
    int classId; 
　　 double classProb; 
　　 getMaxClass(pred, &classId, &classProb);
    res += to_string(classId);
    res += '|';
    res += to_string(classProb);
    strcpy_s(result, 15, res.c_str());
}

4. 调用动态链接库

根据数据的长度申请非托管空间参考：https://blog.csdn.net/xiaoyong_net/article/details/50178021

文中说：“一定要加1,否则后面是乱码，原因未找到 ”，应该是打印字符串时会打印到“\n”为止，没有遇到\n会一直打印下去。.Length方法没有计算"\n"，+1的空间用于存放“\n”。

using System;
using System.Runtime.InteropServices;

namespace Test
{
    class Program
    {
        [DllImport("E:/c++project/caffedll/x64/Debug/caffedll.dll", EntryPoint = "Classfication")]

        unsafe private static extern void Classfication(IntPtr imgpath, IntPtr result);
        private static IntPtr mallocIntptr(string strData)
        {
            //先将字符串转化成字节方式
            Byte[] btData = System.Text.Encoding.Default.GetBytes(strData);
            //申请非拖管空间
            IntPtr m_ptr = Marshal.AllocHGlobal(btData.Length);
            //给非拖管空间清０
            Byte[] btZero = new Byte[btData.Length + 1]; //一定要加1,否则后面是乱码，原因未找到
            Marshal.Copy(btZero, 0, m_ptr, btZero.Length);
            //给指针指向的空间赋值
            Marshal.Copy(btData, 0, m_ptr, btData.Length);
            return m_ptr;
        }
        private static IntPtr mallocIntptr(int length)
        {
            //申请非拖管空间
            IntPtr m_ptr = Marshal.AllocHGlobal(length);
            //给非拖管空间清０
            Byte[] btZero = new Byte[length];
            Marshal.Copy(btZero, 0, m_ptr, btZero.Length);
            //给指针指向的空间赋值
            Marshal.Copy(btZero, 0, m_ptr, length);
            return m_ptr;
        }
        static void Main(string[] args)
        {
            string s = "C:\\Users\\ATWER\\Desktop\\9.png";
            IntPtr ptrFileName;
            IntPtr res;
            //根据数据的长度申请非托管空间
            ptrFileName = mallocIntptr(s);
            res = mallocIntptr(50);
            Classfication(ptrFileName, res);
            string result = Marshal.PtrToStringAnsi(res);
            string[] a = result.Split('|');
            Console.WriteLine("class:"+a[0]+"\n"+"score:"+a[1]);
            Marshal.FreeHGlobal(res);
        }
    }
}