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dnn神经网络_OpenCv-C++-深度神经网络(DNN)模块-使用FCN模型实现图像分割

时间:2021/6/10 7:09:21|来源:|点击: 次

FCN是什么?中文名称是“全卷积网络”,它将传统CNN中的全连接层转化成一个个的卷积层。在传统的CNN结构中,前5层是卷积层,第6层和第7层分别是一个长度为4096的一维向量,第8层是长度为1000的一维向量,分别对应1000个类别的概率。如下图所示:

4924a21463c5c97a55902119045a93cc.png

实例:

#include

#include

#include

using namespace cv;

using namespace std;

using namespace cv::dnn;

const size_t width = 500;

const size_t height = 500;//定义图像文件宽高

vector labels_color();

string label_file = "D:/test/dnn/fcn/labelmap.txt";

string deploy_file = "D:/test/dnn/fcn/fcn8s-heavy-pascal.prototxt";

string model_file = "D:/test/dnn/fcn/fcn8s-heavy-pascal.caffemodel";

int main(int argc, char **argv)

{

Mat src = imread("D:/test/person_bike.jpg");

if (!src.data)

{

cout << "图像文件未找到!!!" << endl;

return -1;

}

resize(src, src, Size(500, 500), 0, 0);

vectorcolors = labels_color();

Net net;

net = readNetFromCaffe(deploy_file, model_file);//读取二进制文件和描述文件

float t1 = getTickCount();

Mat inputblob = blobFromImage(src);

net.setInput(inputblob, "data");

Mat score=net.forward("score");

float t2 = getTickCount();

float t = (t2 - t1) / getTickFrequency();

cout << "运行时间:" <

const int rows = score.size[2]; //图像的高

const int cols = score.size[3]; //图像的宽

const int chns = score.size[1]; //图像的通道数

Mat maxCl(rows, cols, CV_8UC1);

Mat maxVal(rows, cols, CV_32FC1);

for (int c = 0; c < chns; c++) {

for (int row = 0; row < rows; row++) {

const float *ptrScore = score.ptr(0, c, row);

uchar *ptrMaxCl = maxCl.ptr(row);

float *ptrMaxVal = maxVal.ptr(row);

for (int col = 0; col < cols; col++) {

if (ptrScore[col] > ptrMaxVal[col]) {

ptrMaxVal[col] = ptrScore[col];

ptrMaxCl[col] = (uchar)c;

}

}

}

}

// look up colors

Mat result = Mat::zeros(rows, cols, CV_8UC3);

for (int row = 0; row < rows; row++) {

const uchar *ptrMaxCl = maxCl.ptr(row);

Vec3b *ptrColor = result.ptr(row);

for (int col = 0; col < cols; col++) {

ptrColor[col] = colors[ptrMaxCl[col]];

}

}

Mat dst;

addWeighted(src, 0.3, result, 0.7, 0, dst); //图像合并

imshow("FCN-demo

相关资源:FCN模型实现图像分割配套资料分享.txt

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