C++ OpenCV调用caffe分类模型

OpenCV调用caffe分类模型-深度学习文档类资源-CSDN文库

源码

#include <iostream>
#include <fstream>
#include <sstream>
#include <opencv2/opencv.hpp>
#include <opencv2/dnn.hpp>
#include <time.h>

using namespace std;
using namespace cv;
using namespace ::dnn;
clock_t start, finish;

String model_file = "caffe/model/model.caffemodel";
String model_text = "caffe/model/deploy.prototxt";

double detect_NN(Mat detectImg, Net net)
{
	if (net.empty())
	{
		cout << "no model!" << endl;
		return -1;
	}
	Mat src = detectImg.clone();
	if (src.empty())
	{
		return -1;
	}

	start = clock();
	Mat inputBlob;
	inputBlob = blobFromImage(src, 1.0, Size(227, 227), Scalar(92.71, 106.44, 118.11));

	Mat prob;
	for (int i = 0; i < 1; i++)
	{
		net.setInput(inputBlob, "data");
		prob = net.forward("prob");
	}
	Mat probMat = prob.reshape(1, 1);
	Point classNumber;
	double classProb;
	minMaxLoc(probMat, NULL, &classProb, NULL, &classNumber);
	int classidx = classNumber.x;
	printf("classidx is:%d\n", classidx);
	printf("prob is %f\n", classProb);
	finish = clock();
	double duration = (double)(finish - start);
	printf("run time is %f ms\n", duration);
	return duration;
}

int main()
{
	Net net = readNetFromCaffe(model_text, model_file);
	Mat detectImg = imread("caffe/image/husky.jpg");
	double runTime = detect_NN(detectImg, net);
	system("pause");
	return 0;
}

测试图片 

运行结果 

查询ImageNet1000分类结果可得，编号250为Siberian husky