OpenCV dnn模块支持Caffe

#include 
#include 
#include 
using namespace cv;
using namespace cv::dnn;
#include 
#include 
#include 
using namespace std;
/* Find best class for the blob (i. e. class with maximal probability) */
void getMaxClass(dnn::Blob &probBlob, int *classId, double *classProb)
{
	Mat probMat = probBlob.matRefConst().reshape(1, 1); //reshape the blob to 1x1000 matrix
	Point classNumber;
	minMaxLoc(probMat, NULL, classProb, NULL, &classNumber);
	*classId = classNumber.x;
}
std::vector readClassNames(const char *filename = "synset_words.txt")
{
	std::vector classNames;
	std::ifstream fp(filename);
	if (!fp.is_open())
	{
		std::cerr << "File with classes labels not found: " << filename << std::endl;
		exit(-1);
	}
	std::string name;
	while (!fp.eof())
	{
		std::getline(fp, name);
		if (name.length())
			classNames.push_back(name.substr(name.find(' ') + 1));
	}
	fp.close();
	return classNames;
}
int main(int argc, char **argv)
{
	String modelTxt = "bvlc_googlenet.prototxt";
	String modelBin = "bvlc_googlenet.caffemodel";
	String imageFile = (argc > 1) ? argv[1] : "space_shuttle.jpg";
	Ptr importer;
	try                                     //Try to import Caffe GoogleNet model
	{
		importer = dnn::createCaffeImporter(modelTxt, modelBin);
	}
	catch (const cv::Exception &err)        //Importer can throw errors, we will catch them
	{
		std::cerr << err.msg << std::endl;
	}
	if (!importer)
	{
		std::cerr << "Can't load network by using the following files: " << std::endl;
		std::cerr << "prototxt:   " << modelTxt << std::endl;
		std::cerr << "caffemodel: " << modelBin << std::endl;
		std::cerr << "bvlc_googlenet.caffemodel can be downloaded here:" << std::endl;
		std::cerr << "http://dl.caffe.berkeleyvision.org/bvlc_googlenet.caffemodel" << std::endl;
		exit(-1);
	}
	dnn::Net net;
	importer->populateNet(net);
	importer.release();                     //We don't need importer anymore
	Mat img = imread(imageFile);
	if (img.empty())
	{
		std::cerr << "Can't read image from the file: " << imageFile << std::endl;
		exit(-1);
	}
	resize(img, img, Size(224, 224));       //GoogLeNet accepts only 224x224 RGB-images
	dnn::Blob inputBlob = dnn::Blob(img);   //Convert Mat to dnn::Blob image batch
	net.setBlob(".data", inputBlob);        //set the network input
	net.forward();                          //compute output
	dnn::Blob prob = net.getBlob("prob");   //gather output of "prob" layer
	int classId;
	double classProb;
	getMaxClass(prob, &classId, &classProb);//find the best class
	std::vector classNames = readClassNames();
	std::cout << "Best class: #" << classId << " '" << classNames.at(classId) << "'" << std::endl;
	std::cout << "Probability: " << classProb * 100 << "%" << std::endl;
	return 0;
} //main

demo来自http://docs.opencv.org/master/d5/de7/tutorial_dnn_googlenet.html

应用会更加方便了