caffe ni c++ da ishlatish

caffec++

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

int main(int argc, char** argv) {
    // Load input image.
    cv::Mat inputMat = cv::imread("accordion.jpg");
    inputMat.convertTo(inputMat, CV_32F);  // Cast to floats
    cv::resize(inputMat, inputMat, cv::Size(227, 227));  // Resize.
    // Convert from interleaved image (BGRBGR) to planar with swapped channels (RRRGGGBBB).
    inputMat = cv::dnn::blobFromImage(inputMat);

    // Load Caffe model using Caffe.
    caffe::Caffe::set_mode(caffe::Caffe::CPU);
    caffe::Net<float> caffeNet("bvlc_alexnet.prototxt", caffe::TEST);
    caffeNet.CopyTrainedLayersFrom("bvlc_alexnet.caffemodel");

    // Load Caffe model using DNN.
    cv::dnn::Net dnnNet = cv::dnn::readNetFromCaffe("bvlc_alexnet.prototxt",
                                                    "bvlc_alexnet.caffemodel");

    // Run Caffe model using Caffe.
    caffe::Blob<float>* caffeInput = caffeNet.input_blobs()[0];
    // Wrap Caffe's input blob to cv::Mat.
    cv::Mat caffeInputMat(caffeInput->shape(), CV_32F, (char*)caffeInput->cpu_data());
    // Copy image.
    inputMat.copyTo(caffeInputMat);

    caffe::Blob<float>* caffeOut = caffeNet.Forward()[0];

    // Run Caffe model using DNN.
    dnnNet.setInput(inputMat);
    cv::Mat dnnOut = dnnNet.forward();

    // Print results.
    cv::Mat caffeOutMat(caffeOut->shape(), CV_32F, (char*)caffeOut->cpu_data());

    cv::Point classNumber;
    double classProb;
    cv::minMaxLoc(caffeOutMat, NULL, &classProb, NULL, &classNumber);
    std::cout << "caffe: " << classNumber.x << " " << classProb << std::endl;

    cv::minMaxLoc(dnnOut, NULL, &classProb, NULL, &classNumber);
    std::cout << "dnn: " << classNumber.x << " " << classProb << std::endl;

ref : opencv/opencv#9427