使用opencv dnn.hpp运行tensorflow模型以实现超分辨率

Question

#include "opencv2/core.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/videoio.hpp"
#include "opencv2/imgproc.hpp"
#include<opencv2/opencv.hpp>
#include<opencv2/dnn.hpp>
#include <iostream>

using namespace std;
using namespace cv;

const size_t inWidth = 300;
const size_t inHeight = 300;
const float WHRatio = inWidth / (float)inHeight;
const char* classNames\[\] = { "background","face" };
void saveMat(cv::Mat inputMat,char* filename);
int main() {

    String model = "opt_srcnn_vgg_test.pb";
    dnn::Net net = cv::dnn::readNetFromTensorflow(model);
    Mat img = imread("test.bmp");
    Mat input;
    img.copyTo(input);
    cvtColor(input,input,CV_BGR2GRAY);//turn the rgb to gray
    cout<<"load finish!"<<endl;
    Mat inputBlob = dnn::blobFromImage(input, 1./255, Size(img.cols, img.rows));
    imshow("input",input);
    waitKey(0);
    cout<<inputBlob.size;
    net.setInput(inputBlob, "input");//set the network input, 
    cout<<"feed finish!"<<endl;
    Mat pred = net.forward();
    resize(pred,pred,Size(img.cols,img.rows));
    imshow("result",pred);
    waitKey(0);
    return 0;
}

我们尝试使用opencv dnn使用tensorflow训练的.pb文件来实现超分辨率。我们的预期结果如图1所示，但我们得到了图2的结果（注意：我们确定.pb文件没有错误）。为什么是这样？谢谢！