Cv_ANN_MLP ::裝載沒有給出正確的值，在異或程序中使用

Question

我想通過查找示例來了解Cv_ANN_MLP。這是我想出的。我想讓MultiLayer Perceptron爲異或問題尋找解決方案。訓練完CvANN_MLP類型的「mlp」後，我想將它保存到「mlp.yaml」文件中。這是節省，但當我加載它使用，它不起作用。

最後，有一個函數「void mlp（__）」。我嘗試評論「mlp.load」，訓練並保存它。後來我評論了「mlp.save」和「mlp.train」，但它不起作用。

謝謝！

完整的源代碼（使用OpenCV的2.3.1與代碼::塊）

#include <iostream> 
#include <math.h> 
#include <string> 
#include <opencv2/opencv.hpp> 

using namespace std; 
using namespace cv; 

void mlp(cv::Mat& trainingData, cv::Mat& trainingClasses, cv::Mat& testData, cv::Mat& testClasses); 


float evaluate(cv::Mat& predicted, cv::Mat& actual) { 
    assert(predicted.rows == actual.rows); 
    int t = 0; 
    int f = 0; 
    for(int i = 0; i < actual.rows; i++) { 
     float p = predicted.at<float>(i,0); 
     float a = actual.at<float>(i,0); 
     if((p >= 0.5 && a >= 0.5) || (p <= 0.5 && a <= 0.5)) { 
      t++; 
     } else { 
      f++; 
     } 
    } 
    cout<<endl<<"("<<t<<"/"<<t+f<<")"<<endl; 
    return (t * 1.0)/(t + f); 
} 


using namespace cv; 

int main(int argc, char* argv) 
{ 
    Mat trainingData(4, 2, CV_32FC1); 
    Mat testData(4, 2, CV_32FC1); 

    cv::Mat trainResult(trainingData.rows, 1, CV_32FC1); 
    cv::Mat testResult(trainingData.rows, 1, CV_32FC1); 


    trainingData.at<float>(0, 0) = 0; 
    trainingData.at<float>(0, 1) = 0; 
    trainResult.at<float>(0, 0) = 0; 

    trainingData.at<float>(1, 0) = 0; 
    trainingData.at<float>(1, 1) = 1; 
    trainResult.at<float>(1, 0) = 1; 

    trainingData.at<float>(2, 0) = 1; 
    trainingData.at<float>(2, 1) = 0; 
    trainResult.at<float>(2, 0) = 1; 

    trainingData.at<float>(3, 0) = 1; 
    trainingData.at<float>(3, 1) = 1; 
    trainResult.at<float>(3, 0) = 0; 


    cout<<"Training Data\n "<<trainingData<<"\n\n"; 
    cout<<"Training Result\n "<<trainResult<<"\n\n"; 

    testData.at<float>(0, 0) = 0; 
    testData.at<float>(0, 1) = 0; 
    testResult.at<float>(0, 0) = 0; 

    testData.at<float>(1, 0) = 0; 
    testData.at<float>(1, 1) = 1; 
    testResult.at<float>(1, 0) = 1; 

    testData.at<float>(2, 0) = 1; 
    testData.at<float>(2, 1) = 0; 
    testResult.at<float>(2, 0) = 1; 

    testData.at<float>(3, 0) = 1; 
    testData.at<float>(3, 1) = 1; 
    testResult.at<float>(3, 0) = 0; 

    cout<<"Test Data\n "<<testData<<"\n\n"; 
    cout<<"Test Result\n "<<testResult<<"\n\n"; 

    mlp(trainingData, trainResult, testData, testResult); 

    return 0; 
} 

void mlp(cv::Mat& trainingData, cv::Mat& trainingClasses, cv::Mat& testData, cv::Mat& testClasses) { 

    CvANN_MLP mlp; 
    CvANN_MLP_TrainParams params; 
    CvTermCriteria criteria; 

    mlp.load("mlp.yaml"); 

    cv::Mat layers = cv::Mat(4, 1, CV_32SC1); 


    layers.row(0) = cv::Scalar(2); 
    layers.row(1) = cv::Scalar(2); 
    layers.row(2) = cv::Scalar(15); 
    layers.row(3) = cv::Scalar(1); 



    criteria.max_iter = 300; 
    criteria.epsilon = 0.00001f; 
    criteria.type = CV_TERMCRIT_ITER | CV_TERMCRIT_EPS; 
    params.train_method = CvANN_MLP_TrainParams::BACKPROP; 
    params.bp_dw_scale = 0.05f; 
    params.bp_moment_scale = 0.05f; 
    params.term_crit = criteria; 

    mlp.create(layers); 


    mlp.train(trainingData, trainingClasses, cv::Mat(), cv::Mat(), params); 

    cv::Mat response(1, 1, CV_32FC1); 
    cv::Mat predicted(testClasses.rows, 1, CV_32F); 
    for(int i = 0; i < testData.rows; i++) { 
     cv::Mat response(1, 1, CV_32FC1); 
     cv::Mat sample = testData.row(i); 

     mlp.predict(sample, response); 
     predicted.at<float>(i,0) = response.at<float>(0,0); 

     cout<<testData.at<float>(i, 0)<<", "<<testData.at<float>(i, 1)<<" = "<<response.at<float>(0, 0)<<endl; 
    } 

    cout << "Accuracy_{MLP} = " << evaluate(predicted, testClasses) << endl; 



    mlp.save("mlp.yaml"); 
} 

Answer 1

一些更多的測試之後，我想通了。

註釋掉mlp.save（）也需要我評論mlp.create（）。

mlp.create（）是從文件加載後替換mlp對象的圖層。