OpenCV神经网络ANN代码编译运行与解读（二）

川长思鸟来 2021-12-18 22:07 353阅读 0赞

【转载自】《[OpenCV笔记（4）实现神经网络（ANN）][OpenCV_4_ANN]》  
作者的原文参考了：《[OpenCV中使用神经网络 CvANN\_MLP][OpenCV_ CvANN_MLP]》

实际上的预测结果是并非一个确定值，所以即使用训练集去做测试，也可能出现不完全匹配的情况。（后续需进一步实验证实）

备份代码在此：

#include <stdio.h>
    #include "opencv2/core/core.hpp"
    #include "opencv2/imgproc/imgproc.hpp"
    #include "opencv2/imgcodecs/imgcodecs.hpp"
    #include "opencv2/highgui/highgui.hpp"
    #include "opencv2/ml/ml.hpp"
     
    using namespace cv;
    using namespace ml;
    using namespace std;
     
    int main()
    {
    	int width = 512, height = 512;
    	Mat img = Mat::zeros(height, width, CV_8UC3);
     
    	//建立训练样本
    	float train_data[6][2] = {
       {500,60},{245,40},{480,250},{160,380},{400,25},{55,400}};
    	float labels[6] = { 0, 0, 0, 1, 0, 1 }; 
    	Mat train_data_mat(6, 2, CV_32FC1, train_data);
    	Mat labels_mat(6, 1, CV_32FC1, labels);
    	Mat layers_size = (Mat_<int>(1, 3) << 2, 6, 1);
     
    	//模型创建和参数设置
    	Ptr<ml::ANN_MLP> ann = ml::ANN_MLP::create();//创建一个空模型
    	ann->setLayerSizes(layers_size);
    	ann->setTrainMethod(ml::ANN_MLP::BACKPROP, 0.1, 0.1);
    	ann->setActivationFunction(ml::ANN_MLP::SIGMOID_SYM);
    	ann->setTermCriteria(TermCriteria(TermCriteria::MAX_ITER, 10000, 1e-6));
     
    	//设置训练数据并训练分类器
    	Ptr<TrainData> tData = TrainData::create(train_data_mat, ROW_SAMPLE, labels_mat);
    	ann->train(tData);
     
    	//显示分类的结果
    	Vec3b green(0, 255, 0), blue(255, 0, 0);
    	for (int i = 0; i<img.rows; ++i) 
    	{
    		for (int j = 0; j<img.cols; ++j) 
    		{
    			Mat sample_mat = (Mat_<float>(1, 2) << j, i);
    			Mat response_mat;
    			ann->predict(sample_mat, response_mat);
    			float response = response_mat.ptr<float>(0)[0];
    			if (response > 0.5) 
    			{
    				img.at<Vec3b>(i, j) = green;
    			}
    			else if (response < 0.5) 
    			{
    				img.at<Vec3b>(i, j) = blue;
    			}
    		}
    	}
     
    	//画出训练样本数据
    	int thickness = -1;
    	int lineType = 8;
    	circle(img, Point(500, 60), 5, Scalar(255, 255, 255), thickness, lineType);
    	circle(img, Point(245, 40), 5, Scalar(255, 255, 255), thickness, lineType);
    	circle(img, Point(480, 250), 5, Scalar(255, 255, 255), thickness, lineType);
    	circle(img, Point(160, 380), 5, Scalar(0, 0, 255), thickness, lineType);
    	circle(img, Point(400, 25), 5, Scalar(255, 255, 255), thickness, lineType);
    	circle(img, Point(55, 400), 5, Scalar(0, 0, 255), thickness, lineType);
          
    	imshow("Example", img);
    	waitKey(0);
    }

[OpenCV_4_ANN]: https://blog.csdn.net/qq_41051855/article/details/79923635
[OpenCV_ CvANN_MLP]: https://blog.csdn.net/xiaowei_cqu/article/details/9027617