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Add Java and Python code for ML tutorials.

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catree
2018-07-13 15:11:00 +02:00
parent 4dc7e617a4
commit 41b95cae38
15 changed files with 1141 additions and 180 deletions
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samples/cpp/tutorial_code/ml/introduction_to_svm/introduction_to_svm.cpp
+19 -20
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@@ -1,6 +1,6 @@
#include <opencv2/core.hpp>
#include <opencv2/imgproc.hpp>
#include "opencv2/imgcodecs.hpp"
#include <opencv2/imgcodecs.hpp>
#include <opencv2/highgui.hpp>
#include <opencv2/ml.hpp>
@@ -9,21 +9,16 @@ using namespace cv::ml;
int main(int, char**)
{
// Data for visual representation
int width = 512, height = 512;
Mat image = Mat::zeros(height, width, CV_8UC3);
// Set up training data
//! [setup1]
int labels[4] = {1, -1, -1, -1};
float trainingData[4][2] = { {501, 10}, {255, 10}, {501, 255}, {10, 501} };
//! [setup1]
//! [setup2]
Mat trainingDataMat(4, 2, CV_32FC1, trainingData);
Mat trainingDataMat(4, 2, CV_32F, trainingData);
Mat labelsMat(4, 1, CV_32SC1, labels);
//! [setup2]
// Train the SVM
//! [init]
Ptr<SVM> svm = SVM::create();
@@ -35,11 +30,16 @@ int main(int, char**)
svm->train(trainingDataMat, ROW_SAMPLE, labelsMat);
//! [train]
// Data for visual representation
int width = 512, height = 512;
Mat image = Mat::zeros(height, width, CV_8UC3);
// Show the decision regions given by the SVM
//! [show]
Vec3b green(0,255,0), blue (255,0,0);
for (int i = 0; i < image.rows; ++i)
for (int j = 0; j < image.cols; ++j)
Vec3b green(0,255,0), blue(255,0,0);
for (int i = 0; i < image.rows; i++)
{
for (int j = 0; j < image.cols; j++)
{
Mat sampleMat = (Mat_<float>(1,2) << j,i);
float response = svm->predict(sampleMat);
@@ -49,34 +49,33 @@ int main(int, char**)
else if (response == -1)
image.at<Vec3b>(i,j) = blue;
}
}
//! [show]
// Show the training data
//! [show_data]
int thickness = -1;
int lineType = 8;
circle( image, Point(501, 10), 5, Scalar( 0, 0, 0), thickness, lineType );
circle( image, Point(255, 10), 5, Scalar(255, 255, 255), thickness, lineType );
circle( image, Point(501, 255), 5, Scalar(255, 255, 255), thickness, lineType );
circle( image, Point( 10, 501), 5, Scalar(255, 255, 255), thickness, lineType );
circle( image, Point(501, 10), 5, Scalar( 0, 0, 0), thickness );
circle( image, Point(255, 10), 5, Scalar(255, 255, 255), thickness );
circle( image, Point(501, 255), 5, Scalar(255, 255, 255), thickness );
circle( image, Point( 10, 501), 5, Scalar(255, 255, 255), thickness );
//! [show_data]
// Show support vectors
//! [show_vectors]
thickness = 2;
lineType = 8;
Mat sv = svm->getUncompressedSupportVectors();
for (int i = 0; i < sv.rows; ++i)
for (int i = 0; i < sv.rows; i++)
{
const float* v = sv.ptr<float>(i);
circle( image, Point( (int) v[0], (int) v[1]), 6, Scalar(128, 128, 128), thickness, lineType);
circle(image, Point( (int) v[0], (int) v[1]), 6, Scalar(128, 128, 128), thickness);
}
//! [show_vectors]
imwrite("result.png", image); // save the image
imshow("SVM Simple Example", image); // show it to the user
waitKey(0);
waitKey();
return 0;
}