Open Source Computer Vision Library https://opencv.org/
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#include "opencv2/core.hpp"
#include "opencv2/video/tracking.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/ml.hpp"
using namespace cv;
using namespace cv::ml;
struct Data
{
Mat img;
Mat samples; //Set of train samples. Contains points on image
Mat responses; //Set of responses for train samples
Data()
{
const int WIDTH = 841;
const int HEIGHT = 594;
img = Mat::zeros(HEIGHT, WIDTH, CV_8UC3);
imshow("Train svmsgd", img);
}
};
//Train with SVMSGD algorithm
//(samples, responses) is a train set
//weights is a required vector for decision function of SVMSGD algorithm
bool doTrain(const Mat samples, const Mat responses, Mat &weights, float &shift);
//function finds two points for drawing line (wx = 0)
bool findPointsForLine(const Mat &weights, float shift, Point points[], int width, int height);
// function finds cross point of line (wx = 0) and segment ( (y = HEIGHT, 0 <= x <= WIDTH) or (x = WIDTH, 0 <= y <= HEIGHT) )
bool findCrossPointWithBorders(const Mat &weights, float shift, const std::pair<Point,Point> &segment, Point &crossPoint);
//segments' initialization ( (y = HEIGHT, 0 <= x <= WIDTH) and (x = WIDTH, 0 <= y <= HEIGHT) )
void fillSegments(std::vector<std::pair<Point,Point> > &segments, int width, int height);
//redraw points' set and line (wx = 0)
void redraw(Data data, const Point points[2]);
//add point in train set, train SVMSGD algorithm and draw results on image
void addPointRetrainAndRedraw(Data &data, int x, int y, int response);
bool doTrain( const Mat samples, const Mat responses, Mat &weights, float &shift)
{
cv::Ptr<SVMSGD> svmsgd = SVMSGD::create();
cv::Ptr<TrainData> trainData = TrainData::create(samples, cv::ml::ROW_SAMPLE, responses);
svmsgd->train( trainData );
if (svmsgd->isTrained())
{
weights = svmsgd->getWeights();
shift = svmsgd->getShift();
return true;
}
return false;
}
void fillSegments(std::vector<std::pair<Point,Point> > &segments, int width, int height)
{
std::pair<Point,Point> currentSegment;
currentSegment.first = Point(width, 0);
currentSegment.second = Point(width, height);
segments.push_back(currentSegment);
currentSegment.first = Point(0, height);
currentSegment.second = Point(width, height);
segments.push_back(currentSegment);
currentSegment.first = Point(0, 0);
currentSegment.second = Point(width, 0);
segments.push_back(currentSegment);
currentSegment.first = Point(0, 0);
currentSegment.second = Point(0, height);
segments.push_back(currentSegment);
}
bool findCrossPointWithBorders(const Mat &weights, float shift, const std::pair<Point,Point> &segment, Point &crossPoint)
{
int x = 0;
int y = 0;
int xMin = std::min(segment.first.x, segment.second.x);
int xMax = std::max(segment.first.x, segment.second.x);
int yMin = std::min(segment.first.y, segment.second.y);
int yMax = std::max(segment.first.y, segment.second.y);
CV_Assert(weights.type() == CV_32FC1);
CV_Assert(xMin == xMax || yMin == yMax);
if (xMin == xMax && weights.at<float>(1) != 0)
{
x = xMin;
y = static_cast<int>(std::floor( - (weights.at<float>(0) * x + shift) / weights.at<float>(1)));
if (y >= yMin && y <= yMax)
{
crossPoint.x = x;
crossPoint.y = y;
return true;
}
}
else if (yMin == yMax && weights.at<float>(0) != 0)
{
y = yMin;
x = static_cast<int>(std::floor( - (weights.at<float>(1) * y + shift) / weights.at<float>(0)));
if (x >= xMin && x <= xMax)
{
crossPoint.x = x;
crossPoint.y = y;
return true;
}
}
return false;
}
bool findPointsForLine(const Mat &weights, float shift, Point points[2], int width, int height)
{
if (weights.empty())
{
return false;
}
int foundPointsCount = 0;
std::vector<std::pair<Point,Point> > segments;
fillSegments(segments, width, height);
for (uint i = 0; i < segments.size(); i++)
{
if (findCrossPointWithBorders(weights, shift, segments[i], points[foundPointsCount]))
foundPointsCount++;
if (foundPointsCount >= 2)
break;
}
return true;
}
void redraw(Data data, const Point points[2])
{
data.img.setTo(0);
Point center;
int radius = 3;
Scalar color;
CV_Assert((data.samples.type() == CV_32FC1) && (data.responses.type() == CV_32FC1));
for (int i = 0; i < data.samples.rows; i++)
{
center.x = static_cast<int>(data.samples.at<float>(i,0));
center.y = static_cast<int>(data.samples.at<float>(i,1));
color = (data.responses.at<float>(i) > 0) ? Scalar(128,128,0) : Scalar(0,128,128);
circle(data.img, center, radius, color, 5);
}
line(data.img, points[0], points[1],cv::Scalar(1,255,1));
imshow("Train svmsgd", data.img);
}
void addPointRetrainAndRedraw(Data &data, int x, int y, int response)
{
Mat currentSample(1, 2, CV_32FC1);
currentSample.at<float>(0,0) = (float)x;
currentSample.at<float>(0,1) = (float)y;
data.samples.push_back(currentSample);
data.responses.push_back(static_cast<float>(response));
Mat weights(1, 2, CV_32FC1);
float shift = 0;
if (doTrain(data.samples, data.responses, weights, shift))
{
Point points[2];
findPointsForLine(weights, shift, points, data.img.cols, data.img.rows);
redraw(data, points);
}
}
static void onMouse( int event, int x, int y, int, void* pData)
{
Data &data = *(Data*)pData;
switch( event )
{
case CV_EVENT_LBUTTONUP:
addPointRetrainAndRedraw(data, x, y, 1);
break;
case CV_EVENT_RBUTTONDOWN:
addPointRetrainAndRedraw(data, x, y, -1);
break;
}
}
int main()
{
Data data;
setMouseCallback( "Train svmsgd", onMouse, &data );
waitKey();
return 0;
}