Open Source Computer Vision Library https://opencv.org/
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#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/objdetect/objdetect.hpp"
#include <iostream>
#include <fstream>
using namespace cv;
using namespace std;
#define SHOW_ALL_RECTS_BY_ONE 0
static void fillColors( vector<Scalar>& colors )
{
cv::RNG rng = theRNG();
for( size_t ci = 0; ci < colors.size(); ci++ )
colors[ci] = Scalar( rng(256), rng(256), rng(256) );
}
static void readTestImageNames( const string& descrFilename, vector<string>& names )
{
names.clear();
ifstream file( descrFilename.c_str() );
if ( !file.is_open() )
return;
while( !file.eof() )
{
string str; getline( file, str );
if( str.empty() ) break;
if( str[0] == '#' ) continue; // comment
names.push_back(str);
}
file.close();
}
// find -name "image_*.png" | grep -v mask | sed 's/.\///' >> images.txt
int main( int argc, char **argv )
{
if( argc != 1 && argc != 3 )
{
cout << "Format: train_data test_data; " << endl << "or without arguments to use default data" << endl;
return -1;
}
string baseDirName, testDirName;
if( argc == 1 )
{
baseDirName = "../../opencv/samples/cpp/dot_data/train/";
testDirName = "../../opencv/samples/cpp/dot_data/test/";
}
else
{
baseDirName = argv[1];
testDirName = argv[2];
baseDirName += (*(baseDirName.end()-1) == '/' ? "" : "/");
testDirName += (*(testDirName.end()-1) == '/' ? "" : "/");
}
DOTDetector::TrainParams trainParams;
trainParams.winSize = Size(84, 84);
trainParams.regionSize = 7;
trainParams.minMagnitude = 60; // we ignore pixels with magnitude less then minMagnitude
trainParams.maxStrongestCount = 7; // we find such count of strongest gradients for each region
trainParams.maxNonzeroBits = 6; // we filter very textured regions (that have more then maxUnzeroBits count of 1s (ones) in the template)
trainParams.minRatio = 0.85f;
// 1. Train detector
DOTDetector dotDetector;
dotDetector.train( baseDirName, trainParams, true );
// dotDetector.save( "../../dot.xml.gz" );
// dotDetector.load( "../../dot.xml.gz" );
const vector<string>& objectClassNames = dotDetector.getObjectClassNames();
const vector<DOTDetector::DOTTemplate>& dotTemplates = dotDetector.getDOTTemplates();
vector<Scalar> colors( objectClassNames.size() );
fillColors( colors );
cout << "Templates count " << dotTemplates.size() << endl;
vector<string> testFilenames;
readTestImageNames( testDirName + "images.txt", testFilenames );
if( testFilenames.empty() )
{
cout << "Can not read no one test images" << endl;
return -1;
}
// 2. Detect objects
DOTDetector::DetectParams detectParams;
detectParams.minRatio = 0.8f;
detectParams.minRegionSize = 5;
detectParams.maxRegionSize = 11;
#if SHOW_ALL_RECTS_BY_ONE
detectParams.isGroup = false;
#endif
for( size_t imgIdx = 0; imgIdx < testFilenames.size(); imgIdx++ )
{
string curFilename = testDirName + testFilenames[imgIdx];
cout << curFilename << endl;
Mat queryImage = imread( curFilename, 0 );
if( queryImage.empty() )
continue;
cout << "Detection start ..." << endl;
vector<vector<Rect> > rects;
#if SHOW_ALL_RECTS_BY_ONE
vector<vector<float> > ratios;
vector<vector<int> > dotTemlateIndices;
dotDetector.detectMultiScale( queryImage, rects, detectParams, &ratios, &dotTemlateIndices );
const vector<DOTDetector::DOTTemplate>& dotTemplates = dotDetector.getDOTTemplates();
#else
dotDetector.detectMultiScale( queryImage, rects, detectParams );
#endif
cout << "end" << endl;
Mat draw;
cvtColor( queryImage, draw, CV_GRAY2BGR );
const int textStep = 25;
for( size_t ci = 0; ci < objectClassNames.size(); ci++ )
{
putText( draw, objectClassNames[ci], Point(textStep, textStep*(1+ci)), 1, 2, colors[ci], 3 );
for( size_t ri = 0; ri < rects[ci].size(); ri++ )
{
rectangle( draw, rects[ci][ri], colors[ci], 3 );
#if SHOW_ALL_RECTS_BY_ONE
int dotTemplateIndex = dotTemlateIndices[ci][ri];
const DOTDetector::DOTTemplate::TrainData* trainData = dotTemplates[dotTemplateIndex].getTrainData(ci);
imshow( "maskedImage", trainData->maskedImage );
imshow( "strongestGradientsMask", trainData->strongestGradientsMask );
Mat scaledDraw;
cv::resize( draw, scaledDraw, Size(640, 480) );
imshow( "detection result", scaledDraw );
cv::waitKey();
#endif
}
}
Mat scaledDraw;
cv::resize( draw, scaledDraw, Size(640, 480) );
imshow( "detection result", scaledDraw );
cv::waitKey();
}
}