// ##########################################################################################
// main() routine entry
// ##########################################################################################
int main( int argc, char** argv )
{
// --------------------------------------------------------------------------------------
// Variables
// --------------------------------------------------------------------------------------
int64 app_start_time = getTickCount();
int64 t;
string fileWithQueryImages, queryDirName, trainDirName;
string fileWithTrainImages;
string dirToSaveResImages;
string reportFile = "matchReport.html";
bool DEBUG;
int matchCount = 0;
double rank;
// --------------------------------------------------------------------------------------
// Argument check
// Application takes one argument of path to directory containing images.
// --------------------------------------------------------------------------------------
if(( argc == 1) || ( argc == 2))
{
readme();
return -1;
}
else if ( argc == 3 )
{
fileWithQueryImages = argv[1]; fileWithTrainImages = argv[2];
}
else if ( argc >= 4 )
{
fileWithQueryImages = argv[1]; fileWithTrainImages = argv[2];
for (int i = 3; i < argc; ++i)
{
if (string(argv[i]) == "--help" || string(argv[i]) == "/?")
{
readme();
return -1;
}
else if (string(argv[i]) == "--debug")
{
DEBUG = true;
}
else if (string(argv[i]) == "--gpu")
{
GPUMODE = true;
}
else if (string(argv[i]) == "--output")
{
reportFile = string(argv[i+1]);
}
}
}
// --------------------------------------------------------------------------------------
// Prepare output report file
// --------------------------------------------------------------------------------------
//string outputfilename = "matchreport-" + dt + ".html";
ofstream fout(reportFile);
//fout << std::string(dt) << endl;
std::time_t result = std::time(NULL);
/* old report format
fout << "Frog Image Match Report" << endl; // Log file output
if (DEBUG == true){
fout << "Ratio, conf, dist, minH: " << ratio << "\t" << confidence << "\t" << dist << "\t" << minHessian << endl;
}
fout << "Start " << std::asctime(std::localtime(&result)); // Log file output
*/
// HTML report begin
fout << "<html xmlns='http://www.w3.org/1999/xhtml' xml:lang='en' lang='en'>" << endl;;
fout << "<head> \n <meta http-equiv='content-type' content='text/html; charset=iso-8859-1' />" << endl;
fout << "<title>Wood Frog Match Report</title>" << endl;
fout << "<style type='text/css' media='screen'>@import 'includes/layout.css';</style>";
fout << "\n</head>" << endl;
fout << "\n<body>\n<div id='Header'>Frog Matching System</div>";
fout << "\n<div id='Content'>";
fout << "\n<h1>Frog Match Report</h1>";
fout << "\n<p><table width='643' border='0' cellspacing='5' cellpadding='5'>";
fout << "\n<tr>\n <td><B>Query Image</td>\n <td>Database Image</td>\n <td>Score</td>\n <td>Rank</B></td>\n </tr>";
fout << endl;
// --------------------------------------------------------------------------------------
// Begin image match sequence
// --------------------------------------------------------------------------------------
vector<string> queryImagesNames;
readSetFilenames(fileWithQueryImages, queryDirName, queryImagesNames);
// Iterate through query images OUTER LOOP
for ( size_t i = 0; i < queryImagesNames.size(); i++)
{
string queryfilename = queryDirName + queryImagesNames[i];
int innerCount=0;
t = getTickCount();
Mat image1 = imread( queryfilename, CV_LOAD_IMAGE_GRAYSCALE );
if( image1.empty() )
{
cout << "\n Error, couldn't read image filename " << queryfilename << endl;
return -1;
}
// --------------------------------------------------------------------------------------
// Loop through database images to test files against the outer loop one by one
// --------------------------------------------------------------------------------------
vector<string> trainImagesNames;
readSetFilenames(fileWithTrainImages, trainDirName, trainImagesNames);
// Iterate through train (database) images INNER LOOP
for ( size_t j = 0; j < trainImagesNames.size(); j++)
{
string trainfilename = trainDirName + trainImagesNames[j];
Mat image2 = imread( trainfilename, CV_LOAD_IMAGE_GRAYSCALE );
if (!image2.data)
return 0;
// ---------------------------------------------------------------------------------
// Prepare the matcher
// ---------------------------------------------------------------------------------
FrogMatcher fmatcher;
fmatcher.setConfidenceLevel(confidence);
fmatcher.setMinDistanceToEpipolar(dist);
fmatcher.setRatio(ratio);
fmatcher.setMinHess(minHessian);
if (GPUMODE == true)
{
//fout << "GPU mode ENABLED" << endl;
fmatcher.setGpu();
}
//fmatcher.setFeatureDetector(pfd);
//fmatcher.setDescriptorExtractor(extractor);
// ---------------------------------------------------------------------------------
// Match the two images
// ---------------------------------------------------------------------------------
std::cout << queryfilename << " : " << trainfilename << std::endl;
std::vector<cv::DMatch> matches;
std::vector<cv::KeyPoint> keypoints1, keypoints2;
//cv::Mat fundamental= fmatcher.match(image1,image2,matches, keypoints1, keypoints2);
Mat fundamental= fmatcher.match(image1,image2,matches, keypoints1, keypoints2);
if (matches.size()>0) {
// We have a match; draw the matches
cv::Mat imageMatches;
//Mat image1, image2;
//image1 = Mat(imageGpu1);
//image2 = Mat(imageGpu2);
/* -----------------------------------------------------------------------------
cv::drawMatches(image1,keypoints1, // 1st image and its keypoints
image2,keypoints2, // 2nd image and its keypoints
matches, // the matches
imageMatches, // the image produced
cv::Scalar(255,255,255)); // color of the lines
------------------------------------------------------------------------------- */
// Convert keypoints into Point2f
std::vector<cv::Point2f> points1, points2;
for (std::vector<cv::DMatch>::const_iterator it= matches.begin();
it!= matches.end(); ++it) {
// Get the position of left keypoints
float x= keypoints1[it->queryIdx].pt.x;
float y= keypoints1[it->queryIdx].pt.y;
points1.push_back(cv::Point2f(x,y));
cv::circle(image1,cv::Point(x,y),3,cv::Scalar(255,255,255),3);
// Get the position of right keypoints
x= keypoints2[it->trainIdx].pt.x;
y= keypoints2[it->trainIdx].pt.y;
cv::circle(image2,cv::Point(x,y),3,cv::Scalar(255,255,255),3);
points2.push_back(cv::Point2f(x,y));
}
// ---------------------------------------------------------------------------------
// Draw the epipolar lines
// ---------------------------------------------------------------------------------
std::vector<cv::Vec3f> lines1;
cv::computeCorrespondEpilines(cv::Mat(points1),1,fundamental,lines1);
for (std::vector<cv::Vec3f>::const_iterator it= lines1.begin();
it!=lines1.end(); ++it) {
cv::line(image2,cv::Point(0,-(*it)[2]/(*it)[1]),
cv::Point(image2.cols,-((*it)[2]+(*it)[0]*image2.cols)/(*it)[1]),
cv::Scalar(255,255,255));
}
std::vector<cv::Vec3f> lines2;
cv::computeCorrespondEpilines(cv::Mat(points2),2,fundamental,lines2);
for (std::vector<cv::Vec3f>::const_iterator it= lines2.begin();
it!=lines2.end(); ++it) {
cv::line(image1,cv::Point(0,-(*it)[2]/(*it)[1]),
cv::Point(image1.cols,-((*it)[2]+(*it)[0]*image1.cols)/(*it)[1]),
cv::Scalar(255,255,255));
}
Mat combinedImage = cvCreateMat(MAX(image1.rows,image2.rows), image1.cols + image2.cols, image1.type());
cv::Mat tmp = combinedImage(cv::Rect(0, 0, image1.cols, image1.rows));
image1.copyTo(tmp);
tmp = combinedImage(cv::Rect(image1.cols, 0, image2.cols, image2.rows));
image2.copyTo(tmp);
// ---------------------------------------------------------------------------------
// Output the combined image (epipolar lines matches)
// ---------------------------------------------------------------------------------
string outputFile = ".\\Output\\" + queryImagesNames[i] + ".matches." + trainImagesNames[j];
//string outimFile = ".\\Output\\" + myFileName + ".im." + myFileName2;
cv::imwrite(outputFile, combinedImage);
//cv::imwrite(outimFile, imageMatches);
// Write out filenames and 1 to indicate a match
double score1 = fmatcher.getScore();
double score2 = fmatcher.getScore2();
rank = score1/score2;
/* old output
fout << queryImagesNames[i] + "\t " + trainImagesNames[j] + "\t " << score1 << "\t " << rank;
if (DEBUG == true){
fout << "\t " << fmatcher.getFerr() << "\t " << fmatcher.getScore2();
}
fout << endl;
*/
fout << "\n<tr>\n <td>" + queryImagesNames[i] + "</td>\n <td>" + trainImagesNames[j] + "</td>\n <td>" << score1;
fout << "</td>\n <td>" << rank << "</td>\n </tr>" << endl;
}
else if (DEBUG == true){
// Write out filenames and 0 to indicate not a match
fout << queryImagesNames[i] + "\t " + trainImagesNames[j] + "\t 0" << "\t " << fmatcher.getScore() << endl;
}
matchCount += 1;
innerCount += 1;
} // end INNER LOOP
// Next iteration (same left image, next right image)
//Output Run time per iteration
//fout << queryfilename + "\t " + " run time (secs): " + "\t " + "\t " + "\t " + "\t " + "\t "<< ((getTickCount() - t) / getTickFrequency()) << "\n";
} // end OUTER LOOP
// Exit application
result = std::time(NULL);
/* Old report totals
fout << "Total Matches\t" << matchCount << endl;
fout << "Run time: " << ((getTickCount() - app_start_time) / getTickFrequency()); // Log file output
*/
// HTML report totals
fout << "\n</tr>\n</table>\n</p>";
fout << "\n<p>Image Pairs Analyzed: " << matchCount << endl;
fout << "</p>\n<p>Run time: " << ((getTickCount() - app_start_time) / getTickFrequency());
fout << "</p>\n</body></html>" << endl;
fout.close();
return 0;
}
