private void QuerySurfAlgo(string queryImagePath)
{
WriteQueryStatus("Start querying...");
SaveSurfSettingValues();
SurfSettings surfSetting = GetSurfSetting();
List <ImageRecord> searchImage = new List <ImageRecord>();
bool didRepoLoadingtookplace = false;
long repoLoadingTimeInMs = 0;
if (!SurfRepository.IsRepositoryInMemoryLoaded(surfSetting.Algorithm))
{
didRepoLoadingtookplace = true;
WriteQueryStatus("Loading Repository in memory...");
_stopWatch = Stopwatch.StartNew();
SurfRepository.LoadRespositoryFromFile(surfSetting.Algorithm);
_stopWatch.Stop();
repoLoadingTimeInMs = _stopWatch.ElapsedMilliseconds;
WriteQueryStatus(string.Format("Repository loading took {0} ms", repoLoadingTimeInMs));
}
string msg;
if (surfSetting.Algorithm == SurfAlgo.Linear)
{
SurfQuery2 surfQuery = new SurfQuery2();
_stopWatch = Stopwatch.StartNew();
searchImage = surfQuery.QueryImage(queryImagePath, surfSetting);
_stopWatch.Stop();
if (didRepoLoadingtookplace)
{
msg = string.Format("Loading tooked {0} ms, quering tooked {1} ms", repoLoadingTimeInMs, _stopWatch.ElapsedMilliseconds);
}
else
{
msg = string.Format("Image Query Completed, it took {0} ms", _stopWatch.ElapsedMilliseconds);
}
WriteQueryStatus(msg);
}
else if (surfSetting.Algorithm == SurfAlgo.Flaan)
{
SurfQuery1 surfQuery = new SurfQuery1();
_stopWatch = Stopwatch.StartNew();
searchImage = surfQuery.QueryImage(queryImagePath, out msg, surfSetting);
_stopWatch.Stop();
if (didRepoLoadingtookplace)
{
msg = string.Format("Loading Repo: {0} ms, Quering Total {1} ms, Details - ", repoLoadingTimeInMs, _stopWatch.ElapsedMilliseconds) + msg;
}
else
{
msg += string.Format(" Total {0} ms", _stopWatch.ElapsedMilliseconds);
}
WriteQueryStatus(msg);
}
this.Dispatcher.Invoke(() =>
{
ImageList.ItemsSource = searchImage;
lblTotalCount.Text = searchImage.Count.ToString();
});
}
public void IndexFiles(FileInfo[] imageFiles, System.ComponentModel.BackgroundWorker IndexBgWorker,
Action <string> logWriter,
SurfSettings surfSetting = null)
{
#region Surf Dectator Region
double hessianThresh = 500;
double uniquenessThreshold = 0.8;
if (surfSetting != null)
{
hessianThresh = surfSetting.HessianThresh.Value;
uniquenessThreshold = surfSetting.UniquenessThreshold.Value;
}
SURFDetector surfDectector = new SURFDetector(hessianThresh, false);
#endregion
List <SURFRecord2> surfRecord2List = new List <SURFRecord2>();
Stopwatch sw1, sw2;
sw1 = Stopwatch.StartNew();
logWriter("Index started...");
int totalFileCount = imageFiles.Length;
for (int i = 0; i < totalFileCount; i++)
{
var fi = imageFiles[i];
using (Image <Gray, byte> observerImage = new Image <Gray, byte>(fi.FullName))
{
ImageFeature <float>[] observerFeatures = surfDectector.DetectFeatures(observerImage, null);
if (observerFeatures.Length > 4)
{
SURFRecord2 record = new SURFRecord2
{
Id = i,
ImageName = fi.Name,
ImagePath = fi.FullName,
observerFeatures = observerFeatures
};
surfRecord2List.Add(record);
}
else
{
Debug.WriteLine(fi.Name + " skip from index, because it didn't have significant feature");
}
}
IndexBgWorker.ReportProgress(i);
}
SurfRepository.AddSURFRecord2List(surfRecord2List);
sw1.Stop();
logWriter(string.Format("Index Complete, it tooked {0} ms. Saving Repository...", sw1.ElapsedMilliseconds));
sw2 = Stopwatch.StartNew();
SurfRepository.SaveRepository(SurfAlgo.Linear);
sw2.Stop();
logWriter(string.Format("Index tooked {0} ms. Saving Repository tooked {1} ms", sw1.ElapsedMilliseconds, sw2.ElapsedMilliseconds));
}
public List <ImageRecord> QueryImage(string queryImagePath, out string messageToLog, SurfSettings surfSetting = null)
{
List <ImageRecord> rtnImageList = new List <ImageRecord>();
#region Diagnostic Region
Stopwatch sw = new Stopwatch();
long IndexingTime = 0; long QueryingTime = 0; long LoopTime = 0;
#endregion Diagnostic Region
SurfDataSet observerDataset = SurfRepository.GetSurfDataSet();
if (observerDataset == null)
{
throw new InvalidOperationException("Can't get the Surf Index, please index first");
}
#region Surf Dectator Region
double hessianThresh = 500;
double uniquenessThreshold = 0.8;
if (surfSetting != null)
{
hessianThresh = surfSetting.HessianThresh.Value;
uniquenessThreshold = surfSetting.UniquenessThreshold.Value;
}
SURFDetector surfDectector = new SURFDetector(hessianThresh, false);
#endregion Surf Dectator Region
Matrix <float> modelDescriptors;
using (Image <Gray, byte> modelImage = new Image <Gray, byte>(queryImagePath))
{
VectorOfKeyPoint modelKeyPoints = new VectorOfKeyPoint();
modelDescriptors = surfDectector.DetectAndCompute(modelImage, null, modelKeyPoints);
if (modelDescriptors.Rows < 4)
{
throw new InvalidOperationException("Model image didn't have any significant features to detect");
}
Matrix <float> superMatrix = observerDataset.SuperMatrix;
sw.Start();
Emgu.CV.Flann.Index flannIndex;
if (!SurfRepository.Exists("flannIndex"))
{
flannIndex = new Emgu.CV.Flann.Index(superMatrix, 4);
SurfRepository.AddFlannIndex(flannIndex, "flannIndex");
}
else
{
flannIndex = SurfRepository.GetFlannIndex("flannIndex");
}
sw.Stop(); IndexingTime = sw.ElapsedMilliseconds; sw.Reset();
var indices = new Matrix <int>(modelDescriptors.Rows, 2); // matrix that will contain indices of the 2-nearest neighbors found
var dists = new Matrix <float>(modelDescriptors.Rows, 2); // matrix that will contain distances to the 2-nearest neighbors found
sw.Start();
flannIndex.KnnSearch(modelDescriptors, indices, dists, 2, 24);
sw.Stop(); QueryingTime = sw.ElapsedMilliseconds; sw.Reset();
List <SURFRecord1> imageList = observerDataset.SurfImageIndexRecord;
imageList.ForEach(x => x.Distance = 0);
//Create Interval Tree for Images
IntervalTreeHelper.CreateTree(imageList);
sw.Start();
for (int i = 0; i < indices.Rows; i++)
{
// filter out all inadequate pairs based on distance between pairs
if (dists.Data[i, 0] < (uniquenessThreshold * dists.Data[i, 1]))
{
var img = IntervalTreeHelper.GetImageforRange(indices[i, 0]);
if (img != null)
{
img.Distance++;
}
}
}
sw.Stop(); LoopTime = sw.ElapsedMilliseconds;
string msg = String.Format("Indexing: {0}, Querying: {1}, Looping: {2}", IndexingTime, QueryingTime, LoopTime);
messageToLog = msg;
rtnImageList = imageList.Where(x => x.Distance > surfSetting.GoodMatchThreshold).OrderByDescending(x => x.Distance).Select(x => (ImageRecord)x).ToList();
}
return(rtnImageList);
}
public void IndexFiles(FileInfo[] imageFiles, System.ComponentModel.BackgroundWorker IndexBgWorker,
Action <string> logWriter,
SurfSettings surfSetting = null)
{
#region Surf Dectator Region
double hessianThresh = 500;
double uniquenessThreshold = 0.8;
if (surfSetting != null)
{
hessianThresh = surfSetting.HessianThresh.Value;
uniquenessThreshold = surfSetting.UniquenessThreshold.Value;
}
SURFDetector surfDectector = new SURFDetector(hessianThresh, false);
#endregion
int rows = 0;
Matrix <float> superMatrix = null;
List <SURFRecord1> observerSurfImageIndexList = new List <SURFRecord1>();
Stopwatch sw1, sw2;
sw1 = Stopwatch.StartNew();
logWriter("Index started...");
int totalFileCount = imageFiles.Length;
for (int i = 0; i < totalFileCount; i++)
{
var fi = imageFiles[i];
using (Image <Gray, byte> observerImage = new Image <Gray, byte>(fi.FullName))
{
VectorOfKeyPoint observerKeyPoints = new VectorOfKeyPoint();
Matrix <float> observerDescriptor = surfDectector.DetectAndCompute(observerImage, null, observerKeyPoints);
if (observerDescriptor.Rows > 4)
{
int initRow = rows; int endRows = rows + observerDescriptor.Rows - 1;
SURFRecord1 record = new SURFRecord1
{
Id = i,
ImageName = fi.Name,
ImagePath = fi.FullName,
IndexStart = rows,
IndexEnd = endRows
};
observerSurfImageIndexList.Add(record);
if (superMatrix == null)
{
superMatrix = observerDescriptor;
}
else
{
superMatrix = superMatrix.ConcateVertical(observerDescriptor);
}
rows = endRows + 1;
}
else
{
Debug.WriteLine(fi.Name + " skip from index, because it didn't have significant feature");
}
}
IndexBgWorker.ReportProgress(i);
}
sw1.Stop();
logWriter(string.Format("Index Complete, it tooked {0} ms. Saving Repository...", sw1.ElapsedMilliseconds));
SurfDataSet surfDataset = new SurfDataSet
{
SurfImageIndexRecord = observerSurfImageIndexList,
SuperMatrix = superMatrix
};
sw2 = Stopwatch.StartNew();
SurfRepository.AddSuperMatrixList(surfDataset);
SurfRepository.SaveRepository(SurfAlgo.Flaan);
sw2.Stop();
logWriter(string.Format("Index tooked {0} ms. Saving Repository tooked {1} ms", sw1.ElapsedMilliseconds, sw2.ElapsedMilliseconds));
}
public List <ImageRecord> QueryImage(string queryImagePath, SurfSettings surfSetting = null)
{
List <ImageRecord> rtnImageList = new List <ImageRecord>();
var observerFeatureSets = SurfRepository.GetSurfRecordList();
#region Surf Dectator Region
double hessianThresh = 500;
double uniquenessThreshold = 0.8;
int minGoodMatchPercent = 50;
if (surfSetting != null)
{
hessianThresh = surfSetting.HessianThresh.Value;
uniquenessThreshold = surfSetting.UniquenessThreshold.Value;
minGoodMatchPercent = surfSetting.GoodMatchThreshold.Value;
}
SURFDetector surfDectector = new SURFDetector(hessianThresh, false);
#endregion
using (Image <Gray, byte> modelImage = new Image <Gray, byte>(queryImagePath))
{
ImageFeature <float>[] modelFeatures = surfDectector.DetectFeatures(modelImage, null);
if (modelFeatures.Length < 4)
{
throw new InvalidOperationException("Model image didn't have any significant features to detect");
}
Features2DTracker <float> tracker = new Features2DTracker <float>(modelFeatures);
foreach (var surfRecord in observerFeatureSets)
{
string queryImageName = System.IO.Path.GetFileName(queryImagePath);
string modelImageName = surfRecord.ImageName;
Features2DTracker <float> .MatchedImageFeature[] matchedFeatures = tracker.MatchFeature(surfRecord.observerFeatures, 2);
Features2DTracker <float> .MatchedImageFeature[] uniqueFeatures = Features2DTracker <float> .VoteForUniqueness(matchedFeatures, uniquenessThreshold);
Features2DTracker <float> .MatchedImageFeature[] uniqueRotOriFeatures = Features2DTracker <float> .VoteForSizeAndOrientation(uniqueFeatures, 1.5, 20);
int goodMatchCount = 0;
goodMatchCount = uniqueRotOriFeatures.Length;
bool isMatch = false;
double totalnumberOfModelFeature = modelFeatures.Length;
double matchPercentage = ((totalnumberOfModelFeature - (double)goodMatchCount) / totalnumberOfModelFeature);
matchPercentage = (1 - matchPercentage) * 100;
matchPercentage = Math.Round(matchPercentage);
if (matchPercentage >= minGoodMatchPercent)
{
HomographyMatrix homography =
Features2DTracker <float> .GetHomographyMatrixFromMatchedFeatures(uniqueRotOriFeatures);
if (homography != null)
{
isMatch = homography.IsValid(5);
if (isMatch)
{
surfRecord.Distance = matchPercentage;
rtnImageList.Add((ImageRecord)surfRecord);
}
}
}
//bool isMatch = false;
//if (uniqueFeatures.Length > 4)
//{
// HomographyMatrix homography =
// Features2DTracker<float>.GetHomographyMatrixFromMatchedFeatures(uniqueRotOriFeatures);
// if (homography != null)
// {
// isMatch = homography.IsValid(5);
// }
//}
//if (isMatch)
//{
// surfRecord.Distance = goodMatchCount;
// rtnImageList.Add((ImageRecord)surfRecord);
//}
//int goodMatchCount = 0;
//foreach (Features2DTracker<float>.MatchedImageFeature ms in matchedFeatures)
//{
// if (ms.SimilarFeatures[0].Distance < uniquenessThreshold)
// goodMatchCount++;
//}
//double totalnumberOfModelFeature = modelFeatures.Length;
//double matchPercentage = ((totalnumberOfModelFeature - (double)goodMatchCount) / totalnumberOfModelFeature);
//matchPercentage = (1 - matchPercentage) * 100;
//matchPercentage = Math.Round(matchPercentage);
//if (matchPercentage >= minGoodMatchPercent)
//{
// surfRecord.Distance = matchPercentage;
// rtnImageList.Add((ImageRecord)surfRecord);
//}
}
}
rtnImageList = rtnImageList.OrderByDescending(x => x.Distance).ToList();
return(rtnImageList);
}
