static void Main()
{
Application.EnableVisualStyles();
Application.SetCompatibleTextRenderingDefault(false);
long matchTime; int Inliers = 10, OutLiers;
string mImage = "C:\\inetpub\\wwwroot\\memomface\\UserContent\\Member\\2\\1f99e8d4-be1d-4ca1-b094-67a45e298f65.JPG";
string oImage = "C:\\inetpub\\wwwroot\\memomface\\UserContent\\Album\\1\\45d2c5b1-2079-408a-af48-e60edad56f5f--IMG_0185-3.JPG";
//using(Image<Gray, Byte> modelImage = new Image<Gray, byte>("FaceBoy.jpg"))
//using (Image<Gray, Byte> observedImage = new Image<Gray, byte>("YesBoy.jpg"))
using (Image <Gray, Byte> modelImage = new Image <Gray, byte>(mImage))
using (Image <Gray, Byte> observedImage = new Image <Gray, byte>(oImage))
{
//Image<Bgr, byte> result = DrawMatches.Draw(modelImage, observedImage, out matchTime);
Image <Bgr, byte> result = BruteForceMatcher.Draw(modelImage, observedImage, out matchTime, out Inliers, out OutLiers);
ImageViewer.Show(result, String.Format("Matched using {0} in {1} milliseconds", GpuInvoke.HasCuda ? "GPU" : "CPU", matchTime));
}
}
public static FindMatchResult FindMatchInSource(MatchInput matchInput)
{
FindMatchResult matchResult = new FindMatchResult();
long matchTime; int inLiers, outLiers;
string MatchFolderPath, MatchFile, MatchAbsolutePath, MatchedFaceFile;
MatchFolderPath = MatchFile = MatchedFaceFile = MatchAbsolutePath = "";
//file folders assignment
MatchFolderPath = matchInput.WebFolderPath;
MatchAbsolutePath = matchInput.FindInFile.DirectoryName + "\\" + "MatchFiles";
using (Image <Gray, Byte> modelImage = new Image <Gray, byte>(matchInput.MatchFile.FullName))
using (Image <Gray, Byte> observedImage = new Image <Gray, byte>(matchInput.FindInFile.FullName))
{
Image <Bgr, byte> result = BruteForceMatcher.Draw(modelImage, observedImage, out matchTime, out inLiers, out outLiers);
//ImageViewer.Show(result, String.Format("Matched using {0} in {1} milliseconds", GpuInvoke.HasCuda ? "GPU" : "CPU", matchTime));
if (inLiers > matchInput.InlierThreshold)
{
matchResult.Matched = true;
MatchedFaceFile = Guid.NewGuid().ToString();
bool exists = System.IO.Directory.Exists(MatchAbsolutePath);
if (!exists)
{
System.IO.Directory.CreateDirectory(MatchAbsolutePath);
}
result.Save(MatchAbsolutePath + "\\" + MatchedFaceFile + matchInput.FindInFile.Extension);
}
matchResult.Inliers = inLiers;
matchResult.Outliers = outLiers;
matchResult.FolderPath = MatchFolderPath;
matchResult.AbsolutePath = MatchAbsolutePath + "\\";
matchResult.MatchedFaceFile = MatchedFaceFile;
}
return(matchResult);
}
public static void FindMatch(Image <Gray, Byte> modelImage, Image <Gray, byte> observedImage, out long matchTime, out VectorOfKeyPoint modelKeyPoints, out VectorOfKeyPoint observedKeyPoints, out Matrix <int> indices, out Matrix <byte> mask, out HomographyMatrix homography)
{
int k = 2;
double uniquenessThreshold = 0.8;
SURFDetector surfCPU = new SURFDetector(500, false);
Stopwatch watch;
homography = null;
if (GpuInvoke.HasCuda)
{
GpuSURFDetector surfGPU = new GpuSURFDetector(surfCPU.SURFParams, 0.01f);
using (GpuImage <Gray, Byte> gpuModelImage = new GpuImage <Gray, byte>(modelImage))
//extract features from the object image
using (GpuMat <float> gpuModelKeyPoints = surfGPU.DetectKeyPointsRaw(gpuModelImage, null))
using (GpuMat <float> gpuModelDescriptors = surfGPU.ComputeDescriptorsRaw(gpuModelImage, null, gpuModelKeyPoints))
using (GpuBruteForceMatcher <float> matcher = new GpuBruteForceMatcher <float>(DistanceType.L2))
{
modelKeyPoints = new VectorOfKeyPoint();
surfGPU.DownloadKeypoints(gpuModelKeyPoints, modelKeyPoints);
watch = Stopwatch.StartNew();
// extract features from the observed image
using (GpuImage <Gray, Byte> gpuObservedImage = new GpuImage <Gray, byte>(observedImage))
using (GpuMat <float> gpuObservedKeyPoints = surfGPU.DetectKeyPointsRaw(gpuObservedImage, null))
using (GpuMat <float> gpuObservedDescriptors = surfGPU.ComputeDescriptorsRaw(gpuObservedImage, null, gpuObservedKeyPoints))
using (GpuMat <int> gpuMatchIndices = new GpuMat <int>(gpuObservedDescriptors.Size.Height, k, 1, true))
using (GpuMat <float> gpuMatchDist = new GpuMat <float>(gpuObservedDescriptors.Size.Height, k, 1, true))
using (GpuMat <Byte> gpuMask = new GpuMat <byte>(gpuMatchIndices.Size.Height, 1, 1))
using (Stream stream = new Stream())
{
matcher.KnnMatchSingle(gpuObservedDescriptors, gpuModelDescriptors, gpuMatchIndices, gpuMatchDist, k, null, stream);
indices = new Matrix <int>(gpuMatchIndices.Size);
mask = new Matrix <byte>(gpuMask.Size);
//gpu implementation of voteForUniquess
using (GpuMat <float> col0 = gpuMatchDist.Col(0))
using (GpuMat <float> col1 = gpuMatchDist.Col(1))
{
GpuInvoke.Multiply(col1, new MCvScalar(uniquenessThreshold), col1, stream);
GpuInvoke.Compare(col0, col1, gpuMask, CMP_TYPE.CV_CMP_LE, stream);
}
observedKeyPoints = new VectorOfKeyPoint();
surfGPU.DownloadKeypoints(gpuObservedKeyPoints, observedKeyPoints);
//wait for the stream to complete its tasks
//We can perform some other CPU intesive stuffs here while we are waiting for the stream to complete.
stream.WaitForCompletion();
gpuMask.Download(mask);
gpuMatchIndices.Download(indices);
if (GpuInvoke.CountNonZero(gpuMask) >= 4)
{
int nonZeroCount = Features2DToolbox.VoteForSizeAndOrientation(modelKeyPoints, observedKeyPoints, indices, mask, 1.5, 20);
if (nonZeroCount >= 4)
{
homography = Features2DToolbox.GetHomographyMatrixFromMatchedFeatures(modelKeyPoints, observedKeyPoints, indices, mask, 2);
}
}
watch.Stop();
}
}
}
else
{
//extract features from the object image
modelKeyPoints = new VectorOfKeyPoint();
Matrix <float> modelDescriptors = surfCPU.DetectAndCompute(modelImage, null, modelKeyPoints);
watch = Stopwatch.StartNew();
// extract features from the observed image
observedKeyPoints = new VectorOfKeyPoint();
Matrix <float> observedDescriptors = surfCPU.DetectAndCompute(observedImage, null, observedKeyPoints);
BruteForceMatcher <float> matcher = new BruteForceMatcher <float>(DistanceType.L2);
matcher.Add(modelDescriptors);
indices = new Matrix <int>(observedDescriptors.Rows, k);
using (Matrix <float> dist = new Matrix <float>(observedDescriptors.Rows, k))
{
matcher.KnnMatch(observedDescriptors, indices, dist, k, null);
mask = new Matrix <byte>(dist.Rows, 1);
mask.SetValue(255);
Features2DToolbox.VoteForUniqueness(dist, uniquenessThreshold, mask);
}
int nonZeroCount = CvInvoke.cvCountNonZero(mask);
if (nonZeroCount >= 4)
{
nonZeroCount = Features2DToolbox.VoteForSizeAndOrientation(modelKeyPoints, observedKeyPoints, indices, mask, 1.5, 20);
if (nonZeroCount >= 4)
{
homography = Features2DToolbox.GetHomographyMatrixFromMatchedFeatures(modelKeyPoints, observedKeyPoints, indices, mask, 2);
}
}
watch.Stop();
}
matchTime = watch.ElapsedMilliseconds;
}
static void Run(string[] args, bool verboseShow)
{
// Dependency Injection to reuse all stuff developed so far
IKernel kernel = new StandardKernel();
DependencyInjection(kernel);
// service initializatons
var _albumInstanceDetailSvc = kernel.Get <IAlbumInstanceDetailService>();
var _albumInstanceSvc = kernel.Get <IAlbumInstanceService>();
var _memberSvc = kernel.Get <IMemberService>();
//class variable intializations
string MatchFolderPath, MatchFile;
IEnumerable <UserAlbumInstanceDetail> batchPhotos = _albumInstanceDetailSvc.GetPhotosForBatchProcssing();
Console.WriteLine("About to process {0} records", batchPhotos.Count().ToString());
if (batchPhotos.Count() > 0)
{
if (verboseShow)
{
Console.WriteLine("Total records retrieved for processing : {0}", batchPhotos.Count().ToString());
}
foreach (UserAlbumInstanceDetail batchPhoto in batchPhotos)
{
long ticks = DateTime.Now.Ticks;
if (verboseShow)
{
Console.WriteLine("Ticks-{0} : Processig record AlbumInstanceKey : {1}, MmeberKey : {2}, FaceToFind : {3}....", ticks.ToString(), batchPhoto.UserAlbumInstanceKey, batchPhoto.MemberKey, batchPhoto.FaceImage);
}
UserAlbumInstance photoImage = null;
Member member = null;
FindMatchResult findMatchResult = null;
MatchFolderPath = MatchFile = "";
photoImage = _albumInstanceSvc.FindAlbumInstance(batchPhoto.UserAlbumInstanceKey);
member = _memberSvc.FindMember(batchPhoto.MemberKey);
MatchInput matchInput = new MatchInput();
matchInput.FindInFile = new FileInfo(photoImage.AbsolutePath);
matchInput.MatchFile = new FileInfo(member.AbsoultePath + batchPhoto.FaceImage);
matchInput.WebFolderPath = photoImage.FolderPath + "MatchFiles";
if (verboseShow)
{
Console.WriteLine(JsonConvert.SerializeObject(matchInput, Formatting.Indented));
}
try
{
findMatchResult = BruteForceMatcher.FindMatchInSource(matchInput);
}
catch (Exception e)
{
Console.WriteLine("Error processing AlbumInstanceKey : {0}", batchPhoto.UserAlbumInstanceKey);
Console.Error.WriteLine("Exception");
Console.Error.WriteLine(e.Message);
Console.Error.WriteLine("Inner Exception");
Console.Error.WriteLine(e.InnerException.ToString());
}
finally
{
if (findMatchResult != null)
{
if (findMatchResult.Matched)
{
batchPhoto.FaceMatchFile = findMatchResult.MatchedFaceFile;
}
batchPhoto.Inliers = findMatchResult.Inliers;
batchPhoto.OpenCVMethod = findMatchResult.OpenCvMethod;
batchPhoto.FaceFound = findMatchResult.Matched;
batchPhoto.FolderPath = findMatchResult.FolderPath;
batchPhoto.AbsolutePath = findMatchResult.AbsolutePath;
batchPhoto.ProcessedOn = DateTime.Now;
batchPhoto.Processed = true;
_albumInstanceDetailSvc.Update(batchPhoto);
if (verboseShow)
{
Console.WriteLine("Ticks-{0} : Processed successfully AlbumInstanceKey : {1}, MmeberKey : {2}, FaceToFind : {3}....", ticks.ToString(), batchPhoto.UserAlbumInstanceKey, batchPhoto.MemberKey, batchPhoto.FaceImage);
}
}
}
}
}
}
public static void FindMatch(Image <Gray, Byte> modelImage, Image <Gray, byte> observedImage, out long matchTime, out VectorOfKeyPoint modelKeyPoints, out VectorOfKeyPoint observedKeyPoints, VectorOfVectorOfDMatch matches, out Matrix <byte> mask, out HomographyMatrix homography)
{
int k = 2;
double uniquenessThreshold = 0.8;
double hessianThresh = 300;
Stopwatch watch;
homography = null;
modelKeyPoints = new VectorOfKeyPoint();
observedKeyPoints = new VectorOfKeyPoint();
#if !IOS
if (CudaInvoke.HasCuda)
{
CudaSURFDetector surfCuda = new CudaSURFDetector((float)hessianThresh);
using (GpuMat gpuModelImage = new GpuMat(modelImage))
//extract features from the object image
using (GpuMat gpuModelKeyPoints = surfCuda.DetectKeyPointsRaw(gpuModelImage, null))
using (GpuMat gpuModelDescriptors = surfCuda.ComputeDescriptorsRaw(gpuModelImage, null, gpuModelKeyPoints))
using (CudaBruteForceMatcher matcher = new CudaBruteForceMatcher(DistanceType.L2))
{
surfCuda.DownloadKeypoints(gpuModelKeyPoints, modelKeyPoints);
watch = Stopwatch.StartNew();
// extract features from the observed image
using (GpuMat gpuObservedImage = new GpuMat(observedImage))
using (GpuMat gpuObservedKeyPoints = surfCuda.DetectKeyPointsRaw(gpuObservedImage, null))
using (GpuMat gpuObservedDescriptors = surfCuda.ComputeDescriptorsRaw(gpuObservedImage, null, gpuObservedKeyPoints))
//using (GpuMat tmp = new GpuMat())
//using (Stream stream = new Stream())
{
matcher.KnnMatch(gpuObservedDescriptors, gpuModelDescriptors, matches, k);
surfCuda.DownloadKeypoints(gpuObservedKeyPoints, observedKeyPoints);
mask = new Matrix <byte>(matches.Size, 1);
mask.SetValue(255);
Features2DToolbox.VoteForUniqueness(matches, uniquenessThreshold, mask);
int nonZeroCount = CvInvoke.CountNonZero(mask);
if (nonZeroCount >= 4)
{
nonZeroCount = Features2DToolbox.VoteForSizeAndOrientation(modelKeyPoints, observedKeyPoints,
matches, mask, 1.5, 20);
if (nonZeroCount >= 4)
{
homography = Features2DToolbox.GetHomographyMatrixFromMatchedFeatures(modelKeyPoints,
observedKeyPoints, matches, mask, 2);
}
}
}
watch.Stop();
}
}
else
#endif
{
using (UMat uModelImage = modelImage.Mat.ToUMat(AccessType.Read))
using (UMat uObservedImage = observedImage.Mat.ToUMat(AccessType.Read))
{
SURFDetector surfCPU = new SURFDetector(hessianThresh);
//extract features from the object image
UMat modelDescriptors = new UMat();
surfCPU.DetectAndCompute(uModelImage, null, modelKeyPoints, modelDescriptors, false);
watch = Stopwatch.StartNew();
// extract features from the observed image
UMat observedDescriptors = new UMat();
surfCPU.DetectAndCompute(uObservedImage, null, observedKeyPoints, observedDescriptors, false);
BruteForceMatcher matcher = new BruteForceMatcher(DistanceType.L2);
matcher.Add(modelDescriptors);
matcher.KnnMatch(observedDescriptors, matches, k, null);
mask = new Matrix <byte>(matches.Size, 1);
mask.SetValue(255);
Features2DToolbox.VoteForUniqueness(matches, uniquenessThreshold, mask);
int nonZeroCount = CvInvoke.CountNonZero(mask);
if (nonZeroCount >= 4)
{
nonZeroCount = Features2DToolbox.VoteForSizeAndOrientation(modelKeyPoints, observedKeyPoints,
matches, mask, 1.5, 20);
if (nonZeroCount >= 4)
{
homography = Features2DToolbox.GetHomographyMatrixFromMatchedFeatures(modelKeyPoints,
observedKeyPoints, matches, mask, 2);
}
}
watch.Stop();
}
}
matchTime = watch.ElapsedMilliseconds;
}
static void Run()
{
Image <Gray, Byte> modelImage = new Image <Gray, byte>("box.png");
Image <Gray, Byte> observedImage = new Image <Gray, byte>("box_in_scene.png");
Stopwatch watch;
HomographyMatrix homography = null;
SURFDetector surfCPU = new SURFDetector(500, false);
VectorOfKeyPoint modelKeyPoints;
VectorOfKeyPoint observedKeyPoints;
Matrix <int> indices;
Matrix <float> dist;
Matrix <byte> mask;
if (GpuInvoke.HasCuda)
{
GpuSURFDetector surfGPU = new GpuSURFDetector(surfCPU.SURFParams, 0.01f);
using (GpuImage <Gray, Byte> gpuModelImage = new GpuImage <Gray, byte>(modelImage))
//extract features from the object image
using (GpuMat <float> gpuModelKeyPoints = surfGPU.DetectKeyPointsRaw(gpuModelImage, null))
using (GpuMat <float> gpuModelDescriptors = surfGPU.ComputeDescriptorsRaw(gpuModelImage, null, gpuModelKeyPoints))
using (GpuBruteForceMatcher matcher = new GpuBruteForceMatcher(GpuBruteForceMatcher.DistanceType.L2))
{
modelKeyPoints = new VectorOfKeyPoint();
surfGPU.DownloadKeypoints(gpuModelKeyPoints, modelKeyPoints);
watch = Stopwatch.StartNew();
// extract features from the observed image
using (GpuImage <Gray, Byte> gpuObservedImage = new GpuImage <Gray, byte>(observedImage))
using (GpuMat <float> gpuObservedKeyPoints = surfGPU.DetectKeyPointsRaw(gpuObservedImage, null))
using (GpuMat <float> gpuObservedDescriptors = surfGPU.ComputeDescriptorsRaw(gpuObservedImage, null, gpuObservedKeyPoints))
using (GpuMat <int> gpuMatchIndices = new GpuMat <int>(gpuObservedDescriptors.Size.Height, 2, 1))
using (GpuMat <float> gpuMatchDist = new GpuMat <float>(gpuMatchIndices.Size, 1))
{
observedKeyPoints = new VectorOfKeyPoint();
surfGPU.DownloadKeypoints(gpuObservedKeyPoints, observedKeyPoints);
matcher.KnnMatch(gpuObservedDescriptors, gpuModelDescriptors, gpuMatchIndices, gpuMatchDist, 2, null);
indices = new Matrix <int>(gpuMatchIndices.Size);
dist = new Matrix <float>(indices.Size);
gpuMatchIndices.Download(indices);
gpuMatchDist.Download(dist);
mask = new Matrix <byte>(dist.Rows, 1);
mask.SetValue(255);
Features2DTracker.VoteForUniqueness(dist, 0.8, mask);
int nonZeroCount = CvInvoke.cvCountNonZero(mask);
if (nonZeroCount >= 4)
{
nonZeroCount = Features2DTracker.VoteForSizeAndOrientation(modelKeyPoints, observedKeyPoints, indices, mask, 1.5, 20);
if (nonZeroCount >= 4)
{
homography = Features2DTracker.GetHomographyMatrixFromMatchedFeatures(modelKeyPoints, observedKeyPoints, indices, mask, 3);
}
}
watch.Stop();
}
}
}
else
{
//extract features from the object image
modelKeyPoints = surfCPU.DetectKeyPointsRaw(modelImage, null);
//MKeyPoint[] kpts = modelKeyPoints.ToArray();
Matrix <float> modelDescriptors = surfCPU.ComputeDescriptorsRaw(modelImage, null, modelKeyPoints);
watch = Stopwatch.StartNew();
// extract features from the observed image
observedKeyPoints = surfCPU.DetectKeyPointsRaw(observedImage, null);
Matrix <float> observedDescriptors = surfCPU.ComputeDescriptorsRaw(observedImage, null, observedKeyPoints);
BruteForceMatcher matcher = new BruteForceMatcher(BruteForceMatcher.DistanceType.L2F32);
matcher.Add(modelDescriptors);
int k = 2;
indices = new Matrix <int>(observedDescriptors.Rows, k);
dist = new Matrix <float>(observedDescriptors.Rows, k);
matcher.KnnMatch(observedDescriptors, indices, dist, k, null);
mask = new Matrix <byte>(dist.Rows, 1);
mask.SetValue(255);
Features2DTracker.VoteForUniqueness(dist, 0.8, mask);
int nonZeroCount = CvInvoke.cvCountNonZero(mask);
if (nonZeroCount >= 4)
{
nonZeroCount = Features2DTracker.VoteForSizeAndOrientation(modelKeyPoints, observedKeyPoints, indices, mask, 1.5, 20);
if (nonZeroCount >= 4)
{
homography = Features2DTracker.GetHomographyMatrixFromMatchedFeatures(modelKeyPoints, observedKeyPoints, indices, mask, 3);
}
}
watch.Stop();
}
//Draw the matched keypoints
Image <Bgr, Byte> result = Features2DTracker.DrawMatches(modelImage, modelKeyPoints, observedImage, observedKeyPoints,
indices, new Bgr(255, 255, 255), new Bgr(255, 255, 255), mask, Features2DTracker.KeypointDrawType.NOT_DRAW_SINGLE_POINTS);
#region draw the projected region on the image
if (homography != null)
{ //draw a rectangle along the projected model
Rectangle rect = modelImage.ROI;
PointF[] pts = new PointF[] {
new PointF(rect.Left, rect.Bottom),
new PointF(rect.Right, rect.Bottom),
new PointF(rect.Right, rect.Top),
new PointF(rect.Left, rect.Top)
};
homography.ProjectPoints(pts);
result.DrawPolyline(Array.ConvertAll <PointF, Point>(pts, Point.Round), true, new Bgr(Color.Red), 5);
}
#endregion
ImageViewer.Show(result, String.Format("Matched using {0} in {1} milliseconds", GpuInvoke.HasCuda ? "GPU" : "CPU", watch.ElapsedMilliseconds));
}
