public IplImage Init(string fileName1)
{
_Obj = Cv.LoadImage(fileName1, LoadMode.GrayScale);
_ObjColor = Cv.CreateImage(_Obj.Size, BitDepth.U8, 3);
using (CvMemStorage storage = Cv.CreateMemStorage(0))
{
Cv.CvtColor(_Obj, _ObjColor, ColorConversion.GrayToBgr);
Stopwatch watch = Stopwatch.StartNew();
{
CvSURFParams param = new CvSURFParams(500, true);
Cv.ExtractSURF(_Obj, null, out _ObjectKeypoints, out _ObjectDescriptors, storage, param);
Console.WriteLine("Object Descriptors: {0}", _ObjectDescriptors.Total);
}
watch.Stop();
}
return _Obj;
}
/// <summary>
/// 画像中からSURF（Speeded Up Robust Features）を検出する
/// </summary>
/// <param name="image">8ビット，グレースケールの入力画像． </param>
/// <param name="mask">オプション：8ビットのマスク画像．非0 のマスクピクセルが50%以上を占める領域からのみ，特徴点検出を行う．</param>
/// <param name="keypoints">出力パラメータ．キーポイントのシーケンスへのポインタのポインタ． これは，CvSURFPoint 構造体のシーケンスになる</param>
/// <param name="descriptors">オプション：出力パラメータ．ディスクリプタのシーケンスへのポインタのポインタ． シーケンスの各要素は，params.extended の値に依存して， 64-要素，あるいは 128-要素の浮動小数点数（CV_32F）ベクトルとなる． パラメータが NULL の場合，ディスクリプタは計算されない．</param>
/// <param name="storage">キーポイントとディスクリプタが格納されるメモリストレージ</param>
/// <param name="param">CvSURFParams 構造体に入れられた，様々なアルゴリズムパラメータ</param>
/// <param name="useProvidedKeyPts">If useProvidedKeyPts!=0, keypoints are not detected, but descriptors are computed at the locations provided in keypoints (a CvSeq of CvSURFPoint).</param>
#else
/// <summary>
/// Extracts Speeded Up Robust Features from image
/// </summary>
/// <param name="image">The input 8-bit grayscale image. </param>
/// <param name="mask">The optional input 8-bit mask. The features are only found in the areas that contain more than 50% of non-zero mask pixels. </param>
/// <param name="keypoints">The output parameter; double pointer to the sequence of keypoints. This will be the sequence of CvSURFPoint structures.</param>
/// <param name="descriptors">The optional output parameter; double pointer to the sequence of descriptors; Depending on the params.extended value, each element of the sequence will be either 64-element or 128-element floating-point (CV_32F) vector. If the parameter is null, the descriptors are not computed. </param>
/// <param name="storage">Memory storage where keypoints and descriptors will be stored. </param>
/// <param name="param">Various algorithm parameters put to the structure CvSURFParams</param>
/// <param name="useProvidedKeyPts">If useProvidedKeyPts!=0, keypoints are not detected, but descriptors are computed at the locations provided in keypoints (a CvSeq of CvSURFPoint).</param>
#endif
public static void ExtractSURF(CvArr image, CvArr mask, ref CvSeq<CvSURFPoint> keypoints, out CvSeq<float> descriptors, CvMemStorage storage, CvSURFParams param, bool useProvidedKeyPts)
{
if (image == null)
throw new ArgumentNullException("img");
if (storage == null)
throw new ArgumentNullException("img");
IntPtr maskPtr = (mask == null) ? IntPtr.Zero : mask.CvPtr;
IntPtr descriptorsPtr = IntPtr.Zero;
IntPtr keypointsPtr = IntPtr.Zero;
if (useProvidedKeyPts)
{
keypoints = new CvSeq<CvSURFPoint>(SeqType.Zero, storage);
keypointsPtr = keypoints.CvPtr;
CvInvoke.cvExtractSURF(image.CvPtr, maskPtr, ref keypointsPtr, ref descriptorsPtr, storage.CvPtr, param.Struct, useProvidedKeyPts);
descriptors = new CvSeq<float>(descriptorsPtr);
}
else
{
CvInvoke.cvExtractSURF(image.CvPtr, maskPtr, ref keypointsPtr, ref descriptorsPtr, storage.CvPtr, param.Struct, useProvidedKeyPts);
keypoints = new CvSeq<CvSURFPoint>(keypointsPtr);
descriptors = new CvSeq<float>(descriptorsPtr);
}
}
/// <summary>
/// 画像中からSURF（Speeded Up Robust Features）を検出する
/// </summary>
/// <param name="image">8ビット，グレースケールの入力画像． </param>
/// <param name="mask">オプション：8ビットのマスク画像．非0 のマスクピクセルが50%以上を占める領域からのみ，特徴点検出を行う．</param>
/// <param name="keypoints">出力パラメータ．キーポイントのシーケンスへのポインタのポインタ． これは，CvSURFPoint 構造体のシーケンスになる</param>
/// <param name="descriptors">オプション：出力パラメータ．ディスクリプタのシーケンスへのポインタのポインタ． シーケンスの各要素は，params.extended の値に依存して， 64-要素，あるいは 128-要素の浮動小数点数（CV_32F）ベクトルとなる． パラメータが NULL の場合，ディスクリプタは計算されない．</param>
/// <param name="storage">キーポイントとディスクリプタが格納されるメモリストレージ</param>
/// <param name="param">CvSURFParams 構造体に入れられた，様々なアルゴリズムパラメータ</param>
#else
/// <summary>
/// Extracts Speeded Up Robust Features from image
/// </summary>
/// <param name="image">The input 8-bit grayscale image. </param>
/// <param name="mask">The optional input 8-bit mask. The features are only found in the areas that contain more than 50% of non-zero mask pixels. </param>
/// <param name="keypoints">The output parameter; double pointer to the sequence of keypoints. This will be the sequence of CvSURFPoint structures.</param>
/// <param name="descriptors">The optional output parameter; double pointer to the sequence of descriptors; Depending on the params.extended value, each element of the sequence will be either 64-element or 128-element floating-point (CV_32F) vector. If the parameter is null, the descriptors are not computed. </param>
/// <param name="storage">Memory storage where keypoints and descriptors will be stored. </param>
/// <param name="param">Various algorithm parameters put to the structure CvSURFParams</param>
#endif
public static void ExtractSURF(CvArr image, CvArr mask, out CvSeq<CvSURFPoint> keypoints, out CvSeq<float> descriptors, CvMemStorage storage, CvSURFParams param)
{
keypoints = null;
ExtractSURF(image, mask, ref keypoints, out descriptors, storage, param, false);
}
public SURFSample()
{
// cvExtractSURF
// SURFで対応点検出
// call cv::initModule_nonfree() before using SURF/SIFT.
CvCpp.InitModule_NonFree();
using (IplImage obj = Cv.LoadImage(Const.ImageSurfBox, LoadMode.GrayScale))
using (IplImage image = Cv.LoadImage(Const.ImageSurfBoxinscene, LoadMode.GrayScale))
using (IplImage objColor = Cv.CreateImage(obj.Size, BitDepth.U8, 3))
using (IplImage correspond = Cv.CreateImage(new CvSize(image.Width, obj.Height + image.Height), BitDepth.U8, 1))
{
Cv.CvtColor(obj, objColor, ColorConversion.GrayToBgr);
Cv.SetImageROI(correspond, new CvRect(0, 0, obj.Width, obj.Height));
Cv.Copy(obj, correspond);
Cv.SetImageROI(correspond, new CvRect(0, obj.Height, correspond.Width, correspond.Height));
Cv.Copy(image, correspond);
Cv.ResetImageROI(correspond);
// SURFの処理
CvSURFPoint[] objectKeypoints, imageKeypoints;
float[][] objectDescriptors, imageDescriptors;
Stopwatch watch = Stopwatch.StartNew();
{
CvSURFParams param = new CvSURFParams(500, true);
Cv.ExtractSURF(obj, null, out objectKeypoints, out objectDescriptors, param);
Console.WriteLine("Object Descriptors: {0}", objectDescriptors.Length);
Cv.ExtractSURF(image, null, out imageKeypoints, out imageDescriptors, param);
Console.WriteLine("Image Descriptors: {0}", imageDescriptors.Length);
}
watch.Stop();
Console.WriteLine("Extraction time = {0}ms", watch.ElapsedMilliseconds);
watch.Reset();
watch.Start();
// シーン画像にある局所画像の領域を線で囲む
CvPoint[] srcCorners = new CvPoint[4]
{
new CvPoint(0, 0), new CvPoint(obj.Width, 0), new CvPoint(obj.Width, obj.Height), new CvPoint(0, obj.Height)
};
CvPoint[] dstCorners = LocatePlanarObject(objectKeypoints, objectDescriptors, imageKeypoints, imageDescriptors, srcCorners);
if (dstCorners != null)
{
for (int i = 0; i < 4; i++)
{
CvPoint r1 = dstCorners[i%4];
CvPoint r2 = dstCorners[(i + 1)%4];
Cv.Line(correspond, new CvPoint(r1.X, r1.Y + obj.Height), new CvPoint(r2.X, r2.Y + obj.Height), CvColor.White);
}
}
// 対応点同士を線で引く
int[] ptPairs = FindPairs(objectKeypoints, objectDescriptors, imageKeypoints, imageDescriptors);
for (int i = 0; i < ptPairs.Length; i += 2)
{
CvSURFPoint r1 = objectKeypoints[ptPairs[i]];
CvSURFPoint r2 = imageKeypoints[ptPairs[i + 1]];
Cv.Line(correspond, r1.Pt, new CvPoint(Cv.Round(r2.Pt.X), Cv.Round(r2.Pt.Y + obj.Height)), CvColor.White);
}
// 特徴点の場所に円を描く
for (int i = 0; i < objectKeypoints.Length; i++)
{
CvSURFPoint r = objectKeypoints[i];
CvPoint center = new CvPoint(Cv.Round(r.Pt.X), Cv.Round(r.Pt.Y));
int radius = Cv.Round(r.Size*(1.2/9.0)*2);
Cv.Circle(objColor, center, radius, CvColor.Red, 1, LineType.AntiAlias, 0);
}
watch.Stop();
Console.WriteLine("Drawing time = {0}ms", watch.ElapsedMilliseconds);
// ウィンドウに表示
using (CvWindow windowObject = new CvWindow("Object", WindowMode.AutoSize))
using (CvWindow windowCorrespond = new CvWindow("Object Correspond", WindowMode.AutoSize))
{
windowObject.ShowImage(correspond);
windowCorrespond.ShowImage(objColor);
Cv.WaitKey(0);
}
}
}
private static float[][] ExtractSurfDescriptors(IntPtr descriptorsPtr, CvSURFParams param)
{
CvSeq<IntPtr> descriptorsSeq = new CvSeq<IntPtr>(descriptorsPtr);
float[][] descriptors = new float[descriptorsSeq.Total][];
int dim = (param.Extended) ? 128 : 64;
for (int i = 0; i < descriptorsSeq.Total; i++)
{
descriptors[i] = new float[dim];
IntPtr? ptr = descriptorsSeq[i];
if (ptr.HasValue)
Marshal.Copy(ptr.Value, descriptors[i], 0, dim);
}
return descriptors;
}
/// <summary>
/// 画像中からSURF（Speeded Up Robust Features）を検出する
/// </summary>
/// <param name="image">8ビット，グレースケールの入力画像． </param>
/// <param name="mask">オプション：8ビットのマスク画像．非0 のマスクピクセルが50%以上を占める領域からのみ，特徴点検出を行う．</param>
/// <param name="keypoints">出力パラメータ．キーポイントのシーケンスへのポインタのポインタ． これは，CvSURFPoint 構造体のシーケンスになる</param>
/// <param name="descriptors">オプション：出力パラメータ．ディスクリプタのシーケンスへのポインタのポインタ． シーケンスの各要素は，params.extended の値に依存して， 64-要素，あるいは 128-要素の浮動小数点数（CV_32F）ベクトルとなる． パラメータが NULL の場合，ディスクリプタは計算されない．</param>
/// <param name="param">CvSURFParams 構造体に入れられた，様々なアルゴリズムパラメータ</param>
/// <param name="useProvidedKeyPts">If useProvidedKeyPts!=0, keypoints are not detected, but descriptors are computed at the locations provided in keypoints (a CvSeq of CvSURFPoint).</param>
#else
/// <summary>
/// Extracts Speeded Up Robust Features from image
/// </summary>
/// <param name="image">The input 8-bit grayscale image. </param>
/// <param name="mask">The optional input 8-bit mask. The features are only found in the areas that contain more than 50% of non-zero mask pixels. </param>
/// <param name="keypoints">The output parameter; double pointer to the sequence of keypoints. This will be the sequence of CvSURFPoint structures.</param>
/// <param name="descriptors">The optional output parameter; double pointer to the sequence of descriptors; Depending on the params.extended value, each element of the sequence will be either 64-element or 128-element floating-point (CV_32F) vector. If the parameter is null, the descriptors are not computed. </param>
/// <param name="param">Various algorithm parameters put to the structure CvSURFParams</param>
/// <param name="useProvidedKeyPts">If useProvidedKeyPts!=0, keypoints are not detected, but descriptors are computed at the locations provided in keypoints (a CvSeq of CvSURFPoint).</param>
#endif
public static void ExtractSURF(CvArr image, CvArr mask, ref CvSURFPoint[] keypoints, out float[][] descriptors, CvSURFParams param, bool useProvidedKeyPts)
{
if (!useProvidedKeyPts)
{
ExtractSURF(image, mask, out keypoints, out descriptors, param);
return;
}
if (image == null)
throw new ArgumentNullException("image");
if (param == null)
throw new ArgumentNullException("param");
if (keypoints == null)
throw new ArgumentNullException("keypoints");
using (CvMemStorage storage = new CvMemStorage(0))
using (CvSeq <CvSURFPoint> keypointsSeqIn = CvSeq<CvSURFPoint>.FromArray(keypoints, SeqType.Zero, storage))
{
IntPtr maskPtr = (mask == null) ? IntPtr.Zero : mask.CvPtr;
IntPtr descriptorsPtr = IntPtr.Zero;
IntPtr keypointsPtr = keypointsSeqIn.CvPtr;
NativeMethods.cvExtractSURF(image.CvPtr, maskPtr, ref keypointsPtr, ref descriptorsPtr, storage.CvPtr, param.Struct, false);
CvSeq<CvSURFPoint> keypointsSeqOut = new CvSeq<CvSURFPoint>(keypointsPtr);
keypoints = keypointsSeqOut.ToArray();
descriptors = ExtractSurfDescriptors(descriptorsPtr, param);
}
}
/// <summary>
/// 画像中からSURF（Speeded Up Robust Features）を検出する
/// </summary>
/// <param name="image">8ビット，グレースケールの入力画像． </param>
/// <param name="mask">オプション：8ビットのマスク画像．非0 のマスクピクセルが50%以上を占める領域からのみ，特徴点検出を行う．</param>
/// <param name="keypoints">出力パラメータ．キーポイントのシーケンスへのポインタのポインタ． これは，CvSURFPoint 構造体のシーケンスになる</param>
/// <param name="descriptors">オプション：出力パラメータ．ディスクリプタのシーケンスへのポインタのポインタ． シーケンスの各要素は，params.extended の値に依存して， 64-要素，あるいは 128-要素の浮動小数点数（CV_32F）ベクトルとなる． パラメータが NULL の場合，ディスクリプタは計算されない．</param>
/// <param name="param">CvSURFParams 構造体に入れられた，様々なアルゴリズムパラメータ</param>
#else
/// <summary>
/// Extracts Speeded Up Robust Features from image
/// </summary>
/// <param name="image">The input 8-bit grayscale image. </param>
/// <param name="mask">The optional input 8-bit mask. The features are only found in the areas that contain more than 50% of non-zero mask pixels. </param>
/// <param name="keypoints">The output parameter; double pointer to the sequence of keypoints. This will be the sequence of CvSURFPoint structures.</param>
/// <param name="descriptors">The optional output parameter; double pointer to the sequence of descriptors; Depending on the params.extended value, each element of the sequence will be either 64-element or 128-element floating-point (CV_32F) vector. If the parameter is null, the descriptors are not computed. </param>
/// <param name="param">Various algorithm parameters put to the structure CvSURFParams</param>
#endif
public static void ExtractSURF(CvArr image, CvArr mask, out CvSURFPoint[] keypoints, out float[][] descriptors, CvSURFParams param)
{
if (image == null)
throw new ArgumentNullException("image");
if (param == null)
throw new ArgumentNullException("param");
using (CvMemStorage storage = new CvMemStorage(0))
{
IntPtr maskPtr = (mask == null) ? IntPtr.Zero : mask.CvPtr;
IntPtr descriptorsPtr = IntPtr.Zero;
IntPtr keypointsPtr = IntPtr.Zero;
NativeMethods.cvExtractSURF(image.CvPtr, maskPtr, ref keypointsPtr, ref descriptorsPtr, storage.CvPtr, param.Struct, false);
CvSeq<CvSURFPoint> keypointsSeq = new CvSeq<CvSURFPoint>(keypointsPtr);
keypoints = keypointsSeq.ToArray();
descriptors = ExtractSurfDescriptors(descriptorsPtr, param);
}
}
public IplImage Test(string fileName2)
{
IplImage correspond = null;
using (CvMemStorage storage = Cv.CreateMemStorage(0))
using (IplImage image = Cv.LoadImage(fileName2, LoadMode.GrayScale))
{
correspond = Cv.CreateImage(new CvSize(image.Width, _Obj.Height + image.Height), BitDepth.U8, 1);
Cv.SetImageROI(correspond, new CvRect(0, 0, _Obj.Width, _Obj.Height));
Cv.Copy(_Obj, correspond);
Cv.SetImageROI(correspond, new CvRect(0, _Obj.Height, correspond.Width, correspond.Height));
Cv.Copy(image, correspond);
Cv.ResetImageROI(correspond);
// SURFの処理
CvSeq<CvSURFPoint> imageKeypoints;
CvSeq<float> imageDescriptors;
Stopwatch watch = Stopwatch.StartNew();
{
CvSURFParams param = new CvSURFParams(500, true);
Cv.ExtractSURF(image, null, out imageKeypoints, out imageDescriptors, storage, param);
Console.WriteLine("Image Descriptors: {0}", imageDescriptors.Total);
}
watch.Stop();
Console.WriteLine("Extraction time = {0}ms", watch.ElapsedMilliseconds);
watch.Reset();
watch.Start();
// シーン画像にある局所画像の領域を線で囲む
CvPoint[] srcCorners = new CvPoint[4]{
new CvPoint(0,0), new CvPoint(_Obj.Width,0), new CvPoint(_Obj.Width, _Obj.Height), new CvPoint(0, _Obj.Height)
};
CvPoint[] dstCorners = LocatePlanarObject(_ObjectKeypoints, _ObjectDescriptors, imageKeypoints, imageDescriptors, srcCorners);
if (dstCorners != null)
{
for (int i = 0; i < 4; i++)
{
CvPoint r1 = dstCorners[i % 4];
CvPoint r2 = dstCorners[(i + 1) % 4];
Cv.Line(correspond, new CvPoint(r1.X, r1.Y + _Obj.Height), new CvPoint(r2.X, r2.Y + _Obj.Height), CvColor.White);
}
}
// 対応点同士を線で引く
int[] ptpairs = FindPairs(_ObjectKeypoints, _ObjectDescriptors, imageKeypoints, imageDescriptors);
for (int i = 0; i < ptpairs.Length; i += 2)
{
CvSURFPoint r1 = Cv.GetSeqElem<CvSURFPoint>(_ObjectKeypoints, ptpairs[i]).Value;
CvSURFPoint r2 = Cv.GetSeqElem<CvSURFPoint>(imageKeypoints, ptpairs[i + 1]).Value;
Cv.Line(correspond, r1.Pt, new CvPoint(Cv.Round(r2.Pt.X), Cv.Round(r2.Pt.Y + _Obj.Height)), CvColor.White);
}
// 特徴点の場所に円を描く
for (int i = 0; i < _ObjectKeypoints.Total; i++)
{
CvSURFPoint r = Cv.GetSeqElem<CvSURFPoint>(_ObjectKeypoints, i).Value;
CvPoint center = new CvPoint(Cv.Round(r.Pt.X), Cv.Round(r.Pt.Y));
int radius = Cv.Round(r.Size * (1.2 / 9.0) * 2);
Cv.Circle(_ObjColor, center, radius, CvColor.Red, 1, LineType.AntiAlias, 0);
}
watch.Stop();
Console.WriteLine("Drawing time = {0}ms", watch.ElapsedMilliseconds);
}
return correspond;
}
