/// <summary> /// Detect keypoints in the OclImage /// </summary> /// <param name="img">The image where keypoints will be detected from</param> /// <param name="mask">The optional mask, can be null if not needed</param> /// <returns> /// The keypoints OclMat that will have 1 row. /// keypoints.at<float[6]>(1, i) contains i'th keypoint /// format: (x, y, size, response, angle, octave) /// </returns> public OclMat <float> DetectKeyPointsRaw(OclImage <Gray, Byte> img, OclImage <Gray, Byte> mask) { OclMat <float> result = new OclMat <float>(); OclInvoke.oclSURFDetectorDetectKeyPoints(_ptr, img, mask, result); return(result); }
/// <summary> /// Compute the descriptor given the image and the point location /// </summary> /// <param name="image">The image where the descriptor will be computed from</param> /// <param name="mask">The optional mask, can be null if not needed</param> /// <param name="keyPoints">The keypoint where the descriptor will be computed from. The order of the keypoints might be changed unless the GPU_SURF detector is UP-RIGHT.</param> /// <returns>The image features founded on the keypoint location</returns> public OclMat <float> ComputeDescriptorsRaw(OclImage <Gray, Byte> image, OclImage <Gray, byte> mask, OclMat <float> keyPoints) { OclMat <float> descriptors = new OclMat <float>(keyPoints.Size.Height, DescriptorSize, 1); OclInvoke.oclSURFDetectorCompute(_ptr, image, mask, keyPoints, descriptors, true); return(descriptors); }
/// <summary> /// Calculate an optical flow for a sparse feature set. /// </summary> /// <param name="frame0">First 8-bit input image (supports both grayscale and color images).</param> /// <param name="frame1">Second input image of the same size and the same type as <paramref name="frame0"/></param> /// <param name="points0"> /// Vector of 2D points for which the flow needs to be found. It must be one row /// matrix with 2 channels /// </param> /// <param name="points1"> /// Output vector of 2D points (with single-precision two channel floating-point coordinates) /// containing the calculated new positions of input features in the second image.</param> /// <param name="status"> /// Output status vector (CV_8UC1 type). Each element of the vector is set to 1 if the /// flow for the corresponding features has been found. Otherwise, it is set to 0. /// </param> /// <param name="err"> /// Output vector (CV_32FC1 type) that contains the difference between patches around /// the original and moved points or min eigen value if getMinEigenVals is checked. It can be /// null, if not needed. /// </param> public void Sparse(OclImage <Gray, byte> frame0, OclImage <Gray, byte> frame1, OclMat <float> points0, out OclMat <float> points1, out OclMat <Byte> status, out OclMat <float> err) { points1 = new OclMat <float>(); status = new OclMat <byte>(); err = new OclMat <float>(); OclInvoke.oclPyrLKOpticalFlowSparse(_ptr, frame0, frame1, points0, points1, status, err); }
/* * /// <summary> * /// Add the model descriptors * /// </summary> * /// <param name="modelDescriptors">The model discriptors</param> * public void Add(Matrix<Byte> modelDescriptors) * { * if (!(_distanceType == DistanceType.HammingDist)) * throw new ArgumentException("Hamming distance type requires model descriptor to be Matrix<Byte>"); * gpuBruteForceMatcherAdd(_ptr, modelDescriptors); * } * * /// <summary> * /// Add the model descriptors * /// </summary> * /// <param name="modelDescriptors">The model discriptors</param> * public void Add(Matrix<float> modelDescriptors) * { * if (!(_distanceType == DistanceType.L2 || _distanceType == DistanceType.L1)) * throw new ArgumentException("L1 / L2 distance type requires model descriptor to be Matrix<float>"); * gpuBruteForceMatcherAdd(_ptr, modelDescriptors); * }*/ /// <summary> /// Find the k nearest neighbour using the brute force matcher. /// </summary> /// <param name="queryDescriptors">The query descriptors</param> /// <param name="modelDescriptors">The model descriptors</param> /// <param name="modelIdx">The model index. A n x <paramref name="k"/> matrix where n = <paramref name="queryDescriptors"/>.Cols</param> /// <param name="distance">The matrix where the distance valus is stored. A n x <paramref name="k"/> matrix where n = <paramref name="queryDescriptors"/>.Size.Height</param> /// <param name="k">The number of nearest neighbours to be searched</param> /// <param name="mask">The mask</param> /// <param name="stream">Use a Stream to call the function asynchronously (non-blocking) or null to call the function synchronously (blocking).</param> public void KnnMatchSingle(OclMat <T> queryDescriptors, OclMat <T> modelDescriptors, OclMat <int> modelIdx, OclMat <float> distance, int k, OclMat <Byte> mask) { /* * if (k == 2 && !(modelIdx.IsContinuous && distance.IsContinuous)) * { * throw new ArgumentException("For k == 2, the allocated index matrix and distance matrix must be continuous"); * }*/ OclInvoke.oclBruteForceMatcherKnnMatchSingle(_ptr, queryDescriptors, modelDescriptors, modelIdx, distance, k, mask); }
/// <summary> /// Detect keypoints in the OclImage /// </summary> /// <param name="img">The image where keypoints will be detected from</param> /// <param name="mask">The optional mask, can be null if not needed</param> /// <returns>An array of keypoints</returns> public MKeyPoint[] DetectKeyPoints(OclImage <Gray, Byte> img, OclImage <Gray, Byte> mask) { using (OclMat <float> tmp = DetectKeyPointsRaw(img, mask)) using (VectorOfKeyPoint kpts = new VectorOfKeyPoint()) { DownloadKeypoints(tmp, kpts); return(kpts.ToArray()); } }
/// <summary> /// Obtain the keypoints array from OclMat /// </summary> /// <param name="src">The keypoints obtained from DetectKeyPointsRaw</param> /// <param name="dst">The vector of keypoints</param> public void DownloadKeypoints(OclMat <float> src, VectorOfKeyPoint dst) { OclInvoke.oclSURFDownloadKeypoints(_ptr, src, dst); }
/// <summary> /// Obtain an OclMat from the keypoints array /// </summary> /// <param name="src">The keypoints array</param> /// <param name="dst">An OclMat that represent the keypoints</param> public void UploadKeypoints(VectorOfKeyPoint src, OclMat <float> dst) { OclInvoke.oclSURFUploadKeypoints(_ptr, src, dst); }