コード例 #1
0
ファイル: SampleForm.cs プロジェクト: ipud2/OpenGL.Net-1
        private void SampleForm_FormClosing(object sender, FormClosingEventArgs e)
        {
            // Query graph performance using VX_GRAPH_PERFORMANCE and print timing
            // in milliseconds. Note that time units of vx_perf_t fields are nanoseconds.
            Perf perfHarris = new Perf(), perfTrack = new Perf();

            VX.Query(_GraphHarris, GraphAttribute.Performance, out perfHarris);
            VX.Query(_GraphTrack, GraphAttribute.Performance, out perfTrack);

            // Release all the OpenVX objects created in this exercise, and make the context as the last one to release.
            // To release an OpenVX object, you need to call vxRelease<Object> API which takes a pointer to the object.
            // If the release operation is successful, the OpenVX framework will reset the object to NULL.

            VX.Release(ref _Context);
        }
コード例 #2
0
ファイル: SampleForm.cs プロジェクト: ipud2/OpenGL.Net-1
        private void SampleForm_Load(object sender, EventArgs e)
        {
            #region Corner Tracking Initialization

            uint                width = 1024, height = 1024;
            UIntPtr             max_keypoint_count      = (UIntPtr)10000;           // maximum number of keypoints to track
            float               harris_strength_thresh  = 0.0005f;                  // minimum corner strength to keep a corner
            float               harris_min_distance     = 5.0f;                     // radial L2 distance for non-max suppression
            float               harris_sensitivity      = 0.04f;                    // multiplier k in det(A) - k * trace(A)^2
            int                 harris_gradient_size    = 3;                        // window size for gradient computation
            int                 harris_block_size       = 3;                        // block window size for Harris corner score
            UIntPtr             lk_pyramid_levels       = (UIntPtr)6;               // number of pyramid levels for optical flow
            float               lk_pyramid_scale        = VX.SCALE_PYRAMID_HALF;    // pyramid levels scale by factor of two
            TerminationCriteria lk_termination          = TerminationCriteria.Both; // iteration termination criteria (eps & iterations)
            float               lk_epsilon              = 0.01f;                    // convergence criterion
            uint                lk_num_iterations       = 5;                        // maximum number of iterations
            bool                lk_use_initial_estimate = false;                    // don't use initial estimate
            uint                lk_window_dimension     = 6;                        // window size for evaluation
            float               trackable_kp_ratio_thr  = 0.8f;                     // threshold for the ration of tracked keypoints to all

            // Create the OpenVX context and make sure the returned context is valid.
            _Context = VX.CreateContext();

            // Create OpenVX image object for input RGB image.
            _ImageInput = VX.CreateImage(_Context, width, height, DfImage.Rgb);

            // OpenVX optical flow functionality requires image pyramids for the current
            // and the previous image. It also requires keypoints that correspond
            // to the previous pyramid and will output updated keypoints into
            // another keypoint array. To be able to toggle between the current and
            // the previous buffers, you need to use OpenVX delay objects and vxAgeDelay().
            // Create OpenVX pyramid and array object exemplars and create OpenVX delay
            // objects for both to hold two of each. Note that the exemplar objects are not
            // needed once the delay objects are created.
            using (Pyramid pyramid = VX.CreatePyramid(_Context, lk_pyramid_levels, lk_pyramid_scale, width, height, DfImage.U8))
                _PyramidDelay = VX.CreateDelay(_Context, pyramid, (UIntPtr)2);

            using (OpenVX.Array keypoints = VX.CreateArray(_Context, OpenVX.Type.Keypoint, max_keypoint_count))
                _KeypointsDelay = VX.CreateDelay(_Context, keypoints, (UIntPtr)2);


            // An object from a delay slot can be accessed using vxGetReferenceFromDelay API.
            // You need to use index = 0 for the current object and index = -1 for the previous object.

            _PyramidCurrent    = VX.GetReferenceFromDelay(_PyramidDelay, 0);
            _PyramidPrevious   = VX.GetReferenceFromDelay(_PyramidDelay, -1);
            _KeypointsCurrent  = VX.GetReferenceFromDelay(_KeypointsDelay, 0);
            _KeypointsPrevious = VX.GetReferenceFromDelay(_KeypointsDelay, -1);

            // Harris and optical flow algorithms require their own graph objects.
            // The Harris graph needs to extract gray scale image out of input RGB,
            // compute an initial set of keypoints, and compute an initial pyramid for use
            // by the optical flow graph.
            Graph graphHarris = VX.CreateGraph(_Context);
            Graph graphTrack  = VX.CreateGraph(_Context);

            // Harris and pyramid computation expect input to be an 8-bit image.
            // Given that input is an RGB image, it is best to extract a gray image
            // from RGB image, which requires two steps:
            //   - perform RGB to IYUV color conversion
            //   - extract Y channel from IYUV image
            // This requires two intermediate OpenVX image objects. Since you don't
            // need to access these objects from the application, they can be virtual
            // objects that can be created using the vxCreateVirtualImage API.
            OpenVX.Image harris_yuv_image       = VX.CreateVirtualImage(graphHarris, width, height, DfImage.Iyuv);
            OpenVX.Image harris_gray_image      = VX.CreateVirtualImage(graphHarris, width, height, DfImage.U8);
            OpenVX.Image opticalflow_yuv_image  = VX.CreateVirtualImage(graphTrack, width, height, DfImage.Iyuv);
            OpenVX.Image opticalflow_gray_image = VX.CreateVirtualImage(graphTrack, width, height, DfImage.U8);

            // The Harris corner detector and optical flow nodes (see "VX/vx_nodes.h")
            // need several scalar objects as parameters.
            Scalar strength_thresh      = VX.CreateScalar(_Context, ref harris_strength_thresh);
            Scalar min_distance         = VX.CreateScalar(_Context, ref harris_min_distance);
            Scalar sensitivity          = VX.CreateScalar(_Context, ref harris_sensitivity);
            Scalar epsilon              = VX.CreateScalar(_Context, ref lk_epsilon);
            Scalar num_iterations       = VX.CreateScalar(_Context, ref lk_num_iterations);
            Scalar use_initial_estimate = VX.CreateScalar(_Context, ref lk_use_initial_estimate);

            // Now all the objects have been created for building the graphs.
            // First, build a graph that performs Harris corner detection and initial pyramid computation.
            // See "VX/vx_nodes.h" for APIs how to add nodes into a graph.
            Node[] nodesHarris = new Node[] {
                VX.ColorConvertNode(graphHarris, _ImageInput, harris_yuv_image),
                VX.ChannelExtractNode(graphHarris, harris_yuv_image, Channel.ChannelY, harris_gray_image),
                VX.GaussianPyramidNode(graphHarris, harris_gray_image, _PyramidCurrent),
                VX.HarrisCornersNode(graphHarris, harris_gray_image, strength_thresh, min_distance, sensitivity, harris_gradient_size, harris_block_size, _KeypointsCurrent, Reference.Null)
            };
            VX.Release(nodesHarris);

            VX.VerifyGraph(graphHarris);

            // Now, build a graph that computes image pyramid for the next frame,
            // and tracks features using optical flow.
            Node[] nodesTrack = new Node[] {
                VX.ColorConvertNode(graphTrack, _ImageInput, opticalflow_yuv_image),
                VX.ChannelExtractNode(graphTrack, opticalflow_yuv_image, Channel.ChannelY, opticalflow_gray_image),
                VX.GaussianPyramidNode(graphTrack, opticalflow_gray_image, _PyramidCurrent),
                VX.OpticalFlowPyrLKNode(graphTrack, _PyramidPrevious, _PyramidCurrent, _KeypointsPrevious, _KeypointsPrevious, _KeypointsCurrent,
                                        lk_termination, epsilon, num_iterations,
                                        use_initial_estimate, (UIntPtr)lk_window_dimension
                                        )
            };
            VX.Release(nodesTrack);

            VX.VerifyGraph(graphTrack);

            _GraphHarris = graphHarris;
            _GraphTrack  = graphTrack;

            #endregion
        }