C++ Image::data方法代码示例

void FastCornerDetector::detect
(
  const image::Image<unsigned char> & ima,
  std::vector<PointFeature> & regions
)
{
  using FastDetectorCall =
    xy* (*) (const unsigned char *, int, int, int, int, int *);

  FastDetectorCall detector = nullptr;
  if (size_ ==  9) detector =  fast9_detect_nonmax;
  if (size_ == 10) detector = fast10_detect_nonmax;
  if (size_ == 11) detector = fast11_detect_nonmax;
  if (size_ == 12) detector = fast12_detect_nonmax;
  if (!detector)
  {
    std::cout << "Invalid size for FAST detector: " << size_ << std::endl;
    return;
  }

  int num_corners = 0;
  xy* detections = detector(ima.data(),
     ima.Width(), ima.Height(), ima.Width(),
     threshold_, &num_corners);
  regions.clear();
  regions.reserve(num_corners);
  for (int i = 0; i < num_corners; ++i)
  {
    regions.emplace_back(detections[i].x, detections[i].y);
  }
  free( detections );
}

    /**
    @brief Detect regions on the image and compute their attributes (description)
    @param image Image.
    @param regions The detected regions and attributes (the caller must delete the allocated data)
    @param mask 8-bit gray image for keypoint filtering (optional).
       Non-zero values depict the region of interest.
    */
    bool Describe(const image::Image<unsigned char>& image,
                  std::unique_ptr<Regions> &regions,
                  const image::Image<unsigned char> * mask = NULL)
    {
        const int w = image.Width(), h = image.Height();
        //Convert to float
        const image::Image<float> If(image.GetMat().cast<float>());

        VlSiftFilt *filt = vl_sift_new(w, h,
                                       _params._num_octaves, _params._num_scales, _params._first_octave);
        if (_params._edge_threshold >= 0)
            vl_sift_set_edge_thresh(filt, _params._edge_threshold);
        if (_params._peak_threshold >= 0)
            vl_sift_set_peak_thresh(filt, 255*_params._peak_threshold/_params._num_scales);

        Descriptor<vl_sift_pix, 128> descr;
        Descriptor<unsigned char, 128> descriptor;

        // Process SIFT computation
        vl_sift_process_first_octave(filt, If.data());

        Allocate(regions);

        // Build alias to cached data
        SIFT_Regions * regionsCasted = dynamic_cast<SIFT_Regions*>(regions.get());
        // reserve some memory for faster keypoint saving
        regionsCasted->Features().reserve(2000);
        regionsCasted->Descriptors().reserve(2000);

        while (true) {
            vl_sift_detect(filt);

            VlSiftKeypoint const *keys  = vl_sift_get_keypoints(filt);
            const int nkeys = vl_sift_get_nkeypoints(filt);

            // Update gradient before launching parallel extraction
            vl_sift_update_gradient(filt);

#ifdef OPENMVG_USE_OPENMP
            #pragma omp parallel for private(descr, descriptor)
#endif
            for (int i = 0; i < nkeys; ++i) {

                // Feature masking
                if (mask)
                {
                    const image::Image<unsigned char> & maskIma = *mask;
                    if (maskIma(keys[i].y, keys[i].x) == 0)
                        continue;
                }

                double angles [4] = {0.0, 0.0, 0.0, 0.0};
                int nangles = 1; // by default (1 upright feature)
                if (_bOrientation)
                {   // compute from 1 to 4 orientations
                    nangles = vl_sift_calc_keypoint_orientations(filt, angles, keys+i);
                }

                for (int q=0 ; q < nangles ; ++q) {
                    vl_sift_calc_keypoint_descriptor(filt, &descr[0], keys+i, angles[q]);
                    const SIOPointFeature fp(keys[i].x, keys[i].y,
                                             keys[i].sigma, static_cast<float>(angles[q]));

                    siftDescToUChar(&descr[0], descriptor, _params._root_sift);
#ifdef OPENMVG_USE_OPENMP
                    #pragma omp critical
#endif
                    {
                        regionsCasted->Descriptors().push_back(descriptor);
                        regionsCasted->Features().push_back(fp);
                    }
                }
            }
            if (vl_sift_process_next_octave(filt))
                break; // Last octave
        }
        vl_sift_delete(filt);

        return true;
    };