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> ®ions,
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;
};