Structure containing image keypoints and descriptors.
struct CV_EXPORTS ImageFeatures
{
int img_idx;
Size img_size;
std::vector<KeyPoint> keypoints;
Mat descriptors;
};
Feature finders base class.
class CV_EXPORTS FeaturesFinder
{
public:
virtual ~FeaturesFinder() {}
void operator ()(const Mat &image, ImageFeatures &features);
void operator ()(const Mat &image, ImageFeatures &features, const std::vector<cv::Rect> &rois);
virtual void collectGarbage() {}
protected:
virtual void find(const Mat &image, ImageFeatures &features) = 0;
};
Finds features in the given image.
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See also
Frees unused memory allocated before if there is any.
This method must implement features finding logic in order to make the wrappers detail::FeaturesFinder::operator() work.
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See also
SURF features finder.
class CV_EXPORTS SurfFeaturesFinder : public FeaturesFinder
{
public:
SurfFeaturesFinder(double hess_thresh = 300., int num_octaves = 3, int num_layers = 4,
int num_octaves_descr = /*4*/3, int num_layers_descr = /*2*/4);
private:
/* hidden */
};
See also
ORB features finder.
class CV_EXPORTS OrbFeaturesFinder : public FeaturesFinder
{
public:
OrbFeaturesFinder(Size _grid_size = Size(3,1), size_t n_features = 1500,
const ORB::CommonParams &detector_params = ORB::CommonParams(1.3f, 5));
private:
/* hidden */
};
See also
Structure containing information about matches between two images. It’s assumed that there is a homography between those images.
struct CV_EXPORTS MatchesInfo
{
MatchesInfo();
MatchesInfo(const MatchesInfo &other);
const MatchesInfo& operator =(const MatchesInfo &other);
int src_img_idx, dst_img_idx; // Images indices (optional)
std::vector<DMatch> matches;
std::vector<uchar> inliers_mask; // Geometrically consistent matches mask
int num_inliers; // Number of geometrically consistent matches
Mat H; // Estimated homography
double confidence; // Confidence two images are from the same panorama
};
Feature matchers base class.
class CV_EXPORTS FeaturesMatcher
{
public:
virtual ~FeaturesMatcher() {}
void operator ()(const ImageFeatures &features1, const ImageFeatures &features2,
MatchesInfo& matches_info) { match(features1, features2, matches_info); }
void operator ()(const std::vector<ImageFeatures> &features, std::vector<MatchesInfo> &pairwise_matches,
const Mat &mask = cv::Mat());
bool isThreadSafe() const { return is_thread_safe_; }
virtual void collectGarbage() {}
protected:
FeaturesMatcher(bool is_thread_safe = false) : is_thread_safe_(is_thread_safe) {}
virtual void match(const ImageFeatures &features1, const ImageFeatures &features2,
MatchesInfo& matches_info) = 0;
bool is_thread_safe_;
};
Performs images matching.
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The function is parallelized with the TBB library.
See also
Returns: | True, if it’s possible to use the same matcher instance in parallel, false otherwise |
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Frees unused memory allocated before if there is any.
This method must implement matching logic in order to make the wrappers detail::FeaturesMatcher::operator() work.
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Features matcher which finds two best matches for each feature and leaves the best one only if the ratio between descriptor distances is greater than the threshold match_conf.
class CV_EXPORTS BestOf2NearestMatcher : public FeaturesMatcher
{
public:
BestOf2NearestMatcher(bool try_use_gpu = false, float match_conf = 0.65f,
int num_matches_thresh1 = 6, int num_matches_thresh2 = 6);
void collectGarbage();
protected:
void match(const ImageFeatures &features1, const ImageFeatures &features2, MatchesInfo &matches_info);
int num_matches_thresh1_;
int num_matches_thresh2_;
Ptr<FeaturesMatcher> impl_;
};
See also
Constructs a “best of 2 nearest” matcher.
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