1
0
mirror of https://github.com/opencv/opencv.git synced 2026-07-31 08:13:04 +04:00

refactor CUDA ORB feature detector/extractor algorithm:

use new abstract interface and hidden implementation
This commit is contained in:
Vladislav Vinogradov
2015-01-13 10:40:58 +03:00
parent 554ddd2ec4
commit f960a5707d
5 changed files with 447 additions and 442 deletions
@@ -284,9 +284,11 @@ public:
virtual int getMaxNumPoints() const = 0;
};
/** @brief Class for extracting ORB features and descriptors from an image. :
*/
class CV_EXPORTS ORB_CUDA
//
// ORB
//
class CV_EXPORTS ORB : public cv::ORB, public Feature2DAsync
{
public:
enum
@@ -300,113 +302,20 @@ public:
ROWS_COUNT
};
enum
{
DEFAULT_FAST_THRESHOLD = 20
};
/** @brief Constructor.
@param nFeatures The number of desired features.
@param scaleFactor Coefficient by which we divide the dimensions from one scale pyramid level to
the next.
@param nLevels The number of levels in the scale pyramid.
@param edgeThreshold How far from the boundary the points should be.
@param firstLevel The level at which the image is given. If 1, that means we will also look at the
image scaleFactor times bigger.
@param WTA_K
@param scoreType
@param patchSize
*/
explicit ORB_CUDA(int nFeatures = 500, float scaleFactor = 1.2f, int nLevels = 8, int edgeThreshold = 31,
int firstLevel = 0, int WTA_K = 2, int scoreType = 0, int patchSize = 31);
/** @overload */
void operator()(const GpuMat& image, const GpuMat& mask, std::vector<KeyPoint>& keypoints);
/** @overload */
void operator()(const GpuMat& image, const GpuMat& mask, GpuMat& keypoints);
/** @brief Detects keypoints and computes descriptors for them.
@param image Input 8-bit grayscale image.
@param mask Optional input mask that marks the regions where we should detect features.
@param keypoints The input/output vector of keypoints. Can be stored both in CPU and GPU memory.
For GPU memory:
- keypoints.ptr\<float\>(X_ROW)[i] contains x coordinate of the i'th feature.
- keypoints.ptr\<float\>(Y_ROW)[i] contains y coordinate of the i'th feature.
- keypoints.ptr\<float\>(RESPONSE_ROW)[i] contains the response of the i'th feature.
- keypoints.ptr\<float\>(ANGLE_ROW)[i] contains orientation of the i'th feature.
- keypoints.ptr\<float\>(OCTAVE_ROW)[i] contains the octave of the i'th feature.
- keypoints.ptr\<float\>(SIZE_ROW)[i] contains the size of the i'th feature.
@param descriptors Computed descriptors. if blurForDescriptor is true, image will be blurred
before descriptors calculation.
*/
void operator()(const GpuMat& image, const GpuMat& mask, std::vector<KeyPoint>& keypoints, GpuMat& descriptors);
/** @overload */
void operator()(const GpuMat& image, const GpuMat& mask, GpuMat& keypoints, GpuMat& descriptors);
/** @brief Download keypoints from GPU to CPU memory.
*/
static void downloadKeyPoints(const GpuMat& d_keypoints, std::vector<KeyPoint>& keypoints);
/** @brief Converts keypoints from CUDA representation to vector of KeyPoint.
*/
static void convertKeyPoints(const Mat& d_keypoints, std::vector<KeyPoint>& keypoints);
//! returns the descriptor size in bytes
inline int descriptorSize() const { return kBytes; }
inline void setFastParams(int threshold, bool nonmaxSuppression = true)
{
fastDetector_->setThreshold(threshold);
fastDetector_->setNonmaxSuppression(nonmaxSuppression);
}
/** @brief Releases inner buffer memory.
*/
void release();
static Ptr<ORB> create(int nfeatures=500,
float scaleFactor=1.2f,
int nlevels=8,
int edgeThreshold=31,
int firstLevel=0,
int WTA_K=2,
int scoreType=ORB::HARRIS_SCORE,
int patchSize=31,
int fastThreshold=20,
bool blurForDescriptor=false);
//! if true, image will be blurred before descriptors calculation
bool blurForDescriptor;
private:
enum { kBytes = 32 };
void buildScalePyramids(const GpuMat& image, const GpuMat& mask);
void computeKeyPointsPyramid();
void computeDescriptors(GpuMat& descriptors);
void mergeKeyPoints(GpuMat& keypoints);
int nFeatures_;
float scaleFactor_;
int nLevels_;
int edgeThreshold_;
int firstLevel_;
int WTA_K_;
int scoreType_;
int patchSize_;
//! The number of desired features per scale
std::vector<size_t> n_features_per_level_;
//! Points to compute BRIEF descriptors from
GpuMat pattern_;
std::vector<GpuMat> imagePyr_;
std::vector<GpuMat> maskPyr_;
GpuMat buf_;
std::vector<GpuMat> keyPointsPyr_;
std::vector<int> keyPointsCount_;
Ptr<cv::cuda::FastFeatureDetector> fastDetector_;
Ptr<cuda::Filter> blurFilter;
GpuMat d_keypoints_;
virtual void setBlurForDescriptor(bool blurForDescriptor) = 0;
virtual bool getBlurForDescriptor() const = 0;
};
//! @}