mirror of
https://github.com/opencv/opencv.git
synced 2024-12-30 21:25:58 +08:00
189 lines
7.9 KiB
ReStructuredText
189 lines
7.9 KiB
ReStructuredText
Object Detection
|
|
=============================
|
|
|
|
.. highlight:: cpp
|
|
|
|
ocl::OclCascadeClassifier
|
|
-------------------------
|
|
.. ocv:class:: ocl::OclCascadeClassifier : public CascadeClassifier
|
|
|
|
Cascade classifier class used for object detection. Supports HAAR cascade classifier in the form of cross link ::
|
|
|
|
class CV_EXPORTS OclCascadeClassifier : public CascadeClassifier
|
|
{
|
|
public:
|
|
OclCascadeClassifier() {};
|
|
~OclCascadeClassifier() {};
|
|
CvSeq *oclHaarDetectObjects(oclMat &gimg, CvMemStorage *storage,
|
|
double scaleFactor,int minNeighbors,
|
|
int flags, CvSize minSize = cvSize(0, 0),
|
|
CvSize maxSize = cvSize(0, 0));
|
|
};
|
|
|
|
ocl::OclCascadeClassifier::oclHaarDetectObjects
|
|
------------------------------------------------------
|
|
Returns the detected objects by a list of rectangles
|
|
|
|
.. ocv:function:: CvSeq* ocl::OclCascadeClassifier::oclHaarDetectObjects(oclMat &gimg, CvMemStorage *storage, double scaleFactor,int minNeighbors, int flags, CvSize minSize = cvSize(0, 0), CvSize maxSize = cvSize(0, 0))
|
|
|
|
:param image: Matrix of type CV_8U containing an image where objects should be detected.
|
|
|
|
:param imageobjectsBuff: Buffer to store detected objects (rectangles). If it is empty, it is allocated with the defaultsize. If not empty, the function searches not more than N objects, where N = sizeof(objectsBufers data)/sizeof(cv::Rect).
|
|
|
|
:param scaleFactor: Parameter specifying how much the image size is reduced at each image scale.
|
|
|
|
:param minNeighbors: Parameter specifying how many neighbors each candidate rectangle should have to retain it.
|
|
|
|
:param minSize: Minimum possible object size. Objects smaller than that are ignored.
|
|
|
|
Detects objects of different sizes in the input image,only tested for face detection now. The function returns the number of detected objects.
|
|
|
|
ocl::MatchTemplateBuf
|
|
---------------------
|
|
.. ocv:struct:: ocl::MatchTemplateBuf
|
|
|
|
Class providing memory buffers for :ocv:func:`ocl::matchTemplate` function, plus it allows to adjust some specific parameters. ::
|
|
|
|
struct CV_EXPORTS MatchTemplateBuf
|
|
{
|
|
Size user_block_size;
|
|
oclMat imagef, templf;
|
|
std::vector<oclMat> images;
|
|
std::vector<oclMat> image_sums;
|
|
std::vector<oclMat> image_sqsums;
|
|
};
|
|
|
|
You can use field `user_block_size` to set specific block size for :ocv:func:`ocl::matchTemplate` function. If you leave its default value `Size(0,0)` then automatic estimation of block size will be used (which is optimized for speed). By varying `user_block_size` you can reduce memory requirements at the cost of speed.
|
|
|
|
ocl::matchTemplate
|
|
------------------
|
|
Computes a proximity map for a raster template and an image where the template is searched for.
|
|
|
|
.. ocv:function:: void ocl::matchTemplate(const oclMat& image, const oclMat& templ, oclMat& result, int method)
|
|
|
|
.. ocv:function:: void ocl::matchTemplate(const oclMat& image, const oclMat& templ, oclMat& result, int method, MatchTemplateBuf &buf)
|
|
|
|
:param image: Source image. ``CV_32F`` and ``CV_8U`` depth images (1..4 channels) are supported for now.
|
|
|
|
:param templ: Template image with the size and type the same as ``image`` .
|
|
|
|
:param result: Map containing comparison results ( ``CV_32FC1`` ). If ``image`` is *W x H* and ``templ`` is *w x h*, then ``result`` must be *W-w+1 x H-h+1*.
|
|
|
|
:param method: Specifies the way to compare the template with the image.
|
|
|
|
:param buf: Optional buffer to avoid extra memory allocations and to adjust some specific parameters. See :ocv:struct:`ocl::MatchTemplateBuf`.
|
|
|
|
The following methods are supported for the ``CV_8U`` depth images for now:
|
|
|
|
* ``CV_TM_SQDIFF``
|
|
* ``CV_TM_SQDIFF_NORMED``
|
|
* ``CV_TM_CCORR``
|
|
* ``CV_TM_CCORR_NORMED``
|
|
* ``CV_TM_CCOEFF``
|
|
* ``CV_TM_CCOEFF_NORMED``
|
|
|
|
The following methods are supported for the ``CV_32F`` images for now:
|
|
|
|
* ``CV_TM_SQDIFF``
|
|
* ``CV_TM_CCORR``
|
|
|
|
.. seealso:: :ocv:func:`matchTemplate`
|
|
|
|
|
|
ocl::SURF_OCL
|
|
-------------
|
|
.. ocv:class:: ocl::SURF_OCL
|
|
|
|
Class used for extracting Speeded Up Robust Features (SURF) from an image. ::
|
|
|
|
class SURF_OCL
|
|
{
|
|
public:
|
|
enum KeypointLayout
|
|
{
|
|
X_ROW = 0,
|
|
Y_ROW,
|
|
LAPLACIAN_ROW,
|
|
OCTAVE_ROW,
|
|
SIZE_ROW,
|
|
ANGLE_ROW,
|
|
HESSIAN_ROW,
|
|
ROWS_COUNT
|
|
};
|
|
|
|
//! the default constructor
|
|
SURF_OCL();
|
|
//! the full constructor taking all the necessary parameters
|
|
explicit SURF_OCL(double _hessianThreshold, int _nOctaves=4,
|
|
int _nOctaveLayers=2, bool _extended=false, float _keypointsRatio=0.01f, bool _upright = false);
|
|
|
|
//! returns the descriptor size in float's (64 or 128)
|
|
int descriptorSize() const;
|
|
|
|
//! upload host keypoints to device memory
|
|
void uploadKeypoints(const vector<KeyPoint>& keypoints,
|
|
oclMat& keypointsocl);
|
|
//! download keypoints from device to host memory
|
|
void downloadKeypoints(const oclMat& keypointsocl,
|
|
vector<KeyPoint>& keypoints);
|
|
|
|
//! download descriptors from device to host memory
|
|
void downloadDescriptors(const oclMat& descriptorsocl,
|
|
vector<float>& descriptors);
|
|
|
|
void operator()(const oclMat& img, const oclMat& mask,
|
|
oclMat& keypoints);
|
|
|
|
void operator()(const oclMat& img, const oclMat& mask,
|
|
oclMat& keypoints, oclMat& descriptors,
|
|
bool useProvidedKeypoints = false);
|
|
|
|
void operator()(const oclMat& img, const oclMat& mask,
|
|
std::vector<KeyPoint>& keypoints);
|
|
|
|
void operator()(const oclMat& img, const oclMat& mask,
|
|
std::vector<KeyPoint>& keypoints, oclMat& descriptors,
|
|
bool useProvidedKeypoints = false);
|
|
|
|
void operator()(const oclMat& img, const oclMat& mask,
|
|
std::vector<KeyPoint>& keypoints,
|
|
std::vector<float>& descriptors,
|
|
bool useProvidedKeypoints = false);
|
|
|
|
void releaseMemory();
|
|
|
|
// SURF parameters
|
|
double hessianThreshold;
|
|
int nOctaves;
|
|
int nOctaveLayers;
|
|
bool extended;
|
|
bool upright;
|
|
|
|
//! max keypoints = min(keypointsRatio * img.size().area(), 65535)
|
|
float keypointsRatio;
|
|
|
|
oclMat sum, mask1, maskSum, intBuffer;
|
|
|
|
oclMat det, trace;
|
|
|
|
oclMat maxPosBuffer;
|
|
};
|
|
|
|
|
|
The class ``SURF_OCL`` implements Speeded Up Robust Features descriptor. There is a fast multi-scale Hessian keypoint detector that can be used to find the keypoints (which is the default option). But the descriptors can also be computed for the user-specified keypoints. Only 8-bit grayscale images are supported.
|
|
|
|
The class ``SURF_OCL`` can store results in the GPU and CPU memory. It provides functions to convert results between CPU and GPU version ( ``uploadKeypoints``, ``downloadKeypoints``, ``downloadDescriptors`` ). The format of CPU results is the same as ``SURF`` results. GPU results are stored in ``oclMat``. The ``keypoints`` matrix is :math:`\texttt{nFeatures} \times 7` matrix with the ``CV_32FC1`` type.
|
|
|
|
* ``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>(LAPLACIAN_ROW)[i]`` contains the laplacian sign 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.
|
|
* ``keypoints.ptr<float>(ANGLE_ROW)[i]`` contain orientation of the i-th feature.
|
|
* ``keypoints.ptr<float>(HESSIAN_ROW)[i]`` contains the response of the i-th feature.
|
|
|
|
The ``descriptors`` matrix is :math:`\texttt{nFeatures} \times \texttt{descriptorSize}` matrix with the ``CV_32FC1`` type.
|
|
|
|
The class ``SURF_OCL`` uses some buffers and provides access to it. All buffers can be safely released between function calls.
|
|
|
|
.. seealso:: :ocv:class:`SURF` |