Merge pull request #2465 from SpecLad:merge-2.4

This commit is contained in:
Roman Donchenko 2014-03-12 17:08:43 +04:00 committed by OpenCV Buildbot
commit 290b93422c
29 changed files with 70 additions and 118 deletions

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@ -129,7 +129,7 @@ PERF_TEST_P(PointsNum, DISABLED_SolvePnPRansac, testing::Values(4, 3*9, 7*13))
Mat tvec;
#ifdef HAVE_TBB
// limit concurrency to get determenistic result
// limit concurrency to get deterministic result
tbb::task_scheduler_init one_thread(1);
#endif

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@ -274,7 +274,7 @@ TEST(DISABLED_Calib3d_SolvePnPRansac, concurrency)
Mat tvec1, tvec2;
{
// limit concurrency to get determenistic result
// limit concurrency to get deterministic result
cv::theRNG().state = 20121010;
tbb::task_scheduler_init one_thread(1);
solvePnPRansac(object, image, camera_mat, dist_coef, rvec1, tvec1);

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@ -224,7 +224,7 @@ Mat subspaceReconstruct(InputArray _W, InputArray _mean, InputArray _src)
String error_message = format("Wrong mean shape for the given eigenvector matrix. Expected %d, but was %d.", W.cols, mean.total());
CV_Error(Error::StsBadArg, error_message);
}
// initalize temporary matrices
// initialize temporary matrices
Mat X, Y;
// copy data & make sure we are using the correct type
src.convertTo(Y, W.type());

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@ -120,7 +120,7 @@ CVAPI(void) cvResetImageROI( IplImage* image );
/* Retrieves image ROI */
CVAPI(CvRect) cvGetImageROI( const IplImage* image );
/* Allocates and initalizes CvMat header */
/* Allocates and initializes CvMat header */
CVAPI(CvMat*) cvCreateMatHeader( int rows, int cols, int type );
#define CV_AUTOSTEP 0x7fffffff

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@ -2904,7 +2904,7 @@ cvCreateImage( CvSize size, int depth, int channels )
}
// initalize IplImage header, allocated by the user
// initialize IplImage header, allocated by the user
CV_IMPL IplImage*
cvInitImageHeader( IplImage * image, CvSize size, int depth,
int channels, int origin, int align )

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@ -24,7 +24,7 @@ Class used for corner detection using the FAST algorithm. ::
// all features have same size
static const int FEATURE_SIZE = 7;
explicit FAST_CUDA(int threshold, bool nonmaxSupression = true,
explicit FAST_CUDA(int threshold, bool nonmaxSuppression = true,
double keypointsRatio = 0.05);
void operator ()(const GpuMat& image, const GpuMat& mask, GpuMat& keypoints);
@ -39,7 +39,7 @@ Class used for corner detection using the FAST algorithm. ::
void release();
bool nonmaxSupression;
bool nonmaxSuppression;
int threshold;
@ -61,11 +61,11 @@ cuda::FAST_CUDA::FAST_CUDA
--------------------------
Constructor.
.. ocv:function:: cuda::FAST_CUDA::FAST_CUDA(int threshold, bool nonmaxSupression = true, double keypointsRatio = 0.05)
.. ocv:function:: cuda::FAST_CUDA::FAST_CUDA(int threshold, bool nonmaxSuppression = true, double keypointsRatio = 0.05)
:param threshold: Threshold on difference between intensity of the central pixel and pixels on a circle around this pixel.
:param nonmaxSupression: If it is true, non-maximum suppression is applied to detected corners (keypoints).
:param nonmaxSuppression: If it is true, non-maximum suppression is applied to detected corners (keypoints).
:param keypointsRatio: Inner buffer size for keypoints store is determined as (keypointsRatio * image_width * image_height).
@ -115,7 +115,7 @@ Releases inner buffer memory.
cuda::FAST_CUDA::calcKeyPointsLocation
--------------------------------------
Find keypoints and compute it's response if ``nonmaxSupression`` is true.
Find keypoints and compute it's response if ``nonmaxSuppression`` is true.
.. ocv:function:: int cuda::FAST_CUDA::calcKeyPointsLocation(const GpuMat& image, const GpuMat& mask)
@ -185,7 +185,7 @@ Class for extracting ORB features and descriptors from an image. ::
int descriptorSize() const;
void setParams(size_t n_features, const ORB::CommonParams& detector_params);
void setFastParams(int threshold, bool nonmaxSupression = true);
void setFastParams(int threshold, bool nonmaxSuppression = true);
void release();

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@ -216,7 +216,7 @@ public:
// all features have same size
static const int FEATURE_SIZE = 7;
explicit FAST_CUDA(int threshold, bool nonmaxSupression = true, double keypointsRatio = 0.05);
explicit FAST_CUDA(int threshold, bool nonmaxSuppression = true, double keypointsRatio = 0.05);
//! finds the keypoints using FAST detector
//! supports only CV_8UC1 images
@ -232,19 +232,19 @@ public:
//! release temporary buffer's memory
void release();
bool nonmaxSupression;
bool nonmaxSuppression;
int threshold;
//! max keypoints = keypointsRatio * img.size().area()
double keypointsRatio;
//! find keypoints and compute it's response if nonmaxSupression is true
//! find keypoints and compute it's response if nonmaxSuppression is true
//! return count of detected keypoints
int calcKeyPointsLocation(const GpuMat& image, const GpuMat& mask);
//! get final array of keypoints
//! performs nonmax supression if needed
//! performs nonmax suppression if needed
//! return final count of keypoints
int getKeyPoints(GpuMat& keypoints);
@ -303,10 +303,10 @@ public:
//! returns the descriptor size in bytes
inline int descriptorSize() const { return kBytes; }
inline void setFastParams(int threshold, bool nonmaxSupression = true)
inline void setFastParams(int threshold, bool nonmaxSuppression = true)
{
fastDetector_.threshold = threshold;
fastDetector_.nonmaxSupression = nonmaxSupression;
fastDetector_.nonmaxSuppression = nonmaxSuppression;
}
//! release temporary buffer's memory

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@ -49,9 +49,9 @@ using namespace perf;
//////////////////////////////////////////////////////////////////////
// FAST
DEF_PARAM_TEST(Image_Threshold_NonMaxSupression, string, int, bool);
DEF_PARAM_TEST(Image_Threshold_NonMaxSuppression, string, int, bool);
PERF_TEST_P(Image_Threshold_NonMaxSupression, FAST,
PERF_TEST_P(Image_Threshold_NonMaxSuppression, FAST,
Combine(Values<string>("gpu/perf/aloe.png"),
Values(20),
Bool()))

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@ -318,9 +318,9 @@ namespace cv { namespace cuda { namespace device
}
///////////////////////////////////////////////////////////////////////////
// nonmaxSupression
// nonmaxSuppression
__global__ void nonmaxSupression(const short2* kpLoc, int count, const PtrStepSzi scoreMat, short2* locFinal, float* responseFinal)
__global__ void nonmaxSuppression(const short2* kpLoc, int count, const PtrStepSzi scoreMat, short2* locFinal, float* responseFinal)
{
#if defined(__CUDA_ARCH__) && (__CUDA_ARCH__ >= 110)
@ -356,7 +356,7 @@ namespace cv { namespace cuda { namespace device
#endif
}
int nonmaxSupression_gpu(const short2* kpLoc, int count, PtrStepSzi score, short2* loc, float* response)
int nonmaxSuppression_gpu(const short2* kpLoc, int count, PtrStepSzi score, short2* loc, float* response)
{
void* counter_ptr;
cudaSafeCall( cudaGetSymbolAddress(&counter_ptr, g_counter) );
@ -368,7 +368,7 @@ namespace cv { namespace cuda { namespace device
cudaSafeCall( cudaMemset(counter_ptr, 0, sizeof(unsigned int)) );
nonmaxSupression<<<grid, block>>>(kpLoc, count, score, loc, response);
nonmaxSuppression<<<grid, block>>>(kpLoc, count, score, loc, response);
cudaSafeCall( cudaGetLastError() );
cudaSafeCall( cudaDeviceSynchronize() );

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@ -58,8 +58,8 @@ int cv::cuda::FAST_CUDA::getKeyPoints(GpuMat&) { throw_no_cuda(); return 0; }
#else /* !defined (HAVE_CUDA) */
cv::cuda::FAST_CUDA::FAST_CUDA(int _threshold, bool _nonmaxSupression, double _keypointsRatio) :
nonmaxSupression(_nonmaxSupression), threshold(_threshold), keypointsRatio(_keypointsRatio), count_(0)
cv::cuda::FAST_CUDA::FAST_CUDA(int _threshold, bool _nonmaxSuppression, double _keypointsRatio) :
nonmaxSuppression(_nonmaxSuppression), threshold(_threshold), keypointsRatio(_keypointsRatio), count_(0)
{
}
@ -113,7 +113,7 @@ namespace cv { namespace cuda { namespace device
namespace fast
{
int calcKeypoints_gpu(PtrStepSzb img, PtrStepSzb mask, short2* kpLoc, int maxKeypoints, PtrStepSzi score, int threshold);
int nonmaxSupression_gpu(const short2* kpLoc, int count, PtrStepSzi score, short2* loc, float* response);
int nonmaxSuppression_gpu(const short2* kpLoc, int count, PtrStepSzi score, short2* loc, float* response);
}
}}}
@ -128,13 +128,13 @@ int cv::cuda::FAST_CUDA::calcKeyPointsLocation(const GpuMat& img, const GpuMat&
ensureSizeIsEnough(1, maxKeypoints, CV_16SC2, kpLoc_);
if (nonmaxSupression)
if (nonmaxSuppression)
{
ensureSizeIsEnough(img.size(), CV_32SC1, score_);
score_.setTo(Scalar::all(0));
}
count_ = calcKeypoints_gpu(img, mask, kpLoc_.ptr<short2>(), maxKeypoints, nonmaxSupression ? score_ : PtrStepSzi(), threshold);
count_ = calcKeypoints_gpu(img, mask, kpLoc_.ptr<short2>(), maxKeypoints, nonmaxSuppression ? score_ : PtrStepSzi(), threshold);
count_ = std::min(count_, maxKeypoints);
return count_;
@ -149,8 +149,8 @@ int cv::cuda::FAST_CUDA::getKeyPoints(GpuMat& keypoints)
ensureSizeIsEnough(ROWS_COUNT, count_, CV_32FC1, keypoints);
if (nonmaxSupression)
return nonmaxSupression_gpu(kpLoc_.ptr<short2>(), count_, score_, keypoints.ptr<short2>(LOCATION_ROW), keypoints.ptr<float>(RESPONSE_ROW));
if (nonmaxSuppression)
return nonmaxSuppression_gpu(kpLoc_.ptr<short2>(), count_, score_, keypoints.ptr<short2>(LOCATION_ROW), keypoints.ptr<float>(RESPONSE_ROW));
GpuMat locRow(1, count_, kpLoc_.type(), keypoints.ptr(0));
kpLoc_.colRange(0, count_).copyTo(locRow);

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@ -52,20 +52,20 @@ using namespace cvtest;
namespace
{
IMPLEMENT_PARAM_CLASS(FAST_Threshold, int)
IMPLEMENT_PARAM_CLASS(FAST_NonmaxSupression, bool)
IMPLEMENT_PARAM_CLASS(FAST_NonmaxSuppression, bool)
}
PARAM_TEST_CASE(FAST, cv::cuda::DeviceInfo, FAST_Threshold, FAST_NonmaxSupression)
PARAM_TEST_CASE(FAST, cv::cuda::DeviceInfo, FAST_Threshold, FAST_NonmaxSuppression)
{
cv::cuda::DeviceInfo devInfo;
int threshold;
bool nonmaxSupression;
bool nonmaxSuppression;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
threshold = GET_PARAM(1);
nonmaxSupression = GET_PARAM(2);
nonmaxSuppression = GET_PARAM(2);
cv::cuda::setDevice(devInfo.deviceID());
}
@ -77,7 +77,7 @@ CUDA_TEST_P(FAST, Accuracy)
ASSERT_FALSE(image.empty());
cv::cuda::FAST_CUDA fast(threshold);
fast.nonmaxSupression = nonmaxSupression;
fast.nonmaxSuppression = nonmaxSuppression;
if (!supportFeature(devInfo, cv::cuda::GLOBAL_ATOMICS))
{
@ -97,7 +97,7 @@ CUDA_TEST_P(FAST, Accuracy)
fast(loadMat(image), cv::cuda::GpuMat(), keypoints);
std::vector<cv::KeyPoint> keypoints_gold;
cv::FAST(image, keypoints_gold, threshold, nonmaxSupression);
cv::FAST(image, keypoints_gold, threshold, nonmaxSuppression);
ASSERT_KEYPOINTS_EQ(keypoints_gold, keypoints);
}
@ -106,7 +106,7 @@ CUDA_TEST_P(FAST, Accuracy)
INSTANTIATE_TEST_CASE_P(CUDA_Features2D, FAST, testing::Combine(
ALL_DEVICES,
testing::Values(FAST_Threshold(25), FAST_Threshold(50)),
testing::Values(FAST_NonmaxSupression(false), FAST_NonmaxSupression(true))));
testing::Values(FAST_NonmaxSuppression(false), FAST_NonmaxSuppression(true))));
/////////////////////////////////////////////////////////////////////////////////////////////////
// ORB

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@ -139,7 +139,7 @@ PERF_TEST_P(Image, HoughLinesP,
const float rho = 1.0f;
const float theta = static_cast<float>(CV_PI / 180.0);
const int threshold = 100;
const int minLineLenght = 50;
const int minLineLength = 50;
const int maxLineGap = 5;
const cv::Mat image = cv::imread(fileName, cv::IMREAD_GRAYSCALE);
@ -153,7 +153,7 @@ PERF_TEST_P(Image, HoughLinesP,
const cv::cuda::GpuMat d_mask(mask);
cv::cuda::GpuMat d_lines;
cv::Ptr<cv::cuda::HoughSegmentDetector> hough = cv::cuda::createHoughSegmentDetector(rho, theta, minLineLenght, maxLineGap);
cv::Ptr<cv::cuda::HoughSegmentDetector> hough = cv::cuda::createHoughSegmentDetector(rho, theta, minLineLength, maxLineGap);
TEST_CYCLE() hough->detect(d_mask, d_lines);
@ -167,7 +167,7 @@ PERF_TEST_P(Image, HoughLinesP,
{
std::vector<cv::Vec4i> cpu_lines;
TEST_CYCLE() cv::HoughLinesP(mask, cpu_lines, rho, theta, threshold, minLineLenght, maxLineGap);
TEST_CYCLE() cv::HoughLinesP(mask, cpu_lines, rho, theta, threshold, minLineLength, maxLineGap);
SANITY_CHECK(cpu_lines);
}

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@ -11,8 +11,8 @@ FAST
----
Detects corners using the FAST algorithm
.. ocv:function:: void FAST( InputArray image, vector<KeyPoint>& keypoints, int threshold, bool nonmaxSupression=true )
.. ocv:function:: void FAST( InputArray image, vector<KeyPoint>& keypoints, int threshold, bool nonmaxSupression, int type )
.. ocv:function:: void FAST( InputArray image, vector<KeyPoint>& keypoints, int threshold, bool nonmaxSuppression=true )
.. ocv:function:: void FAST( InputArray image, vector<KeyPoint>& keypoints, int threshold, bool nonmaxSuppression, int type )
.. ocv:pyfunction:: cv2.FastFeatureDetector([, threshold[, nonmaxSuppression]]) -> <FastFeatureDetector object>
.. ocv:pyfunction:: cv2.FastFeatureDetector(threshold, nonmaxSuppression, type) -> <FastFeatureDetector object>
@ -25,7 +25,7 @@ Detects corners using the FAST algorithm
:param threshold: threshold on difference between intensity of the central pixel and pixels of a circle around this pixel.
:param nonmaxSupression: if true, non-maximum suppression is applied to detected corners (keypoints).
:param nonmaxSuppression: if true, non-maximum suppression is applied to detected corners (keypoints).
:param type: one of the three neighborhoods as defined in the paper: ``FastFeatureDetector::TYPE_9_16``, ``FastFeatureDetector::TYPE_7_12``, ``FastFeatureDetector::TYPE_5_8``

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@ -517,10 +517,10 @@ protected:
//! detects corners using FAST algorithm by E. Rosten
CV_EXPORTS void FAST( InputArray image, CV_OUT std::vector<KeyPoint>& keypoints,
int threshold, bool nonmaxSupression=true );
int threshold, bool nonmaxSuppression=true );
CV_EXPORTS void FAST( InputArray image, CV_OUT std::vector<KeyPoint>& keypoints,
int threshold, bool nonmaxSupression, int type );
int threshold, bool nonmaxSuppression, int type );
class CV_EXPORTS_W FastFeatureDetector : public FeatureDetector
{

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@ -127,7 +127,7 @@ public:
Point2f center;
Scalar ellipse; // 3 elements a, b, c: ax^2+2bxy+cy^2=1
Size_<float> axes; // half lenght of elipse axes
Size_<float> axes; // half length of ellipse axes
Size_<float> boundingBox; // half sizes of bounding box which sides are parallel to the coordinate axes
};

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@ -321,7 +321,6 @@ typedef struct CvCaptureCAM_V4L
struct v4l2_control control;
enum v4l2_buf_type type;
struct v4l2_queryctrl queryctrl;
struct v4l2_querymenu querymenu;
/* V4L2 control variables */
v4l2_ctrl_range** v4l2_ctrl_ranges;
@ -491,25 +490,6 @@ static int try_init_v4l2(CvCaptureCAM_V4L* capture, char *deviceName)
}
static void v4l2_scan_controls_enumerate_menu(CvCaptureCAM_V4L* capture)
{
// printf (" Menu items:\n");
CLEAR (capture->querymenu);
capture->querymenu.id = capture->queryctrl.id;
for (capture->querymenu.index = capture->queryctrl.minimum;
(int)capture->querymenu.index <= capture->queryctrl.maximum;
capture->querymenu.index++)
{
if (0 == xioctl (capture->deviceHandle, VIDIOC_QUERYMENU,
&capture->querymenu))
{
//printf (" %s\n", capture->querymenu.name);
} else {
perror ("VIDIOC_QUERYMENU");
}
}
}
static void v4l2_free_ranges(CvCaptureCAM_V4L* capture) {
int i;
if (capture->v4l2_ctrl_ranges != NULL) {
@ -590,9 +570,6 @@ static void v4l2_scan_controls(CvCaptureCAM_V4L* capture) {
if(capture->queryctrl.flags & V4L2_CTRL_FLAG_DISABLED) {
continue;
}
if (capture->queryctrl.type == V4L2_CTRL_TYPE_MENU) {
v4l2_scan_controls_enumerate_menu(capture);
}
if(capture->queryctrl.type != V4L2_CTRL_TYPE_INTEGER &&
capture->queryctrl.type != V4L2_CTRL_TYPE_BOOLEAN &&
capture->queryctrl.type != V4L2_CTRL_TYPE_MENU) {
@ -613,9 +590,6 @@ static void v4l2_scan_controls(CvCaptureCAM_V4L* capture) {
if(capture->queryctrl.flags & V4L2_CTRL_FLAG_DISABLED) {
continue;
}
if (capture->queryctrl.type == V4L2_CTRL_TYPE_MENU) {
v4l2_scan_controls_enumerate_menu(capture);
}
if(capture->queryctrl.type != V4L2_CTRL_TYPE_INTEGER &&
capture->queryctrl.type != V4L2_CTRL_TYPE_BOOLEAN &&
capture->queryctrl.type != V4L2_CTRL_TYPE_MENU) {
@ -637,9 +611,6 @@ static void v4l2_scan_controls(CvCaptureCAM_V4L* capture) {
continue;
}
if (capture->queryctrl.type == V4L2_CTRL_TYPE_MENU) {
v4l2_scan_controls_enumerate_menu(capture);
}
if(capture->queryctrl.type != V4L2_CTRL_TYPE_INTEGER &&
capture->queryctrl.type != V4L2_CTRL_TYPE_BOOLEAN &&

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@ -325,7 +325,6 @@ typedef struct CvCaptureCAM_V4L
struct v4l2_control control;
enum v4l2_buf_type type;
struct v4l2_queryctrl queryctrl;
struct v4l2_querymenu querymenu;
struct timeval timestamp;
@ -641,24 +640,6 @@ static int autosetup_capture_mode_v4l(CvCaptureCAM_V4L* capture)
#ifdef HAVE_CAMV4L2
static void v4l2_scan_controls_enumerate_menu(CvCaptureCAM_V4L* capture)
{
// printf (" Menu items:\n");
CLEAR (capture->querymenu);
capture->querymenu.id = capture->queryctrl.id;
for (capture->querymenu.index = capture->queryctrl.minimum;
(int)capture->querymenu.index <= capture->queryctrl.maximum;
capture->querymenu.index++)
{
if (0 == ioctl (capture->deviceHandle, VIDIOC_QUERYMENU,
&capture->querymenu))
{
// printf (" %s\n", capture->querymenu.name);
} else {
perror ("VIDIOC_QUERYMENU");
}
}
}
static void v4l2_scan_controls(CvCaptureCAM_V4L* capture)
{
@ -723,8 +704,6 @@ static void v4l2_scan_controls(CvCaptureCAM_V4L* capture)
capture->v4l2_exposure_max = capture->queryctrl.maximum;
}
if (capture->queryctrl.type == V4L2_CTRL_TYPE_MENU)
v4l2_scan_controls_enumerate_menu(capture);
} else {
@ -793,9 +772,6 @@ static void v4l2_scan_controls(CvCaptureCAM_V4L* capture)
capture->v4l2_exposure_max = capture->queryctrl.maximum;
}
if (capture->queryctrl.type == V4L2_CTRL_TYPE_MENU)
v4l2_scan_controls_enumerate_menu(capture);
} else {
if (errno == EINVAL)

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@ -1536,7 +1536,7 @@ CvWindow::CvWindow(QString name, int arg2)
setWindowTitle(name);
setObjectName(name);
setFocus( Qt::PopupFocusReason ); //#1695 arrow keys are not recieved without the explicit focus
setFocus( Qt::PopupFocusReason ); //#1695 arrow keys are not received without the explicit focus
resize(400, 300);
setMinimumSize(1, 1);

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@ -569,7 +569,7 @@ static int icvCreateTrackbar (const char* trackbar_name,
//pad size maxvalue in pixel
Point qdSize;
char valueinchar[strlen(trackbar_name)+1 +1 +1+nbDigit+1];//lenght+\n +space +(+nbDigit+)
char valueinchar[strlen(trackbar_name)+1 +1 +1+nbDigit+1];//length+\n +space +(+nbDigit+)
sprintf(valueinchar, "%s (%d)",trackbar_name, trackbar->maxval);
SInt16 baseline;
CFStringRef text = CFStringCreateWithCString(NULL,valueinchar,kCFStringEncodingASCII);

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@ -97,7 +97,7 @@ Harris corner detector.
.. ocv:pyfunction:: cv2.cornerHarris(src, blockSize, ksize, k[, dst[, borderType]]) -> dst
.. ocv:cfunction:: void cvCornerHarris( const CvArr* image, CvArr* harris_responce, int block_size, int aperture_size=3, double k=0.04 )
.. ocv:cfunction:: void cvCornerHarris( const CvArr* image, CvArr* harris_response, int block_size, int aperture_size=3, double k=0.04 )
:param src: Input single-channel 8-bit or floating-point image.

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@ -303,7 +303,7 @@ CVAPI(int) cvFindContours( CvArr* image, CvMemStorage* storage, CvSeq** first_c
int method CV_DEFAULT(CV_CHAIN_APPROX_SIMPLE),
CvPoint offset CV_DEFAULT(cvPoint(0,0)));
/* Initalizes contour retrieving process.
/* Initializes contour retrieving process.
Calls cvStartFindContours.
Calls cvFindNextContour until null pointer is returned
or some other condition becomes true.
@ -333,7 +333,7 @@ CVAPI(CvSeq*) cvApproxChains( CvSeq* src_seq, CvMemStorage* storage,
int minimal_perimeter CV_DEFAULT(0),
int recursive CV_DEFAULT(0));
/* Initalizes Freeman chain reader.
/* Initializes Freeman chain reader.
The reader is used to iteratively get coordinates of all the chain points.
If the Freeman codes should be read as is, a simple sequence reader should be used */
CVAPI(void) cvStartReadChainPoints( CvChain* chain, CvChainPtReader* reader );
@ -572,7 +572,7 @@ CVAPI(void) cvCornerMinEigenVal( const CvArr* image, CvArr* eigenval,
/* Harris corner detector:
Calculates det(M) - k*(trace(M)^2), where M is 2x2 gradient covariation matrix for each pixel */
CVAPI(void) cvCornerHarris( const CvArr* image, CvArr* harris_responce,
CVAPI(void) cvCornerHarris( const CvArr* image, CvArr* harris_response,
int block_size, int aperture_size CV_DEFAULT(3),
double k CV_DEFAULT(0.04) );

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@ -220,7 +220,7 @@ CvSeq* icvApproximateChainTC89( CvChain* chain, int header_size,
current = temp.next;
/* Pass 2.
Performs non-maxima supression */
Performs non-maxima suppression */
do
{
int k2 = current->k >> 1;

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@ -325,7 +325,7 @@ void cv::Canny( InputArray _src, OutputArray _dst,
#define CANNY_PUSH(d) *(d) = uchar(2), *stack_top++ = (d)
#define CANNY_POP(d) (d) = *--stack_top
// calculate magnitude and angle of gradient, perform non-maxima supression.
// calculate magnitude and angle of gradient, perform non-maxima suppression.
// fill the map with one of the following values:
// 0 - the pixel might belong to an edge
// 1 - the pixel can not belong to an edge

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@ -376,7 +376,7 @@ public:
// processing time (in this case there should be possibility to interrupt such a function
FAIL_HANG=-13,
// unexpected responce on passing bad arguments to the tested function
// unexpected response on passing bad arguments to the tested function
// (the function crashed, proceed succesfully (while it should not), or returned
// error code that is different from what is expected)
FAIL_BAD_ARG_CHECK=-14,

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@ -44,6 +44,7 @@ if __name__ == "__main__":
parser.add_option("", "--match", dest="match", default=None)
parser.add_option("", "--match-replace", dest="match_replace", default="")
parser.add_option("", "--regressions-only", dest="regressionsOnly", default=None, metavar="X-FACTOR", help="show only tests with performance regressions not")
parser.add_option("", "--intersect-logs", dest="intersect_logs", default=False, help="show only tests present in all log files")
(options, args) = parser.parse_args()
options.generateHtml = detectHtmlOutputType(options.format)
@ -162,6 +163,10 @@ if __name__ == "__main__":
for i in range(setsCount):
case = cases[i]
if case is None:
if options.intersect_logs:
needNewRow = False
break
tbl.newCell(str(i), "-")
if options.calc_relatives and i > 0:
tbl.newCell(str(i) + "%", "-")

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@ -398,7 +398,7 @@ This 3D Widget defines a cone. ::
{
public:
//! create default cone, oriented along x-axis with center of its base located at origin
WCone(double lenght, double radius, int resolution = 6.0, const Color &color = Color::white());
WCone(double length, double radius, int resolution = 6.0, const Color &color = Color::white());
//! creates repositioned cone
WCone(double radius, const Point3d& center, const Point3d& tip, int resolution = 6.0, const Color &color = Color::white());

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@ -214,12 +214,12 @@ public class ManagerActivity extends Activity
}
});
mPackageChangeReciever = new BroadcastReceiver() {
mPackageChangeReceiver = new BroadcastReceiver() {
@Override
public void onReceive(Context context, Intent intent) {
Log.d("OpenCVManager/Reciever", "Bradcast message " + intent.getAction() + " reciever");
Log.d("OpenCVManager/Reciever", "Filling package list on broadcast message");
Log.d("OpenCVManager/Receiver", "Broadcast message " + intent.getAction() + " receiver");
Log.d("OpenCVManager/Receiver", "Filling package list on broadcast message");
if (!bindService(new Intent("org.opencv.engine.BIND"), new OpenCVEngineServiceConnection(), Context.BIND_AUTO_CREATE))
{
TextView EngineVersionView = (TextView)findViewById(R.id.EngineVersionValue);
@ -235,14 +235,14 @@ public class ManagerActivity extends Activity
filter.addAction(Intent.ACTION_PACKAGE_REMOVED);
filter.addAction(Intent.ACTION_PACKAGE_REPLACED);
registerReceiver(mPackageChangeReciever, filter);
registerReceiver(mPackageChangeReceiver, filter);
}
@Override
protected void onDestroy() {
super.onDestroy();
if (mPackageChangeReciever != null)
unregisterReceiver(mPackageChangeReciever);
if (mPackageChangeReceiver != null)
unregisterReceiver(mPackageChangeReceiver);
}
@Override
@ -273,7 +273,7 @@ public class ManagerActivity extends Activity
protected int ManagerApiLevel = 0;
protected String ManagerVersion;
protected BroadcastReceiver mPackageChangeReciever = null;
protected BroadcastReceiver mPackageChangeReceiver = null;
protected class OpenCVEngineServiceConnection implements ServiceConnection
{

View File

@ -10,7 +10,7 @@ static void help()
printf("\nShow off image morphology: erosion, dialation, open and close\n"
"Call:\n morphology2 [image]\n"
"This program also shows use of rect, elipse and cross kernels\n\n");
"This program also shows use of rect, ellipse and cross kernels\n\n");
printf( "Hot keys: \n"
"\tESC - quit the program\n"
"\tr - use rectangle structuring element\n"

View File

@ -113,7 +113,7 @@ void App::help()
cout << "Show off image morphology: erosion, dialation, open and close \n";
cout << "Call: \n";
cout << " gpu-example-morphology [image] \n";
cout << "This program also shows use of rect, elipse and cross kernels \n" << endl;
cout << "This program also shows use of rect, ellipse and cross kernels \n" << endl;
cout << "Hot keys: \n";
cout << "\tESC - quit the program \n";