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Commit 9399394e authored by Andrey Kamaev's avatar Andrey Kamaev
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Fixed #1996

parent 1a572c8e
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Showing with 81 additions and 32 deletions
modules/features2d/src/fast.cpp
View file @ 9399394e
......@@ -16,8 +16,8 @@ are met:
notice, this list of conditions and the following disclaimer in the
documentation and/or other materials provided with the distribution.
*Neither the name of the University of Cambridge nor the names of
its contributors may be used to endorse or promote products derived
*Neither the name of the University of Cambridge nor the names of
its contributors may be used to endorse or promote products derived
from this software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
......@@ -35,7 +35,7 @@ SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
/*
The references are:
* Machine learning for high-speed corner detection,
* Machine learning for high-speed corner detection,
E. Rosten and T. Drummond, ECCV 2006
* Faster and better: A machine learning approach to corner detection
E. Rosten, R. Porter and T. Drummond, PAMI, 2009
......@@ -64,7 +64,7 @@ static void makeOffsets(int pixel[], int row_stride)
pixel[13] = -3 + row_stride * 1;
pixel[14] = -2 + row_stride * 2;
pixel[15] = -1 + row_stride * 3;
}
}
static int cornerScore(const uchar* ptr, const int pixel[], int threshold)
{
......@@ -73,7 +73,7 @@ static int cornerScore(const uchar* ptr, const int pixel[], int threshold)
short d[N];
for( k = 0; k < N; k++ )
d[k] = (short)(v - ptr[pixel[k]]);
#if CV_SSE2
__m128i q0 = _mm_set1_epi16(-1000), q1 = _mm_set1_epi16(1000);
for( k = 0; k < 16; k += 8 )
......@@ -128,7 +128,7 @@ static int cornerScore(const uchar* ptr, const int pixel[], int threshold)
a0 = std::max(a0, std::min(a, (int)d[k]));
a0 = std::max(a0, std::min(a, (int)d[k+9]));
}
int b0 = -a0;
for( k = 0; k < 16; k += 2 )
{
......@@ -141,14 +141,14 @@ static int cornerScore(const uchar* ptr, const int pixel[], int threshold)
b = std::max(b, (int)d[k+6]);
b = std::max(b, (int)d[k+7]);
b = std::max(b, (int)d[k+8]);
b0 = std::min(b0, std::max(b, (int)d[k]));
b0 = std::min(b0, std::max(b, (int)d[k+9]));
}
threshold = -b0-1;
#endif
#if 0
// check that with the computed "threshold" the pixel is still a corner
// and that with the increased-by-1 "threshold" the pixel is not a corner anymore
......@@ -157,7 +157,7 @@ static int cornerScore(const uchar* ptr, const int pixel[], int threshold)
int v0 = std::min(ptr[0] + threshold + delta, 255);
int v1 = std::max(ptr[0] - threshold - delta, 0);
int c0 = 0, c1 = 0;
for( int k = 0; k < N; k++ )
{
int x = ptr[pixel[k]];
......@@ -184,7 +184,7 @@ static int cornerScore(const uchar* ptr, const int pixel[], int threshold)
#endif
return threshold;
}
void FAST(InputArray _img, std::vector<KeyPoint>& keypoints, int threshold, bool nonmax_suppression)
{
......@@ -214,7 +214,7 @@ void FAST(InputArray _img, std::vector<KeyPoint>& keypoints, int threshold, bool
cpbuf[1] = cpbuf[0] + img.cols + 1;
cpbuf[2] = cpbuf[1] + img.cols + 1;
memset(buf[0], 0, img.cols*3);
for(i = 3; i < img.rows-2; i++)
{
const uchar* ptr = img.ptr<uchar>(i) + 3;
......@@ -222,7 +222,7 @@ void FAST(InputArray _img, std::vector<KeyPoint>& keypoints, int threshold, bool
int* cornerpos = cpbuf[(i - 3)%3];
memset(curr, 0, img.cols);
int ncorners = 0;
if( i < img.rows - 3 )
{
j = 3;
......@@ -233,7 +233,7 @@ void FAST(InputArray _img, std::vector<KeyPoint>& keypoints, int threshold, bool
__m128i v0 = _mm_loadu_si128((const __m128i*)ptr);
__m128i v1 = _mm_xor_si128(_mm_subs_epu8(v0, t), delta);
v0 = _mm_xor_si128(_mm_adds_epu8(v0, t), delta);
__m128i x0 = _mm_sub_epi8(_mm_loadu_si128((const __m128i*)(ptr + pixel[0])), delta);
__m128i x1 = _mm_sub_epi8(_mm_loadu_si128((const __m128i*)(ptr + pixel[4])), delta);
__m128i x2 = _mm_sub_epi8(_mm_loadu_si128((const __m128i*)(ptr + pixel[8])), delta);
......@@ -256,24 +256,24 @@ void FAST(InputArray _img, std::vector<KeyPoint>& keypoints, int threshold, bool
ptr -= 8;
continue;
}
__m128i c0 = _mm_setzero_si128(), c1 = c0, max0 = c0, max1 = c0;
for( k = 0; k < N; k++ )
{
__m128i x = _mm_xor_si128(_mm_loadu_si128((const __m128i*)(ptr + pixel[k])), delta);
m0 = _mm_cmpgt_epi8(x, v0);
m1 = _mm_cmpgt_epi8(v1, x);
c0 = _mm_and_si128(_mm_sub_epi8(c0, m0), m0);
c1 = _mm_and_si128(_mm_sub_epi8(c1, m1), m1);
max0 = _mm_max_epu8(max0, c0);
max1 = _mm_max_epu8(max1, c1);
}
max0 = _mm_max_epu8(max0, max1);
int m = _mm_movemask_epi8(_mm_cmpgt_epi8(max0, K16));
for( k = 0; m > 0 && k < 16; k++, m >>= 1 )
if(m & 1)
{
......@@ -288,26 +288,26 @@ void FAST(InputArray _img, std::vector<KeyPoint>& keypoints, int threshold, bool
int v = ptr[0];
const uchar* tab = &threshold_tab[0] - v + 255;
int d = tab[ptr[pixel[0]]] | tab[ptr[pixel[8]]];
if( d == 0 )
continue;
d &= tab[ptr[pixel[2]]] | tab[ptr[pixel[10]]];
d &= tab[ptr[pixel[4]]] | tab[ptr[pixel[12]]];
d &= tab[ptr[pixel[6]]] | tab[ptr[pixel[14]]];
if( d == 0 )
continue;
d &= tab[ptr[pixel[1]]] | tab[ptr[pixel[9]]];
d &= tab[ptr[pixel[3]]] | tab[ptr[pixel[11]]];
d &= tab[ptr[pixel[5]]] | tab[ptr[pixel[13]]];
d &= tab[ptr[pixel[7]]] | tab[ptr[pixel[15]]];
if( d & 1 )
{
int vt = v - threshold, count = 0;
for( k = 0; k < N; k++ )
{
int x = ptr[pixel[k]];
......@@ -325,11 +325,11 @@ void FAST(InputArray _img, std::vector<KeyPoint>& keypoints, int threshold, bool
count = 0;
}
}
if( d & 2 )
{
int vt = v + threshold, count = 0;
for( k = 0; k < N; k++ )
{
int x = ptr[pixel[k]];
......@@ -349,17 +349,17 @@ void FAST(InputArray _img, std::vector<KeyPoint>& keypoints, int threshold, bool
}
}
}
cornerpos[-1] = ncorners;
if( i == 3 )
continue;
const uchar* prev = buf[(i - 4 + 3)%3];
const uchar* pprev = buf[(i - 5 + 3)%3];
cornerpos = cpbuf[(i - 4 + 3)%3];
ncorners = cornerpos[-1];
for( k = 0; k < ncorners; k++ )
{
j = cornerpos[k];
......@@ -375,7 +375,7 @@ void FAST(InputArray _img, std::vector<KeyPoint>& keypoints, int threshold, bool
}
}
/*
* FastFeatureDetector
*/
......
modules/features2d/src/orb.cpp
View file @ 9399394e
This diff is collapsed.
modules/features2d/test/test_features2d.cpp
View file @ 9399394e
......@@ -1091,3 +1091,51 @@ TEST( Features2d_DescriptorMatcher_FlannBased, regression )
CV_DescriptorMatcherTest test( "descriptor-matcher-flann-based", new FlannBasedMatcher, 0.04f );
test.safe_run();
}
TEST(Features2D_ORB, _1996)
{
cv::Ptr<cv::FeatureDetector> fd = cv::FeatureDetector::create("ORB");
cv::Ptr<cv::DescriptorExtractor> de = cv::DescriptorExtractor::create("ORB");
Mat image = cv::imread(string(cvtest::TS::ptr()->get_data_path()) + "shared/lena.jpg");
ASSERT_FALSE(image.empty());
Mat roi(image.size(), CV_8UC1, Scalar(0));
Point poly[] = {Point(100, 20), Point(300, 50), Point(400, 200), Point(10, 500)};
fillConvexPoly(roi, poly, int(sizeof(poly) / sizeof(poly[0])), Scalar(255));
std::vector<cv::KeyPoint> keypoints;
fd->detect(image, keypoints, roi);
cv::Mat descriptors;
de->compute(image, keypoints, descriptors);
//image.setTo(Scalar(255,255,255), roi);
int roiViolations = 0;
for(std::vector<cv::KeyPoint>::const_iterator kp = keypoints.begin(); kp != keypoints.end(); ++kp)
{
int x = cvRound(kp->pt.x);
int y = cvRound(kp->pt.y);
ASSERT_LE(0, x);
ASSERT_LE(0, y);
ASSERT_GT(image.cols, x);
ASSERT_GT(image.rows, y);
// if (!roi.at<uchar>(y,x))
// {
// roiViolations++;
// circle(image, kp->pt, 3, Scalar(0,0,255));
// }
}
// if(roiViolations)
// {
// imshow("img", image);
// waitKey();
// }
ASSERT_EQ(0, roiViolations);
}
\ No newline at end of file
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