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features2d: fixed out of bounds access in SIFT

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pull/26148/head
Maksim Shabunin 2 months ago
parent 4c81e174bf
commit 6308739638
2 changed files with 38 additions and 24 deletions
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  1. 50
      modules/features2d/src/sift.simd.hpp
  2. 12
      modules/features2d/test/test_sift.cpp

50
modules/features2d/src/sift.simd.hpp
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@ -150,7 +150,7 @@ void findScaleSpaceExtrema(
void calcSIFTDescriptor(
const Mat& img, Point2f ptf, float ori, float scl,
int d, int n, Mat& dst, int row
const int d, const int n, Mat& dst, int row
);
@ -708,7 +708,7 @@ void findScaleSpaceExtrema(
void calcSIFTDescriptor(
const Mat& img, Point2f ptf, float ori, float scl,
int d, int n, Mat& dstMat, int row
const int d, const int n, Mat& dstMat, int row
)
{
CV_TRACE_FUNCTION();
@ -725,7 +725,10 @@ void calcSIFTDescriptor(
cos_t /= hist_width;
sin_t /= hist_width;
int i, j, k, len = (radius*2+1)*(radius*2+1), histlen = (d+2)*(d+2)*(n+2);
int i, j, k;
const int len = (radius*2+1)*(radius*2+1);
const int len_hist = (d+2)*(d+2)*(n+2);
const int len_ddn = d * d * n;
int rows = img.rows, cols = img.cols;
cv::utils::BufferArea area;
@ -736,8 +739,8 @@ void calcSIFTDescriptor(
area.allocate(W, len, CV_SIMD_WIDTH);
area.allocate(RBin, len, CV_SIMD_WIDTH);
area.allocate(CBin, len, CV_SIMD_WIDTH);
area.allocate(hist, histlen, CV_SIMD_WIDTH);
area.allocate(rawDst, len, CV_SIMD_WIDTH);
area.allocate(hist, len_hist, CV_SIMD_WIDTH);
area.allocate(rawDst, len_ddn, CV_SIMD_WIDTH);
area.commit();
Mag = Y;
@ -771,10 +774,10 @@ void calcSIFTDescriptor(
}
}
len = k;
cv::hal::fastAtan2(Y, X, Ori, len, true);
cv::hal::magnitude32f(X, Y, Mag, len);
cv::hal::exp32f(W, W, len);
const int len_left = k;
cv::hal::fastAtan2(Y, X, Ori, len_left, true);
cv::hal::magnitude32f(X, Y, Mag, len_left);
cv::hal::exp32f(W, W, len_left);
k = 0;
#if (CV_SIMD || CV_SIMD_SCALABLE)
@ -788,7 +791,7 @@ void calcSIFTDescriptor(
const v_int32 __1 = vx_setall_s32(1);
const v_int32 __d_plus_2 = vx_setall_s32(d+2);
const v_int32 __n_plus_2 = vx_setall_s32(n+2);
for( ; k <= len - vecsize; k += vecsize )
for( ; k <= len_left - vecsize; k += vecsize )
{
v_float32 rbin = vx_load_aligned(RBin + k);
v_float32 cbin = vx_load_aligned(CBin + k);
@ -839,7 +842,7 @@ void calcSIFTDescriptor(
}
}
#endif
for( ; k < len; k++ )
for( ; k < len_left; k++ )
{
float rbin = RBin[k], cbin = CBin[k];
float obin = (Ori[k] - ori)*bins_per_rad;
@ -892,13 +895,12 @@ void calcSIFTDescriptor(
// and scale the result, so that it can be easily converted
// to byte array
float nrm2 = 0;
len = d*d*n;
k = 0;
#if (CV_SIMD || CV_SIMD_SCALABLE)
{
v_float32 __nrm2 = vx_setzero_f32();
v_float32 __rawDst;
for( ; k <= len - VTraits<v_float32>::vlanes(); k += VTraits<v_float32>::vlanes() )
for( ; k <= len_ddn - VTraits<v_float32>::vlanes(); k += VTraits<v_float32>::vlanes() )
{
__rawDst = vx_load_aligned(rawDst + k);
__nrm2 = v_fma(__rawDst, __rawDst, __nrm2);
@ -906,10 +908,10 @@ void calcSIFTDescriptor(
nrm2 = (float)v_reduce_sum(__nrm2);
}
#endif
for( ; k < len; k++ )
for( ; k < len_ddn; k++ )
nrm2 += rawDst[k]*rawDst[k];
float thr = std::sqrt(nrm2)*SIFT_DESCR_MAG_THR;
const float thr = std::sqrt(nrm2)*SIFT_DESCR_MAG_THR;
i = 0, nrm2 = 0;
#if 0 //CV_AVX2
@ -920,7 +922,7 @@ void calcSIFTDescriptor(
__m256 __dst;
__m256 __nrm2 = _mm256_setzero_ps();
__m256 __thr = _mm256_set1_ps(thr);
for( ; i <= len - 8; i += 8 )
for( ; i <= len_ddn - 8; i += 8 )
{
__dst = _mm256_loadu_ps(&rawDst[i]);
__dst = _mm256_min_ps(__dst, __thr);
@ -936,7 +938,7 @@ void calcSIFTDescriptor(
nrm2_buf[4] + nrm2_buf[5] + nrm2_buf[6] + nrm2_buf[7];
}
#endif
for( ; i < len; i++ )
for( ; i < len_ddn; i++ )
{
float val = std::min(rawDst[i], thr);
rawDst[i] = val;
@ -954,7 +956,7 @@ if( dstMat.type() == CV_32F )
v_float32 __min = vx_setzero_f32();
v_float32 __max = vx_setall_f32(255.0f); // max of uchar
v_float32 __nrm2 = vx_setall_f32(nrm2);
for( k = 0; k <= len - VTraits<v_float32>::vlanes(); k += VTraits<v_float32>::vlanes() )
for( k = 0; k <= len_ddn - VTraits<v_float32>::vlanes(); k += VTraits<v_float32>::vlanes() )
{
__dst = vx_load_aligned(rawDst + k);
__dst = v_min(v_max(v_cvt_f32(v_round(v_mul(__dst, __nrm2))), __min), __max);
@ -965,7 +967,7 @@ if( dstMat.type() == CV_32F )
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Waggressive-loop-optimizations" // iteration XX invokes undefined behavior
#endif
for( ; k < len; k++ )
for( ; k < len_ddn; k++ )
{
dst[k] = saturate_cast<uchar>(rawDst[k]*nrm2);
}
@ -980,7 +982,7 @@ else // CV_8U
v_float32 __dst0, __dst1;
v_uint16 __pack01;
v_float32 __nrm2 = vx_setall_f32(nrm2);
for( k = 0; k <= len - VTraits<v_float32>::vlanes() * 2; k += VTraits<v_float32>::vlanes() * 2 )
for( k = 0; k <= len_ddn - VTraits<v_float32>::vlanes() * 2; k += VTraits<v_float32>::vlanes() * 2 )
{
__dst0 = vx_load_aligned(rawDst + k);
__dst1 = vx_load_aligned(rawDst + k + VTraits<v_float32>::vlanes());
@ -994,7 +996,7 @@ else // CV_8U
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Waggressive-loop-optimizations" // iteration XX invokes undefined behavior
#endif
for( ; k < len; k++ )
for( ; k < len_ddn; k++ )
{
dst[k] = saturate_cast<uchar>(rawDst[k]*nrm2);
}
@ -1004,7 +1006,7 @@ else // CV_8U
}
#else
float nrm1 = 0;
for( k = 0; k < len; k++ )
for( k = 0; k < len_ddn; k++ )
{
rawDst[k] *= nrm2;
nrm1 += rawDst[k];
@ -1013,7 +1015,7 @@ else // CV_8U
if( dstMat.type() == CV_32F )
{
float *dst = dstMat.ptr<float>(row);
for( k = 0; k < len; k++ )
for( k = 0; k < len_ddn; k++ )
{
dst[k] = std::sqrt(rawDst[k] * nrm1);
}
@ -1021,7 +1023,7 @@ else // CV_8U
else // CV_8U
{
uint8_t *dst = dstMat.ptr<uint8_t>(row);
for( k = 0; k < len; k++ )
for( k = 0; k < len_ddn; k++ )
{
dst[k] = saturate_cast<uchar>(std::sqrt(rawDst[k] * nrm1)*SIFT_INT_DESCR_FCTR);
}

12
modules/features2d/test/test_sift.cpp
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@ -30,5 +30,17 @@ TEST(Features2d_SIFT, descriptor_type)
ASSERT_EQ(countNonZero(diff), 0) << "descriptors are not identical";
}
TEST(Features2d_SIFT, regression_26139)
{
auto extractor = cv::SIFT::create();
cv::Mat1b image{cv::Size{300, 300}, 0};
std::vector<cv::KeyPoint> kps {
cv::KeyPoint(154.076813f, 136.160904f, 111.078636f, 216.195618f, 0.00000899323549f, 7)
};
cv::Mat descriptors;
extractor->compute(image, kps, descriptors); // we expect no memory corruption
ASSERT_EQ(descriptors.size(), Size(128, 1));
}
}} // namespace

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