mirror of
https://github.com/opencv/opencv.git
synced 2026-07-31 00:03:03 +04:00
Merge pull request #23098 from savuor:nanMask
finiteMask() and doubles for patchNaNs() #23098 Related to #22826 Connected PR in extra: [#1037@extra](https://github.com/opencv/opencv_extra/pull/1037) ### TODOs: - [ ] Vectorize `finiteMask()` for 64FC3 and 64FC4 ### Changes This PR: * adds a new function `finiteMask()` * extends `patchNaNs()` by CV_64F support * moves `patchNaNs()` and `finiteMask()` to a separate file **NOTE:** now the function is called `finiteMask()` as discussed with the OpenCV core team ### Pull Request Readiness Checklist See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request - [x] I agree to contribute to the project under Apache 2 License. - [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV - [x] The PR is proposed to the proper branch - [x] There is a reference to the original bug report and related work - [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable Patch to opencv_extra has the same branch name. - [x] The feature is well documented and sample code can be built with the project CMake
This commit is contained in:
Rostislav Vasilikhin
committed by
GitHub
GitHub
parent
34f34f6227
commit
53aad98a1a
@@ -729,6 +729,88 @@ struct InRangeOp : public BaseArithmOp
|
||||
}
|
||||
};
|
||||
|
||||
namespace reference {
|
||||
|
||||
template<typename _Tp>
|
||||
struct SoftType;
|
||||
|
||||
template<>
|
||||
struct SoftType<float>
|
||||
{
|
||||
typedef softfloat type;
|
||||
};
|
||||
|
||||
template<>
|
||||
struct SoftType<double>
|
||||
{
|
||||
typedef softdouble type;
|
||||
};
|
||||
|
||||
|
||||
template <typename _Tp>
|
||||
static void finiteMask_(const _Tp *src, uchar *dst, size_t total, int cn)
|
||||
{
|
||||
for(size_t i = 0; i < total; i++ )
|
||||
{
|
||||
bool good = true;
|
||||
for (int c = 0; c < cn; c++)
|
||||
{
|
||||
_Tp val = src[i * cn + c];
|
||||
typename SoftType<_Tp>::type sval(val);
|
||||
|
||||
good = good && !sval.isNaN() && !sval.isInf();
|
||||
}
|
||||
dst[i] = good ? 255 : 0;
|
||||
}
|
||||
}
|
||||
|
||||
static void finiteMask(const Mat& src, Mat& dst)
|
||||
{
|
||||
dst.create(src.dims, &src.size[0], CV_8UC1);
|
||||
|
||||
const Mat *arrays[]={&src, &dst, 0};
|
||||
Mat planes[2];
|
||||
NAryMatIterator it(arrays, planes);
|
||||
size_t total = planes[0].total();
|
||||
size_t i, nplanes = it.nplanes;
|
||||
int depth = src.depth(), cn = src.channels();
|
||||
|
||||
for( i = 0; i < nplanes; i++, ++it )
|
||||
{
|
||||
const uchar* sptr = planes[0].ptr();
|
||||
uchar* dptr = planes[1].ptr();
|
||||
|
||||
switch( depth )
|
||||
{
|
||||
case CV_32F: finiteMask_<float >((const float*)sptr, dptr, total, cn); break;
|
||||
case CV_64F: finiteMask_<double>((const double*)sptr, dptr, total, cn); break;
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
struct FiniteMaskOp : public BaseElemWiseOp
|
||||
{
|
||||
FiniteMaskOp() : BaseElemWiseOp(1, 0, 1, 1, Scalar::all(0)) {}
|
||||
void op(const vector<Mat>& src, Mat& dst, const Mat&)
|
||||
{
|
||||
cv::finiteMask(src[0], dst);
|
||||
}
|
||||
void refop(const vector<Mat>& src, Mat& dst, const Mat&)
|
||||
{
|
||||
reference::finiteMask(src[0], dst);
|
||||
}
|
||||
int getRandomType(RNG& rng)
|
||||
{
|
||||
return cvtest::randomType(rng, _OutputArray::DEPTH_MASK_FLT, 1, 4);
|
||||
}
|
||||
double getMaxErr(int)
|
||||
{
|
||||
return 0;
|
||||
}
|
||||
};
|
||||
|
||||
|
||||
struct ConvertScaleOp : public BaseElemWiseOp
|
||||
{
|
||||
@@ -1573,6 +1655,8 @@ INSTANTIATE_TEST_CASE_P(Core_CmpS, ElemWiseTest, ::testing::Values(ElemWiseOpPtr
|
||||
INSTANTIATE_TEST_CASE_P(Core_InRangeS, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new InRangeSOp)));
|
||||
INSTANTIATE_TEST_CASE_P(Core_InRange, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new InRangeOp)));
|
||||
|
||||
INSTANTIATE_TEST_CASE_P(Core_FiniteMask, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new FiniteMaskOp)));
|
||||
|
||||
INSTANTIATE_TEST_CASE_P(Core_Flip, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new FlipOp)));
|
||||
INSTANTIATE_TEST_CASE_P(Core_Transpose, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new TransposeOp)));
|
||||
INSTANTIATE_TEST_CASE_P(Core_SetIdentity, ElemWiseTest, ::testing::Values(ElemWiseOpPtr(new SetIdentityOp)));
|
||||
@@ -2876,4 +2960,76 @@ TEST(Core_CartPolar, inplace)
|
||||
EXPECT_THROW(cv::cartToPolar(uA[0], uA[1], uA[0], uA[1]), cv::Exception);
|
||||
}
|
||||
|
||||
|
||||
// Check different values for finiteMask()
|
||||
|
||||
template<typename _Tp>
|
||||
_Tp randomNan(RNG& rng);
|
||||
|
||||
template<>
|
||||
float randomNan(RNG& rng)
|
||||
{
|
||||
uint32_t r = rng.next();
|
||||
Cv32suf v;
|
||||
v.u = r;
|
||||
// exp & set a bit to avoid zero mantissa
|
||||
v.u = v.u | 0x7f800001;
|
||||
return v.f;
|
||||
}
|
||||
|
||||
template<>
|
||||
double randomNan(RNG& rng)
|
||||
{
|
||||
uint32_t r0 = rng.next();
|
||||
uint32_t r1 = rng.next();
|
||||
Cv64suf v;
|
||||
v.u = (uint64_t(r0) << 32) | uint64_t(r1);
|
||||
// exp &set a bit to avoid zero mantissa
|
||||
v.u = v.u | 0x7ff0000000000001;
|
||||
return v.f;
|
||||
}
|
||||
|
||||
template<typename T>
|
||||
Mat generateFiniteMaskData(int cn, RNG& rng)
|
||||
{
|
||||
typedef typename reference::SoftType<T>::type SFT;
|
||||
|
||||
SFT pinf = SFT::inf();
|
||||
SFT ninf = SFT::inf().setSign(true);
|
||||
|
||||
const int len = 100;
|
||||
Mat_<T> plainData(1, cn*len);
|
||||
for(int i = 0; i < cn*len; i++)
|
||||
{
|
||||
int r = rng.uniform(0, 3);
|
||||
plainData(i) = r == 0 ? T(rng.uniform(0, 2) ? pinf : ninf) :
|
||||
r == 1 ? randomNan<T>(rng) : T(0);
|
||||
}
|
||||
|
||||
return Mat(plainData).reshape(cn);
|
||||
}
|
||||
|
||||
typedef std::tuple<int, int> FiniteMaskFixtureParams;
|
||||
class FiniteMaskFixture : public ::testing::TestWithParam<FiniteMaskFixtureParams> {};
|
||||
|
||||
TEST_P(FiniteMaskFixture, flags)
|
||||
{
|
||||
auto p = GetParam();
|
||||
int depth = get<0>(p);
|
||||
int channels = get<1>(p);
|
||||
|
||||
RNG rng((uint64)ARITHM_RNG_SEED);
|
||||
Mat data = (depth == CV_32F) ? generateFiniteMaskData<float >(channels, rng)
|
||||
/* CV_64F */ : generateFiniteMaskData<double>(channels, rng);
|
||||
|
||||
Mat nans, gtNans;
|
||||
cv::finiteMask(data, nans);
|
||||
reference::finiteMask(data, gtNans);
|
||||
|
||||
EXPECT_MAT_NEAR(nans, gtNans, 0);
|
||||
}
|
||||
|
||||
// Params are: depth, channels 1 to 4
|
||||
INSTANTIATE_TEST_CASE_P(Core_FiniteMask, FiniteMaskFixture, ::testing::Combine(::testing::Values(CV_32F, CV_64F), ::testing::Range(1, 5)));
|
||||
|
||||
}} // namespace
|
||||
|
||||
Reference in New Issue
Block a user