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Bug #1991 : fixed gpu interpolation (remap, resize, warp...)

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pull/2/head
Vladislav Vinogradov 13 years ago
parent eb4ce67dac
commit 6f32fb025d
3 changed files with 68 additions and 41 deletions
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  1. 48
      modules/gpu/src/opencv2/gpu/device/filters.hpp
  2. 59
      modules/gpu/test/interpolation.hpp
  3. 2
      modules/gpu/test/test_remap.cpp

48
modules/gpu/src/opencv2/gpu/device/filters.hpp
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@ -59,7 +59,7 @@ namespace cv { namespace gpu { namespace device
__device__ __forceinline__ elem_type operator ()(float y, float x) const
{
return src(__float2int_rd(y), __float2int_rd(x));
return src(__float2int_rn(y), __float2int_rn(x));
}
const Ptr2D src;
@ -78,9 +78,6 @@ namespace cv { namespace gpu { namespace device
work_type out = VecTraits<work_type>::all(0);
x -= 0.5f;
y -= 0.5f;
const int x1 = __float2int_rd(x);
const int y1 = __float2int_rd(y);
const int x2 = x1 + 1;
@ -112,24 +109,47 @@ namespace cv { namespace gpu { namespace device
explicit __host__ __device__ __forceinline__ CubicFilter(const Ptr2D& src_) : src(src_) {}
static __device__ __forceinline__ work_type cubicInterpolate(typename TypeTraits<work_type>::ParameterType p0, typename TypeTraits<work_type>::ParameterType p1, typename TypeTraits<work_type>::ParameterType p2, typename TypeTraits<work_type>::ParameterType p3, float x)
static __device__ __forceinline__ float bicubicCoeff(float x_)
{
return p1 + 0.5f * x * (p2 - p0 + x * (2.0f * p0 - 5.0f * p1 + 4.0f * p2 - p3 + x * (3.0f * (p1 - p2) + p3 - p0)));
float x = fabsf(x_);
if (x <= 1.0f)
{
return x * x * (1.5f * x - 2.5f) + 1.0f;
}
else if (x < 2.0f)
{
return x * (x * (-0.5f * x + 2.5f) - 4.0f) + 2.0f;
}
else
{
return 0.0f;
}
}
__device__ elem_type operator ()(float y, float x) const
{
const int xi = __float2int_rn(x);
const int yi = __float2int_rn(y);
const float xmin = ::ceilf(x - 2.0f);
const float xmax = ::floorf(x + 2.0f);
const float ymin = ::ceilf(y - 2.0f);
const float ymax = ::floorf(y + 2.0f);
work_type sum = VecTraits<work_type>::all(0);
float wsum = 0.0f;
work_type arr[4];
for (float cy = ymin; cy <= ymax; cy += 1.0f)
{
for (float cx = xmin; cx <= xmax; cx += 1.0f)
{
const float w = bicubicCoeff(x - cx) * bicubicCoeff(y - cy);
sum = sum + w * src(__float2int_rd(cy), __float2int_rd(cx));
wsum += w;
}
}
arr[0] = cubicInterpolate(saturate_cast<work_type>(src(yi - 2, xi - 2)), saturate_cast<work_type>(src(yi - 2, xi - 1)), saturate_cast<work_type>(src(yi - 2, xi)), saturate_cast<work_type>(src(yi - 2, xi + 1)), (x - xi + 2.0f) / 4.0f);
arr[1] = cubicInterpolate(saturate_cast<work_type>(src(yi - 1, xi - 2)), saturate_cast<work_type>(src(yi - 1, xi - 1)), saturate_cast<work_type>(src(yi - 1, xi)), saturate_cast<work_type>(src(yi - 1, xi + 1)), (x - xi + 2.0f) / 4.0f);
arr[2] = cubicInterpolate(saturate_cast<work_type>(src(yi , xi - 2)), saturate_cast<work_type>(src(yi , xi - 1)), saturate_cast<work_type>(src(yi , xi)), saturate_cast<work_type>(src(yi , xi + 1)), (x - xi + 2.0f) / 4.0f);
arr[3] = cubicInterpolate(saturate_cast<work_type>(src(yi + 1, xi - 2)), saturate_cast<work_type>(src(yi + 1, xi - 1)), saturate_cast<work_type>(src(yi + 1, xi)), saturate_cast<work_type>(src(yi + 1, xi + 1)), (x - xi + 2.0f) / 4.0f);
work_type res = (!wsum)? VecTraits<work_type>::all(0) : sum / wsum;
return saturate_cast<elem_type>(cubicInterpolate(arr[0], arr[1], arr[2], arr[3], (y - yi + 2.0f) / 4.0f));
return saturate_cast<elem_type>(res);
}
const Ptr2D src;

59
modules/gpu/test/interpolation.hpp
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@ -54,7 +54,7 @@ template <typename T> struct NearestInterpolator
{
static T getValue(const cv::Mat& src, float y, float x, int c, int border_type, cv::Scalar borderVal = cv::Scalar())
{
return readVal<T>(src, cvFloor(y), cvFloor(x), c, border_type, borderVal);
return readVal<T>(src, cvRound(y), cvRound(x), c, border_type, borderVal);
}
};
@ -62,9 +62,6 @@ template <typename T> struct LinearInterpolator
{
static T getValue(const cv::Mat& src, float y, float x, int c, int border_type, cv::Scalar borderVal = cv::Scalar())
{
x -= 0.5f;
y -= 0.5f;
int x1 = cvFloor(x);
int y1 = cvFloor(y);
int x2 = x1 + 1;
@ -83,37 +80,47 @@ template <typename T> struct LinearInterpolator
template <typename T> struct CubicInterpolator
{
static float getValue(float p[4], float x)
static float bicubicCoeff(float x_)
{
return static_cast<float>(p[1] + 0.5 * x * (p[2] - p[0] + x*(2.0*p[0] - 5.0*p[1] + 4.0*p[2] - p[3] + x*(3.0*(p[1] - p[2]) + p[3] - p[0]))));
float x = fabsf(x_);
if (x <= 1.0f)
{
return x * x * (1.5f * x - 2.5f) + 1.0f;
}
else if (x < 2.0f)
{
return x * (x * (-0.5f * x + 2.5f) - 4.0f) + 2.0f;
}
else
{
return 0.0f;
}
}
static float getValue(float p[4][4], float x, float y)
static T getValue(const cv::Mat& src, float y, float x, int c, int border_type, cv::Scalar borderVal = cv::Scalar())
{
float arr[4];
const float xmin = ceilf(x - 2.0f);
const float xmax = floorf(x + 2.0f);
arr[0] = getValue(p[0], x);
arr[1] = getValue(p[1], x);
arr[2] = getValue(p[2], x);
arr[3] = getValue(p[3], x);
const float ymin = ceilf(y - 2.0f);
const float ymax = floorf(y + 2.0f);
return getValue(arr, y);
}
float sum = 0.0f;
float wsum = 0.0f;
static T getValue(const cv::Mat& src, float y, float x, int c, int border_type, cv::Scalar borderVal = cv::Scalar())
{
int ix = cvRound(x);
int iy = cvRound(y);
float vals[4][4] =
for (float cy = ymin; cy <= ymax; cy += 1.0f)
{
{(float)readVal<T>(src, iy - 2, ix - 2, c, border_type, borderVal), (float)readVal<T>(src, iy - 2, ix - 1, c, border_type, borderVal), (float)readVal<T>(src, iy - 2, ix, c, border_type, borderVal), (float)readVal<T>(src, iy - 2, ix + 1, c, border_type, borderVal)},
{(float)readVal<T>(src, iy - 1, ix - 2, c, border_type, borderVal), (float)readVal<T>(src, iy - 1, ix - 1, c, border_type, borderVal), (float)readVal<T>(src, iy - 1, ix, c, border_type, borderVal), (float)readVal<T>(src, iy - 1, ix + 1, c, border_type, borderVal)},
{(float)readVal<T>(src, iy , ix - 2, c, border_type, borderVal), (float)readVal<T>(src, iy , ix - 1, c, border_type, borderVal), (float)readVal<T>(src, iy , ix, c, border_type, borderVal), (float)readVal<T>(src, iy , ix + 1, c, border_type, borderVal)},
{(float)readVal<T>(src, iy + 1, ix - 2, c, border_type, borderVal), (float)readVal<T>(src, iy + 1, ix - 1, c, border_type, borderVal), (float)readVal<T>(src, iy + 1, ix, c, border_type, borderVal), (float)readVal<T>(src, iy + 1, ix + 1, c, border_type, borderVal)},
};
for (float cx = xmin; cx <= xmax; cx += 1.0f)
{
const float w = bicubicCoeff(x - cx) * bicubicCoeff(y - cy);
sum += w * readVal<T>(src, cvFloor(cy), cvFloor(cx), c, border_type, borderVal);
wsum += w;
}
}
return cv::saturate_cast<T>(getValue(vals, static_cast<float>((x - ix + 2.0) / 4.0), static_cast<float>((y - iy + 2.0) / 4.0)));
float res = (!wsum)? 0 : sum / wsum;
return cv::saturate_cast<T>(res);
}
};

2
modules/gpu/test/test_remap.cpp
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@ -163,7 +163,7 @@ TEST_P(Remap, Accuracy)
cv::Mat dst_gold;
remapGold(src, xmap, ymap, dst_gold, interpolation, borderType, val);
EXPECT_MAT_NEAR(dst_gold, dst, src.depth() == CV_32F ? 1e-4 : 1.0);
EXPECT_MAT_NEAR(dst_gold, dst, src.depth() == CV_32F ? 1e-3 : 1.0);
}
INSTANTIATE_TEST_CASE_P(GPU_ImgProc, Remap, testing::Combine(

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