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Merge pull request #25984 from fengyuentau:imgproc/warpaffine_opt

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imgproc: add optimized warpAffine kernels for 8U/16U/32F + C1/C3/C4 inputs #25984

Merge wtih https://github.com/opencv/opencv_extra/pull/1198.
Merge with https://github.com/opencv/opencv_contrib/pull/3787.


### 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:
Yuantao Feng
2024-10-03 19:01:36 +08:00
committed by GitHub
parent ebf11d36f4
commit 97681bdfce
16 changed files with 3070 additions and 179 deletions
Download Patch File Download Diff File Expand all files Collapse all files
modules/ts/include/opencv2/ts.hpp
+70 -2
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@@ -748,8 +748,76 @@ struct DefaultRngAuto
// test images generation functions
void fillGradient(Mat& img, int delta = 5);
void smoothBorder(Mat& img, const Scalar& color, int delta = 3);
template<typename T>
void fillGradient(Mat& img, int delta = 5)
{
CV_UNUSED(delta);
const int ch = img.channels();
int r, c, i;
for(r=0; r<img.rows; r++)
{
for(c=0; c<img.cols; c++)
{
T vals[] = {(T)r, (T)c, (T)(r*c), (T)(r*c/(r+c+1))};
T *p = (T*)img.ptr(r, c);
for(i=0; i<ch; i++) p[i] = (T)vals[i];
}
}
}
template<>
void fillGradient<uint8_t>(Mat& img, int delta);
template<typename T>
void smoothBorder(Mat& img, const Scalar& color, int delta = 3)
{
const int ch = img.channels();
CV_Assert(!img.empty() && ch <= 4);
Scalar s;
int n = 100/delta;
int nR = std::min(n, (img.rows+1)/2), nC = std::min(n, (img.cols+1)/2);
int r, c, i;
for(r=0; r<nR; r++)
{
double k1 = r*delta/100., k2 = 1-k1;
for(c=0; c<img.cols; c++)
{
auto *p = img.ptr<T>(r, c);
for(i=0; i<ch; i++) s[i] = p[i];
s = s * k1 + color * k2;
for(i=0; i<ch; i++) p[i] = static_cast<T>((s[i]));
}
for(c=0; c<img.cols; c++)
{
auto *p = img.ptr<T>(img.rows-r-1, c);
for(i=0; i<ch; i++) s[i] = p[i];
s = s * k1 + color * k2;
for(i=0; i<ch; i++) p[i] = static_cast<T>((s[i]));
}
}
for(r=0; r<img.rows; r++)
{
for(c=0; c<nC; c++)
{
double k1 = c*delta/100., k2 = 1-k1;
auto *p = img.ptr<T>(r, c);
for(i=0; i<ch; i++) s[i] = p[i];
s = s * k1 + color * k2;
for(i=0; i<ch; i++) p[i] = static_cast<T>((s[i]));
}
for(c=0; c<n; c++)
{
double k1 = c*delta/100., k2 = 1-k1;
auto *p = img.ptr<T>(r, img.cols-c-1);
for(i=0; i<ch; i++) s[i] = p[i];
s = s * k1 + color * k2;
for(i=0; i<ch; i++) p[i] = static_cast<T>((s[i]));
}
}
}
// Utility functions