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Merge pull request #3916 from CodeLinaro:normalizeLocalBox_extension_Fastcv

Adding FastCV extension for normalizeLocalBox u8 and f32 #3916

Fastcv extension for normalizeLocalBox u8 and f32

### 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
- [ ] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake
This commit is contained in:
adsha-quic
2025-04-10 10:21:35 +05:30
committed by GitHub
parent 1fffe354d2
commit 43a4786af7
4 changed files with 87 additions and 4 deletions

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@@ -1,5 +1,5 @@
/*
* Copyright (c) 2024 Qualcomm Innovation Center, Inc. All rights reserved.
* Copyright (c) 2024-2025 Qualcomm Innovation Center, Inc. All rights reserved.
* SPDX-License-Identifier: Apache-2.0
*/
@@ -58,6 +58,22 @@ CV_EXPORTS_W void filter2D(InputArray _src, OutputArray _dst, int ddepth, InputA
CV_EXPORTS_W void sepFilter2D(InputArray _src, OutputArray _dst, int ddepth, InputArray _kernelX, InputArray _kernelY);
//! @}
//! @addtogroup fastcv
//! @{
/**
* @brief Calculates the local subtractive and contrastive normalization of the image.
* Each pixel of the image is normalized by the mean and standard deviation of the patch centred at the pixel.
* It is optimized for Qualcomm's processors.
* @param _src Input image, should have one channel CV_8U or CV_32F
* @param _dst Output array, should be one channel, CV_8S if src of type CV_8U, or CV_32F if src of CV_32F
* @param pSize Patch size for mean and std dev calculation
* @param useStdDev If 1, bot mean and std dev will be used for normalization, if 0, only mean used
*/
CV_EXPORTS_W void normalizeLocalBox(InputArray _src, OutputArray _dst, Size pSize, bool useStdDev);
//! @}
} // fastcv::
} // cv::

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@@ -1,5 +1,5 @@
/*
* Copyright (c) 2024 Qualcomm Innovation Center, Inc. All rights reserved.
* Copyright (c) 2024-2025 Qualcomm Innovation Center, Inc. All rights reserved.
* SPDX-License-Identifier: Apache-2.0
*/
@@ -120,4 +120,29 @@ PERF_TEST_P(SepFilter2DPerfTest, run,
SANITY_CHECK_NOTHING();
}
typedef perf::TestBaseWithParam<tuple<Size, int, Size, int>> NormalizeLocalBoxPerfTest;
PERF_TEST_P(NormalizeLocalBoxPerfTest, run,
::testing::Combine(::testing::Values(perf::szVGA, perf::sz720p, perf::sz1080p), // image size
::testing::Values(CV_8U,CV_32F), // src image depth
::testing::Values(Size(3,3),Size(5,5)), // patch size
::testing::Values(0,1) // use std dev or not
)
)
{
cv::Size srcSize = get<0>(GetParam());
int depth = get<1>(GetParam());
Size sz = get<2>(GetParam());
bool useStdDev = get<3>(GetParam());
cv::Mat src(srcSize, depth);
cv::Mat dst;
RNG& rng = cv::theRNG();
cvtest::randUni(rng, src, Scalar::all(0), Scalar::all(255));
TEST_CYCLE() cv::fastcv::normalizeLocalBox(src, dst, sz, useStdDev);
SANITY_CHECK_NOTHING();
}
} // namespace

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@@ -1,5 +1,5 @@
/*
* Copyright (c) 2024 Qualcomm Innovation Center, Inc. All rights reserved.
* Copyright (c) 2024-2025 Qualcomm Innovation Center, Inc. All rights reserved.
* SPDX-License-Identifier: Apache-2.0
*/
@@ -361,5 +361,26 @@ void sepFilter2D(InputArray _src, OutputArray _dst, int ddepth, InputArray _kern
}
}
void normalizeLocalBox(InputArray _src, OutputArray _dst, Size pSize, bool useStdDev)
{
CV_Assert(!_src.empty());
int type = _src.type();
CV_Assert(type == CV_8UC1 || type == CV_32FC1);
Size size = _src.size();
int dst_type = type == CV_8UC1 ? CV_8SC1 : CV_32FC1;
_dst.create(size, dst_type);
Mat src = _src.getMat();
Mat dst = _dst.getMat();
if(type == CV_8UC1)
fcvNormalizeLocalBoxu8(src.data, src.cols, src.rows, src.step[0],
pSize.width, pSize.height, useStdDev, (int8_t*)dst.data, dst.step[0]);
else if(type == CV_32FC1)
fcvNormalizeLocalBoxf32((float*)src.data, src.cols, src.rows, src.step[0],
pSize.width, pSize.height, useStdDev, (float*)dst.data, dst.step[0]);
}
} // fastcv::
} // cv::

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@@ -1,5 +1,5 @@
/*
* Copyright (c) 2024 Qualcomm Innovation Center, Inc. All rights reserved.
* Copyright (c) 2024-2025 Qualcomm Innovation Center, Inc. All rights reserved.
* SPDX-License-Identifier: Apache-2.0
*/
@@ -108,6 +108,24 @@ TEST_P(SepFilter2DTest, accuracy)
EXPECT_LT(num_diff_pixels, (src.rows+src.cols)*ksize);
}
typedef testing::TestWithParam<tuple<int>> NormalizeLocalBoxTest;
TEST_P(NormalizeLocalBoxTest, accuracy)
{
bool use_stddev = get<0>(GetParam());
cv::Mat src, dst;
src = imread(cvtest::findDataFile("cv/shared/baboon.png"), cv::IMREAD_GRAYSCALE);
cv::fastcv::normalizeLocalBox(src, dst, Size(5,5), use_stddev);
Scalar s = cv::mean(dst);
if(use_stddev)
EXPECT_LT(s[0],1);
else
EXPECT_LT(s[0],50);
}
INSTANTIATE_TEST_CASE_P(FastCV_Extension, GaussianBlurTest, Combine(
/*image size*/ ::testing::Values(perf::szVGA, perf::sz720p, perf::sz1080p),
/*image depth*/ ::testing::Values(CV_8U,CV_16S,CV_32S),
@@ -126,4 +144,7 @@ INSTANTIATE_TEST_CASE_P(FastCV_Extension, SepFilter2DTest, Combine(
/*kernel size*/ Values(3, 5, 7, 9, 11)
));
INSTANTIATE_TEST_CASE_P(FastCV_Extension, NormalizeLocalBoxTest, Values(0,1));
}} // namespaces opencv_test, ::