add HAL for adaptiveThreshold

pull/10171/head
elenagvo 7 years ago
parent c4b158ff91
commit 11ddb9332c
  1. 3
      modules/imgproc/include/opencv2/imgproc.hpp
  2. 15
      modules/imgproc/perf/perf_threshold.cpp
  3. 17
      modules/imgproc/src/hal_replacement.hpp
  4. 5
      modules/imgproc/src/thresh.cpp

@ -2805,7 +2805,8 @@ The function can process the image in-place.
@param src Source 8-bit single-channel image.
@param dst Destination image of the same size and the same type as src.
@param maxValue Non-zero value assigned to the pixels for which the condition is satisfied
@param adaptiveMethod Adaptive thresholding algorithm to use, see cv::AdaptiveThresholdTypes
@param adaptiveMethod Adaptive thresholding algorithm to use, see cv::AdaptiveThresholdTypes.
The BORDER_REPLICATE | BORDER_ISOLATED is used to process boundaries.
@param thresholdType Thresholding type that must be either THRESH_BINARY or THRESH_BINARY_INV,
see cv::ThresholdTypes.
@param blockSize Size of a pixel neighborhood that is used to calculate a threshold value for the

@ -60,15 +60,16 @@ PERF_TEST_P(Size_Only, threshold_otsu, testing::Values(TYPICAL_MAT_SIZES))
CV_ENUM(AdaptThreshType, THRESH_BINARY, THRESH_BINARY_INV)
CV_ENUM(AdaptThreshMethod, ADAPTIVE_THRESH_MEAN_C, ADAPTIVE_THRESH_GAUSSIAN_C)
typedef std::tr1::tuple<Size, AdaptThreshType, AdaptThreshMethod, int> Size_AdaptThreshType_AdaptThreshMethod_BlockSize_t;
typedef perf::TestBaseWithParam<Size_AdaptThreshType_AdaptThreshMethod_BlockSize_t> Size_AdaptThreshType_AdaptThreshMethod_BlockSize;
typedef std::tr1::tuple<Size, AdaptThreshType, AdaptThreshMethod, int, double> Size_AdaptThreshType_AdaptThreshMethod_BlockSize_Delta_t;
typedef perf::TestBaseWithParam<Size_AdaptThreshType_AdaptThreshMethod_BlockSize_Delta_t> Size_AdaptThreshType_AdaptThreshMethod_BlockSize_Delta;
PERF_TEST_P(Size_AdaptThreshType_AdaptThreshMethod_BlockSize, adaptiveThreshold,
PERF_TEST_P(Size_AdaptThreshType_AdaptThreshMethod_BlockSize_Delta, adaptiveThreshold,
testing::Combine(
testing::Values(TYPICAL_MAT_SIZES),
AdaptThreshType::all(),
AdaptThreshMethod::all(),
testing::Values(3, 5)
testing::Values(3, 5),
testing::Values(0.0, 10.0)
)
)
{
@ -76,12 +77,14 @@ PERF_TEST_P(Size_AdaptThreshType_AdaptThreshMethod_BlockSize, adaptiveThreshold,
AdaptThreshType adaptThreshType = get<1>(GetParam());
AdaptThreshMethod adaptThreshMethod = get<2>(GetParam());
int blockSize = get<3>(GetParam());
double C = get<4>(GetParam());
double maxValue = theRNG().uniform(1, 254);
double C = 10.0;
int type = CV_8UC1;
Mat src(sz, type);
Mat src_full(cv::Size(sz.width + 2, sz.height + 2), type);
Mat src = src_full(cv::Rect(1, 1, sz.width, sz.height));
Mat dst(sz, type);
declare.in(src, WARMUP_RNG).out(dst);

@ -630,6 +630,23 @@ inline int hal_ni_medianBlur(const uchar* src_data, size_t src_step, uchar* dst_
#define cv_hal_medianBlur hal_ni_medianBlur
//! @endcond
/**
@brief Calculates adaptive threshold
@param src_data,src_step Source image
@param dst_data,dst_step Destination image
@param width,height Source image dimensions
@param maxValue Value assigned to the pixels for which the condition is satisfied
@param adaptiveMethod Adaptive thresholding algorithm
@param thresholdType Thresholding type
@param blockSize Size of a pixel neighborhood that is used to calculate a threshold value
@param C Constant subtracted from the mean or weighted mean
*/
inline int hal_ni_adaptiveThreshold(const uchar* src_data, size_t src_step, uchar* dst_data, size_t dst_step, int width, int height, double maxValue, int adaptiveMethod, int thresholdType, int blockSize, double C) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
//! @cond IGNORED
#define cv_hal_adaptiveThreshold hal_ni_adaptiveThreshold
//! @endcond
//! @}
#if defined __GNUC__

@ -1530,6 +1530,9 @@ void cv::adaptiveThreshold( InputArray _src, OutputArray _dst, double maxValue,
return;
}
CALL_HAL(adaptiveThreshold, cv_hal_adaptiveThreshold, src.data, src.step, dst.data, dst.step, src.cols, src.rows,
maxValue, method, type, blockSize, delta);
Mat mean;
if( src.data != dst.data )
@ -1537,7 +1540,7 @@ void cv::adaptiveThreshold( InputArray _src, OutputArray _dst, double maxValue,
if (method == ADAPTIVE_THRESH_MEAN_C)
boxFilter( src, mean, src.type(), Size(blockSize, blockSize),
Point(-1,-1), true, BORDER_REPLICATE );
Point(-1,-1), true, BORDER_REPLICATE|BORDER_ISOLATED );
else if (method == ADAPTIVE_THRESH_GAUSSIAN_C)
{
Mat srcfloat,meanfloat;

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