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define adaptiveMethod and thresholdType for HAL
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@ -21,6 +21,26 @@
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#define CV_HAL_MORPH_DILATE 1
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#define CV_HAL_MORPH_DILATE 1
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//! @}
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//! @}
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//! @name Threshold types
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//! @sa cv::ThresholdTypes
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//! @{
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#define CV_HAL_THRESH_BINARY 0
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#define CV_HAL_THRESH_BINARY_INV 1
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#define CV_HAL_THRESH_TRUNC 2
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#define CV_HAL_THRESH_TOZERO 3
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#define CV_HAL_THRESH_TOZERO_INV 4
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#define CV_HAL_THRESH_MASK 7
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#define CV_HAL_THRESH_OTSU 8
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#define CV_HAL_THRESH_TRIANGLE 16
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//! @}
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//! @name Adaptive threshold algorithm
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//! @sa cv::AdaptiveThresholdTypes
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//! @{
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#define CV_HAL_ADAPTIVE_THRESH_MEAN_C 0
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#define CV_HAL_ADAPTIVE_THRESH_GAUSSIAN_C 1
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//! @}
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//! @}
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//! @}
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#endif
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#endif
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@ -1549,7 +1549,7 @@ void cv::adaptiveThreshold( InputArray _src, OutputArray _dst, double maxValue,
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Mat srcfloat,meanfloat;
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Mat srcfloat,meanfloat;
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src.convertTo(srcfloat,CV_32F);
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src.convertTo(srcfloat,CV_32F);
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meanfloat=srcfloat;
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meanfloat=srcfloat;
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GaussianBlur(srcfloat, meanfloat, Size(blockSize, blockSize), 0, 0, BORDER_REPLICATE);
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GaussianBlur(srcfloat, meanfloat, Size(blockSize, blockSize), 0, 0, BORDER_REPLICATE|BORDER_ISOLATED);
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meanfloat.convertTo(mean, src.type());
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meanfloat.convertTo(mean, src.type());
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}
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}
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else
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else
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