mirror of
https://github.com/opencv/opencv.git
synced 2026-07-21 19:33:03 +04:00
Extracted IPP to HAL for calcHist function
This commit is contained in:
Akansha Mallick
@@ -26,6 +26,7 @@ add_library(ipphal STATIC
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"${CMAKE_CURRENT_SOURCE_DIR}/src/canny_ipp.cpp"
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"${CMAKE_CURRENT_SOURCE_DIR}/src/threshold_ipp.cpp"
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"${CMAKE_CURRENT_SOURCE_DIR}/src/distancetransform_ipp.cpp"
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"${CMAKE_CURRENT_SOURCE_DIR}/src/histogram_ipp.cpp"
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)
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#TODO: HAVE_IPP_ICV and HAVE_IPP_IW added as private macro till OpenCV itself is
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@@ -154,6 +154,11 @@ int ipp_hal_distanceTransform(const uchar* src_data, size_t src_step, uchar* dst
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#undef cv_hal_distanceTransform
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#define cv_hal_distanceTransform ipp_hal_distanceTransform
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int ipp_hal_calcHist(const uchar* src_data, size_t src_step, int src_type, int src_width, int src_height,
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float* hist_data, int hist_size, const float** ranges, bool uniform, bool accumulate);
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#undef cv_hal_calcHist
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#define cv_hal_calcHist ipp_hal_calcHist
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#endif // IPP_VERSION_X100 >= 700
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#define IPP_DISABLE_PERF_CANNY_MT 1 // cv::Canny OpenCV MT performance is better
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@@ -0,0 +1,223 @@
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// This file is part of OpenCV project.
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// It is subject to the license terms in the LICENSE file found in the top-level directory
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// of this distribution and at http://opencv.org/license.html.
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// Copyright (C) 2026, BigVision LLC, all rights reserved.
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// Third party copyrights are property of their respective owners.
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#include "ipp_hal_imgproc.hpp"
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#include <opencv2/core.hpp>
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#include <opencv2/core/utils/tls.hpp>
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#include "precomp_ipp.hpp"
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#if IPP_VERSION_X100 >= 700
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#define IPP_HISTOGRAM_PARALLEL 1
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namespace cv { namespace ipp { unsigned long long getIppTopFeatures(); } }
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using namespace cv;
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namespace {
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typedef IppStatus(CV_STDCALL * IppiHistogram_C1)(const void* pSrc, int srcStep,
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IppiSize roiSize, Ipp32u* pHist, const IppiHistogramSpec* pSpec, Ipp8u* pBuffer);
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static IppiHistogram_C1 getIppiHistogramFunction_C1(int type)
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{
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IppiHistogram_C1 ippFunction =
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(type == CV_8UC1) ? (IppiHistogram_C1)ippiHistogram_8u_C1R :
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(type == CV_16UC1) ? (IppiHistogram_C1)ippiHistogram_16u_C1R :
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(type == CV_32FC1) ? (IppiHistogram_C1)ippiHistogram_32f_C1R :
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NULL;
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return ippFunction;
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}
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class ipp_calcHistParallelTLS
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{
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public:
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ipp_calcHistParallelTLS() {}
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IppAutoBuffer<IppiHistogramSpec> spec;
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IppAutoBuffer<Ipp8u> buffer;
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IppAutoBuffer<Ipp32u> thist;
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};
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class ipp_calcHistParallel: public ParallelLoopBody
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{
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public:
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ipp_calcHistParallel(const Mat &src, Mat &hist, Ipp32s histSize, const float *ranges, bool uniform, bool &ok):
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ParallelLoopBody(), m_src(src), m_hist(hist), m_ok(ok)
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{
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ok = true;
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m_uniform = uniform;
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m_ranges = ranges;
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m_histSize = histSize;
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m_type = ippiGetDataType(src.type());
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m_levelsNum = histSize+1;
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ippiHistogram_C1 = getIppiHistogramFunction_C1(src.type());
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m_fullRoi = ippiSize(src.size());
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m_bufferSize = 0;
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m_specSize = 0;
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if(!ippiHistogram_C1)
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{
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ok = false;
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return;
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}
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if(ippiHistogramGetBufferSize(m_type, m_fullRoi, &m_levelsNum, 1, 1, &m_specSize, &m_bufferSize) < 0)
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{
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ok = false;
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return;
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}
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hist.setTo(0);
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}
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virtual void operator() (const Range & range) const CV_OVERRIDE
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{
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if(!m_ok)
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return;
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ipp_calcHistParallelTLS *pTls = m_tls.get();
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IppiSize roi = {m_src.cols, range.end - range.start };
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bool mtLoop = false;
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if(m_fullRoi.height != roi.height)
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mtLoop = true;
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if(!pTls->spec)
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{
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pTls->spec.allocate(m_specSize);
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if(!pTls->spec.get())
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{
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m_ok = false;
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return;
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}
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pTls->buffer.allocate(m_bufferSize);
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if(!pTls->buffer.get() && m_bufferSize)
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{
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m_ok = false;
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return;
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}
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if(m_uniform)
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{
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if(ippiHistogramUniformInit(m_type, (Ipp32f*)&m_ranges[0], (Ipp32f*)&m_ranges[1], (Ipp32s*)&m_levelsNum, 1, pTls->spec) < 0)
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{
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m_ok = false;
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return;
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}
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}
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else
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{
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if(ippiHistogramInit(m_type, (const Ipp32f**)&m_ranges, (Ipp32s*)&m_levelsNum, 1, pTls->spec) < 0)
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{
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m_ok = false;
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return;
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}
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}
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pTls->thist.allocate(m_histSize*sizeof(Ipp32u));
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}
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if(CV_INSTRUMENT_FUN_IPP(ippiHistogram_C1, m_src.ptr(range.start), (int)m_src.step, roi, pTls->thist, pTls->spec, pTls->buffer) < 0)
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{
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m_ok = false;
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return;
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}
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if(mtLoop)
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{
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for(int i = 0; i < m_histSize; i++)
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CV_XADD((int*)(m_hist.ptr(i)), *(int*)((Ipp32u*)pTls->thist + i));
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}
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else
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ippiCopy_32s_C1R((Ipp32s*)pTls->thist.get(), sizeof(Ipp32u), (Ipp32s*)m_hist.ptr(), (int)m_hist.step, ippiSize(1, m_histSize));
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}
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private:
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const Mat &m_src;
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Mat &m_hist;
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Ipp32s m_histSize;
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const float *m_ranges;
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bool m_uniform;
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IppiHistogram_C1 ippiHistogram_C1;
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IppiSize m_fullRoi;
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IppDataType m_type;
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Ipp32s m_levelsNum;
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int m_bufferSize;
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int m_specSize;
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mutable Mutex m_syncMutex;
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TLSData<ipp_calcHistParallelTLS> m_tls;
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volatile bool &m_ok;
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const ipp_calcHistParallel & operator = (const ipp_calcHistParallel & );
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};
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static bool ipp_calchist(const Mat &image, Mat &hist, int histSize, const float** ranges, bool uniform, bool accumulate)
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{
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#if IPP_VERSION_X100 < 201801
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// No SSE42 optimization for uniform 32f
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if(uniform && image.depth() == CV_32F && cv::ipp::getIppTopFeatures() == ippCPUID_SSE42)
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return false;
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#endif
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// IPP_DISABLE_HISTOGRAM - https://github.com/opencv/opencv/issues/11544
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// and https://github.com/opencv/opencv/issues/21595
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if ((uniform && (ranges[0][1] - ranges[0][0]) != histSize) || abs(ranges[0][0]) != cvFloor(ranges[0][0]))
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return false;
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Mat ihist = hist;
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if(accumulate)
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ihist.create(1, &histSize, CV_32S);
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bool ok = true;
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int threads = ippiSuggestThreadsNum(image.cols, image.rows, image.elemSize(), (1+((double)ihist.total()/image.total()))*2);
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Range range(0, image.rows);
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ipp_calcHistParallel invoker(image, ihist, histSize, ranges[0], uniform, ok);
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if(!ok)
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return false;
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if(IPP_HISTOGRAM_PARALLEL && threads > 1)
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parallel_for_(range, invoker, threads*2);
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else
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invoker(range);
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if(ok)
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{
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if(accumulate)
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{
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IppiSize histRoi = ippiSize(1, histSize);
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IppAutoBuffer<Ipp32f> fhist(histSize*sizeof(Ipp32f));
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CV_INSTRUMENT_FUN_IPP(ippiConvert_32s32f_C1R, (Ipp32s*)ihist.ptr(), (int)ihist.step, (Ipp32f*)fhist, sizeof(Ipp32f), histRoi);
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CV_INSTRUMENT_FUN_IPP(ippiAdd_32f_C1IR, (Ipp32f*)fhist, sizeof(Ipp32f), (Ipp32f*)hist.ptr(), (int)hist.step, histRoi);
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}
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else
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CV_INSTRUMENT_FUN_IPP(ippiConvert_32s32f_C1R, (Ipp32s*)ihist.ptr(), (int)ihist.step, (Ipp32f*)hist.ptr(), (int)hist.step, ippiSize(1, histSize));
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}
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return ok;
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}
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} // namespace
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int ipp_hal_calcHist(const uchar* src_data, size_t src_step, int src_type, int src_width, int src_height,
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float* hist_data, int hist_size, const float** ranges, bool uniform, bool accumulate)
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{
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CV_HAL_CHECK_USE_IPP();
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Mat image(src_height, src_width, src_type, (void*)src_data, src_step);
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Mat hist(1, &hist_size, CV_32F, (void*)hist_data);
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if(ipp_calchist(image, hist, hist_size, ranges, uniform, accumulate))
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return CV_HAL_ERROR_OK;
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return CV_HAL_ERROR_NOT_IMPLEMENTED;
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}
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#endif
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@@ -120,4 +120,30 @@ static inline int ippiSuggestRowThreadsNum(const ::ipp::IwiImage &image, size_t
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}
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#endif
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#if IPP_VERSION_X100 >= 201700
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#define CV_IPP_MALLOC(SIZE) ippMalloc_L(SIZE)
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#else
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#define CV_IPP_MALLOC(SIZE) ippMalloc((int)SIZE)
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#endif
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template<typename T>
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class IppAutoBuffer
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{
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public:
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IppAutoBuffer() { m_size = 0; m_pBuffer = NULL; }
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explicit IppAutoBuffer(size_t size) { m_size = 0; m_pBuffer = NULL; allocate(size); }
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~IppAutoBuffer() { deallocate(); }
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T* allocate(size_t size) { if(m_size < size) { deallocate(); m_pBuffer = (T*)CV_IPP_MALLOC(size); m_size = size; } return m_pBuffer; }
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void deallocate() { if(m_pBuffer) { ippFree(m_pBuffer); m_pBuffer = NULL; } m_size = 0; }
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inline T* get() { return (T*)m_pBuffer;}
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inline operator T* () { return (T*)m_pBuffer;}
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inline operator const T* () const { return (const T*)m_pBuffer;}
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private:
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IppAutoBuffer(IppAutoBuffer &) {}
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IppAutoBuffer& operator =(const IppAutoBuffer &) {return *this;}
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size_t m_size;
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T* m_pBuffer;
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};
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#endif //__PRECOMP_IPP_HPP__
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@@ -688,152 +688,6 @@ calcHist_8u( std::vector<uchar*>& _ptrs, const std::vector<int>& _deltas,
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}
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}
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#ifdef HAVE_IPP
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typedef IppStatus(CV_STDCALL * IppiHistogram_C1)(const void* pSrc, int srcStep,
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IppiSize roiSize, Ipp32u* pHist, const IppiHistogramSpec* pSpec, Ipp8u* pBuffer);
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static IppiHistogram_C1 getIppiHistogramFunction_C1(int type)
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{
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IppiHistogram_C1 ippFunction =
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(type == CV_8UC1) ? (IppiHistogram_C1)ippiHistogram_8u_C1R :
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(type == CV_16UC1) ? (IppiHistogram_C1)ippiHistogram_16u_C1R :
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(type == CV_32FC1) ? (IppiHistogram_C1)ippiHistogram_32f_C1R :
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NULL;
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return ippFunction;
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}
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class ipp_calcHistParallelTLS
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{
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public:
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ipp_calcHistParallelTLS() {}
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IppAutoBuffer<IppiHistogramSpec> spec;
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IppAutoBuffer<Ipp8u> buffer;
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IppAutoBuffer<Ipp32u> thist;
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};
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class ipp_calcHistParallel: public ParallelLoopBody
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{
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public:
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ipp_calcHistParallel(const Mat &src, Mat &hist, Ipp32s histSize, const float *ranges, bool uniform, bool &ok):
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ParallelLoopBody(), m_src(src), m_hist(hist), m_ok(ok)
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{
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ok = true;
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m_uniform = uniform;
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m_ranges = ranges;
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m_histSize = histSize;
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m_type = ippiGetDataType(src.type());
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m_levelsNum = histSize+1;
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ippiHistogram_C1 = getIppiHistogramFunction_C1(src.type());
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m_fullRoi = ippiSize(src.size());
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m_bufferSize = 0;
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m_specSize = 0;
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if(!ippiHistogram_C1)
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{
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ok = false;
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return;
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}
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if(ippiHistogramGetBufferSize(m_type, m_fullRoi, &m_levelsNum, 1, 1, &m_specSize, &m_bufferSize) < 0)
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{
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ok = false;
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return;
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}
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hist.setTo(0);
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}
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virtual void operator() (const Range & range) const CV_OVERRIDE
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{
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CV_INSTRUMENT_REGION_IPP();
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if(!m_ok)
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return;
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ipp_calcHistParallelTLS *pTls = m_tls.get();
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IppiSize roi = {m_src.cols, range.end - range.start };
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bool mtLoop = false;
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if(m_fullRoi.height != roi.height)
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mtLoop = true;
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if(!pTls->spec)
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{
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pTls->spec.allocate(m_specSize);
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if(!pTls->spec.get())
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{
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m_ok = false;
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return;
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}
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pTls->buffer.allocate(m_bufferSize);
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if(!pTls->buffer.get() && m_bufferSize)
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{
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m_ok = false;
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return;
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}
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if(m_uniform)
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{
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if(ippiHistogramUniformInit(m_type, (Ipp32f*)&m_ranges[0], (Ipp32f*)&m_ranges[1], (Ipp32s*)&m_levelsNum, 1, pTls->spec) < 0)
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{
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m_ok = false;
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return;
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}
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}
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else
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{
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if(ippiHistogramInit(m_type, (const Ipp32f**)&m_ranges, (Ipp32s*)&m_levelsNum, 1, pTls->spec) < 0)
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{
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m_ok = false;
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return;
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}
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}
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pTls->thist.allocate(m_histSize*sizeof(Ipp32u));
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}
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if(CV_INSTRUMENT_FUN_IPP(ippiHistogram_C1, m_src.ptr(range.start), (int)m_src.step, roi, pTls->thist, pTls->spec, pTls->buffer) < 0)
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{
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m_ok = false;
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return;
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}
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if(mtLoop)
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{
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for(int i = 0; i < m_histSize; i++)
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CV_XADD((int*)(m_hist.ptr(i)), *(int*)((Ipp32u*)pTls->thist + i));
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}
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else
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ippiCopy_32s_C1R((Ipp32s*)pTls->thist.get(), sizeof(Ipp32u), (Ipp32s*)m_hist.ptr(), (int)m_hist.step, ippiSize(1, m_histSize));
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}
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private:
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const Mat &m_src;
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Mat &m_hist;
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Ipp32s m_histSize;
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const float *m_ranges;
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bool m_uniform;
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IppiHistogram_C1 ippiHistogram_C1;
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IppiSize m_fullRoi;
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IppDataType m_type;
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Ipp32s m_levelsNum;
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int m_bufferSize;
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int m_specSize;
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mutable Mutex m_syncMutex;
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TLSData<ipp_calcHistParallelTLS> m_tls;
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volatile bool &m_ok;
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const ipp_calcHistParallel & operator = (const ipp_calcHistParallel & );
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};
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#endif
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}
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#ifdef HAVE_OPENVX
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@@ -894,58 +748,6 @@ namespace cv
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}
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#endif
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#ifdef HAVE_IPP
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#define IPP_HISTOGRAM_PARALLEL 1
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namespace cv
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{
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static bool ipp_calchist(const Mat &image, Mat &hist, int histSize, const float** ranges, bool uniform, bool accumulate)
|
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{
|
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CV_INSTRUMENT_REGION_IPP();
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||||
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#if IPP_VERSION_X100 < 201801
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||||
// No SSE42 optimization for uniform 32f
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if(uniform && image.depth() == CV_32F && cv::ipp::getIppTopFeatures() == ippCPUID_SSE42)
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return false;
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||||
#endif
|
||||
|
||||
// IPP_DISABLE_HISTOGRAM - https://github.com/opencv/opencv/issues/11544
|
||||
// and https://github.com/opencv/opencv/issues/21595
|
||||
if ((uniform && (ranges[0][1] - ranges[0][0]) != histSize) || abs(ranges[0][0]) != cvFloor(ranges[0][0]))
|
||||
return false;
|
||||
|
||||
Mat ihist = hist;
|
||||
if(accumulate)
|
||||
ihist.create(1, &histSize, CV_32S);
|
||||
|
||||
bool ok = true;
|
||||
int threads = ippiSuggestThreadsNum(image, (1+((double)ihist.total()/image.total()))*2);
|
||||
Range range(0, image.rows);
|
||||
ipp_calcHistParallel invoker(image, ihist, histSize, ranges[0], uniform, ok);
|
||||
if(!ok)
|
||||
return false;
|
||||
|
||||
if(IPP_HISTOGRAM_PARALLEL && threads > 1)
|
||||
parallel_for_(range, invoker, threads*2);
|
||||
else
|
||||
invoker(range);
|
||||
|
||||
if(ok)
|
||||
{
|
||||
if(accumulate)
|
||||
{
|
||||
IppiSize histRoi = ippiSize(1, histSize);
|
||||
IppAutoBuffer<Ipp32f> fhist(histSize*sizeof(Ipp32f));
|
||||
CV_INSTRUMENT_FUN_IPP(ippiConvert_32s32f_C1R, (Ipp32s*)ihist.ptr(), (int)ihist.step, (Ipp32f*)fhist, sizeof(Ipp32f), histRoi);
|
||||
CV_INSTRUMENT_FUN_IPP(ippiAdd_32f_C1IR, (Ipp32f*)fhist, sizeof(Ipp32f), (Ipp32f*)hist.ptr(), (int)hist.step, histRoi);
|
||||
}
|
||||
else
|
||||
CV_INSTRUMENT_FUN_IPP(ippiConvert_32s32f_C1R, (Ipp32s*)ihist.ptr(), (int)ihist.step, (Ipp32f*)hist.ptr(), (int)hist.step, ippiSize(1, histSize));
|
||||
}
|
||||
return ok;
|
||||
}
|
||||
}
|
||||
#endif
|
||||
|
||||
void cv::calcHist( const Mat* images, int nimages, const int* channels,
|
||||
InputArray _mask, OutputArray _hist, int dims, const int* histSize,
|
||||
const float** ranges, bool uniform, bool accumulate )
|
||||
@@ -973,11 +775,6 @@ void cv::calcHist( const Mat* images, int nimages, const int* channels,
|
||||
if(histdata != hist.data)
|
||||
accumulate = false;
|
||||
|
||||
CV_IPP_RUN(
|
||||
nimages == 1 && dims == 1 && channels && channels[0] == 0
|
||||
&& _mask.empty() && images[0].dims <= 2 && ranges && ranges[0],
|
||||
ipp_calchist(images[0], hist, histSize[0], ranges, uniform, accumulate));
|
||||
|
||||
if (nimages == 1 && dims == 1 && channels && channels[0] == 0 && _mask.empty() && images[0].dims <= 2 && ranges && ranges[0]) {
|
||||
CALL_HAL(calcHist, cv_hal_calcHist, images[0].data, images[0].step, images[0].type(), images[0].cols, images[0].rows,
|
||||
hist.ptr<float>(), histSize[0], ranges, uniform, accumulate);
|
||||
|
||||
Reference in New Issue
Block a user