generic-library/opencv
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made improvements in ECC code (comments from https://github.com/Itseez/opencv/pull/3845), as well as minor tweak in pthread's based parallel for.

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This commit is contained in:
Vadim Pisarevsky 2015-06-02 01:30:00 +03:00
parent 78e07d3210
commit a4073ed676
2 changed files with 20 additions and 11 deletions
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14
modules/core/src/parallel_pthreads.cpp
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@ -252,7 +252,14 @@ pthread_mutex_t ThreadManager::m_manager_access_mutex = PTHREAD_RECURSIVE_MUTEX_
ThreadManager::ptr_holder ThreadManager::m_instance; ThreadManager::ptr_holder ThreadManager::m_instance;
const char ThreadManager::m_env_name[] = "OPENCV_FOR_THREADS_NUM"; const char ThreadManager::m_env_name[] = "OPENCV_FOR_THREADS_NUM";
#ifdef ANDROID
// many modern phones/tables have 4-core CPUs. Let's use no more
// than 2 threads by default not to overheat the devices
const unsigned int ThreadManager::m_default_number_of_threads = 2;
#else
const unsigned int ThreadManager::m_default_number_of_threads = 8; const unsigned int ThreadManager::m_default_number_of_threads = 8;
#endif
ForThread::~ForThread() ForThread::~ForThread()
{ {
@ -399,11 +406,10 @@ ThreadManager::~ThreadManager()
void ThreadManager::run(const cv::Range& range, const cv::ParallelLoopBody& body, double nstripes) void ThreadManager::run(const cv::Range& range, const cv::ParallelLoopBody& body, double nstripes)
{ {
bool is_work_thread; bool is_work_thread = m_is_work_thread.get()->value;
is_work_thread = m_is_work_thread.get()->value; if( (getNumOfThreads() > 1) && !is_work_thread &&
(range.end - range.start > 1) && (nstripes <= 0 || nstripes >= 1.5) )
if( (getNumOfThreads() > 1) && !is_work_thread && (range.end - range.start > 1) )
{ {
int res = pthread_mutex_trylock(&m_manager_access_mutex); int res = pthread_mutex_trylock(&m_manager_access_mutex);

17
modules/video/src/ecc.cpp
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@ -402,16 +402,19 @@ double cv::findTransformECC(InputArray templateImage,
Mat inputMaskMat = inputMask.getMat(); Mat inputMaskMat = inputMask.getMat();
//to use it for mask warping //to use it for mask warping
Mat preMask = Mat preMask;
inputMaskMat.empty() ? Mat::ones(hd, wd, CV_8U) : inputMaskMat; if(inputMask.empty())
preMask = Mat::ones(hd, wd, CV_8U);
else
threshold(inputMask, preMask, 0, 1, THRESH_BINARY);
//gaussian filtering is optional //gaussian filtering is optional
src.convertTo(templateFloat, templateFloat.type()); src.convertTo(templateFloat, templateFloat.type());
GaussianBlur(templateFloat, templateFloat, Size(5, 5), 0, 0);//is in-place filtering slower? GaussianBlur(templateFloat, templateFloat, Size(5, 5), 0, 0);
Mat preMaskFloat = Mat(hd, wd, CV_32F); Mat preMaskFloat;
preMask.convertTo(preMaskFloat, preMaskFloat.type()); preMask.convertTo(preMaskFloat, CV_32F);
GaussianBlur(preMaskFloat, preMaskFloat, Size(5, 5), 0, 0);//is in-place filtering slower? GaussianBlur(preMaskFloat, preMaskFloat, Size(5, 5), 0, 0);
// Change threshold. // Change threshold.
preMaskFloat *= (0.5/0.95); preMaskFloat *= (0.5/0.95);
// Rounding conversion. // Rounding conversion.
@ -512,7 +515,7 @@ double cv::findTransformECC(InputArray templateImage,
// calculate enhanced correlation coefficiont (ECC)->rho // calculate enhanced correlation coefficiont (ECC)->rho
last_rho = rho; last_rho = rho;
rho = correlation/(imgNorm*tmpNorm); rho = correlation/(imgNorm*tmpNorm);
if (isnan(rho)) { if (cvIsNaN(rho)) {
CV_Error(Error::StsNoConv, "NaN encountered."); CV_Error(Error::StsNoConv, "NaN encountered.");
} }