本文整理汇总了C++中misclib::Vector::pop_back方法的典型用法代码示例。如果您正苦于以下问题：C++ Vector::pop_back方法的具体用法？C++ Vector::pop_back怎么用？C++ Vector::pop_back使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类misclib::Vector的用法示例。
在下文中一共展示了Vector::pop_back方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的C++代码示例。
示例1: FindBestCandidate
bool RansacShapeDetector::FindBestCandidate(CandidatesType &candidates,
const MiscLib::Vector< ImmediateOctreeType * > &octrees, const PointCloud &pc,
ScoreVisitorT &scoreVisitor, size_t currentSize,
size_t drawnCandidates, size_t numInvalid, size_t minSize, float numLevels,
float *maxForgottenCandidate, float *candidateFailProb) const
{
if(!candidates.size())
return false;
size_t maxImproveSubsetDuringMaxSearch = octrees.size();
// sort by expected value
std::sort(candidates.begin(), candidates.end());
// check if max is smaller than forgotten candidate
if(candidates.size() && candidates.back().ExpectedValue() < *maxForgottenCandidate)
{
// drawn candidates is wrong!
// need to correct the value
drawnCandidates = std::max(candidates.size(), (size_t)1);
*maxForgottenCandidate = 0;
}
MiscLib::Vector< Candidate * > candHeap;
for(size_t i = candidates.size() - 1; i != -1; --i)
{
if(CandidateFailureProbability(
candidates[i].ExpectedValue(),
currentSize - numInvalid, drawnCandidates, numLevels) > m_options.m_probability)
break;
candHeap.push_back(&candidates[i]);
}
if(!candHeap.size())
{
return false;
}
std::make_heap(candHeap.begin(), candHeap.end(), CandidateHeapPred());
MiscLib::Vector< Candidate * > beatenCands;
Candidate *trial = candHeap.front();
std::pop_heap(candHeap.begin(), candHeap.end(), CandidateHeapPred());
candHeap.pop_back();
float bestCandidateFailureProbability;
while(candHeap.size())
{
if(trial->IsEquivalent(*candHeap.front(), pc, m_options.m_epsilon,
m_options.m_normalThresh))
{
std::pop_heap(candHeap.begin(), candHeap.end(),
CandidateHeapPred());
candHeap.pop_back();
continue;
}
bool isEquivalent = false;
for(size_t j = 0; j < beatenCands.size(); ++j)
{
if(beatenCands[j]->IsEquivalent(*candHeap.front(), pc,
m_options.m_epsilon, m_options.m_normalThresh))
{
isEquivalent = true;
break;
}
}
if(isEquivalent)
{
std::pop_heap(candHeap.begin(), candHeap.end(),
CandidateHeapPred());
candHeap.pop_back();
continue;
}
bestCandidateFailureProbability = CandidateFailureProbability(
trial->ExpectedValue(),
currentSize - numInvalid, drawnCandidates, numLevels);
while((bestCandidateFailureProbability <= m_options.m_probability)
&& (*trial >= *candHeap.front())
&& (trial->UpperBound() >= minSize)
&& trial->ImproveBounds(octrees, pc, scoreVisitor, currentSize,
m_options.m_bitmapEpsilon, octrees.size()))
{
bestCandidateFailureProbability = CandidateFailureProbability(
trial->ExpectedValue(),
currentSize - numInvalid, drawnCandidates, numLevels);
}
if(bestCandidateFailureProbability <= m_options.m_probability
&& trial->UpperBound() >= minSize
&& trial->ComputedSubsets() >= octrees.size()
&& *trial >= *candHeap.front())
break;
if(bestCandidateFailureProbability <= m_options.m_probability
&& trial->UpperBound() >= minSize)
{
candHeap.push_back(trial);
std::push_heap(candHeap.begin(), candHeap.end(), CandidateHeapPred());
}
else if((int)trial->ComputedSubsets()
> std::max(2, ((int)octrees.size()) - 2))
beatenCands.push_back(trial);
//nextCandidate
trial = candHeap.front();
std::pop_heap(candHeap.begin(), candHeap.end(), CandidateHeapPred());
//.........这里部分代码省略.........