本文整理汇总了C++中Vocabulary::update方法的典型用法代码示例。如果您正苦于以下问题：C++ Vocabulary::update方法的具体用法？C++ Vocabulary::update怎么用？C++ Vocabulary::update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Vocabulary的用法示例。
在下文中一共展示了Vocabulary::update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: main
int main()
{
int imgNum=300;
vector<Mat> imgVec;
imgVec.resize(imgNum);
vector<string> nameVec;
nameVec.resize(imgNum);
vector<vector<KeyPoint> > keyPointsVec;
keyPointsVec.resize(imgNum);
vector<Mat> descriptorsVec;
descriptorsVec.resize(imgNum);
for(int i=0; i<imgNum; i++)
{
char fileName[1024] ={NULL};
sprintf(fileName, "/home/lili/workspace/SLAM/vocabTree/Lip6IndoorDataSet/Images/lip6kennedy_bigdoubleloop_%06d.ppm", i);
nameVec[i]=string(fileName);
imgVec[i]=imread(nameVec[i], CV_LOAD_IMAGE_GRAYSCALE);
}
//-- Step 1: Detect the keypoints using SURF Detector
int minHessian = 400;
SurfFeatureDetector detector(minHessian);
SurfDescriptorExtractor extractor;
vector<unsigned int> labels;
for(int i=0; i<imgNum; i++)
{
detector.detect(imgVec[i], keyPointsVec[i]);
extractor.compute(imgVec[i], keyPointsVec[i], descriptorsVec[i]);
for(int j = 0; j<descriptorsVec[i].rows; j++)
{
labels.push_back(i);
}
}
Mat all_descriptors;
for(int i = 0; i<descriptorsVec.size(); i++)
{
all_descriptors.push_back(descriptorsVec[i]);
}
assert(labels.size() == all_descriptors.rows);
cout<<"all_descriptors.rows "<<all_descriptors.rows<<endl;
cout<<"hahha1 "<<endl;
Vocabulary vocab;
vocab.indexedDescriptors_ = all_descriptors;
vector<KeyPoint> newKeypoints;
Mat newDescriptors;
///add new image to the randomized kd tree
{
string newImageName="/home/lili/workspace/SLAM/vocabTree/Lip6IndoorDataSet/Images/lip6kennedy_bigdoubleloop_000350.ppm";
Mat newImg=imread(newImageName, CV_LOAD_IMAGE_GRAYSCALE);
detector.detect(newImg, newKeypoints);
extractor.compute(newImg, newKeypoints, newDescriptors);
cout<<"newDescriptors.rows: "<<newDescriptors.rows<<endl;
}
vocab.notIndexedDescriptors_ = newDescriptors;
///clustering
int clustersNum;
Mat clusters(15000,64,CV_32F);
//Mat float_all_descriptors;
clustersNum=vocab.clustering(all_descriptors, clusters);
cout<<"clustersNum "<<clustersNum<<endl;
///flann build tree
clock_t begin1 = clock();
vocab.update();
clock_t end1 = clock();
double buildTree_time = double(end1 - begin1) / CLOCKS_PER_SEC;
cout.precision(5);
cout<<"buildTree time "<<buildTree_time<<endl;
cout<<"hahha2 "<<endl;
vector<KeyPoint> queryKeypoints;
Mat queryDescriptors;
///QueryImage
{
string queryImageName="/home/lili/workspace/SLAM/vocabTree/Lip6IndoorDataSet/Images/lip6kennedy_bigdoubleloop_000381.ppm";
//.........这里部分代码省略.........