更新时间:2023-02-27 11:18:31
在opencv中可以使用hog class如下
You can use hog class in opencv as follows
HOGDescriptor hog;
vector<float> ders;
vector<Point> locs;
此函数为您计算 hog 特征
This function computes the hog features for you
hog.compute(grayImg, ders, Size(32, 32), Size(0, 0), locs);
为grayImg
计算的HOG特征存储在ders
向量中,形成一个矩阵,以后可以用于训练.
The HOG features computed for grayImg
are stored in ders
vector to make it into a matrix, which can be used later for training.
Mat Hogfeat(ders.size(), 1, CV_32FC1);
for(int i=0;i<ders.size();i++)
Hogfeat.at<float>(i,0)=ders.at(i);
现在您的 HOG 特征存储在 Hogfeat 矩阵中.
Now your HOG features are stored in Hogfeat matrix.
你也可以通过object hog
来设置窗口大小、单元格大小和块大小,如下:
You can also set the window size, cell size and block size by using object hog
as follows:
hog.blockSize = 16;
hog.cellSize = 4;
hog.blockStride = 8;
// This is for comparing the HOG features of two images without using any SVM
// (It is not an efficient way but useful when you want to compare only few or two images)
// Simple distance
// Consider you have two HOG feature vectors for two images Hogfeat1 and Hogfeat2 and those are same size.
double distance = 0;
for(int i = 0; i < Hogfeat.rows; i++)
distance += abs(Hogfeat.at<float>(i, 0) - Hogfeat.at<float>(i, 0));
if (distance < Threshold)
cout<<"Two images are of same class"<<endl;
else
cout<<"Two images are of different class"<<endl;
希望有用:)