看高博的十四講，跑了建立字典的例子，但是顯示單詞數是0：Number of words=0

vocabulary info: Vocabulary: k = 10, L = 5, Weighting = tf-idf, Scoring = L1-norm, Number of words = 0

於是懷疑圖片路徑不對，填寫了完整的路徑，發現可以了。

#include "DBoW3/DBoW3.h"
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/features2d/features2d.hpp>
#include <iostream>
#include <vector>
#include <string>

using namespace cv;
using namespace std;

/***************************************************
 * 本節演示瞭如何根據data/目錄下的十張圖訓練字典
 * ************************************************/

int main( int argc, char** argv )
{
    // read the image 
    cout<<"reading images... "<<endl;
    vector<Mat> images; 
    for ( int i=0; i<10; i++ )
    {
        string path = "/home/user/ch12/data/"+to_string(i+1)+".png";//需要完整路徑
        images.push_back( imread(path) );
	if(!images[i].empty())//如果讀取的圖片為空就輸出提示，很坑啊，希望大家注意
	{
		imshow("讀取影象", images[i]);
			
      		waitKey(30);
	}
	else
	{
		cout<<"image is empty"<<endl;
	}
	
    }
    // detect ORB features
    cout<<"detecting ORB features ... "<<endl;
    Ptr< Feature2D > detector = ORB::create();
    vector<Mat> descriptors;
    for ( Mat& image:images )
    {
        vector<KeyPoint> keypoints; 
        Mat descriptor;
        detector->detectAndCompute( image, Mat(), keypoints, descriptor );
        descriptors.push_back( descriptor );
	
    }
    
    // create vocabulary 
    cout<<"creating vocabulary ... "<<endl;
    DBoW3::Vocabulary vocab;
    vocab.create( descriptors );
    cout<<"vocabulary info: "<<vocab<<endl;
    vocab.save( "vocabulary.yml.gz" );
    cout<<"done"<<endl;
    
    return 0;
}
 

耐心一些，多去找方法想問題。

每天一點進步，堅持下去。