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C++提取文件中信息的方法

更新時(shí)間：2017年07月05日 17:06:50 作者：Anita-ff

這篇文章主要為大家詳細(xì)介紹了C++提取文件中信息的方法，具有一定的參考價(jià)值，感興趣的小伙伴們可以參考一下

對(duì)于文件比較復(fù)雜的時(shí)候，為了獲取文件中的信息，需要一些比較特殊的函數(shù)，比如，getline()、replace（）、atoi,atof等

例子一，讀取以下文件中的數(shù)據(jù)，并保存進(jìn)一個(gè)類里面。

首先，類的定義如下，感覺(jué)是struct，但是按照struct的處理，我這段代碼出錯(cuò)了，不知道什么問(wèn)題，暫時(shí)po出來(lái)吧，有空看看。

struct ImageLabel{
  std::string imagePath;//save圖片路徑名
  int faceBox[4];//輸入點(diǎn)集的最外層包絡(luò)矩形rect四個(gè)參數(shù)
  int landmarkPos[2*LandmarkPointsNum];//輸入點(diǎn)集

private:
  friend class cereal::access;
  /**
   * Serialises this class using cereal.
   *
   * @param[in] ar The archive to serialise to (or to serialise from).
   */
  template<class Archive>
  void serialize(Archive& ar)
  {
    ar(imagePath, faceBox, landmarkPos);
  }
};

然后讀入一系列如下文件，每個(gè)文件的數(shù)據(jù)保存格式相同，因此定義了一個(gè)vector，來(lái)順序存儲(chǔ)每一個(gè)文件對(duì)應(yīng)的類

文件如下：*.pts文件

version: 1
n_points: 68
{
446.000 91.000
449.459 119.344
450.957 150.614
460.552 176.986
471.486 202.157
488.087 226.842
506.016 246.438
524.662 263.865
553.315 271.435
578.732 266.260
599.361 248.966
615.947 220.651
627.439 197.999
635.375 179.064
642.063 156.371
647.302 124.753
646.518 92.944
470.271 117.870
486.218 109.415
503.097 114.454
519.714 120.090
533.680 127.609
571.937 123.590
585.702 117.155
602.344 109.070
620.077 103.951
633.964 111.236
554.931 145.072
554.589 161.106
554.658 177.570
554.777 194.295
532.717 197.930
543.637 202.841
555.652 205.483
565.441 202.069
576.368 197.061
487.474 136.436
499.184 132.337
513.781 133.589
527.594 143.047
513.422 144.769
499.117 144.737
579.876 140.815
590.901 130.008
605.648 128.376
618.343 132.671
606.771 140.525
593.466 141.419
519.040 229.040
536.292 221.978
}

所有pts文件名都保存在一個(gè)TXT文件中，對(duì)應(yīng)的圖像名也保存在一個(gè)TXT文件中，我們需要把圖片的文件路徑加文件名保存到類里面，為了處理方便我們用了replace函數(shù)，直接替換pts文件名的的后三位，得到新的文件名。

void readpic(std::vector<ImageLabel> &Imagelabels){
   cout<<"test readpic"<<endl;

   string filePath = "/Users/anitafang/Downloads/Datasets/300W/300w/01_Indoor/";
  //打開(kāi)png圖片名存儲(chǔ)的TXT文件
  ifstream pngfile;
  pngfile.open("/Users/anitafang/Downloads/Datasets/300W/300w/01_Indoor/pnglist.txt");
    if(!pngfile.is_open()){
    cout<<"不能打開(kāi)文件!"<<endl;
  }
  //ImageLabel* mImageLabel = NULL;//保存圖像信息的類
  string line;//讀取文件的每一行
  while(getline(pngfile,line)){
    //mImageLabel = new ImageLabel();
    ImageLabel mImageLabel;
    //mImageLabel->imagePath=filePath+line;//將文件全路徑保存在 mImageLabel->imagePath
    mImageLabel.imagePath=filePath+line;//將文件全路徑保存在 mImageLabel->imagePath
    cout<<line<<endl;
    //得到pts文件路徑
    string ress="pts";
    string ptss=filePath+line.replace(11,3,ress);
    cout<<line.replace(11,3,ress)<<endl;
    cout<<ptss<<endl;
    //讀取pts文件里面的數(shù)據(jù)
    std::ifstream LabelsFile(ptss, std::ios::in);
    if(!LabelsFile.is_open())
      return;
   //開(kāi)始讀取pts文件內(nèi)容
    int index=0;
    vector<Point2f> vp2f;
    char line11[1024]={0};//存放每行數(shù)據(jù)
    //將文件逐行讀取到string linestr中，然后對(duì)行的內(nèi)容進(jìn)行判斷
    while(LabelsFile.getline(line11, sizeof(line11))){
      //從第四行開(kāi)始把數(shù)據(jù)寫(xiě)進(jìn)landmark數(shù)組中
      if((index>=3)&&(index<139)){
        string x = "";
        string y = "";
        std::stringstream word(line11);
        word >> x;
        word >> y;
        cout<<atof(x.c_str())<<" "<<atof(y.c_str())<<endl;
        mImageLabel.landmarkPos[index-3] =atof(x.c_str());
        mImageLabel.landmarkPos[index+LandmarkPointsNum-3] =atof(y.c_str());
        
        vp2f.push_back(Point2f(mImageLabel.landmarkPos[index-3],mImageLabel.landmarkPos[index+LandmarkPointsNum-3]));
        cout<<"x:"<<mImageLabel.landmarkPos[index-3]<<" y:"<<mImageLabel.landmarkPos[index+LandmarkPointsNum-3]<<endl;
        
      }
      index++;
      
    }
    
  
  Rect rect = boundingRect(vp2f);

  //根據(jù)得到的矩形 輸入到facebox中
  mImageLabel.faceBox[0] = rect.x;
  mImageLabel.faceBox[1] = rect.y;
  mImageLabel.faceBox[2] = rect.width;
  mImageLabel.faceBox[3] = rect.height;
  
  cout<<"facebox"<<mImageLabel.faceBox[0]<<mImageLabel.faceBox[1]<<mImageLabel.faceBox[2]<<mImageLabel.faceBox[3]<<endl;
    
     // close file
  LabelsFile.close();
    //free the object
  Imagelabels.push_back(mImageLabel);

  //mImageLabel == NULL;
    
  }
}

其中，因?yàn)镚etLine讀出來(lái)的數(shù)據(jù)是string類型，因此需要將數(shù)據(jù)轉(zhuǎn)成int型，看到pts文件中數(shù)據(jù)是都是float型，因此先要將string轉(zhuǎn)成float，用的是atof函數(shù)。

另外如果把 Imagelabels 當(dāng)做類來(lái)處理只需要，最開(kāi)始，ImageLabel mImageLabel;后面直接push_back，不需要delete。所有的引用都變成：mImageLabel.faceBox，不能用mImageLabel->landmarkPos。

另外一個(gè)升級(jí)的例子，處理起來(lái)很復(fù)雜，這里把ImageLabel當(dāng)做一個(gè)struct來(lái)處理，這樣需要new，也需要delete,引用的時(shí)候也是用的->，這個(gè)需要注意。

文件是：labels_ibug_300W.xml

稍微看一部分，了解下它的構(gòu)成。

<?xml version='1.0' encoding='ISO-8859-1'?>
<?xml-stylesheet type='text/xsl' href='image_metadata_stylesheet.xsl'?>
<dataset>
<name>iBUG face point dataset - All images</name>
<comment>This folder contains data downloaded from:
http://ibug.doc.ic.ac.uk/resources/facial-point-annotations/

The dataset is actually a combination of the AFW, HELEN, iBUG, and LFPW
face landmark datasets. But the iBUG people have aggregated it all together
and gave them a consistent set of 68 landmarks across all the images, thereby
turning it into one big dataset.

Note that we have adjusted the coordinates of the points from the MATLAB convention
of 1 being the first index to 0 being the first index. So the coordinates in this
file are in the normal C 0-indexed coordinate system.

We have also added left right flips (i.e. mirrors) of each image and also
appropriately flipped the landmarks. This doubles the size of the dataset.
Each of the mirrored versions of the images has a filename that ends with
_mirror.jpg.

Finally, note that the bounding boxes are from dlib's default face detector. For the
faces the detector failed to detect, we guessed at what the bounding box would have been
had the detector found it and used that.</comment>
<images>
 <image file='afw/1051618982_1.jpg'>
  <box top='206' left='469' width='216' height='216'>
   <part name='00' x='482' y='267'/>
   <part name='01' x='483' y='298'/>
   <part name='02' x='487' y='329'/>
   <part name='03' x='491' y='358'/>
   <part name='04' x='503' y='386'/>
   <part name='05' x='523' y='409'/>
   <part name='06' x='543' y='428'/>
   <part name='07' x='565' y='442'/>
   <part name='08' x='591' y='447'/>
   <part name='09' x='620' y='443'/>
   <part name='10' x='647' y='429'/>
   <part name='11' x='671' y='409'/>
   <part name='12' x='688' y='385'/>
   <part name='13' x='699' y='359'/>
   <part name='14' x='704' y='332'/>
   <part name='15' x='707' y='305'/>
   <part name='16' x='708' y='277'/>
   <part name='17' x='502' y='250'/>
   <part name='18' x='518' y='237'/>
   <part name='19' x='537' y='234'/>
   <part name='20' x='557' y='236'/>
   <part name='21' x='575' y='243'/>
   <part name='22' x='619' y='243'/>
   <part name='23' x='639' y='237'/>
   <part name='24' x='659' y='234'/>
   <part name='25' x='679' y='238'/>
   <part name='26' x='693' y='250'/>
   <part name='27' x='596' y='268'/>
   <part name='28' x='595' y='287'/>
   <part name='29' x='594' y='305'/>
   <part name='30' x='593' y='324'/>
   <part name='31' x='570' y='336'/>
   <part name='32' x='581' y='338'/>
   <part name='33' x='593' y='342'/>
   <part name='34' x='605' y='338'/>
   <part name='35' x='615' y='336'/>
   <part name='36' x='523' y='272'/>
   <part name='37' x='536' y='263'/>
   <part name='38' x='551' y='263'/>
   <part name='39' x='564' y='277'/>
   <part name='40' x='550' y='277'/>
   <part name='41' x='535' y='276'/>
   <part name='42' x='626' y='279'/>
   <part name='43' x='642' y='265'/>
   <part name='44' x='657' y='267'/>
   <part name='45' x='670' y='276'/>
   <part name='46' x='658' y='280'/>
   <part name='47' x='642' y='279'/>
   <part name='48' x='544' y='364'/>
   <part name='49' x='565' y='360'/>
   <part name='50' x='580' y='357'/>
   <part name='51' x='591' y='360'/>
   <part name='52' x='603' y='358'/>
   <part name='53' x='621' y='361'/>
   <part name='54' x='641' y='366'/>
   <part name='55' x='621' y='382'/>
   <part name='56' x='603' y='385'/>
   <part name='57' x='590' y='384'/>
   <part name='58' x='579' y='383'/>
   <part name='59' x='563' y='378'/>
   <part name='60' x='552' y='366'/>
   <part name='61' x='580' y='370'/>
   <part name='62' x='591' y='370'/>
   <part name='63' x='603' y='371'/>
   <part name='64' x='634' y='369'/>
   <part name='65' x='603' y='371'/>
   <part name='66' x='591' y='370'/>
   <part name='67' x='580' y='370'/>
  </box>
 </image>
 <image file='afw/111076519_1.jpg'>
  <box top='724' left='1122' width='150' height='150'>
   <part name='00' x='1126' y='765'/>
   <part name='01' x='1123' y='784'/>
   <part name='02' x='1123' y='804'/>
   <part name='03' x='1124' y='822'/>
   <part name='04' x='1131' y='839'/>
   <part name='05' x='1142' y='853'/>
   <part name='06' x='1157' y='865'/>
   <part name='07' x='1172' y='874'/>
   <part name='08' x='1190' y='878'/>
   <part name='09' x='1208' y='878'/>
   <part name='10' x='1225' y='873'/>
   <part name='11' x='1238' y='862'/>
   <part name='12' x='1249' y='846'/>
   <part name='13' x='1256' y='829'/>
   <part name='14' x='1261' y='810'/>
   <part name='15' x='1263' y='792'/>
   <part name='16' x='1264' y='774'/>
   <part name='17' x='1148' y='749'/>
   <part name='18' x='1160' y='745'/>
   <part name='19' x='1171' y='744'/>
   <part name='20' x='1183' y='748'/>
   <part name='21' x='1194' y='753'/>
   <part name='22' x='1227' y='756'/>
   <part name='23' x='1236' y='753'/>
   <part name='24' x='1244' y='753'/>
   <part name='25' x='1251' y='754'/>
   <part name='26' x='1256' y='759'/>
   <part name='27' x='1210' y='769'/>
   <part name='28' x='1210' y='779'/>
   <part name='29' x='1210' y='790'/>
   <part name='30' x='1209' y='800'/>
   <part name='31' x='1187' y='808'/>
   <part name='32' x='1196' y='811'/>
   <part name='33' x='1205' y='814'/>
   <part name='34' x='1212' y='813'/>
   <part name='35' x='1218' y='812'/>
   <part name='36' x='1159' y='766'/>
   <part name='37' x='1167' y='763'/>
   <part name='38' x='1176' y='764'/>
   <part name='39' x='1183' y='770'/>
   <part name='40' x='1175' y='770'/>
   <part name='41' x='1166' y='769'/>
   <part name='42' x='1225' y='776'/>
   <part name='43' x='1235' y='773'/>
   <part name='44' x='1243' y='774'/>
   <part name='45' x='1248' y='777'/>
   <part name='46' x='1241' y='779'/>
   <part name='47' x='1233' y='779'/>
   <part name='48' x='1160' y='825'/>
   <part name='49' x='1176' y='820'/>
   <part name='50' x='1190' y='822'/>
   <part name='51' x='1199' y='824'/>
   <part name='52' x='1209' y='825'/>
   <part name='53' x='1221' y='827'/>
   <part name='54' x='1229' y='833'/>
   <part name='55' x='1218' y='847'/>
   <part name='56' x='1205' y='852'/>
   <part name='57' x='1194' y='851'/>
   <part name='58' x='1184' y='849'/>
   <part name='59' x='1171' y='840'/>
   <part name='60' x='1165' y='827'/>
   <part name='61' x='1189' y='828'/>
   <part name='62' x='1199' y='830'/>
   <part name='63' x='1208' y='831'/>
   <part name='64' x='1225' y='834'/>
   <part name='65' x='1206' y='844'/>
   <part name='66' x='1196' y='844'/>
   <part name='67' x='1186' y='841'/>
  </box>
 </image>
 <image file='afw/111076519_2.jpg'>
  <box top='590' left='1028' width='180' height='180'>
   <part name='00' x='1050' y='620'/>
   <part name='01' x='1046' y='641'/>
   <part name='02' x='1040' y='663'/>

可以找到一些規(guī)律，按照這些規(guī)律來(lái)得到我們需要的數(shù)據(jù)，直接上代碼：

void ReadLabelsFromFile(std::vector<ImageLabel> &Imagelabels, std::string Path = "labels_ibug_300W.xml"){
  std::string ParentPath(trainFilePath);
  std::ifstream LabelsFile(ParentPath+Path, std::ios::in);
  if(!LabelsFile.is_open())
    return;
  std::string linestr;
  while(std::getline(LabelsFile, linestr)){
    linestr = trim(linestr);
    linestr = replace(linestr, "</", "");
    linestr = replace(linestr, "/>", "");
    linestr = replace(linestr, "<", "");
    linestr = replace(linestr, ">", "");
    linestr = replace(linestr, "'", "");
 
    std::vector<std::string> strNodes = split(linestr, " ");
    static ImageLabel* mImageLabel = NULL;
    switch (strNodes.size()) {
    case 1:
      if(strNodes[0] == "image"){
        Imagelabels.push_back(*mImageLabel);
        delete mImageLabel;
      }
      break;
    case 2:
      if(strNodes[0] == "image"){
        mImageLabel = new ImageLabel();
        mImageLabel->imagePath = ParentPath + split(strNodes[1], "=")[1];
//        std::cout << mImageLabel->imagePath << std::endl;
//        cv::Mat Image = cv::imread(mImageLabel->imagePath);
//        cv::imshow("Image", Image);
//        cv::waitKey(0);
      }
      break;
    case 5:
      if(strNodes[0] == "box"){
        mImageLabel->faceBox[0] = atoi(split(strNodes[1], "=")[1].data());
        mImageLabel->faceBox[1] = atoi(split(strNodes[2], "=")[1].data());
        mImageLabel->faceBox[2] = atoi(split(strNodes[3], "=")[1].data());
        mImageLabel->faceBox[3] = atoi(split(strNodes[4], "=")[1].data());
      }
      break;
    case 4:
      if(strNodes[0] == "part"){
        int index = atoi(split(strNodes[1], "=")[1].data());
        mImageLabel->landmarkPos[index] = atoi(split(strNodes[2], "=")[1].data());
        mImageLabel->landmarkPos[index+LandmarkPointsNum] = atoi(split(strNodes[3], "=")[1].data());
      }
      break;
    default:
      break;
    }
  }
  LabelsFile.close();
}

以上就是本文的全部?jī)?nèi)容，希望對(duì)大家的學(xué)習(xí)有所幫助，也希望大家多多支持腳本之家。

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