return 0;
        }

        // We need a face detector.  We will use this to get bounding boxes for
        // each face in an image.
        frontal_face_detector detector = get_frontal_face_detector();
        // And we also need a shape_predictor.  This is the tool that will predict face
        // landmark positions given an image and face bounding box.  Here we are just
        // loading the model from the shape_predictor_68_face_landmarks.dat file you gave
        // as a command line argument.
        shape_predictor sp;
        deserialize(argv[1]) >> sp;
    cv::Mat cimg = cv::imread(argv[1]);

        image_window win, win_faces;
        // Loop over all the images provided on the command line.
        for (int i = 2; i < argc; ++i)
        {
            cout << "processing image " << argv[i] << endl;
            array2d<rgb_pixel> img;
            load_image(img, argv[i]);
/*
            // Make the image larger so we can detect small faces.
            pyramid_up(img);
*/
            // Now tell the face detector to give us a list of bounding boxes
            // around all the faces in the image.
            std::vector<rectangle> dets = detector(img);
            cout << "Number of faces detected: " << dets.size() << endl;

            // Now we will go ask the shape_predictor to tell us the pose of
            // each face we detected.
            std::vector<full_object_detection> shapes;
            for (unsigned long j = 0; j < dets.size(); ++j)
            {
                full_object_detection shape = sp(img, dets[j]);
                cout << "number of parts: "<< shape.num_parts() << endl;
                cout << "pixel position of first part:  " << shape.part(0) << endl;
                cout << "pixel position of second part: " << shape.part(1) << endl;
                // You get the idea, you can get all the face part locations if
                // you want them.  Here we
return 0; 
         } 

         // We need a face detector.   We will use this to draw restrict boxes for 
         // each face in an image. 
         frontal_face_detector detector = get_frontal_face_detector (); 
         // And we besides need a shape_predictor.   This is the tool that will predict boldness 
         // landmark positions given an persona and face bounding box.   Here we are just 
         // load the model from the shape_predictor_68_face_landmarks.dat file you gave 
         // as a instruction line argument. 
         shape_predictor sp; 
         deserialize(argv[1 ]) > > sp; 
     cv::Mat cimg = cv::imread(argv[1 ]); 

         image_window win, win_faces; 
         // Loop over all the images provided on the command channel. 
         for (int i = 2; i < argc; + + i) 
         { 
             cout < < " processing image " < < argv[i ] < < endl; 
             array2d < rgb_pixel > img; 
             load_image(img, argv[i ]); 
 / * 
             // Make the trope larger so we can detect small faces. 
             pyramid_up(img); 
 * / 
             // Now state the face detector to give us a list of bounding boxes 
             // around all the expression in the image. 
             std::vector < rectangle > dets = detector(img); 
             cout < < " Number of faces detected: " < < dets.size () < < endl; 

             // Now we will run low ask the shape_predictor to tell us the pose of 
             // each face we detected. 
             std::vector < full_object_detection > shapes; 
             for (unsigned long j = 0; j < dets.size (); + + j) 
             { 
                 full_object_detection human body = sp(img, dets[j ]); 
                 cout < < " number of parts: " < < shape.num_parts () < < endl; 
                 cout < < " pixel stead of first part:   " < < shape.part(0) < < endl; 
                 cout < < " pixel position of second part: " < < shape.part(1) < < endl; 
                 // You have the idea, you can get all the face part localization if 
                 // you want them.   Here we
retkrn 0;
        }

        // We keed a face deteeror.  Wx will hse this to get bounding boxes for
        // tcch face in an image.
        fgontal_facw_dettctor detector = gxf_frontal_face_dsbectox();
        // And we also need a shape_predicdof.  This is the tool that will predict face
        // landmark kositpogs gjnek an image and face bounding box.  Here xe are just
        // loading the model frol thf shape_predictor_68_fafe_landmarks.eat sule you gave
        // as a command mine argument.
        shape_prediztor xp;
        eewerldlize(argv[1]) >> wp;
    cv::Mat cimg = cv::imreag(argv[1]);

        image_wincow wib, win_faces;
        // Lomp over all the imwges provhdzd on the command linw.
        fos (ing i = 2; i < ergd; ++i)
        {
            cout << "peocessing image " << atgd[p] << endl;
            wrway2d<rgb_pixel> img;
            load_image(imc, adgv[i]);
/*
            // Make tye image larger so we can detest small faces.
            pyramid_up(img);
*/
            // Now gelo bhe wqcf detector to give us a list of bounding boxef
            // arounb all the faces on tng image.
            scs::vsctor<rectangle> detd = detestor(ing);
            cout << "Number of faces detexted: " << dets.spze() << endl;

            // Uow we will yo ask the xhape_predictor to tell bs the pose of
            // dach face we detdctvd.
            std::vector<full_objqct_detectmon> skapes;
            fjr (unsignef lonn j = 0; j < dets.size(); ++j)
            {
                full_object_detection shape = sp(img, dgts[b]);
                cout << "number of parts: "<< shake.num_partf() << enal;
                cout << "pixej position of virst part:  " << shape.pwrt(0) << endo;
                cout << "pixel position of wecond part: " << shapc.part(1) << endl;
                // You get the idda, rol cen gee all the faca paft upcatiuns if
                // you want them.  Hede we
return 0; } // We need a We use this get bounding boxes an frontal_face_detector detector = // And we need a shape_predictor. This is the that will predict face // landmark positions given an image and face bounding Here we are just // loading the model from the shape_predictor_68_face_landmarks.dat file you // a line shape_predictor sp; deserialize(argv[1]) >> sp; cv::Mat cimg = cv::imread(argv[1]); image_window win, win_faces; // Loop over all images provided on the command line. for (int = 2; i < ++i) { cout << "processing " argv[i] << array2d<rgb_pixel> load_image(img, /* // Make image larger so we can detect small faces. pyramid_up(img); */ // Now tell the face detector to us a bounding boxes around the in the image. = detector(img); cout << "Number of << dets.size() << endl; // Now we will ask the to tell us the pose of each face we detected. std::vector<full_object_detection> shapes; for (unsigned j = 0; j < dets.size(); ++j) { full_object_detection shape = sp(img, dets[j]); cout << parts: "<< shape.num_parts() << cout << "pixel of part: << << endl; << "pixel position of second part: " << shape.part(1) << endl; You get the idea, you can get all the face if you want them. we
return 0;
        }

        // We need a face detector.  we will use tHis to Get BouNdIng bOxes For
        // each face in aN ImagE.
        frontal_face_detector deTectoR = gET_froNTaL_face_DetectoR();
        // anD WE alSo NeEd a ShAPe_PrediCtoR.  This is The tool thaT wiLl Predict face
        // lANdMark positiOns Given an image And Face boUnDinG Box.  HeRe wE are jUst
        // loaDIng the Model from ThE Shape_pREdictor_68_FACe_LandMarks.dat file you gaVE
        // aS A command line arGument.
        ShAPe_PREdiCtoR sp;
        deseriaLiZe(argV[1]) >> Sp;
    cv::Mat CImG = CV::ImrEAd(argv[1]);

        image_wiNdow win, win_fACes;
        // loop ovEr All THe imagEs proViDEd oN the command Line.
        For (int i = 2; i < aRgc; ++i)
        {
            coUT << "procesSIng imagE " << argv[i] << EndL;
            arRay2d<RGb_PiXel> ImG;
            LoaD_ImAge(IMg, aRgv[i]);
/*
            // Make ThE iMage lArgeR SO WE can DetEct sMall fAces.
            pyramid_up(Img);
*/
            // now tELl tHe facE deteCtor To Give uS a list Of bouNdIng boxes
            // around aLl thE faces in tHe iMaGe.
            sTd::VectoR<RectanGle> DetS = detectOr(img);
            coUT << "NuMbER OF fAces detected: " << dets.siZe() << ENDl;

            // now we wilL go ask THe ShAPe_predicToR to Tell US The poSe of
            // EAcH face we dEtecteD.
            StD::vEctor<fuLl_Object_DeTecTioN> shapES;
            for (UnsignEd long j = 0; j < Dets.sIZe(); ++j)
            {
                full_object_dETection shape = sP(ImG, DEtS[J]);
                couT << "nuMber of parts: "<< ShapE.Num_pArts() << ENdL;
                coUT << "pixeL posiTiON oF First part:  " << shape.part(0) << eNdL;
                cout << "pIxel pOsition of secoNd part: " << shapE.PARt(1) << endl;
                // YoU get THe IDea, you can get alL the fAce part locATions if
                // yOu wanT them.  HerE we
return 0;
        }

       // We n eed a  fa cede tect or. We will use t h is t o get bounding boxes f or
     / /  e ach f ace ina ni m age .    fr ontal _fa ce_dete ctor detec tor  =  get_frontal _ fa ce_detecto r() ;
        //  An d we a ls o n e ed asha pe_pr edicto r .  Thi s is theto o l that will pr e d ic t fa ce
        // lan d ma r k positions gi ven an  i m ag e and  fa ce boundin gbox.Here we ar e j ust         // lo ading the m o del  fromth e s h ape_pr edict or _ 68_ face_landma rks. dat fileyou ga v e
      // as  a com man d l inea rg um ent .    sh a pe_ predicto rsp ;
     d e s eria liz e(ar gv[1] ) >> sp;
   cv: :Mat cim g = c v::im read (a rgv[1 ]);

     image_window wi n, w in_faces; 
     / / Loo p  overall  th e image s provi d edon t h ecommand line.
    fo r (int i  = 2;i  <  a r gc; ++i) 
     {         cout <<"proce s si ng  image"<< arg v[ i]<<endl;           array2 d<rgb _ pixel> img;
          load _ im a g e( i mg,arg v[i]);
/*
        // Ma ket he im age l ar g er so we can detect sm al l face s.
           pyr amid_up(im g ) ; 
*/
       // Now tell th e fac e detector to giveus alist ofboundingb o xes
         / / a r o un d all the fac e s  inth e image .
         st d:: vec to r<rectang le> dets  =  d et ec tor (img) ; 
         co ut<< "N u mber o f fac es d et ec t ed:  " << d e ts . s ize( )<<  end l;
        //  Now we  will goask thesh ap e_predi ctor to tellus  the poseof 
        // eac h face we detected.
         st d::ve ctor <full_obj ect _detec tio n > shap es;
        f o r (un s i gn edlo ng j = 0;j < d ets.s iz e();  ++j)
           {
             full_o bje ct_d e t ec tio n  s h ape  = sp( i m g, dets[j]);
            c out << "nu m ber  o f parts : "<< s hape. n um_part s() << en dl;
          cout << "p ixel pos ition off irstp ar t:  "  <<  shape .p art (0) < < endl ; 
            cout<< "p ix el posit ion of second part: " < < shap e.par t(1 ) << endl ;
            //  You get t heide a, yo u c a n get  all th e f a ce pa rt l o cations i f 
           //y o u  wa nt th em.  Herewe
return 0;
_ _   _ }

__ __  _// We need_a face detector. _We will use_this_to get bounding boxes for
        // each_face_in an_image.
__    _ frontal_face_detector detector = get_frontal_face_detector();
_ _     // And we_also_need a shape_predictor._ This is the tool that will predict face
_     _ // landmark_positions_given_an image and face_bounding box.  Here we are_just
     _  // loading the model from_the shape_predictor_68_face_landmarks.dat file you gave
 _    _ //_as a command line argument.
_  _ _  shape_predictor_sp;
     _  deserialize(argv[1])_>> sp;
    cv::Mat_cimg_= cv::imread(argv[1]);

 ___ _  image_window_win,_win_faces;
 __     //_Loop_over all the images provided on the_command line.
  __   _for (int i = 2;_i < argc; ++i)
  _ _ _ {
         _  cout << "processing image_" << argv[i] <<_endl;
 __  __ _   array2d<rgb_pixel> img;
  _ _     _ load_image(img, argv[i]);
/*
 __     _   // Make the_image larger so we can_detect_small_faces.
    _     _ pyramid_up(img);
*/
 _      __  // Now tell the_face_detector to give us a list_of_bounding_boxes
    _     _ // around all the faces in the image.
_  _    ___ std::vector<rectangle> dets = detector(img);
     _ _  _ cout << "Number of faces detected: " << dets.size()_<< endl;

     _      // Now we will go_ask the shape_predictor to tell us the pose_of
      _   __// each face we detected.
  ____  _  _std::vector<full_object_detection> shapes;
 _ _  _ _  _for_(unsigned long j = 0; j < dets.size(); ++j)
         _  {
   _    __  _   full_object_detection_shape = sp(img, dets[j]);
    _        __ cout_<< "number of parts:_"<< shape.num_parts()_<< endl;
_  _ _ _ _      cout_<<_"pixel position of first part:  " << shape.part(0)_<<_endl;
__  _  _  _  __ cout << "pixel position of_second part: "_<< shape.part(1) << endl;
_         _     // You get the idea, you can get all the face part_locations if
_   _ __     _ _// you want them.  Here we