Delphi-OpenCV/samples/VCLDemo/vclPCArecognition/uMainForm.pas

// **************************************************************************************************
// Project Delphi-OpenCV
// **************************************************************************************************
// Contributor:
// Laentir Valetov
// email:laex@bk.ru
// **************************************************************************************************
// You may retrieve the latest version of this file at the GitHub,
// located at git://github.com/Laex/Delphi-OpenCV.git
// **************************************************************************************************
// License:
// The contents of this file are subject to the Mozilla Public License Version 1.1 (the "License");
// you may not use this file except in compliance with the License. You may obtain a copy of the
// License at http://www.mozilla.org/MPL/
//
// Software distributed under the License is distributed on an "AS IS" basis, WITHOUT WARRANTY OF
// ANY KIND, either express or implied. See the License for the specific language governing rights
// and limitations under the License.
//
// Alternatively, the contents of this file may be used under the terms of the
// GNU Lesser General Public License (the  "LGPL License"), in which case the
// provisions of the LGPL License are applicable instead of those above.
// If you wish to allow use of your version of this file only under the terms
// of the LGPL License and not to allow others to use your version of this file
// under the MPL, indicate your decision by deleting  the provisions above and
// replace  them with the notice and other provisions required by the LGPL
// License.  If you do not delete the provisions above, a recipient may use
// your version of this file under either the MPL or the LGPL License.
//
// For more information about the LGPL: http://www.gnu.org/copyleft/lesser.html
// **************************************************************************************************
// The Initial Developer of the Original Code:
// OpenCV: open source computer vision library
// Homepage:    http://opencv.org
// Online docs: http://docs.opencv.org
// Q&A forum:   http://answers.opencv.org
// Dev zone:    http://code.opencv.org
// **************************************************************************************************
// Original: https://sites.google.com/site/komputernoezrenie/end
// **************************************************************************************************
{$POINTERMATH ON}
unit uMainForm;

interface

uses
  Winapi.Windows,
  Winapi.Messages,
  System.SysUtils,
  System.Variants,
  System.Classes,
  Vcl.Graphics,
  Vcl.Controls,
  Vcl.Forms,
  Vcl.Dialogs,
  Vcl.StdCtrls;

type
  TMainForm = class(TForm)
    btn1: TButton;
    Label1: TLabel;
    Label2: TLabel;
    Label3: TLabel;
    Label4: TLabel;
    procedure btn1Click(Sender: TObject);
  private

  public

  end;

var
  MainForm: TMainForm;

implementation

{$R *.dfm}

Uses
  core_c,
  highgui_c,
  core.types_c,
  legacy,
  cvUtils;

procedure TMainForm.btn1Click(Sender: TObject);
const
  N_Samples = 7; // <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>

Type
  TArrayOfpIplImage = pIplImage;
  pArrayOfpIplImage = ^TArrayOfpIplImage;
  TArrayOfFloat     = array [0 .. 0] of Float;
  pArrayOfFloat     = ^TArrayOfFloat;
  ppArrayOfFloat    = ^pArrayOfFloat;

Var
  img_load    : pIplImage;
  img_load_ch1: array [0 .. N_Samples - 1] of pIplImage;

  test_img: pIplImage;

  mean_img     : pIplImage; // <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD> (<28><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD>)
  result_img   : pIplImage; // <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD>
  size         : TCvSize;
  i, j         : Integer;
  facesfilename: AnsiString;
  Tc           : TCvTermCriteria;
  nEigens      : Integer;

  eig_img          : Array Of pIplImage;
  EigenVals        : pCvMat;
  min_val, max_val : double;
  coeffs           : Array Of array of Float;
  projectedTestFace: Array Of Float;
  leastDistSq      : double;
  iTrain, iNearest : Integer;
  distSq           : double;
  d_i              : Float;
  k                : Integer;

begin
  mean_img   := nil; // <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD> (<28><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD>)
  result_img := nil; // <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD>
  // ****************************************
  // <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD> (<28><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>)
  // ****************************************
  for i := 0 to N_Samples - 1 do
  begin
    facesfilename := '../../resource/faces/s' + IntToStr(i + 1) + '/1.pgm';
    img_load      := cvLoadImage(c_str(facesfilename));
    size          := cvSize(
      img_load.width,
      img_load.height);
    img_load_ch1[i] := cvCreateImage(
      size,
      IPL_DEPTH_8U,
      1);
    cvSplit(
      img_load,
      img_load_ch1[i],
      nil,
      nil,
      nil);
    // <20><><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD> <20><> <20><><EFBFBD><EFBFBD><EFBFBD>
    ipDraw(
      10 + (size.width + 10) * i,
      50,
      img_load,
      Handle);
  end;

  // <20><><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD> :)
  Label1.Left    := (10 + (size.width + 10) * N_Samples - Label1.width) div 2;
  Label1.Visible := true;

  Label2.Top  := (50 + (size.height + 10) - 5);
  Label2.Left := (10 + (size.width + 10) + (size.width + 10) * (N_Samples - 1) - Label2.width) div 2;

  Label2.Visible := true;

  Label3.Top  := (50 + (size.height + 20) * 3 - 15);
  Label3.Left := (10 + (size.width + 10) + (size.width + 10) * (N_Samples - 1) - Label3.width) div 2;

  Label3.Visible := true;

  Label4.Top  := (50 + (size.height + 20) * 2 - 15);
  Label4.Left := (10 + (size.width + 10) + (size.width + 10) * (N_Samples - 1) - Label4.width) div 2;

  Label4.Visible := true;

  //

  // ****************************************
  // <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD>
  // ****************************************
  i := 3; // <20><><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
  // <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> (<28><><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD>)
  facesfilename := '../../resource/faces/s' + IntToStr(i + 1) + '/2.pgm';
  img_load      := cvLoadImage(c_str(facesfilename));
  test_img      := cvCreateImage(
    size,
    IPL_DEPTH_8U,
    1);
  cvSplit(
    img_load,
    test_img,
    nil,
    nil,
    nil);
  ipDraw(
    10 + ((size.width + 10) * (N_Samples - 1)) div 2,
    50 + (size.height + 20) * 2,
    img_load,
    Handle);
  // ****************************************
  // <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
  // ****************************************
  // <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD>
  if not Assigned(mean_img) then
  begin
    mean_img := cvCreateImage(
      size,
      IPL_DEPTH_32F,
      1);
  end;
  // <20><><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
  if not Assigned(result_img) then
  begin
    result_img := cvCreateImage(
      size,
      IPL_DEPTH_8U,
      1);
  end;
  // -----------------------------------
  // <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
  // -----------------------------------
  Tc.cType := CV_TERMCRIT_NUMBER or CV_TERMCRIT_EPS;

  // <20><><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> (<28><><EFBFBD><EFBFBD><EFBFBD> <20><> <20><><EFBFBD><EFBFBD><EFBFBD>)
  Tc.max_iter := 100;
  Tc.epsilon  := 0.001;
  // -----------------------------------------------------
  // <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD> = <20><><EFBFBD>-<2D><> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> - 1
  // -----------------------------------------------------
  nEigens := N_Samples - 1;

  // <20><><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD>
  SetLength(
    eig_img,
    nEigens);
  EigenVals := cvCreateMat(
    1,
    nEigens,
    IPL_DEPTH_32F);
  // <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD>
  for i := 0 to N_Samples - 1 do
  begin
    eig_img[i] := cvCreateImage(
      size,
      IPL_DEPTH_32F,
      1);
  end;
  // <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD>
  cvCalcEigenObjects(
    N_Samples,
    @img_load_ch1[0],
    eig_img,
    CV_EIGOBJ_NO_CALLBACK,
    0,
    0,
    @Tc,
    mean_img,
    pFloat(EigenVals.data));
  // ****************************************
  // <20><><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> (<28><><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD>)
  // ****************************************
  for j := 0 to nEigens - 1 do
  begin
    cvMinMaxLoc(
      eig_img[j],
      @min_val,
      @max_val);
    if (min_val <> max_val) then
    begin
      cvConvertScale(
        eig_img[j],
        result_img,
        255.0 / (max_val - min_val),
        -min_val);
      ipDraw(
        10 + (size.width + 10) * j + (size.width + 10) div 2,
        50 + (size.height + 20),
        result_img,
        Handle);
    end;
  end;
  // -----------------------------------------------------------
  // <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
  // -----------------------------------------------------------
  SetLength(
    coeffs,
    N_Samples);
  for i := 0 to N_Samples - 1 do
  begin
    SetLength(
      coeffs[i],
      nEigens);
    cvEigenDecomposite(
      img_load_ch1[i],
      nEigens,
      @eig_img[0],
      CV_EIGOBJ_NO_CALLBACK,
      0,
      mean_img,
      @coeffs[i][0]);
  end;
  // -----------------------------------------------------------
  // <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
  // -----------------------------------------------------------
  SetLength(
    projectedTestFace,
    nEigens);
  cvEigenDecomposite(
    test_img,
    nEigens,
    eig_img,
    CV_EIGOBJ_NO_CALLBACK,
    0,
    mean_img,
    @projectedTestFace[0]);
  // -----------------------------------------------------------
  leastDistSq := DBL_MAX;
  iTrain      := 0;
  iNearest    := 0;

  for iTrain := 0 to N_Samples - 1 do
  begin
    distSq := 0;
    for i  := 0 to nEigens - 1 do
    begin
      d_i    := projectedTestFace[i] - coeffs[iTrain][i];
      distSq := distSq + d_i * d_i / pFloat(EigenVals.data)[i];
    end;
    if distSq < leastDistSq then
    begin
      leastDistSq := distSq;
      iNearest    := iTrain;
    end;

  end;
  // ****************************************
  // <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> (<28><><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>)
  // ****************************************
  // APIDrawIpl(10+(10+size.width),50+(size.height+20)*2,img_load_ch1[iNearest],Form1.Handle);

  for i := 0 to N_Samples - 1 do
  begin
    // <20><><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD> <20><> <20><><EFBFBD><EFBFBD><EFBFBD>
    if (i <> iNearest) then
    begin
      cvLine(
        img_load_ch1[i],
        cvPoint(0, 0),
        cvPoint(size.width, size.height),
        CV_RGB(255, 0, 0),
        3,
        8);
      cvLine(
        img_load_ch1[i],
        cvPoint(size.width, 0),
        cvPoint(0, size.height),
        CV_RGB(255, 0, 0),
        3,
        8);
    end;
    ipDraw(
      10 + (size.width + 10) * i,
      50 + (size.height + 20) * 3,
      img_load_ch1[i],
      Handle);
  end;

  // ****************************************
  // <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
  // ****************************************
  for k := 0 to N_Samples - 1 do
  begin
    cvReleaseImage(eig_img[k]);
    cvReleaseImage(img_load_ch1[k]);
  end;

  // <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
  // for i := 0 to N_Samples - 1 do
  // begin
  // FreeMem(coeffs[i]);
  // end;
  // delete coeffs;

  cvReleaseImage(img_load);
  cvReleaseImage(mean_img);
  cvReleaseImage(test_img);
  cvReleaseImage(result_img);
end;

end.