mirror of
https://github.com/Laex/Delphi-OpenCV.git
synced 2024-11-16 08:15:52 +01:00
4049cda768
Signed-off-by: Laex <laex@bk.ru>
704 lines
16 KiB
ObjectPascal
704 lines
16 KiB
ObjectPascal
// *****************************************************************
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// Delphi-OpenCV Class Demo
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// Copyright (C) 2013 Project Delphi-OpenCV
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// ****************************************************************
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// Contributor:
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// Laentir Valetov
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// email:laex@bk.ru
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// ****************************************************************
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// You may retrieve the latest version of this file at the GitHub,
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// located at git://github.com/Laex/Delphi-OpenCV.git
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// ****************************************************************
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// The contents of this file are used with permission, subject to
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// the Mozilla Public License Version 1.1 (the 'License'); you may
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// not use this file except in compliance with the License. You may
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// obtain a copy of the License at
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// http://www.mozilla.org/MPL/MPL-1_1Final.html
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//
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// Software distributed under the License is distributed on an
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// 'AS IS' basis, WITHOUT WARRANTY OF ANY KIND, either express or
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// implied. See the License for the specific language governing
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// rights and limitations under the License.
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// *******************************************************************
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program ObjectTrack;
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{$APPTYPE CONSOLE}
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{$POINTERMATH ON}
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{$R *.res}
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uses
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System.Math,
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System.SysUtils,
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System.Classes,
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core_c,
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highgui_c,
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imgproc_c,
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imgproc.types_c,
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core.types_c,
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cvUtils;
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// default capture width and height
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const
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FRAME_WIDTH = 640;
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FRAME_HEIGHT = 480;
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// max number of objects to be detected in frame
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MAX_NUM_OBJECTS = 50;
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// minimum and maximum object area
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MIN_OBJECT_AREA = 20 * 20;
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MAX_OBJECT_AREA = FRAME_HEIGHT * FRAME_WIDTH / 1.5;
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// names that will appear at the top of each window
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windowName = 'Original Image';
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windowName1 = 'HSV Image';
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windowName2 = 'Thresholded Image';
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windowName3 = 'After Morphological Operations';
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trackbarWindowName = 'Trackbars';
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Var
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// initial min and max HSV filter values.
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// these will be changed using trackbars
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H_MIN : integer = 170; // 0;
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H_MAX : integer = 180;
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CH_MAX: integer = 256;
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S_MIN : integer = 160; // 0;
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S_MAX : integer = 256;
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CS_MAX: integer = 256;
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V_MIN : integer = 60; // 0;
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V_MAX : integer = 256;
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CV_MAX: integer = 256;
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procedure on_trackbar(i: integer); cdecl;
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begin
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// This function gets called whenever a
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// trackbar position is changed
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end;
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procedure createTrackbars;
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begin
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// create window for trackbars
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cvNamedWindow(
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trackbarWindowName,
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0);
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/// /create memory to store trackbar name on window
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// char TrackbarName[50];
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// sprintf( TrackbarName, 'H_MIN', H_MIN);
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// sprintf( TrackbarName, 'H_MAX', H_MAX);
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// sprintf( TrackbarName, 'S_MIN', S_MIN);
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// sprintf( TrackbarName, 'S_MAX', S_MAX);
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// sprintf( TrackbarName, 'V_MIN', V_MIN);
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// sprintf( TrackbarName, 'V_MAX', V_MAX);
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// create trackbars and insert them into window
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// 3 parameters are: the address of the variable that is changing when the trackbar is moved(eg.H_LOW),
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// the max value the trackbar can move (eg. H_HIGH),
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// and the function that is called whenever the trackbar is moved(eg. on_trackbar)
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// ----> ----> ---->
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cvCreateTrackbar(
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'H_MIN',
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trackbarWindowName,
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@H_MIN,
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CH_MAX,
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on_trackbar);
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cvCreateTrackbar(
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'H_MAX',
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trackbarWindowName,
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@H_MAX,
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CH_MAX,
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on_trackbar);
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cvCreateTrackbar(
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'S_MIN',
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trackbarWindowName,
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@S_MIN,
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CS_MAX,
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on_trackbar);
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cvCreateTrackbar(
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'S_MAX',
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trackbarWindowName,
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@S_MAX,
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CS_MAX,
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on_trackbar);
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cvCreateTrackbar(
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'V_MIN',
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trackbarWindowName,
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@V_MIN,
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CV_MAX,
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on_trackbar);
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cvCreateTrackbar(
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'V_MAX',
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trackbarWindowName,
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@V_MAX,
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CV_MAX,
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on_trackbar);
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end;
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procedure drawObject(x: integer; y: integer; frame: pIplImage);
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Var
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font: TCvFont;
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begin
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// use some of the openCV drawing functions to draw crosshairs
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// on your tracked image!
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// added 'if' and 'else' statements to prevent
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// memory errors from writing off the screen (ie. (-25,-25) is not within the window!)
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cvCircle(
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frame,
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cvPoint(x, y),
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20,
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cvScalar(0, 255, 0),
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2);
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if (y - 25) > 0 then
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cvLine(
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frame,
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cvPoint(x, y),
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cvPoint(x, y - 25),
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cvScalar(0, 255, 0),
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2)
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else
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cvLine(
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frame,
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cvPoint(x, y),
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cvPoint(x, 0),
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cvScalar(0, 255, 0),
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2);
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if (y + 25) < FRAME_HEIGHT then
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cvLine(
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frame,
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cvPoint(x, y),
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cvPoint(x, y + 25),
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cvScalar(0, 255, 0),
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2)
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else
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cvLine(
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frame,
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cvPoint(x, y),
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cvPoint(x, FRAME_HEIGHT),
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cvScalar(0, 255, 0),
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2);
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if (x - 25) > 0 then
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cvLine(
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frame,
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cvPoint(x, y),
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cvPoint(x - 25, y),
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cvScalar(0, 255, 0),
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2)
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else
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cvLine(
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frame,
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cvPoint(x, y),
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cvPoint(0, y),
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cvScalar(0, 255, 0),
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2);
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if (x + 25) < FRAME_WIDTH then
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cvLine(
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frame,
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cvPoint(x, y),
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cvPoint(x + 25, y),
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cvScalar(0, 255, 0),
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2)
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else
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cvLine(
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frame,
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cvPoint(x, y),
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cvPoint(FRAME_WIDTH, y),
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cvScalar(0, 255, 0),
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2);
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cvInitFont(
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@font,
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CV_FONT_HERSHEY_COMPLEX,
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1.0,
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1.0,
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0,
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1,
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CV_AA);
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cvPutText(
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frame,
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c_str(intToStr(x) + ',' + intToStr(y)),
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cvPoint(x, y + 30),
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@font,
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cvScalar(0, 255, 0));
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end;
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procedure morphOps(thresh: pIplImage);
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Var
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erodeElement, dilateElement: pIplConvKernel;
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begin
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// create structuring element that will be used to "dilate" and "erode" image.
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// the element chosen here is a 3px by 3px rectangle
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erodeElement := cvCreateStructuringElementEx(
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3,
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3,
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1,
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1,
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CV_SHAPE_RECT);
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// dilate with larger element so make sure object is nicely visible
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dilateElement := cvCreateStructuringElementEx(
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8,
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8,
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3,
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3,
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CV_SHAPE_RECT);
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cvErode(
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thresh,
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thresh,
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erodeElement,
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2);
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cvDilate(
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thresh,
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thresh,
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dilateElement,
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2);
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cvReleaseStructuringElement(erodeElement);
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cvReleaseStructuringElement(dilateElement);
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end;
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Type
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TContours = TArray<TArray<pCvPoint2D32f>>;
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TVec4<T> = array [0 .. 3] of T;
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TVec4i = TVec4<integer>;
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THierarchy = TArray<TVec4i>;
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function Vec4i(const v0, v1, v2, v3: integer): TVec4i;
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begin
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Result[0] := v0;
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Result[1] := v1;
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Result[2] := v2;
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Result[3] := v3;
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end;
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procedure cfindContours(image: pIplImage; Var _contours: TContours; Var _hierarchy: THierarchy; mode, method: integer;
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offset: TcvPoint);
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Var
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storage : pCvMemStorage;
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_cimage : pIplImage;
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_ccontours : pCvSeq;
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all_contours, ps: pCvSeq;
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j, i, total : integer;
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tree_iterator : TCvTreeNodeIterator;
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h_next, //
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h_prev, //
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v_next, //
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v_prev: integer;
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reader : TCvSeqReader;
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Count : integer;
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begin
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storage := cvCreateMemStorage(0);
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_cimage := cvCloneImage(image);
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_ccontours := nil;
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// SetLength(
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// _hierarchy,
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// 0);
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cvFindContours(
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_cimage,
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storage,
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@_ccontours,
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sizeof(TCvContour),
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mode,
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method,
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offset);
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if not Assigned(_ccontours) then
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begin
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cvReleaseMemStorage(storage);
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cvReleaseImage(_cimage);
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SetLength(
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_contours,
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0);
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Exit;
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end;
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all_contours := cvTreeToNodeSeq(
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_ccontours,
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sizeof(TCvSeq),
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storage);
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ps := all_contours;
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total := 0;
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While Assigned(ps) do
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begin
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Inc(total);
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ps := ps^.h_next;
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end;
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SetLength(
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_contours,
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total);
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SetLength(
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_hierarchy,
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total);
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cvInitTreeNodeIterator(
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tree_iterator,
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all_contours,
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3);
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ps := cvNextTreeNode(@tree_iterator);
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j := 0;
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while Assigned(ps) do
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begin
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// pCvContour(ps)^.color := i;
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Count := ps^.total;
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cvStartReadSeq(
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ps,
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@reader);
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if not CV_IS_SEQ_CLOSED(ps) then
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Count := Count - 1;
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SetLength(
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_contours[j],
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Count);
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for i := 0 to Count - 1 do
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begin
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CV_READ_SEQ_ELEM(
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@_contours[j][i],
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reader,
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sizeof(_contours[j][0]));
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end;
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ps := cvNextTreeNode(@tree_iterator);
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Inc(j);
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end;
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// for i := 0 to total - 1 do
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// begin
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// ps := cvNextTreeNode(@tree_iterator);
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// pCvContour(ps)^.color := i;
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// Count := ps^.total;
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// cvStartReadSeq(
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// ps,
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// @reader);
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// if not CV_IS_SEQ_CLOSED(ps) then
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// Count := Count - 1;
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// CV_READ_SEQ_ELEM(
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// pt,
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// reader);
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//
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// _contours[i] := AllocMem(ps^.total * sizeof(TCvPoint2D32f));
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// // Mat ci = _contours.getMat(i);
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// // return (flags & Mat::CONTINUOUS_FLAG) != 0;
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// // CV_Assert(ci.isContinuous());
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// if ps^.h_next <> nil then
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// cvCvtSeqToArray(
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// ps,
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// @_contours[i],
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// CV_WHOLE_SEQ);
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//
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// h_next := ifthen(
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// Assigned(ps^.h_next),
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// pCvContour(ps^.h_next)^.color,
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// -1);
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// h_prev := ifthen(
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// Assigned(ps^.h_prev),
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// pCvContour(ps^.h_prev)^.color,
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// -1);
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// v_next := ifthen(
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// Assigned(ps^.v_next),
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// pCvContour(ps^.v_next)^.color,
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// -1);
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// v_prev := ifthen(
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// Assigned(ps^.v_prev),
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// pCvContour(ps^.v_prev)^.color,
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// -1);
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// _hierarchy[i] := Vec4i(
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// h_next,
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// h_prev,
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// v_next,
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// v_prev);
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// end;
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end;
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Var
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// Matrix to store each frame of the webcam feed
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cameraFeed: pIplImage;
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procedure findContours(const image: pIplImage; var contours: TContours; Var hierarchy: THierarchy;
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mode, method: integer);
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Var
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_hierarchy : pCvMemStorage;
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_contours : pCvSeq;
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dst_th : pIplImage;
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contoursCont: integer;
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l_pt0, l_pt1: TcvPoint;
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l_reader : TCvSeqReader;
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l_iterator : TCvTreeNodeIterator;
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i : integer;
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begin
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_hierarchy := cvCreateMemStorage(0);
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dst_th := cvCreateImage(
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cvGetSize(image),
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IPL_DEPTH_8U,
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1);
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cvThreshold(
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image,
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dst_th,
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128,
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255,
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// CV_THRESH_BINARY_INV
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CV_THRESH_BINARY);
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cvSmooth(
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dst_th, // function input
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dst_th, // function output
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CV_GAUSSIAN, // use Gaussian filter (average nearby pixels, with closest pixels weighted more)
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9, // smoothing filter window width
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9); // smoothing filter window height
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_contours := nil;
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SetLength(
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contours,
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0);
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SetLength(
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hierarchy,
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0);
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contoursCont := cvFindContours(
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dst_th,
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_hierarchy,
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@_contours,
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sizeof(TCvContour),
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mode,
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method,
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cvPoint(0, 0));
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// cvInitTreeNodeIterator(
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// l_iterator,
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// _contours,
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// 1);
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// _contours := cvNextTreeNode(@l_iterator);
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// while Assigned(_contours) do
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// begin
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// cvStartReadSeq(
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// _contours,
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// @l_reader,
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// 0);
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// // <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD>
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// CV_READ_SEQ_ELEM(
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// @l_pt0,
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// l_reader,
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// sizeof(l_pt0));
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// // l_pts1.push_back(l_pt0);
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// for i := 0 to _contours^.total - 1 do
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// begin
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// // <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD>
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// CV_READ_SEQ_ELEM(
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// @l_pt1,
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// l_reader,
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// sizeof(l_pt0));
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// cvLine(
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// cameraFeed,
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// l_pt0,
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// l_pt1,
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// CV_RGB(0, 255, 0),
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// 2);
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// l_pt0 := l_pt1;
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// // l_pts1.push_back(l_pt0);
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// end;
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// _contours := cvNextTreeNode(@l_iterator);
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// end;
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if contoursCont > 0 then
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While Assigned(_contours) do
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begin
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// if CV_IS_SEQ_CLOSED(_contours) then
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cvDrawContours(
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cameraFeed,
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_contours,
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CV_RGB(52, 201, 36),
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CV_RGB(36, 201, 197),
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-1,
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CV_FILLED,
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CV_AA,
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cvPoint(0, 0)); // <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD> <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
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_contours := _contours^.h_next;
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end;
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cvReleaseMemStorage(_hierarchy);
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cvReleaseImage(dst_th);
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end;
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|
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procedure trackFilteredObject(Var x, y: integer; threshold: pIplImage; var cameraFeed: pIplImage);
|
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Var
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temp, dst: pIplImage;
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index : integer;
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// these two vectors needed for output of findContours
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contours : TContours;
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hierarchy : THierarchy;
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refArea : double;
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objectFound: Boolean;
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numObjects : integer;
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area : double;
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// moment : IMoments;
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begin
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// find contours of filtered image using openCV findContours function
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findContours(
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threshold,
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contours,
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hierarchy,
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CV_RETR_EXTERNAL,
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CV_CHAIN_APPROX_SIMPLE);
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// use moments method to find our filtered object
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refArea := 0;
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objectFound := false;
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//
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// // if hierarchy.block_size>0 then
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// begin
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// numObjects := Length(hierarchy);
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// // if number of objects greater than MAX_NUM_OBJECTS we have a noisy filter
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// if (numObjects < MAX_NUM_OBJECTS) then
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// begin
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// index := 0;
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// While index >= 0 do
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// begin
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// moment := Moments((cv: : Mat)contours[index]);
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// area := moment.m00;
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// // if the area is less than 20 px by 20px then it is probably just noise
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||
// // if the area is the same as the 3/2 of the image size, probably just a bad filter
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||
// // we only want the object with the largest area so we safe a reference area each
|
||
// // iteration and compare it to the area in the next iteration.
|
||
// if (area > MIN_OBJECT_AREA) and (area < MAX_OBJECT_AREA) and (area > refArea) then
|
||
// begin
|
||
// x := moment.m10 / area;
|
||
// y := moment.m01 / area;
|
||
// objectFound = true;
|
||
// end
|
||
// else
|
||
// objectFound = false;
|
||
// index := hierarchy[index][0];
|
||
// end;
|
||
// // let user know you found an object
|
||
// if (objectFound = = true) then
|
||
// begin
|
||
// putText(
|
||
// cameraFeed,
|
||
// 'Tracking Object',
|
||
// cvPoint(0, 50),
|
||
// 2,
|
||
// 1,
|
||
// cvScalar(0, 255, 0),
|
||
// 2);
|
||
// // draw object location on screen
|
||
// drawObject(
|
||
// x,
|
||
// y,
|
||
// cameraFeed);
|
||
// end;
|
||
//
|
||
// end
|
||
// else
|
||
// putText(
|
||
// cameraFeed,
|
||
// 'TOO MUCH NOISE! ADJUST FILTER',
|
||
// cvPoint(0, 50),
|
||
// 1,
|
||
// 2,
|
||
// cvScalar(0, 0, 255),
|
||
// 2);
|
||
// end;
|
||
end;
|
||
|
||
Var
|
||
// some boolean variables for different functionality within this program
|
||
trackObjects: Boolean = true;
|
||
useMorphOps : Boolean = true;
|
||
// matrix storage for HSV image
|
||
HSV: pIplImage = nil;
|
||
// matrix storage for binary threshold image
|
||
threshold: pIplImage = nil;
|
||
// x and y values for the location of the object
|
||
x: integer = 0;
|
||
y: integer = 0;
|
||
// video capture object to acquire webcam feed
|
||
capture: pCvCapture;
|
||
|
||
begin
|
||
try
|
||
// create slider bars for HSV filtering
|
||
createTrackbars();
|
||
// open capture object at location zero (default location for webcam)
|
||
capture := cvCreateCameraCapture(CV_CAP_ANY);
|
||
Assert(Assigned(capture));
|
||
// set height and width of capture frame
|
||
cvSetCaptureProperty(
|
||
capture,
|
||
CV_CAP_PROP_FRAME_WIDTH,
|
||
FRAME_WIDTH);
|
||
cvSetCaptureProperty(
|
||
capture,
|
||
CV_CAP_PROP_FRAME_HEIGHT,
|
||
FRAME_HEIGHT);
|
||
// start an infinite loop where webcam feed is copied to cameraFeed matrix
|
||
// all of our operations will be performed within this loop
|
||
while true do
|
||
begin
|
||
// store image to matrix
|
||
repeat
|
||
cameraFeed := cvQueryFrame(capture);
|
||
until Assigned(cameraFeed);
|
||
// convert frame from BGR to HSV colorspace
|
||
if not Assigned(HSV) then
|
||
HSV := cvCreateImage(
|
||
cvGetSize(cameraFeed),
|
||
8,
|
||
3);
|
||
cvCvtColor(
|
||
cameraFeed,
|
||
HSV,
|
||
CV_BGR2HSV);
|
||
// filter HSV image between values and store filtered image to
|
||
// threshold matrix
|
||
if not Assigned(threshold) then
|
||
threshold := cvCreateImage(
|
||
cvGetSize(cameraFeed),
|
||
8,
|
||
1);
|
||
cvInRangeS(
|
||
HSV,
|
||
cvScalar(H_MIN, S_MIN, V_MIN),
|
||
cvScalar(H_MAX, S_MAX, V_MAX),
|
||
threshold);
|
||
// perform morphological operations on thresholded image to eliminate noise
|
||
// and emphasize the filtered object(s)
|
||
if useMorphOps then
|
||
morphOps(threshold);
|
||
// pass in thresholded frame to our object tracking function
|
||
// this function will return the x and y coordinates of the
|
||
// filtered object
|
||
if trackObjects then
|
||
trackFilteredObject(
|
||
x,
|
||
y,
|
||
threshold,
|
||
cameraFeed);
|
||
|
||
// show frames
|
||
cvShowImage(
|
||
windowName2,
|
||
threshold);
|
||
cvShowImage(
|
||
windowName,
|
||
cameraFeed);
|
||
cvShowImage(
|
||
windowName1,
|
||
HSV);
|
||
|
||
// delay 30ms so that screen can refresh.
|
||
// image will not appear without this waitKey() command
|
||
if cvWaitKey(30) = 27 then
|
||
Break;
|
||
end;
|
||
|
||
if Assigned(capture) then
|
||
cvReleaseCapture(capture);
|
||
|
||
if Assigned(HSV) then
|
||
cvReleaseImage(HSV);
|
||
if Assigned(threshold) then
|
||
cvReleaseImage(threshold);
|
||
|
||
except
|
||
on E: Exception do
|
||
WriteLn(
|
||
E.ClassName,
|
||
': ',
|
||
E.Message);
|
||
end;
|
||
|
||
end.
|