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791 lines
22 KiB
791 lines
22 KiB
/*M/////////////////////////////////////////////////////////////////////////////////////// |
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// |
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. |
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// |
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// By downloading, copying, installing or using the software you agree to this license. |
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// If you do not agree to this license, do not download, install, |
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// copy or use the software. |
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// |
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// |
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// License Agreement |
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// For Open Source Computer Vision Library |
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// |
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// Copyright (C) 2000, Intel Corporation, all rights reserved. |
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// Copyright (C) 2013, OpenCV Foundation, all rights reserved. |
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// Third party copyrights are property of their respective owners. |
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// |
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// Redistribution and use in source and binary forms, with or without modification, |
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// are permitted provided that the following conditions are met: |
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// |
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// * Redistribution's of source code must retain the above copyright notice, |
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// this list of conditions and the following disclaimer. |
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// |
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// * Redistribution's in binary form must reproduce the above copyright notice, |
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// this list of conditions and the following disclaimer in the documentation |
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// and/or other materials provided with the distribution. |
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// |
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// * The name of the copyright holders may not be used to endorse or promote products |
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// derived from this software without specific prior written permission. |
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// |
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// This software is provided by the copyright holders and contributors "as is" and |
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// any express or implied warranties, including, but not limited to, the implied |
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// warranties of merchantability and fitness for a particular purpose are disclaimed. |
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// In no event shall the Intel Corporation or contributors be liable for any direct, |
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// indirect, incidental, special, exemplary, or consequential damages |
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// (including, but not limited to, procurement of substitute goods or services; |
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// loss of use, data, or profits; or business interruption) however caused |
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// and on any theory of liability, whether in contract, strict liability, |
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// or tort (including negligence or otherwise) arising in any way out of |
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// the use of this software, even if advised of the possibility of such damage. |
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// |
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//M*/ |
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#include "precomp.hpp" |
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namespace cv |
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{ |
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static const int DIST_SHIFT = 16; |
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static const int INIT_DIST0 = (INT_MAX >> 2); |
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static void |
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initTopBottom( Mat& temp, int border ) |
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{ |
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Size size = temp.size(); |
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for( int i = 0; i < border; i++ ) |
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{ |
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int* ttop = temp.ptr<int>(i); |
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int* tbottom = temp.ptr<int>(size.height - i - 1); |
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for( int j = 0; j < size.width; j++ ) |
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{ |
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ttop[j] = INIT_DIST0; |
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tbottom[j] = INIT_DIST0; |
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} |
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} |
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} |
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static void |
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distanceTransform_3x3( const Mat& _src, Mat& _temp, Mat& _dist, const float* metrics ) |
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{ |
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const int BORDER = 1; |
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int i, j; |
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const int HV_DIST = CV_FLT_TO_FIX( metrics[0], DIST_SHIFT ); |
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const int DIAG_DIST = CV_FLT_TO_FIX( metrics[1], DIST_SHIFT ); |
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const float scale = 1.f/(1 << DIST_SHIFT); |
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const uchar* src = _src.data; |
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int* temp = _temp.ptr<int>(); |
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float* dist = _dist.ptr<float>(); |
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int srcstep = (int)(_src.step/sizeof(src[0])); |
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int step = (int)(_temp.step/sizeof(temp[0])); |
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int dststep = (int)(_dist.step/sizeof(dist[0])); |
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Size size = _src.size(); |
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initTopBottom( _temp, BORDER ); |
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// forward pass |
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for( i = 0; i < size.height; i++ ) |
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{ |
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const uchar* s = src + i*srcstep; |
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int* tmp = (int*)(temp + (i+BORDER)*step) + BORDER; |
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for( j = 0; j < BORDER; j++ ) |
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tmp[-j-1] = tmp[size.width + j] = INIT_DIST0; |
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for( j = 0; j < size.width; j++ ) |
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{ |
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if( !s[j] ) |
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tmp[j] = 0; |
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else |
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{ |
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int t0 = tmp[j-step-1] + DIAG_DIST; |
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int t = tmp[j-step] + HV_DIST; |
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if( t0 > t ) t0 = t; |
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t = tmp[j-step+1] + DIAG_DIST; |
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if( t0 > t ) t0 = t; |
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t = tmp[j-1] + HV_DIST; |
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if( t0 > t ) t0 = t; |
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tmp[j] = t0; |
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} |
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} |
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} |
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// backward pass |
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for( i = size.height - 1; i >= 0; i-- ) |
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{ |
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float* d = (float*)(dist + i*dststep); |
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int* tmp = (int*)(temp + (i+BORDER)*step) + BORDER; |
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for( j = size.width - 1; j >= 0; j-- ) |
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{ |
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int t0 = tmp[j]; |
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if( t0 > HV_DIST ) |
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{ |
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int t = tmp[j+step+1] + DIAG_DIST; |
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if( t0 > t ) t0 = t; |
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t = tmp[j+step] + HV_DIST; |
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if( t0 > t ) t0 = t; |
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t = tmp[j+step-1] + DIAG_DIST; |
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if( t0 > t ) t0 = t; |
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t = tmp[j+1] + HV_DIST; |
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if( t0 > t ) t0 = t; |
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tmp[j] = t0; |
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} |
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d[j] = (float)(t0 * scale); |
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} |
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} |
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} |
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static void |
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distanceTransform_5x5( const Mat& _src, Mat& _temp, Mat& _dist, const float* metrics ) |
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{ |
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const int BORDER = 2; |
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int i, j; |
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const int HV_DIST = CV_FLT_TO_FIX( metrics[0], DIST_SHIFT ); |
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const int DIAG_DIST = CV_FLT_TO_FIX( metrics[1], DIST_SHIFT ); |
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const int LONG_DIST = CV_FLT_TO_FIX( metrics[2], DIST_SHIFT ); |
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const float scale = 1.f/(1 << DIST_SHIFT); |
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const uchar* src = _src.data; |
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int* temp = _temp.ptr<int>(); |
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float* dist = _dist.ptr<float>(); |
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int srcstep = (int)(_src.step/sizeof(src[0])); |
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int step = (int)(_temp.step/sizeof(temp[0])); |
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int dststep = (int)(_dist.step/sizeof(dist[0])); |
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Size size = _src.size(); |
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initTopBottom( _temp, BORDER ); |
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// forward pass |
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for( i = 0; i < size.height; i++ ) |
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{ |
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const uchar* s = src + i*srcstep; |
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int* tmp = (int*)(temp + (i+BORDER)*step) + BORDER; |
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for( j = 0; j < BORDER; j++ ) |
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tmp[-j-1] = tmp[size.width + j] = INIT_DIST0; |
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for( j = 0; j < size.width; j++ ) |
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{ |
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if( !s[j] ) |
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tmp[j] = 0; |
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else |
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{ |
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int t0 = tmp[j-step*2-1] + LONG_DIST; |
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int t = tmp[j-step*2+1] + LONG_DIST; |
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if( t0 > t ) t0 = t; |
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t = tmp[j-step-2] + LONG_DIST; |
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if( t0 > t ) t0 = t; |
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t = tmp[j-step-1] + DIAG_DIST; |
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if( t0 > t ) t0 = t; |
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t = tmp[j-step] + HV_DIST; |
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if( t0 > t ) t0 = t; |
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t = tmp[j-step+1] + DIAG_DIST; |
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if( t0 > t ) t0 = t; |
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t = tmp[j-step+2] + LONG_DIST; |
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if( t0 > t ) t0 = t; |
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t = tmp[j-1] + HV_DIST; |
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if( t0 > t ) t0 = t; |
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tmp[j] = t0; |
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} |
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} |
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} |
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// backward pass |
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for( i = size.height - 1; i >= 0; i-- ) |
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{ |
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float* d = (float*)(dist + i*dststep); |
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int* tmp = (int*)(temp + (i+BORDER)*step) + BORDER; |
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for( j = size.width - 1; j >= 0; j-- ) |
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{ |
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int t0 = tmp[j]; |
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if( t0 > HV_DIST ) |
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{ |
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int t = tmp[j+step*2+1] + LONG_DIST; |
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if( t0 > t ) t0 = t; |
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t = tmp[j+step*2-1] + LONG_DIST; |
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if( t0 > t ) t0 = t; |
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t = tmp[j+step+2] + LONG_DIST; |
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if( t0 > t ) t0 = t; |
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t = tmp[j+step+1] + DIAG_DIST; |
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if( t0 > t ) t0 = t; |
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t = tmp[j+step] + HV_DIST; |
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if( t0 > t ) t0 = t; |
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t = tmp[j+step-1] + DIAG_DIST; |
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if( t0 > t ) t0 = t; |
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t = tmp[j+step-2] + LONG_DIST; |
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if( t0 > t ) t0 = t; |
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t = tmp[j+1] + HV_DIST; |
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if( t0 > t ) t0 = t; |
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tmp[j] = t0; |
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} |
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d[j] = (float)(t0 * scale); |
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} |
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} |
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} |
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static void |
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distanceTransformEx_5x5( const Mat& _src, Mat& _temp, Mat& _dist, Mat& _labels, const float* metrics ) |
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{ |
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const int BORDER = 2; |
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int i, j; |
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const int HV_DIST = CV_FLT_TO_FIX( metrics[0], DIST_SHIFT ); |
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const int DIAG_DIST = CV_FLT_TO_FIX( metrics[1], DIST_SHIFT ); |
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const int LONG_DIST = CV_FLT_TO_FIX( metrics[2], DIST_SHIFT ); |
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const float scale = 1.f/(1 << DIST_SHIFT); |
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const uchar* src = _src.data; |
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int* temp = _temp.ptr<int>(); |
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float* dist = _dist.ptr<float>(); |
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int* labels = _labels.ptr<int>(); |
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int srcstep = (int)(_src.step/sizeof(src[0])); |
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int step = (int)(_temp.step/sizeof(temp[0])); |
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int dststep = (int)(_dist.step/sizeof(dist[0])); |
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int lstep = (int)(_labels.step/sizeof(dist[0])); |
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Size size = _src.size(); |
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initTopBottom( _temp, BORDER ); |
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// forward pass |
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for( i = 0; i < size.height; i++ ) |
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{ |
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const uchar* s = src + i*srcstep; |
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int* tmp = (int*)(temp + (i+BORDER)*step) + BORDER; |
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int* lls = (int*)(labels + i*lstep); |
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for( j = 0; j < BORDER; j++ ) |
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tmp[-j-1] = tmp[size.width + j] = INIT_DIST0; |
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for( j = 0; j < size.width; j++ ) |
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{ |
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if( !s[j] ) |
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{ |
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tmp[j] = 0; |
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//assert( lls[j] != 0 ); |
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} |
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else |
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{ |
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int t0 = INIT_DIST0, t; |
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int l0 = 0; |
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t = tmp[j-step*2-1] + LONG_DIST; |
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if( t0 > t ) |
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{ |
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t0 = t; |
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l0 = lls[j-lstep*2-1]; |
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} |
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t = tmp[j-step*2+1] + LONG_DIST; |
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if( t0 > t ) |
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{ |
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t0 = t; |
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l0 = lls[j-lstep*2+1]; |
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} |
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t = tmp[j-step-2] + LONG_DIST; |
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if( t0 > t ) |
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{ |
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t0 = t; |
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l0 = lls[j-lstep-2]; |
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} |
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t = tmp[j-step-1] + DIAG_DIST; |
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if( t0 > t ) |
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{ |
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t0 = t; |
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l0 = lls[j-lstep-1]; |
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} |
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t = tmp[j-step] + HV_DIST; |
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if( t0 > t ) |
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{ |
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t0 = t; |
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l0 = lls[j-lstep]; |
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} |
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t = tmp[j-step+1] + DIAG_DIST; |
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if( t0 > t ) |
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{ |
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t0 = t; |
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l0 = lls[j-lstep+1]; |
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} |
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t = tmp[j-step+2] + LONG_DIST; |
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if( t0 > t ) |
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{ |
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t0 = t; |
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l0 = lls[j-lstep+2]; |
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} |
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t = tmp[j-1] + HV_DIST; |
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if( t0 > t ) |
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{ |
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t0 = t; |
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l0 = lls[j-1]; |
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} |
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tmp[j] = t0; |
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lls[j] = l0; |
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} |
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} |
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} |
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// backward pass |
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for( i = size.height - 1; i >= 0; i-- ) |
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{ |
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float* d = (float*)(dist + i*dststep); |
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int* tmp = (int*)(temp + (i+BORDER)*step) + BORDER; |
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int* lls = (int*)(labels + i*lstep); |
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for( j = size.width - 1; j >= 0; j-- ) |
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{ |
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int t0 = tmp[j]; |
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int l0 = lls[j]; |
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if( t0 > HV_DIST ) |
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{ |
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int t = tmp[j+step*2+1] + LONG_DIST; |
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if( t0 > t ) |
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{ |
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t0 = t; |
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l0 = lls[j+lstep*2+1]; |
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} |
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t = tmp[j+step*2-1] + LONG_DIST; |
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if( t0 > t ) |
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{ |
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t0 = t; |
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l0 = lls[j+lstep*2-1]; |
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} |
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t = tmp[j+step+2] + LONG_DIST; |
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if( t0 > t ) |
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{ |
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t0 = t; |
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l0 = lls[j+lstep+2]; |
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} |
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t = tmp[j+step+1] + DIAG_DIST; |
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if( t0 > t ) |
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{ |
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t0 = t; |
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l0 = lls[j+lstep+1]; |
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} |
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t = tmp[j+step] + HV_DIST; |
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if( t0 > t ) |
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{ |
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t0 = t; |
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l0 = lls[j+lstep]; |
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} |
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t = tmp[j+step-1] + DIAG_DIST; |
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if( t0 > t ) |
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{ |
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t0 = t; |
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l0 = lls[j+lstep-1]; |
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} |
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t = tmp[j+step-2] + LONG_DIST; |
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if( t0 > t ) |
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{ |
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t0 = t; |
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l0 = lls[j+lstep-2]; |
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} |
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t = tmp[j+1] + HV_DIST; |
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if( t0 > t ) |
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{ |
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t0 = t; |
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l0 = lls[j+1]; |
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} |
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tmp[j] = t0; |
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lls[j] = l0; |
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} |
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d[j] = (float)(t0 * scale); |
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} |
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} |
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} |
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static void getDistanceTransformMask( int maskType, float *metrics ) |
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{ |
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CV_Assert( metrics != 0 ); |
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switch (maskType) |
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{ |
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case 30: |
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metrics[0] = 1.0f; |
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metrics[1] = 1.0f; |
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break; |
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case 31: |
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metrics[0] = 1.0f; |
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metrics[1] = 2.0f; |
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break; |
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case 32: |
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metrics[0] = 0.955f; |
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metrics[1] = 1.3693f; |
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break; |
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case 50: |
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metrics[0] = 1.0f; |
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metrics[1] = 1.0f; |
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metrics[2] = 2.0f; |
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break; |
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case 51: |
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metrics[0] = 1.0f; |
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metrics[1] = 2.0f; |
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metrics[2] = 3.0f; |
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break; |
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case 52: |
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metrics[0] = 1.0f; |
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metrics[1] = 1.4f; |
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metrics[2] = 2.1969f; |
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break; |
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default: |
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CV_Error(CV_StsBadArg, "Uknown metric type"); |
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} |
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} |
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struct DTColumnInvoker |
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{ |
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DTColumnInvoker( const Mat* _src, Mat* _dst, const int* _sat_tab, const float* _sqr_tab) |
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{ |
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src = _src; |
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dst = _dst; |
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sat_tab = _sat_tab + src->rows*2 + 1; |
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sqr_tab = _sqr_tab; |
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} |
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void operator()( const BlockedRange& range ) const |
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{ |
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int i, i1 = range.begin(), i2 = range.end(); |
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int m = src->rows; |
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size_t sstep = src->step, dstep = dst->step/sizeof(float); |
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AutoBuffer<int> _d(m); |
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int* d = _d; |
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for( i = i1; i < i2; i++ ) |
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{ |
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const uchar* sptr = src->ptr(m-1) + i; |
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float* dptr = dst->ptr<float>() + i; |
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int j, dist = m-1; |
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for( j = m-1; j >= 0; j--, sptr -= sstep ) |
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{ |
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dist = (dist + 1) & (sptr[0] == 0 ? 0 : -1); |
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d[j] = dist; |
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} |
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dist = m-1; |
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for( j = 0; j < m; j++, dptr += dstep ) |
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{ |
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dist = dist + 1 - sat_tab[dist - d[j]]; |
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d[j] = dist; |
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dptr[0] = sqr_tab[dist]; |
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} |
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} |
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} |
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const Mat* src; |
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Mat* dst; |
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const int* sat_tab; |
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const float* sqr_tab; |
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}; |
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struct DTRowInvoker |
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{ |
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DTRowInvoker( Mat* _dst, const float* _sqr_tab, const float* _inv_tab ) |
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{ |
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dst = _dst; |
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sqr_tab = _sqr_tab; |
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inv_tab = _inv_tab; |
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} |
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void operator()( const BlockedRange& range ) const |
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{ |
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const float inf = 1e15f; |
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int i, i1 = range.begin(), i2 = range.end(); |
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int n = dst->cols; |
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AutoBuffer<uchar> _buf((n+2)*2*sizeof(float) + (n+2)*sizeof(int)); |
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float* f = (float*)(uchar*)_buf; |
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float* z = f + n; |
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int* v = alignPtr((int*)(z + n + 1), sizeof(int)); |
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for( i = i1; i < i2; i++ ) |
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{ |
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float* d = dst->ptr<float>(i); |
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int p, q, k; |
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v[0] = 0; |
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z[0] = -inf; |
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z[1] = inf; |
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f[0] = d[0]; |
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for( q = 1, k = 0; q < n; q++ ) |
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{ |
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float fq = d[q]; |
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f[q] = fq; |
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for(;;k--) |
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{ |
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p = v[k]; |
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float s = (fq + sqr_tab[q] - d[p] - sqr_tab[p])*inv_tab[q - p]; |
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if( s > z[k] ) |
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{ |
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k++; |
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v[k] = q; |
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z[k] = s; |
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z[k+1] = inf; |
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break; |
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} |
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} |
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} |
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for( q = 0, k = 0; q < n; q++ ) |
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{ |
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while( z[k+1] < q ) |
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k++; |
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p = v[k]; |
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d[q] = std::sqrt(sqr_tab[std::abs(q - p)] + f[p]); |
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} |
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} |
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} |
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Mat* dst; |
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const float* sqr_tab; |
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const float* inv_tab; |
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}; |
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static void |
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trueDistTrans( const Mat& src, Mat& dst ) |
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{ |
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const float inf = 1e15f; |
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CV_Assert( src.size() == dst.size() ); |
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CV_Assert( src.type() == CV_8UC1 && dst.type() == CV_32FC1 ); |
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int i, m = src.rows, n = src.cols; |
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cv::AutoBuffer<uchar> _buf(std::max(m*2*sizeof(float) + (m*3+1)*sizeof(int), n*2*sizeof(float))); |
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// stage 1: compute 1d distance transform of each column |
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float* sqr_tab = (float*)(uchar*)_buf; |
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int* sat_tab = cv::alignPtr((int*)(sqr_tab + m*2), sizeof(int)); |
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int shift = m*2; |
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for( i = 0; i < m; i++ ) |
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sqr_tab[i] = (float)(i*i); |
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for( i = m; i < m*2; i++ ) |
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sqr_tab[i] = inf; |
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for( i = 0; i < shift; i++ ) |
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sat_tab[i] = 0; |
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for( ; i <= m*3; i++ ) |
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sat_tab[i] = i - shift; |
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|
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cv::parallel_for(cv::BlockedRange(0, n), cv::DTColumnInvoker(&src, &dst, sat_tab, sqr_tab)); |
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|
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// stage 2: compute modified distance transform for each row |
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float* inv_tab = sqr_tab + n; |
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|
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inv_tab[0] = sqr_tab[0] = 0.f; |
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for( i = 1; i < n; i++ ) |
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{ |
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inv_tab[i] = (float)(0.5/i); |
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sqr_tab[i] = (float)(i*i); |
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} |
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|
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cv::parallel_for(cv::BlockedRange(0, m), cv::DTRowInvoker(&dst, sqr_tab, inv_tab)); |
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} |
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|
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/****************************************************************************************\ |
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Non-inplace and Inplace 8u->8u Distance Transform for CityBlock (a.k.a. L1) metric |
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(C) 2006 by Jay Stavinzky. |
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\****************************************************************************************/ |
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|
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//BEGIN ATS ADDITION |
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// 8-bit grayscale distance transform function |
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static void |
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distanceATS_L1_8u( const Mat& src, Mat& dst ) |
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{ |
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int width = src.cols, height = src.rows; |
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|
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int a; |
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uchar lut[256]; |
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int x, y; |
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|
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const uchar *sbase = src.data; |
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uchar *dbase = dst.data; |
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int srcstep = (int)src.step; |
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int dststep = (int)dst.step; |
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|
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CV_Assert( src.type() == CV_8UC1 && dst.type() == CV_8UC1 ); |
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CV_Assert( src.size() == dst.size() ); |
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|
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////////////////////// forward scan //////////////////////// |
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for( x = 0; x < 256; x++ ) |
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lut[x] = CV_CAST_8U(x+1); |
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|
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//init first pixel to max (we're going to be skipping it) |
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dbase[0] = (uchar)(sbase[0] == 0 ? 0 : 255); |
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|
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//first row (scan west only, skip first pixel) |
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for( x = 1; x < width; x++ ) |
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dbase[x] = (uchar)(sbase[x] == 0 ? 0 : lut[dbase[x-1]]); |
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|
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for( y = 1; y < height; y++ ) |
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{ |
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sbase += srcstep; |
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dbase += dststep; |
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|
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//for left edge, scan north only |
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a = sbase[0] == 0 ? 0 : lut[dbase[-dststep]]; |
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dbase[0] = (uchar)a; |
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|
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for( x = 1; x < width; x++ ) |
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{ |
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a = sbase[x] == 0 ? 0 : lut[MIN(a, dbase[x - dststep])]; |
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dbase[x] = (uchar)a; |
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} |
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} |
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|
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////////////////////// backward scan /////////////////////// |
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|
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a = dbase[width-1]; |
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|
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// do last row east pixel scan here (skip bottom right pixel) |
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for( x = width - 2; x >= 0; x-- ) |
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{ |
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a = lut[a]; |
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dbase[x] = (uchar)(CV_CALC_MIN_8U(a, dbase[x])); |
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} |
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|
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// right edge is the only error case |
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for( y = height - 2; y >= 0; y-- ) |
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{ |
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dbase -= dststep; |
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|
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// do right edge |
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a = lut[dbase[width-1+dststep]]; |
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dbase[width-1] = (uchar)(MIN(a, dbase[width-1])); |
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|
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for( x = width - 2; x >= 0; x-- ) |
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{ |
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int b = dbase[x+dststep]; |
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a = lut[MIN(a, b)]; |
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dbase[x] = (uchar)(MIN(a, dbase[x])); |
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} |
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} |
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} |
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//END ATS ADDITION |
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|
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} |
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|
|
|
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// Wrapper function for distance transform group |
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void cv::distanceTransform( InputArray _src, OutputArray _dst, OutputArray _labels, |
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int distType, int maskSize, int labelType ) |
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{ |
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Mat src = _src.getMat(), dst = _dst.getMat(), labels; |
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bool need_labels = _labels.needed(); |
|
|
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CV_Assert( src.type() == CV_8U ); |
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if( dst.size == src.size && dst.type() == CV_8U && !need_labels && distType == CV_DIST_L1 ) |
|
{ |
|
distanceATS_L1_8u(src, dst); |
|
return; |
|
} |
|
|
|
_dst.create( src.size(), CV_32F ); |
|
dst = _dst.getMat(); |
|
|
|
if( need_labels ) |
|
{ |
|
CV_Assert( labelType == DIST_LABEL_PIXEL || labelType == DIST_LABEL_CCOMP ); |
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|
|
_labels.create(src.size(), CV_32S); |
|
labels = _labels.getMat(); |
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maskSize = CV_DIST_MASK_5; |
|
} |
|
|
|
CV_Assert( src.type() == CV_8UC1 ); |
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float _mask[5] = {0}; |
|
|
|
if( maskSize != CV_DIST_MASK_3 && maskSize != CV_DIST_MASK_5 && maskSize != CV_DIST_MASK_PRECISE ) |
|
CV_Error( CV_StsBadSize, "Mask size should be 3 or 5 or 0 (presize)" ); |
|
|
|
if( distType == CV_DIST_C || distType == CV_DIST_L1 ) |
|
maskSize = !need_labels ? CV_DIST_MASK_3 : CV_DIST_MASK_5; |
|
else if( distType == CV_DIST_L2 && need_labels ) |
|
maskSize = CV_DIST_MASK_5; |
|
|
|
if( maskSize == CV_DIST_MASK_PRECISE ) |
|
{ |
|
trueDistTrans( src, dst ); |
|
return; |
|
} |
|
|
|
CV_Assert( distType == CV_DIST_C || distType == CV_DIST_L1 || distType == CV_DIST_L2 ); |
|
|
|
getDistanceTransformMask( (distType == CV_DIST_C ? 0 : |
|
distType == CV_DIST_L1 ? 1 : 2) + maskSize*10, _mask ); |
|
|
|
Size size = src.size(); |
|
|
|
int border = maskSize == CV_DIST_MASK_3 ? 1 : 2; |
|
Mat temp( size.height + border*2, size.width + border*2, CV_32SC1 ); |
|
|
|
if( !need_labels ) |
|
{ |
|
if( maskSize == CV_DIST_MASK_3 ) |
|
distanceTransform_3x3(src, temp, dst, _mask); |
|
else |
|
distanceTransform_5x5(src, temp, dst, _mask); |
|
} |
|
else |
|
{ |
|
labels.setTo(Scalar::all(0)); |
|
|
|
if( labelType == CV_DIST_LABEL_CCOMP ) |
|
{ |
|
Mat zpix = src == 0; |
|
connectedComponents(zpix, labels, 8, CV_32S); |
|
} |
|
else |
|
{ |
|
int k = 1; |
|
for( int i = 0; i < src.rows; i++ ) |
|
{ |
|
const uchar* srcptr = src.ptr(i); |
|
int* labelptr = labels.ptr<int>(i); |
|
|
|
for( int j = 0; j < src.cols; j++ ) |
|
if( srcptr[j] == 0 ) |
|
labelptr[j] = k++; |
|
} |
|
} |
|
|
|
distanceTransformEx_5x5( src, temp, dst, labels, _mask ); |
|
} |
|
} |
|
|
|
|
|
void cv::distanceTransform( InputArray _src, OutputArray _dst, |
|
int distanceType, int maskSize ) |
|
{ |
|
distanceTransform(_src, _dst, noArray(), distanceType, maskSize, DIST_LABEL_PIXEL); |
|
} |
|
|
|
|
|
CV_IMPL void |
|
cvDistTransform( const void* srcarr, void* dstarr, |
|
int distType, int maskSize, |
|
const float * /*mask*/, |
|
void* labelsarr, int labelType ) |
|
{ |
|
cv::Mat src = cv::cvarrToMat(srcarr); |
|
const cv::Mat dst = cv::cvarrToMat(dstarr); |
|
const cv::Mat labels = cv::cvarrToMat(labelsarr); |
|
|
|
cv::distanceTransform(src, dst, labelsarr ? cv::_OutputArray(labels) : cv::_OutputArray(), |
|
distType, maskSize, labelType); |
|
|
|
} |
|
|
|
|
|
/* End of file. */
|
|
|