generic-library/opencv
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Cleanup

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This commit is contained in:
Maksim Shabunin 2016-07-13 15:45:48 +03:00
parent 8215d20dbf
commit b000663a88
1 changed files with 33 additions and 131 deletions
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164
modules/calib3d/src/calibinit.cpp
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@ -79,14 +79,7 @@
//#define ENABLE_TRIM_COL_ROW //#define ENABLE_TRIM_COL_ROW
//#define DEBUG_CHESSBOARD //#define DEBUG_CHESSBOARD
#ifdef DEBUG_CHESSBOARD
# include "opencv2/opencv_modules.hpp"
# ifdef HAVE_OPENCV_HIGHGUI
# include "opencv2/highgui.hpp"
# else
# undef DEBUG_CHESSBOARD
# endif
#endif
#ifdef DEBUG_CHESSBOARD #ifdef DEBUG_CHESSBOARD
static int PRINTF( const char* fmt, ... ) static int PRINTF( const char* fmt, ... )
{ {
@ -400,38 +393,6 @@ bool icvBinarizationHistogramBased( unsigned char* pucImg, int iCols, int iRows
return true; return true;
} }
#if 0
static void
icvCalcAffineTranf2D32f(CvPoint2D32f* pts1, CvPoint2D32f* pts2, int count, CvMat* affine_trans)
{
int i, j;
int real_count = 0;
for( j = 0; j < count; j++ )
{
if( pts1[j].x >= 0 ) real_count++;
}
if(real_count < 3) return;
cv::Ptr<CvMat> xy = cvCreateMat( 2*real_count, 6, CV_32FC1 );
cv::Ptr<CvMat> uv = cvCreateMat( 2*real_count, 1, CV_32FC1 );
//estimate affine transfromation
for( i = 0, j = 0; j < count; j++ )
{
if( pts1[j].x >= 0 )
{
CV_MAT_ELEM( *xy, float, i*2+1, 2 ) = CV_MAT_ELEM( *xy, float, i*2, 0 ) = pts2[j].x;
CV_MAT_ELEM( *xy, float, i*2+1, 3 ) = CV_MAT_ELEM( *xy, float, i*2, 1 ) = pts2[j].y;
CV_MAT_ELEM( *xy, float, i*2, 2 ) = CV_MAT_ELEM( *xy, float, i*2, 3 ) = CV_MAT_ELEM( *xy, float, i*2, 5 ) = \
CV_MAT_ELEM( *xy, float, i*2+1, 0 ) = CV_MAT_ELEM( *xy, float, i*2+1, 1 ) = CV_MAT_ELEM( *xy, float, i*2+1, 4 ) = 0;
CV_MAT_ELEM( *xy, float, i*2, 4 ) = CV_MAT_ELEM( *xy, float, i*2+1, 5 ) = 1;
CV_MAT_ELEM( *uv, float, i*2, 0 ) = pts1[j].x;
CV_MAT_ELEM( *uv, float, i*2+1, 0 ) = pts1[j].y;
i++;
}
}
cvSolve( xy, uv, affine_trans, CV_SVD );
}
#endif
CV_IMPL CV_IMPL
int cvFindChessboardCorners( const void* arr, CvSize pattern_size, int cvFindChessboardCorners( const void* arr, CvSize pattern_size,
@ -449,11 +410,6 @@ int cvFindChessboardCorners( const void* arr, CvSize pattern_size,
const int min_dilations = 0; const int min_dilations = 0;
const int max_dilations = 7; const int max_dilations = 7;
cv::Ptr<CvMat> norm_img, thresh_img; cv::Ptr<CvMat> norm_img, thresh_img;
#ifdef DEBUG_CHESSBOARD
cv::Ptr<IplImage> dbg_img;
cv::Ptr<IplImage> dbg1_img;
cv::Ptr<IplImage> dbg2_img;
#endif
cv::Ptr<CvMemStorage> storage; cv::Ptr<CvMemStorage> storage;
CvMat stub, *img = (CvMat*)arr; CvMat stub, *img = (CvMat*)arr;
@ -487,12 +443,6 @@ int cvFindChessboardCorners( const void* arr, CvSize pattern_size,
storage.reset(cvCreateMemStorage(0)); storage.reset(cvCreateMemStorage(0));
thresh_img.reset(cvCreateMat( img->rows, img->cols, CV_8UC1 )); thresh_img.reset(cvCreateMat( img->rows, img->cols, CV_8UC1 ));
#ifdef DEBUG_CHESSBOARD
dbg_img = cvCreateImage(cvGetSize(img), IPL_DEPTH_8U, 3 );
dbg1_img = cvCreateImage(cvGetSize(img), IPL_DEPTH_8U, 3 );
dbg2_img = cvCreateImage(cvGetSize(img), IPL_DEPTH_8U, 3 );
#endif
if( CV_MAT_CN(img->type) != 1 || (flags & CV_CALIB_CB_NORMALIZE_IMAGE) ) if( CV_MAT_CN(img->type) != 1 || (flags & CV_CALIB_CB_NORMALIZE_IMAGE) )
{ {
// equalize the input image histogram - // equalize the input image histogram -
@ -627,9 +577,12 @@ int cvFindChessboardCorners( const void* arr, CvSize pattern_size,
} }
}//dilations }//dilations
PRINTF("Chessboard detection result 0: %d\n", found);
// revert to old, slower, method if detection failed // revert to old, slower, method if detection failed
if (!found) if (!found)
{ {
PRINTF("Fallback to old algorithm\n");
// empiric threshold level // empiric threshold level
// thresholding performed here and not inside the cycle to save processing time // thresholding performed here and not inside the cycle to save processing time
int thresh_level; int thresh_level;
@ -671,10 +624,6 @@ int cvFindChessboardCorners( const void* arr, CvSize pattern_size,
cvDilate( thresh_img, thresh_img, 0, 1 ); cvDilate( thresh_img, thresh_img, 0, 1 );
} }
#ifdef DEBUG_CHESSBOARD
cvCvtColor(thresh_img,dbg_img,CV_GRAY2BGR);
#endif
// So we can find rectangles that go to the edge, we draw a white line around the image edge. // So we can find rectangles that go to the edge, we draw a white line around the image edge.
// Otherwise FindContours will miss those clipped rectangle contours. // Otherwise FindContours will miss those clipped rectangle contours.
// The border color will be the image mean, because otherwise we risk screwing up filters like cvSmooth()... // The border color will be the image mean, because otherwise we risk screwing up filters like cvSmooth()...
@ -684,31 +633,6 @@ int cvFindChessboardCorners( const void* arr, CvSize pattern_size,
quad_count = icvGenerateQuads( &quads, &corners, storage, thresh_img, flags, &max_quad_buf_size); quad_count = icvGenerateQuads( &quads, &corners, storage, thresh_img, flags, &max_quad_buf_size);
PRINTF("Quad count: %d/%d\n", quad_count, expected_corners_num); PRINTF("Quad count: %d/%d\n", quad_count, expected_corners_num);
#ifdef DEBUG_CHESSBOARD
cvCopy(dbg_img, dbg1_img);
cvNamedWindow("all_quads", 1);
// copy corners to temp array
for(int i = 0; i < quad_count; i++ )
{
for (int z=0; z<4; z++)
{
CvPoint2D32f pt1, pt2;
CvScalar color = CV_RGB(30,255,30);
pt1 = quads[i].corners[z]->pt;
pt2 = quads[i].corners[(z+1)%4]->pt;
pt2.x = (pt1.x + pt2.x)/2;
pt2.y = (pt1.y + pt2.y)/2;
if (z>0)
color = CV_RGB(200,200,0);
cvLine( dbg1_img, cvPointFrom32f(pt1), cvPointFrom32f(pt2), color, 3, 8);
}
}
cvShowImage("all_quads", (IplImage*)dbg1_img);
cvWaitKey();
#endif
if( quad_count <= 0 ) if( quad_count <= 0 )
{ {
continue; continue;
@ -739,33 +663,6 @@ int cvFindChessboardCorners( const void* arr, CvSize pattern_size,
PRINTF("Orig count: %d After ordering: %d\n", icount, count); PRINTF("Orig count: %d After ordering: %d\n", icount, count);
#ifdef DEBUG_CHESSBOARD
cvCopy(dbg_img,dbg2_img);
cvNamedWindow("connected_group", 1);
// copy corners to temp array
for(int i = 0; i < quad_count; i++ )
{
if (quads[i].group_idx == group_idx)
for (int z=0; z<4; z++)
{
CvPoint2D32f pt1, pt2;
CvScalar color = CV_RGB(30,255,30);
if (quads[i].ordered)
color = CV_RGB(255,30,30);
pt1 = quads[i].corners[z]->pt;
pt2 = quads[i].corners[(z+1)%4]->pt;
pt2.x = (pt1.x + pt2.x)/2;
pt2.y = (pt1.y + pt2.y)/2;
if (z>0)
color = CV_RGB(200,200,0);
cvLine( dbg2_img, cvPointFrom32f(pt1), cvPointFrom32f(pt2), color, 3, 8);
}
}
cvShowImage("connected_group", (IplImage*)dbg2_img);
cvWaitKey();
#endif
if (count == 0) if (count == 0)
continue; // haven't found inner quads continue; // haven't found inner quads
@ -812,10 +709,13 @@ int cvFindChessboardCorners( const void* arr, CvSize pattern_size,
}// for k = 0 -> 6 }// for k = 0 -> 6
} }
PRINTF("Chessboard detection result 1: %d\n", found);
if( found ) if( found )
found = icvCheckBoardMonotony( out_corners, pattern_size ); found = icvCheckBoardMonotony( out_corners, pattern_size );
PRINTF("Chessboard detection result 2: %d\n", found);
// check that none of the found corners is too close to the image boundary // check that none of the found corners is too close to the image boundary
if( found ) if( found )
{ {
@ -830,36 +730,38 @@ int cvFindChessboardCorners( const void* arr, CvSize pattern_size,
found = k == pattern_size.width*pattern_size.height; found = k == pattern_size.width*pattern_size.height;
} }
if( found && pattern_size.height % 2 == 0 && pattern_size.width % 2 == 0 ) PRINTF("Chessboard detection result 3: %d\n", found);
if( found )
{ {
if ( pattern_size.height % 2 == 0 && pattern_size.width % 2 == 0 )
{
int last_row = (pattern_size.height-1)*pattern_size.width; int last_row = (pattern_size.height-1)*pattern_size.width;
double dy0 = out_corners[last_row].y - out_corners[0].y; double dy0 = out_corners[last_row].y - out_corners[0].y;
if( dy0 < 0 ) if( dy0 < 0 )
{ {
int n = pattern_size.width*pattern_size.height; int n = pattern_size.width*pattern_size.height;
for(int i = 0; i < n/2; i++ ) for(int i = 0; i < n/2; i++ )
{ {
CvPoint2D32f temp; CvPoint2D32f temp;
CV_SWAP(out_corners[i], out_corners[n-i-1], temp); CV_SWAP(out_corners[i], out_corners[n-i-1], temp);
} }
} }
} }
cv::Ptr<CvMat> gray;
if( found ) if( CV_MAT_CN(img->type) != 1 )
{ {
cv::Ptr<CvMat> gray; gray.reset(cvCreateMat(img->rows, img->cols, CV_8UC1));
if( CV_MAT_CN(img->type) != 1 ) cvCvtColor(img, gray, CV_BGR2GRAY);
{ }
gray.reset(cvCreateMat(img->rows, img->cols, CV_8UC1)); else
cvCvtColor(img, gray, CV_BGR2GRAY); {
} gray.reset(cvCloneMat(img));
else }
{ int wsize = 2;
gray.reset(cvCloneMat(img)); cvFindCornerSubPix( gray, out_corners, pattern_size.width*pattern_size.height,
} cvSize(wsize, wsize), cvSize(-1,-1),
int wsize = 2; cvTermCriteria(CV_TERMCRIT_EPS+CV_TERMCRIT_ITER, 15, 0.1));
cvFindCornerSubPix( gray, out_corners, pattern_size.width*pattern_size.height,
cvSize(wsize, wsize), cvSize(-1,-1), cvTermCriteria(CV_TERMCRIT_EPS+CV_TERMCRIT_ITER, 15, 0.1));
} }
} }
catch(...) catch(...)