int CV_QueryHistTest::validate_test_results( int /*test_case_idx*/ )
{
int code = CvTS::OK;
int i, j, iters = values->cols;
for( i = 0; i < iters; i++ )
{
float v = values->data.fl[i], v0 = values0->data.fl[i];
if( cvIsNaN(v) || cvIsInf(v) )
{
ts->printf( CvTS::LOG, "The bin #%d has invalid value\n", i );
code = CvTS::FAIL_INVALID_OUTPUT;
}
else if( fabs(v - v0) > FLT_EPSILON )
{
ts->printf( CvTS::LOG, "The bin #%d = %g, while it should be %g\n", i, v, v0 );
code = CvTS::FAIL_BAD_ACCURACY;
}
if( code < 0 )
{
ts->printf( CvTS::LOG, "The bin index = (" );
for( j = 0; j < cdims; j++ )
ts->printf( CvTS::LOG, "%d%s", indices->data.i[i*cdims + j],
j < cdims-1 ? ", " : ")\n" );
break;
}
}
if( code < 0 )
ts->set_failed_test_info( code );
return code;
}
int CV_ThreshHistTest::validate_test_results( int /*test_case_idx*/ )
{
int code = CvTS::OK;
int i;
float* ptr0 = values->data.fl;
float* ptr = 0;
CvSparseMat* sparse = 0;
if( hist_type == CV_HIST_ARRAY )
ptr = (float*)cvPtr1D( hist[0]->bins, 0 );
else
sparse = (CvSparseMat*)hist[0]->bins;
if( code > 0 )
{
for( i = 0; i < orig_nz_count; i++ )
{
float v0 = ptr0[i], v;
if( hist_type == CV_HIST_ARRAY )
v = ptr[i];
else
{
v = (float)cvGetRealND( sparse, indices->data.i + i*cdims );
cvClearND( sparse, indices->data.i + i*cdims );
}
if( v0 <= threshold ) v0 = 0.f;
if( cvIsNaN(v) || cvIsInf(v) )
{
ts->printf( CvTS::LOG, "The %d-th bin is invalid (=%g)\n", i, v );
code = CvTS::FAIL_INVALID_OUTPUT;
break;
}
else if( fabs(v0 - v) > FLT_EPSILON*10*fabs(v0) )
{
ts->printf( CvTS::LOG, "The %d-th bin is incorrect (=%g, should be =%g)\n", i, v, v0 );
code = CvTS::FAIL_BAD_ACCURACY;
break;
}
}
}
if( code > 0 && hist_type == CV_HIST_SPARSE )
{
if( sparse->heap->active_count > 0 )
{
ts->printf( CvTS::LOG,
"There some extra histogram bins in the sparse histogram after the thresholding\n" );
code = CvTS::FAIL_INVALID_OUTPUT;
}
}
if( code < 0 )
ts->set_failed_test_info( code );
return code;
}
int CV_MinMaxHistTest::validate_test_results( int /*test_case_idx*/ )
{
int code = CvTS::OK;
if( cvIsNaN(min_val) || cvIsInf(min_val) ||
cvIsNaN(max_val) || cvIsInf(max_val) )
{
ts->printf( CvTS::LOG,
"The extrema histogram bin values are invalid (min = %g, max = %g)\n", min_val, max_val );
code = CvTS::FAIL_INVALID_OUTPUT;
}
else if( fabs(min_val - min_val0) > FLT_EPSILON ||
fabs(max_val - max_val0) > FLT_EPSILON )
{
ts->printf( CvTS::LOG,
"The extrema histogram bin values are incorrect: (min = %g, should be = %g), (max = %g, should be = %g)\n",
min_val, min_val0, max_val, max_val0 );
code = CvTS::FAIL_BAD_ACCURACY;
}
else
{
int i;
for( i = 0; i < cdims; i++ )
{
if( min_idx[i] != min_idx0[i] || max_idx[i] != max_idx0[i] )
{
ts->printf( CvTS::LOG,
"The %d-th coordinates of extrema histogram bin values are incorrect: "
"(min = %d, should be = %d), (max = %d, should be = %d)\n",
i, min_idx[i], min_idx0[i], max_idx[i], max_idx0[i] );
code = CvTS::FAIL_BAD_ACCURACY;
}
}
}
if( code < 0 )
ts->set_failed_test_info( code );
return code;
}
/*
* call-seq:
* angle -> float
*
* Return angle.
*/
VALUE
rb_angle(VALUE self)
{
CvMoments *moments = CVMOMENTS(self);
double
m11 = cvGetCentralMoment(moments, 1, 1),
m20 = cvGetCentralMoment(moments, 2, 0),
m02 = cvGetCentralMoment(moments, 0, 2),
mangle = 0.5 * atan(2 * m11 / (m20 - m02));
if(cvIsNaN(mangle) || cvIsInf(mangle))
return Qnil;
else
return rb_float_new(mangle);
}
int CV_BayesianProbTest::validate_test_results( int /*test_case_idx*/ )
{
int code = CvTS::OK;
int i, j, n = hist_count/2;
double s[CV_MAX_DIM];
const double err_level = 1e-5;
for( i = 0; i < total_size; i++ )
{
double sum = 0;
for( j = 0; j < n; j++ )
{
double v = hist[j]->mat.data.fl[i];
sum += v;
s[j] = v;
}
sum = sum > DBL_EPSILON ? 1./sum : 0;
for( j = 0; j < n; j++ )
{
double v0 = s[j]*sum;
double v = hist[j+n]->mat.data.fl[i];
if( cvIsNaN(v) || cvIsInf(v) )
{
ts->printf( CvTS::LOG,
"The element #%d in the destination histogram #%d is invalid (=%g)\n",
i, j, v );
code = CvTS::FAIL_INVALID_OUTPUT;
break;
}
else if( fabs(v0 - v) > err_level*fabs(v0) )
{
ts->printf( CvTS::LOG,
"The element #%d in the destination histogram #%d is inaccurate (=%g, should be =%g)\n",
i, j, v, v0 );
code = CvTS::FAIL_BAD_ACCURACY;
break;
}
}
if( j < n )
break;
}
if( code < 0 )
ts->set_failed_test_info( code );
return code;
}
int CV_NormHistTest::validate_test_results( int /*test_case_idx*/ )
{
int code = CvTS::OK;
double sum = 0;
if( hist_type == CV_HIST_ARRAY )
{
int i;
const float* ptr = (float*)cvPtr1D( hist[0]->bins, 0 );
for( i = 0; i < total_size; i++ )
sum += ptr[i];
}
else
{
CvSparseMat* sparse = (CvSparseMat*)hist[0]->bins;
CvSparseMatIterator iterator;
CvSparseNode *node;
for( node = cvInitSparseMatIterator( sparse, &iterator );
node != 0; node = cvGetNextSparseNode( &iterator ))
{
sum += *(float*)CV_NODE_VAL(sparse,node);
}
}
if( cvIsNaN(sum) || cvIsInf(sum) )
{
ts->printf( CvTS::LOG,
"The normalized histogram has invalid sum =%g\n", sum );
code = CvTS::FAIL_INVALID_OUTPUT;
}
else if( fabs(sum - factor) > FLT_EPSILON*10*fabs(factor) )
{
ts->printf( CvTS::LOG,
"The normalized histogram has incorrect sum =%g, while it should be =%g\n", sum, factor );
code = CvTS::FAIL_BAD_ACCURACY;
}
if( code < 0 )
ts->set_failed_test_info( code );
return code;
}
bool cv::find4QuadCornerSubpix(InputArray _img, InputOutputArray _corners, Size region_size)
{
CV_INSTRUMENT_REGION();
Mat img = _img.getMat(), cornersM = _corners.getMat();
int ncorners = cornersM.checkVector(2, CV_32F);
CV_Assert( ncorners >= 0 );
Point2f* corners = cornersM.ptr<Point2f>();
const int nbins = 256;
float ranges[] = {0, 256};
const float* _ranges = ranges;
Mat hist;
Mat black_comp, white_comp;
for(int i = 0; i < ncorners; i++)
{
int channels = 0;
Rect roi(cvRound(corners[i].x - region_size.width), cvRound(corners[i].y - region_size.height),
region_size.width*2 + 1, region_size.height*2 + 1);
Mat img_roi = img(roi);
calcHist(&img_roi, 1, &channels, Mat(), hist, 1, &nbins, &_ranges);
int black_thresh = 0, white_thresh = 0;
segment_hist_max(hist, black_thresh, white_thresh);
threshold(img, black_comp, black_thresh, 255.0, THRESH_BINARY_INV);
threshold(img, white_comp, white_thresh, 255.0, THRESH_BINARY);
const int erode_count = 1;
erode(black_comp, black_comp, Mat(), Point(-1, -1), erode_count);
erode(white_comp, white_comp, Mat(), Point(-1, -1), erode_count);
std::vector<std::vector<Point> > white_contours, black_contours;
findContours(black_comp, black_contours, RETR_LIST, CHAIN_APPROX_SIMPLE);
findContours(white_comp, white_contours, RETR_LIST, CHAIN_APPROX_SIMPLE);
if(black_contours.size() < 5 || white_contours.size() < 5) continue;
// find two white and black blobs that are close to the input point
std::vector<std::pair<int, float> > white_order, black_order;
orderContours(black_contours, corners[i], black_order);
orderContours(white_contours, corners[i], white_order);
const float max_dist = 10.0f;
if(black_order[0].second > max_dist || black_order[1].second > max_dist ||
white_order[0].second > max_dist || white_order[1].second > max_dist)
{
continue; // there will be no improvement in this corner position
}
const std::vector<Point>* quads[4] = {&black_contours[black_order[0].first], &black_contours[black_order[1].first],
&white_contours[white_order[0].first], &white_contours[white_order[1].first]};
std::vector<Point2f> quads_approx[4];
Point2f quad_corners[4];
for(int k = 0; k < 4; k++)
{
std::vector<Point2f> temp;
for(size_t j = 0; j < quads[k]->size(); j++) temp.push_back((*quads[k])[j]);
approxPolyDP(Mat(temp), quads_approx[k], 0.5, true);
findCorner(quads_approx[k], corners[i], quad_corners[k]);
quad_corners[k] += Point2f(0.5f, 0.5f);
}
// cross two lines
Point2f origin1 = quad_corners[0];
Point2f dir1 = quad_corners[1] - quad_corners[0];
Point2f origin2 = quad_corners[2];
Point2f dir2 = quad_corners[3] - quad_corners[2];
double angle = acos(dir1.dot(dir2)/(norm(dir1)*norm(dir2)));
if(cvIsNaN(angle) || cvIsInf(angle) || angle < 0.5 || angle > CV_PI - 0.5) continue;
findLinesCrossPoint(origin1, dir1, origin2, dir2, corners[i]);
}
return true;
}
int rotatedRectangleIntersection( const RotatedRect& rect1, const RotatedRect& rect2, OutputArray intersectingRegion )
{
const float samePointEps = 0.00001; // used to test if two points are the same
Point2f vec1[4], vec2[4];
Point2f pts1[4], pts2[4];
std::vector <Point2f> intersection;
rect1.points(pts1);
rect2.points(pts2);
int ret = INTERSECT_FULL;
// Specical case of rect1 == rect2
{
bool same = true;
for( int i = 0; i < 4; i++ )
{
if( fabs(pts1[i].x - pts2[i].x) > samePointEps || (fabs(pts1[i].y - pts2[i].y) > samePointEps) )
{
same = false;
break;
}
}
if(same)
{
intersection.resize(4);
for( int i = 0; i < 4; i++ )
{
intersection[i] = pts1[i];
}
Mat(intersection).copyTo(intersectingRegion);
return INTERSECT_FULL;
}
}
// Line vector
// A line from p1 to p2 is: p1 + (p2-p1)*t, t=[0,1]
for( int i = 0; i < 4; i++ )
{
vec1[i].x = pts1[(i+1)%4].x - pts1[i].x;
vec1[i].y = pts1[(i+1)%4].y - pts1[i].y;
vec2[i].x = pts2[(i+1)%4].x - pts2[i].x;
vec2[i].y = pts2[(i+1)%4].y - pts2[i].y;
}
// Line test - test all line combos for intersection
for( int i = 0; i < 4; i++ )
{
for( int j = 0; j < 4; j++ )
{
// Solve for 2x2 Ax=b
float x21 = pts2[j].x - pts1[i].x;
float y21 = pts2[j].y - pts1[i].y;
float vx1 = vec1[i].x;
float vy1 = vec1[i].y;
float vx2 = vec2[j].x;
float vy2 = vec2[j].y;
float det = vx2*vy1 - vx1*vy2;
float t1 = (vx2*y21 - vy2*x21) / det;
float t2 = (vx1*y21 - vy1*x21) / det;
// This takes care of parallel lines
if( cvIsInf(t1) || cvIsInf(t2) || cvIsNaN(t1) || cvIsNaN(t2) )
{
continue;
}
if( t1 >= 0.0f && t1 <= 1.0f && t2 >= 0.0f && t2 <= 1.0f )
{
float xi = pts1[i].x + vec1[i].x*t1;
float yi = pts1[i].y + vec1[i].y*t1;
intersection.push_back(Point2f(xi,yi));
}
}
}
if( !intersection.empty() )
{
ret = INTERSECT_PARTIAL;
}
// Check for vertices from rect1 inside recct2
for( int i = 0; i < 4; i++ )
{
// We do a sign test to see which side the point lies.
// If the point all lie on the same sign for all 4 sides of the rect,
// then there's an intersection
int posSign = 0;
int negSign = 0;
float x = pts1[i].x;
float y = pts1[i].y;
for( int j = 0; j < 4; j++ )
{
// line equation: Ax + By + C = 0
// see which side of the line this point is at
float A = -vec2[j].y;
float B = vec2[j].x;
float C = -(A*pts2[j].x + B*pts2[j].y);
float s = A*x+ B*y+ C;
if( s >= 0 )
{
posSign++;
}
else
{
negSign++;
}
}
if( posSign == 4 || negSign == 4 )
{
intersection.push_back(pts1[i]);
}
}
// Reverse the check - check for vertices from rect2 inside recct1
for( int i = 0; i < 4; i++ )
{
// We do a sign test to see which side the point lies.
// If the point all lie on the same sign for all 4 sides of the rect,
// then there's an intersection
int posSign = 0;
int negSign = 0;
float x = pts2[i].x;
float y = pts2[i].y;
for( int j = 0; j < 4; j++ )
{
// line equation: Ax + By + C = 0
// see which side of the line this point is at
float A = -vec1[j].y;
float B = vec1[j].x;
float C = -(A*pts1[j].x + B*pts1[j].y);
float s = A*x + B*y + C;
if( s >= 0 )
{
posSign++;
}
else
{
negSign++;
}
}
if( posSign == 4 || negSign == 4 )
{
intersection.push_back(pts2[i]);
}
}
// Get rid of dupes
for( int i = 0; i < (int)intersection.size()-1; i++ )
{
for( size_t j = i+1; j < intersection.size(); j++ )
{
float dx = intersection[i].x - intersection[j].x;
float dy = intersection[i].y - intersection[j].y;
double d2 = dx*dx + dy*dy; // can be a really small number, need double here
if( d2 < samePointEps*samePointEps )
{
// Found a dupe, remove it
std::swap(intersection[j], intersection.back());
intersection.pop_back();
i--; // restart check
}
}
}
if( intersection.empty() )
{
return INTERSECT_NONE ;
}
// If this check fails then it means we're getting dupes, increase samePointEps
CV_Assert( intersection.size() <= 8 );
Mat(intersection).copyTo(intersectingRegion);
return ret;
}
int CV_CompareHistTest::validate_test_results( int /*test_case_idx*/ )
{
int code = CvTS::OK;
int i;
double result0[MAX_METHOD+1];
double s0 = 0, s1 = 0, sq0 = 0, sq1 = 0, t;
for( i = 0; i < MAX_METHOD; i++ )
result0[i] = 0;
if( hist_type == CV_HIST_ARRAY )
{
float* ptr0 = (float*)cvPtr1D( hist[0]->bins, 0 );
float* ptr1 = (float*)cvPtr1D( hist[1]->bins, 0 );
for( i = 0; i < total_size; i++ )
{
double v0 = ptr0[i], v1 = ptr1[i];
result0[CV_COMP_CORREL] += v0*v1;
result0[CV_COMP_INTERSECT] += MIN(v0,v1);
if( fabs(v0 + v1) > DBL_EPSILON )
result0[CV_COMP_CHISQR] += (v0 - v1)*(v0 - v1)/(v0 + v1);
s0 += v0;
s1 += v1;
sq0 += v0*v0;
sq1 += v1*v1;
result0[CV_COMP_BHATTACHARYYA] += sqrt(v0*v1);
}
}
else
{
CvSparseMat* sparse0 = (CvSparseMat*)hist[0]->bins;
CvSparseMat* sparse1 = (CvSparseMat*)hist[1]->bins;
CvSparseMatIterator iterator;
CvSparseNode* node;
for( node = cvInitSparseMatIterator( sparse0, &iterator );
node != 0; node = cvGetNextSparseNode( &iterator ) )
{
const int* idx = CV_NODE_IDX(sparse0, node);
double v0 = *(float*)CV_NODE_VAL(sparse0, node);
double v1 = (float)cvGetRealND(sparse1, idx);
result0[CV_COMP_CORREL] += v0*v1;
result0[CV_COMP_INTERSECT] += MIN(v0,v1);
if( fabs(v0 + v1) > DBL_EPSILON )
result0[CV_COMP_CHISQR] += (v0 - v1)*(v0 - v1)/(v0 + v1);
s0 += v0;
sq0 += v0*v0;
result0[CV_COMP_BHATTACHARYYA] += sqrt(v0*v1);
}
for( node = cvInitSparseMatIterator( sparse1, &iterator );
node != 0; node = cvGetNextSparseNode( &iterator ) )
{
const int* idx = CV_NODE_IDX(sparse1, node);
double v1 = *(float*)CV_NODE_VAL(sparse1, node);
double v0 = (float)cvGetRealND(sparse0, idx);
if( fabs(v0) < DBL_EPSILON )
result0[CV_COMP_CHISQR] += v1;
s1 += v1;
sq1 += v1*v1;
}
}
t = (sq0 - s0*s0/total_size)*(sq1 - s1*s1/total_size);
result0[CV_COMP_CORREL] = fabs(t) > DBL_EPSILON ?
(result0[CV_COMP_CORREL] - s0*s1/total_size)/sqrt(t) : 1;
s1 *= s0;
s0 = result0[CV_COMP_BHATTACHARYYA];
s0 = 1. - s0*(s1 > FLT_EPSILON ? 1./sqrt(s1) : 1.);
result0[CV_COMP_BHATTACHARYYA] = sqrt(MAX(s0,0.));
for( i = 0; i < MAX_METHOD; i++ )
{
double v = result[i], v0 = result0[i];
const char* method_name =
i == CV_COMP_CHISQR ? "Chi-Square" :
i == CV_COMP_CORREL ? "Correlation" :
i == CV_COMP_INTERSECT ? "Intersection" :
i == CV_COMP_BHATTACHARYYA ? "Bhattacharyya" : "Unknown";
if( cvIsNaN(v) || cvIsInf(v) )
{
ts->printf( CvTS::LOG, "The comparison result using the method #%d (%s) is invalid (=%g)\n",
i, method_name, v );
code = CvTS::FAIL_INVALID_OUTPUT;
break;
}
else if( fabs(v0 - v) > FLT_EPSILON*10*MAX(fabs(v0),0.1) )
{
ts->printf( CvTS::LOG, "The comparison result using the method #%d (%s)\n\tis inaccurate (=%g, should be =%g)\n",
i, method_name, v, v0 );
code = CvTS::FAIL_BAD_ACCURACY;
break;
}
}
if( code < 0 )
ts->set_failed_test_info( code );
return code;
}
