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opencv/modules/imgproc/test/test_floodfill.cpp
Alexander Alekhin 8a3c394d6a don't use constructors for C API structures
2018-09-06 14:34:16 +03:00

546 lines
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/*M///////////////////////////////////////////////////////////////////////////////////////
//
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//
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// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// Intel License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000, Intel Corporation, all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
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// and/or other materials provided with the distribution.
//
// * The name of Intel Corporation may not be used to endorse or promote products
// derived from this software without specific prior written permission.
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// This software is provided by the copyright holders and contributors "as is" and
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// (including, but not limited to, procurement of substitute goods or services;
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// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
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//
//M*/
#include "test_precomp.hpp"
namespace opencv_test { namespace {
class CV_FloodFillTest : public cvtest::ArrayTest
{
public:
CV_FloodFillTest();
protected:
void get_test_array_types_and_sizes( int test_case_idx, vector<vector<Size> >& sizes, vector<vector<int> >& types );
double get_success_error_level( int test_case_idx, int i, int j );
void run_func();
void prepare_to_validation( int );
void fill_array( int test_case_idx, int i, int j, Mat& arr );
/*int write_default_params(CvFileStorage* fs);
void get_timing_test_array_types_and_sizes( int test_case_idx, vector<vector<Size> >& sizes, vector<vector<int> >& types
CvSize** whole_sizes, bool *are_images );
void print_timing_params( int test_case_idx, char* ptr, int params_left );*/
Point seed_pt;
Scalar new_val;
Scalar l_diff, u_diff;
int connectivity;
bool use_mask, mask_only;
int range_type;
int new_mask_val;
bool test_cpp;
};
CV_FloodFillTest::CV_FloodFillTest()
{
test_array[INPUT_OUTPUT].push_back(NULL);
test_array[INPUT_OUTPUT].push_back(NULL);
test_array[REF_INPUT_OUTPUT].push_back(NULL);
test_array[REF_INPUT_OUTPUT].push_back(NULL);
test_array[OUTPUT].push_back(NULL);
test_array[REF_OUTPUT].push_back(NULL);
optional_mask = false;
element_wise_relative_error = true;
test_cpp = false;
}
void CV_FloodFillTest::get_test_array_types_and_sizes( int test_case_idx,
vector<vector<Size> >& sizes,
vector<vector<int> >& types )
{
RNG& rng = ts->get_rng();
int depth, cn;
int i;
double buff[8];
cvtest::ArrayTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
depth = cvtest::randInt(rng) % 3;
depth = depth == 0 ? CV_8U : depth == 1 ? CV_32S : CV_32F;
cn = cvtest::randInt(rng) & 1 ? 3 : 1;
use_mask = (cvtest::randInt(rng) & 1) != 0;
connectivity = (cvtest::randInt(rng) & 1) ? 4 : 8;
mask_only = use_mask && (cvtest::randInt(rng) & 1) != 0;
new_mask_val = cvtest::randInt(rng) & 255;
range_type = cvtest::randInt(rng) % 3;
types[INPUT_OUTPUT][0] = types[REF_INPUT_OUTPUT][0] = CV_MAKETYPE(depth, cn);
types[INPUT_OUTPUT][1] = types[REF_INPUT_OUTPUT][1] = CV_8UC1;
types[OUTPUT][0] = types[REF_OUTPUT][0] = CV_64FC1;
sizes[OUTPUT][0] = sizes[REF_OUTPUT][0] = cvSize(9,1);
if( !use_mask )
sizes[INPUT_OUTPUT][1] = sizes[REF_INPUT_OUTPUT][1] = cvSize(0,0);
else
{
Size sz = sizes[INPUT_OUTPUT][0];
sizes[INPUT_OUTPUT][1] = sizes[REF_INPUT_OUTPUT][1] = Size(sz.width+2,sz.height+2);
}
seed_pt.x = cvtest::randInt(rng) % sizes[INPUT_OUTPUT][0].width;
seed_pt.y = cvtest::randInt(rng) % sizes[INPUT_OUTPUT][0].height;
if( range_type == 0 )
l_diff = u_diff = Scalar::all(0.);
else
{
Mat m( 1, 8, CV_16S, buff );
rng.fill( m, RNG::NORMAL, Scalar::all(0), Scalar::all(32) );
for( i = 0; i < 4; i++ )
{
l_diff.val[i] = fabs(m.at<short>(i)/16.);
u_diff.val[i] = fabs(m.at<short>(i+4)/16.);
}
}
new_val = Scalar::all(0.);
for( i = 0; i < cn; i++ )
new_val.val[i] = cvtest::randReal(rng)*255;
test_cpp = (cvtest::randInt(rng) & 256) == 0;
}
double CV_FloodFillTest::get_success_error_level( int /*test_case_idx*/, int i, int j )
{
return i == OUTPUT ? FLT_EPSILON : j == 0 ? FLT_EPSILON : 0;
}
void CV_FloodFillTest::fill_array( int test_case_idx, int i, int j, Mat& arr )
{
RNG& rng = ts->get_rng();
if( i != INPUT && i != INPUT_OUTPUT )
{
cvtest::ArrayTest::fill_array( test_case_idx, i, j, arr );
return;
}
if( j == 0 )
{
Mat tmp = arr;
Scalar m = Scalar::all(128);
Scalar s = Scalar::all(10);
if( arr.depth() == CV_32FC1 )
tmp.create(arr.size(), CV_MAKETYPE(CV_8U, arr.channels()));
if( range_type == 0 )
s = Scalar::all(2);
rng.fill(tmp, RNG::NORMAL, m, s );
if( arr.data != tmp.data )
cvtest::convert(tmp, arr, arr.type());
}
else
{
Scalar l = Scalar::all(-2);
Scalar u = Scalar::all(2);
cvtest::randUni(rng, arr, l, u );
rectangle( arr, Point(0,0), Point(arr.cols-1,arr.rows-1), Scalar::all(1), 1, 8, 0 );
}
}
void CV_FloodFillTest::run_func()
{
int flags = connectivity + (mask_only ? CV_FLOODFILL_MASK_ONLY : 0) +
(range_type == 1 ? CV_FLOODFILL_FIXED_RANGE : 0) + (new_mask_val << 8);
double* odata = test_mat[OUTPUT][0].ptr<double>();
if(!test_cpp)
{
CvConnectedComp comp;
cvFloodFill( test_array[INPUT_OUTPUT][0], cvPoint(seed_pt), cvScalar(new_val), cvScalar(l_diff), cvScalar(u_diff), &comp,
flags, test_array[INPUT_OUTPUT][1] );
odata[0] = comp.area;
odata[1] = comp.rect.x;
odata[2] = comp.rect.y;
odata[3] = comp.rect.width;
odata[4] = comp.rect.height;
odata[5] = comp.value.val[0];
odata[6] = comp.value.val[1];
odata[7] = comp.value.val[2];
odata[8] = comp.value.val[3];
}
else
{
cv::Mat img = cv::cvarrToMat(test_array[INPUT_OUTPUT][0]),
mask = test_array[INPUT_OUTPUT][1] ? cv::cvarrToMat(test_array[INPUT_OUTPUT][1]) : cv::Mat();
cv::Rect rect;
int area;
if( mask.empty() )
area = cv::floodFill( img, seed_pt, new_val, &rect, l_diff, u_diff, flags );
else
area = cv::floodFill( img, mask, seed_pt, new_val, &rect, l_diff, u_diff, flags );
odata[0] = area;
odata[1] = rect.x;
odata[2] = rect.y;
odata[3] = rect.width;
odata[4] = rect.height;
odata[5] = odata[6] = odata[7] = odata[8] = 0;
}
}
typedef struct ff_offset_pair_t
{
int mofs, iofs;
}
ff_offset_pair_t;
static void
cvTsFloodFill( CvMat* _img, CvPoint seed_pt, CvScalar new_val,
CvScalar l_diff, CvScalar u_diff, CvMat* _mask,
double* comp, int connectivity, int range_type,
int new_mask_val, bool mask_only )
{
CvMemStorage* st = cvCreateMemStorage();
ff_offset_pair_t p0, p;
CvSeq* seq = cvCreateSeq( 0, sizeof(CvSeq), sizeof(p0), st );
CvMat* tmp = _img;
CvMat* mask;
CvRect r = cvRect( 0, 0, -1, -1 );
int area = 0;
int i, j;
ushort* m;
float* img;
int mstep, step;
int cn = CV_MAT_CN(_img->type);
int mdelta[8], idelta[8], ncount;
int cols = _img->cols, rows = _img->rows;
int u0 = 0, u1 = 0, u2 = 0;
double s0 = 0, s1 = 0, s2 = 0;
if( CV_MAT_DEPTH(_img->type) == CV_8U || CV_MAT_DEPTH(_img->type) == CV_32S )
{
tmp = cvCreateMat( rows, cols, CV_MAKETYPE(CV_32F,CV_MAT_CN(_img->type)) );
cvtest::convert(cvarrToMat(_img), cvarrToMat(tmp), -1);
}
mask = cvCreateMat( rows + 2, cols + 2, CV_16UC1 );
if( _mask )
cvtest::convert(cvarrToMat(_mask), cvarrToMat(mask), -1);
else
{
Mat m_mask = cvarrToMat(mask);
cvtest::set( m_mask, Scalar::all(0), Mat() );
cvRectangle( mask, cvPoint(0,0), cvPoint(mask->cols-1,mask->rows-1), cvScalar(Scalar::all(1.)), 1, 8, 0 );
}
new_mask_val = (new_mask_val != 0 ? new_mask_val : 1) << 8;
m = (ushort*)(mask->data.ptr + mask->step) + 1;
mstep = mask->step / sizeof(m[0]);
img = tmp->data.fl;
step = tmp->step / sizeof(img[0]);
p0.mofs = seed_pt.y*mstep + seed_pt.x;
p0.iofs = seed_pt.y*step + seed_pt.x*cn;
if( m[p0.mofs] )
goto _exit_;
cvSeqPush( seq, &p0 );
m[p0.mofs] = (ushort)new_mask_val;
if( connectivity == 4 )
{
ncount = 4;
mdelta[0] = -mstep; idelta[0] = -step;
mdelta[1] = -1; idelta[1] = -cn;
mdelta[2] = 1; idelta[2] = cn;
mdelta[3] = mstep; idelta[3] = step;
}
else
{
ncount = 8;
mdelta[0] = -mstep-1; mdelta[1] = -mstep; mdelta[2] = -mstep+1;
idelta[0] = -step-cn; idelta[1] = -step; idelta[2] = -step+cn;
mdelta[3] = -1; mdelta[4] = 1;
idelta[3] = -cn; idelta[4] = cn;
mdelta[5] = mstep-1; mdelta[6] = mstep; mdelta[7] = mstep+1;
idelta[5] = step-cn; idelta[6] = step; idelta[7] = step+cn;
}
if( cn == 1 )
{
float a0 = (float)-l_diff.val[0];
float b0 = (float)u_diff.val[0];
s0 = img[p0.iofs];
if( range_type < 2 )
{
a0 += (float)s0; b0 += (float)s0;
}
while( seq->total )
{
cvSeqPop( seq, &p0 );
float a = a0, b = b0;
float* ptr = img + p0.iofs;
ushort* mptr = m + p0.mofs;
if( range_type == 2 )
a += ptr[0], b += ptr[0];
for( i = 0; i < ncount; i++ )
{
int md = mdelta[i], id = idelta[i];
float v;
if( !mptr[md] && a <= (v = ptr[id]) && v <= b )
{
mptr[md] = (ushort)new_mask_val;
p.mofs = p0.mofs + md;
p.iofs = p0.iofs + id;
cvSeqPush( seq, &p );
}
}
}
}
else
{
float a0 = (float)-l_diff.val[0];
float a1 = (float)-l_diff.val[1];
float a2 = (float)-l_diff.val[2];
float b0 = (float)u_diff.val[0];
float b1 = (float)u_diff.val[1];
float b2 = (float)u_diff.val[2];
s0 = img[p0.iofs];
s1 = img[p0.iofs + 1];
s2 = img[p0.iofs + 2];
if( range_type < 2 )
{
a0 += (float)s0; b0 += (float)s0;
a1 += (float)s1; b1 += (float)s1;
a2 += (float)s2; b2 += (float)s2;
}
while( seq->total )
{
cvSeqPop( seq, &p0 );
float _a0 = a0, _a1 = a1, _a2 = a2;
float _b0 = b0, _b1 = b1, _b2 = b2;
float* ptr = img + p0.iofs;
ushort* mptr = m + p0.mofs;
if( range_type == 2 )
{
_a0 += ptr[0]; _b0 += ptr[0];
_a1 += ptr[1]; _b1 += ptr[1];
_a2 += ptr[2]; _b2 += ptr[2];
}
for( i = 0; i < ncount; i++ )
{
int md = mdelta[i], id = idelta[i];
float v;
if( !mptr[md] &&
_a0 <= (v = ptr[id]) && v <= _b0 &&
_a1 <= (v = ptr[id+1]) && v <= _b1 &&
_a2 <= (v = ptr[id+2]) && v <= _b2 )
{
mptr[md] = (ushort)new_mask_val;
p.mofs = p0.mofs + md;
p.iofs = p0.iofs + id;
cvSeqPush( seq, &p );
}
}
}
}
r.x = r.width = seed_pt.x;
r.y = r.height = seed_pt.y;
if( !mask_only )
{
s0 = new_val.val[0];
s1 = new_val.val[1];
s2 = new_val.val[2];
if( tmp != _img )
{
u0 = saturate_cast<uchar>(s0);
u1 = saturate_cast<uchar>(s1);
u2 = saturate_cast<uchar>(s2);
s0 = u0;
s1 = u1;
s2 = u2;
}
}
else
s0 = s1 = s2 = 0;
new_mask_val >>= 8;
for( i = 0; i < rows; i++ )
{
float* ptr = img + i*step;
ushort* mptr = m + i*mstep;
uchar* dmptr = _mask ? _mask->data.ptr + (i+1)*_mask->step + 1 : 0;
double area0 = area;
for( j = 0; j < cols; j++ )
{
if( mptr[j] > 255 )
{
if( dmptr )
dmptr[j] = (uchar)new_mask_val;
if( !mask_only )
{
if( cn == 1 )
ptr[j] = (float)s0;
else
{
ptr[j*3] = (float)s0;
ptr[j*3+1] = (float)s1;
ptr[j*3+2] = (float)s2;
}
}
else
{
if( cn == 1 )
s0 += ptr[j];
else
{
s0 += ptr[j*3];
s1 += ptr[j*3+1];
s2 += ptr[j*3+2];
}
}
area++;
if( r.x > j )
r.x = j;
if( r.width < j )
r.width = j;
}
}
if( area != area0 )
{
if( r.y > i )
r.y = i;
if( r.height < i )
r.height = i;
}
}
_exit_:
cvReleaseMat( &mask );
if( tmp != _img )
{
if( !mask_only )
cvtest::convert(cvarrToMat(tmp), cvarrToMat(_img), -1);
cvReleaseMat( &tmp );
}
comp[0] = area;
comp[1] = r.x;
comp[2] = r.y;
comp[3] = r.width - r.x + 1;
comp[4] = r.height - r.y + 1;
#if 0
if( mask_only )
{
double t = area ? 1./area : 0;
s0 *= t;
s1 *= t;
s2 *= t;
}
comp[5] = s0;
comp[6] = s1;
comp[7] = s2;
#else
comp[5] = new_val.val[0];
comp[6] = new_val.val[1];
comp[7] = new_val.val[2];
#endif
comp[8] = 0;
cvReleaseMemStorage(&st);
}
void CV_FloodFillTest::prepare_to_validation( int /*test_case_idx*/ )
{
double* comp = test_mat[REF_OUTPUT][0].ptr<double>();
CvMat _input = cvMat(test_mat[REF_INPUT_OUTPUT][0]);
CvMat _mask = cvMat(test_mat[REF_INPUT_OUTPUT][1]);
cvTsFloodFill( &_input, cvPoint(seed_pt), cvScalar(new_val), cvScalar(l_diff), cvScalar(u_diff),
_mask.data.ptr ? &_mask : 0,
comp, connectivity, range_type,
new_mask_val, mask_only );
if(test_cpp)
comp[5] = comp[6] = comp[7] = comp[8] = 0;
}
TEST(Imgproc_FloodFill, accuracy) { CV_FloodFillTest test; test.safe_run(); }
TEST(Imgproc_FloodFill, maskValue)
{
const int n = 50;
Mat img = Mat::zeros(n, n, CV_8U);
Mat mask = Mat::zeros(n + 2, n + 2, CV_8U);
circle(img, Point(n/2, n/2), 20, Scalar(100), 4);
int flags = 4 + CV_FLOODFILL_MASK_ONLY;
floodFill(img, mask, Point(n/2 + 13, n/2), Scalar(100), NULL, Scalar(), Scalar(), flags);
ASSERT_EQ(1, cvtest::norm(mask.rowRange(1, n-1).colRange(1, n-1), NORM_INF));
}
}} // namespace
/* End of file. */
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