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opencv/modules/features2d/test/test_mser.cpp
Vladislav Sovrasov 25af743902 mser: add a couple of new regression tests
2017-07-14 20:07:32 +03:00

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/*M///////////////////////////////////////////////////////////////////////////////////////
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// License Agreement
// For Open Source Computer Vision Library
//
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#include "test_precomp.hpp"
#include "opencv2/highgui.hpp"
#include <vector>
#include <string>
using namespace std;
using namespace cv;
#undef RENDER_MSERS
#define RENDER_MSERS 0
#if defined RENDER_MSERS && RENDER_MSERS
static void renderMSERs(const Mat& gray, Mat& img, const vector<vector<Point> >& msers)
{
cvtColor(gray, img, COLOR_GRAY2BGR);
RNG rng((uint64)1749583);
for( int i = 0; i < (int)msers.size(); i++ )
{
uchar b = rng.uniform(0, 256);
uchar g = rng.uniform(0, 256);
uchar r = rng.uniform(0, 256);
Vec3b color(b, g, r);
const Point* pt = &msers[i][0];
size_t j, n = msers[i].size();
for( j = 0; j < n; j++ )
img.at<Vec3b>(pt[j]) = color;
}
}
#endif
TEST(Features2d_MSER, cases)
{
uchar buf[] =
{
255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 0, 0, 0, 0, 255, 255, 255, 255, 255, 255, 255, 255, 255, 0, 0, 0, 0, 255, 255, 255, 255,
255, 255, 255, 255, 255, 0, 0, 0, 0, 0, 255, 255, 255, 255, 255, 255, 255, 255, 0, 0, 0, 0, 255, 255, 255, 255,
255, 255, 255, 255, 255, 0, 0, 0, 0, 0, 255, 255, 255, 255, 255, 255, 255, 255, 0, 0, 0, 0, 255, 255, 255, 255,
255, 255, 255, 255, 255, 0, 0, 0, 0, 255, 255, 255, 255, 255, 255, 255, 255, 255, 0, 0, 0, 0, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 0, 0, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 0, 0, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255
};
Mat big_image = imread(cvtest::TS::ptr()->get_data_path() + "mser/puzzle.png", 0);
Mat small_image(14, 26, CV_8U, buf);
static const int thresharr[] = { 0, 70, 120, 180, 255 };
const int kDelta = 5;
Ptr<MSER> mserExtractor = MSER::create( kDelta );
vector<vector<Point> > msers;
vector<Rect> boxes;
RNG rng((uint64)123456);
for( int i = 0; i < 100; i++ )
{
bool use_big_image = rng.uniform(0, 7) != 0;
bool invert = rng.uniform(0, 2) != 0;
bool binarize = use_big_image ? rng.uniform(0, 5) != 0 : false;
bool blur = rng.uniform(0, 2) != 0;
int thresh = thresharr[rng.uniform(0, 5)];
/*if( i == 0 )
{
use_big_image = true;
invert = binarize = blur = false;
}*/
const Mat& src0 = use_big_image ? big_image : small_image;
Mat src = src0.clone();
int kMinArea = use_big_image ? 256 : 10;
int kMaxArea = (int)src.total()/4;
mserExtractor->setMinArea(kMinArea);
mserExtractor->setMaxArea(kMaxArea);
if( invert )
bitwise_not(src, src);
if( binarize )
threshold(src, src, thresh, 255, THRESH_BINARY);
if( blur )
GaussianBlur(src, src, Size(5, 5), 1.5, 1.5);
int minRegs = use_big_image ? 7 : 2;
int maxRegs = use_big_image ? 1000 : 20;
if( binarize && (thresh == 0 || thresh == 255) )
minRegs = maxRegs = 0;
mserExtractor->detectRegions( src, msers, boxes );
int nmsers = (int)msers.size();
ASSERT_EQ(nmsers, (int)boxes.size());
if( maxRegs < nmsers || minRegs > nmsers )
{
printf("%d. minArea=%d, maxArea=%d, nmsers=%d, minRegs=%d, maxRegs=%d, "
"image=%s, invert=%d, binarize=%d, thresh=%d, blur=%d\n",
i, kMinArea, kMaxArea, nmsers, minRegs, maxRegs, use_big_image ? "big" : "small",
(int)invert, (int)binarize, thresh, (int)blur);
#if defined RENDER_MSERS && RENDER_MSERS
Mat image;
imshow("source", src);
renderMSERs(src, image, msers);
imshow("result", image);
waitKey();
#endif
}
ASSERT_LE(minRegs, nmsers);
ASSERT_GE(maxRegs, nmsers);
}
}
TEST(Features2d_MSER, history_update_regression)
{
String dataPath = cvtest::TS::ptr()->get_data_path() + "mser/";
vector<Mat> tstImages;
tstImages.push_back(imread(dataPath + "mser_test.png", IMREAD_GRAYSCALE));
tstImages.push_back(imread(dataPath + "mser_test2.png", IMREAD_GRAYSCALE));
for(size_t j = 0; j < tstImages.size(); j++)
{
size_t previous_size = 0;
for(int minArea = 100; minArea > 10; minArea--)
{
Ptr<MSER> mser = MSER::create(1, minArea, (int)(tstImages[j].cols * tstImages[j].rows * 0.2));
mser->setPass2Only(true);
vector<vector<Point> > mserContours;
vector<Rect> boxRects;
mser->detectRegions(tstImages[j], mserContours, boxRects);
ASSERT_LE(previous_size, mserContours.size());
previous_size = mserContours.size();
}
}
}
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