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opencv/modules/imgproc/test/test_connectedcomponents.cpp
Federico Bolelli 9695165877
Merge pull request #19631 from prittt:sota-ccl 
* Add Spaghetti algorithm for CCL

* Add stat tests for new and old algorithms

* Switch license header to short version
2021-02-27 17:27:24 +00:00

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
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//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., 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,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
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//M*/
#include "test_precomp.hpp"
namespace opencv_test { namespace {
class CV_ConnectedComponentsTest : public cvtest::BaseTest
{
public:
CV_ConnectedComponentsTest();
~CV_ConnectedComponentsTest();
protected:
void run(int);
};
CV_ConnectedComponentsTest::CV_ConnectedComponentsTest() {}
CV_ConnectedComponentsTest::~CV_ConnectedComponentsTest() {}
// This function force a row major order for the labels
void normalizeLabels(Mat1i& imgLabels, int iNumLabels) {
vector<int> vecNewLabels(iNumLabels + 1, 0);
int iMaxNewLabel = 0;
for (int r = 0; r<imgLabels.rows; ++r) {
for (int c = 0; c<imgLabels.cols; ++c) {
int iCurLabel = imgLabels(r, c);
if (iCurLabel>0) {
if (vecNewLabels[iCurLabel] == 0) {
vecNewLabels[iCurLabel] = ++iMaxNewLabel;
}
imgLabels(r, c) = vecNewLabels[iCurLabel];
}
}
}
}
void CV_ConnectedComponentsTest::run( int /* start_from */)
{
int ccltype[] = { cv::CCL_DEFAULT, cv::CCL_WU, cv::CCL_GRANA, cv::CCL_BOLELLI, cv::CCL_SAUF, cv::CCL_BBDT, cv::CCL_SPAGHETTI };
string exp_path = string(ts->get_data_path()) + "connectedcomponents/ccomp_exp.png";
Mat exp = imread(exp_path, 0);
Mat orig = imread(string(ts->get_data_path()) + "connectedcomponents/concentric_circles.png", 0);
if (orig.empty())
{
ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_TEST_DATA);
return;
}
Mat bw = orig > 128;
for (uint cclt = 0; cclt < sizeof(ccltype)/sizeof(int); ++cclt)
{
Mat1i labelImage;
int nLabels = connectedComponents(bw, labelImage, 8, CV_32S, ccltype[cclt]);
normalizeLabels(labelImage, nLabels);
// Validate test results
for (int r = 0; r < labelImage.rows; ++r){
for (int c = 0; c < labelImage.cols; ++c){
int l = labelImage.at<int>(r, c);
bool pass = l >= 0 && l <= nLabels;
if (!pass){
ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_OUTPUT);
return;
}
}
}
if (exp.empty() || orig.size() != exp.size())
{
imwrite(exp_path, labelImage);
exp = labelImage;
}
if (0 != cvtest::norm(labelImage > 0, exp > 0, NORM_INF))
{
ts->set_failed_test_info(cvtest::TS::FAIL_MISMATCH);
return;
}
if (nLabels != cvtest::norm(labelImage, NORM_INF) + 1)
{
ts->set_failed_test_info(cvtest::TS::FAIL_MISMATCH);
return;
}
}
ts->set_failed_test_info(cvtest::TS::OK);
}
TEST(Imgproc_ConnectedComponents, regression) { CV_ConnectedComponentsTest test; test.safe_run(); }
TEST(Imgproc_ConnectedComponents, grana_buffer_overflow)
{
cv::Mat darkMask;
darkMask.create(31, 87, CV_8U);
darkMask = 0;
cv::Mat labels;
cv::Mat stats;
cv::Mat centroids;
int nbComponents = cv::connectedComponentsWithStats(darkMask, labels, stats, centroids, 8, CV_32S, cv::CCL_GRANA);
EXPECT_EQ(1, nbComponents);
}
static cv::Mat createCrashMat(int numThreads) {
const int h = numThreads * 4 * 2 + 8;
const double nParallelStripes = std::max(1, std::min(h / 2, numThreads * 4));
const int w = 4;
const int nstripes = cvRound(nParallelStripes <= 0 ? h : MIN(MAX(nParallelStripes, 1.), h));
const cv::Range stripeRange(0, nstripes);
const cv::Range wholeRange(0, h);
cv::Mat m(h, w, CV_8U);
m = 0;
// Look for a range that starts with odd value and ends with even value
cv::Range bugRange;
for (int s = stripeRange.start; s < stripeRange.end; s++) {
cv::Range sr(s, s + 1);
cv::Range r;
r.start = (int) (wholeRange.start +
((uint64) sr.start * (wholeRange.end - wholeRange.start) + nstripes / 2) / nstripes);
r.end = sr.end >= nstripes ?
wholeRange.end :
(int) (wholeRange.start +
((uint64) sr.end * (wholeRange.end - wholeRange.start) + nstripes / 2) / nstripes);
if (r.start > 0 && r.start % 2 == 1 && r.end % 2 == 0 && r.end >= r.start + 2) {
bugRange = r;
break;
}
}
if (bugRange.empty()) { // Could not create a buggy range
return m;
}
// Fill in bug Range
for (int x = 1; x < w; x++) {
m.at<char>(bugRange.start - 1, x) = 1;
}
m.at<char>(bugRange.start + 0, 0) = 1;
m.at<char>(bugRange.start + 0, 1) = 1;
m.at<char>(bugRange.start + 0, 3) = 1;
m.at<char>(bugRange.start + 1, 1) = 1;
m.at<char>(bugRange.start + 2, 1) = 1;
m.at<char>(bugRange.start + 2, 3) = 1;
m.at<char>(bugRange.start + 3, 0) = 1;
m.at<char>(bugRange.start + 3, 1) = 1;
return m;
}
TEST(Imgproc_ConnectedComponents, parallel_wu_labels)
{
cv::Mat mat = createCrashMat(cv::getNumThreads());
if(mat.empty()) {
return;
}
const int nbPixels = cv::countNonZero(mat);
cv::Mat labels;
cv::Mat stats;
cv::Mat centroids;
int nb = 0;
EXPECT_NO_THROW( nb = cv::connectedComponentsWithStats(mat, labels, stats, centroids, 8, CV_32S, cv::CCL_WU) );
int area = 0;
for(int i=1; i<nb; ++i) {
area += stats.at<int32_t>(i, cv::CC_STAT_AREA);
}
EXPECT_EQ(nbPixels, area);
}
TEST(Imgproc_ConnectedComponents, missing_background_pixels)
{
cv::Mat m = Mat::ones(10, 10, CV_8U);
cv::Mat labels;
cv::Mat stats;
cv::Mat centroids;
EXPECT_NO_THROW(cv::connectedComponentsWithStats(m, labels, stats, centroids, 8, CV_32S, cv::CCL_WU) );
EXPECT_EQ(stats.at<int32_t>(0, cv::CC_STAT_WIDTH), 0);
EXPECT_EQ(stats.at<int32_t>(0, cv::CC_STAT_HEIGHT), 0);
EXPECT_EQ(stats.at<int32_t>(0, cv::CC_STAT_LEFT), -1);
EXPECT_TRUE(std::isnan(centroids.at<double>(0, 0)));
EXPECT_TRUE(std::isnan(centroids.at<double>(0, 1)));
}
TEST(Imgproc_ConnectedComponents, spaghetti_bbdt_sauf_stats)
{
cv::Mat1b img(16, 16);
img << 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 1, 1, 1, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0,
0, 1, 1, 1, 0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 0, 0,
0, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0,
0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0,
0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 0, 0,
0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 0, 0,
0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 1,
0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 1,
0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1;
cv::Mat1i labels;
cv::Mat1i stats;
cv::Mat1d centroids;
int ccltype[] = { cv::CCL_WU, cv::CCL_GRANA, cv::CCL_BOLELLI, cv::CCL_SAUF, cv::CCL_BBDT, cv::CCL_SPAGHETTI };
for (uint cclt = 0; cclt < sizeof(ccltype) / sizeof(int); ++cclt) {
EXPECT_NO_THROW(cv::connectedComponentsWithStats(img, labels, stats, centroids, 8, CV_32S, ccltype[cclt]));
EXPECT_EQ(stats(0, cv::CC_STAT_LEFT), 0);
EXPECT_EQ(stats(0, cv::CC_STAT_TOP), 0);
EXPECT_EQ(stats(0, cv::CC_STAT_WIDTH), 16);
EXPECT_EQ(stats(0, cv::CC_STAT_HEIGHT), 15);
EXPECT_EQ(stats(0, cv::CC_STAT_AREA), 144);
EXPECT_EQ(stats(1, cv::CC_STAT_LEFT), 1);
EXPECT_EQ(stats(1, cv::CC_STAT_TOP), 1);
EXPECT_EQ(stats(1, cv::CC_STAT_WIDTH), 3);
EXPECT_EQ(stats(1, cv::CC_STAT_HEIGHT), 3);
EXPECT_EQ(stats(1, cv::CC_STAT_AREA), 9);
EXPECT_EQ(stats(2, cv::CC_STAT_LEFT), 1);
EXPECT_EQ(stats(2, cv::CC_STAT_TOP), 1);
EXPECT_EQ(stats(2, cv::CC_STAT_WIDTH), 8);
EXPECT_EQ(stats(2, cv::CC_STAT_HEIGHT), 7);
EXPECT_EQ(stats(2, cv::CC_STAT_AREA), 40);
EXPECT_EQ(stats(3, cv::CC_STAT_LEFT), 10);
EXPECT_EQ(stats(3, cv::CC_STAT_TOP), 2);
EXPECT_EQ(stats(3, cv::CC_STAT_WIDTH), 5);
EXPECT_EQ(stats(3, cv::CC_STAT_HEIGHT), 2);
EXPECT_EQ(stats(3, cv::CC_STAT_AREA), 8);
EXPECT_EQ(stats(4, cv::CC_STAT_LEFT), 11);
EXPECT_EQ(stats(4, cv::CC_STAT_TOP), 5);
EXPECT_EQ(stats(4, cv::CC_STAT_WIDTH), 3);
EXPECT_EQ(stats(4, cv::CC_STAT_HEIGHT), 3);
EXPECT_EQ(stats(4, cv::CC_STAT_AREA), 9);
EXPECT_EQ(stats(5, cv::CC_STAT_LEFT), 2);
EXPECT_EQ(stats(5, cv::CC_STAT_TOP), 9);
EXPECT_EQ(stats(5, cv::CC_STAT_WIDTH), 1);
EXPECT_EQ(stats(5, cv::CC_STAT_HEIGHT), 1);
EXPECT_EQ(stats(5, cv::CC_STAT_AREA), 1);
EXPECT_EQ(stats(6, cv::CC_STAT_LEFT), 12);
EXPECT_EQ(stats(6, cv::CC_STAT_TOP), 9);
EXPECT_EQ(stats(6, cv::CC_STAT_WIDTH), 1);
EXPECT_EQ(stats(6, cv::CC_STAT_HEIGHT), 1);
EXPECT_EQ(stats(6, cv::CC_STAT_AREA), 1);
// Labels' order could be different!
if (cclt == cv::CCL_WU || cclt == cv::CCL_SAUF) {
// CCL_SAUF, CCL_WU
EXPECT_EQ(stats(9, cv::CC_STAT_LEFT), 1);
EXPECT_EQ(stats(9, cv::CC_STAT_TOP), 11);
EXPECT_EQ(stats(9, cv::CC_STAT_WIDTH), 4);
EXPECT_EQ(stats(9, cv::CC_STAT_HEIGHT), 2);
EXPECT_EQ(stats(9, cv::CC_STAT_AREA), 8);
EXPECT_EQ(stats(7, cv::CC_STAT_LEFT), 6);
EXPECT_EQ(stats(7, cv::CC_STAT_TOP), 10);
EXPECT_EQ(stats(7, cv::CC_STAT_WIDTH), 4);
EXPECT_EQ(stats(7, cv::CC_STAT_HEIGHT), 2);
EXPECT_EQ(stats(7, cv::CC_STAT_AREA), 8);
EXPECT_EQ(stats(8, cv::CC_STAT_LEFT), 0);
EXPECT_EQ(stats(8, cv::CC_STAT_TOP), 10);
EXPECT_EQ(stats(8, cv::CC_STAT_WIDTH), 16);
EXPECT_EQ(stats(8, cv::CC_STAT_HEIGHT), 6);
EXPECT_EQ(stats(8, cv::CC_STAT_AREA), 21);
}
else {
// CCL_BBDT, CCL_GRANA, CCL_SPAGHETTI, CCL_BOLELLI
EXPECT_EQ(stats(7, cv::CC_STAT_LEFT), 1);
EXPECT_EQ(stats(7, cv::CC_STAT_TOP), 11);
EXPECT_EQ(stats(7, cv::CC_STAT_WIDTH), 4);
EXPECT_EQ(stats(7, cv::CC_STAT_HEIGHT), 2);
EXPECT_EQ(stats(7, cv::CC_STAT_AREA), 8);
EXPECT_EQ(stats(8, cv::CC_STAT_LEFT), 6);
EXPECT_EQ(stats(8, cv::CC_STAT_TOP), 10);
EXPECT_EQ(stats(8, cv::CC_STAT_WIDTH), 4);
EXPECT_EQ(stats(8, cv::CC_STAT_HEIGHT), 2);
EXPECT_EQ(stats(8, cv::CC_STAT_AREA), 8);
EXPECT_EQ(stats(9, cv::CC_STAT_LEFT), 0);
EXPECT_EQ(stats(9, cv::CC_STAT_TOP), 10);
EXPECT_EQ(stats(9, cv::CC_STAT_WIDTH), 16);
EXPECT_EQ(stats(9, cv::CC_STAT_HEIGHT), 6);
EXPECT_EQ(stats(9, cv::CC_STAT_AREA), 21);
}
EXPECT_EQ(stats(10, cv::CC_STAT_LEFT), 9);
EXPECT_EQ(stats(10, cv::CC_STAT_TOP), 12);
EXPECT_EQ(stats(10, cv::CC_STAT_WIDTH), 5);
EXPECT_EQ(stats(10, cv::CC_STAT_HEIGHT), 2);
EXPECT_EQ(stats(10, cv::CC_STAT_AREA), 7);
}
}
}} // namespace
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