mirror of https://github.com/opencv/opencv.git
Merge pull request #10232 from TomBecker-BD:hough-many-circles
Hough many circles (#10232) * Add Hui's optimization. Merge with latest changes in OpenCV. * Use conditional compilation instead of a runtime flag. * Whitespace. * Create the sequence for the nonzero edge pixels only if using that approach. * Improve performance for finding very large numbers of circles * Return the circles with the larger accumulator values first, as per API documentation. Use a separate step to check distance between circles. Allows circles to be sorted by strength first. Avoids locking in EstimateRadius which was slowing it down. Return centers only if maxRadius == 0 as per API documentation. * Sort the circles so results are deterministic. Otherwise the order of circles with the same strength depends on parallel processing completion order. * Add test for HoughCircles. * Add beads test. * Wrap the non-zero points structure in a common interface so the code can use either a vector or a matrix. * Remove the special case for skipping the radius search if maxRadius==0. * Add performance tests. * Use NULL instead of nullptr. OpenCV should compile with C++98 compiler. * Put test suite name first. Use different test suite names for each test to avoid an error from the test runner. * Address build bot errors and warnings. * Skip radius search if maxRadius < 0. * Dynamically switch to NZPointList when it will be faster than NZPointSet. * Fix compile error: missing 'typename' prior to dependent type name. * Fix compile error: missing 'typename' prior to dependent type name. This time fix it the non C++ 11 way. * Fix compile error: no type named 'const_reference' in 'class cv::NZPointList' * Disable ManySmallCircles tests. Failing on Mac. * Change beads image to JPEG for smaller file size. Try enabling the ManySmallCircles tests again. * Remove ManySmallCircles tests. They are failing on the Mac build. * Fix expectations to check all circles. * Changing case on a case-insensitive file system Step 1: remove the old file names * Changing case on a case-insensitive file system Step 2: add them back with the new names * Fix cmpAccum function to be strictly weak ordered. * Add tests for many small circles. * imgproc(perf): fix HoughCircles tests * imgproc(houghCircles): refactor code - simplify NZPointList - drop broken (de-synchronization of 'current'/'mi' fields) NZPointSet iterator - NZPointSet iterator is replaced to direct area scan - use SIMD intrinsics - avoid std exceptions (build for embedded systems)pull/10463/head
Tom Becker
7 years ago
committed by
Alexander Alekhin
parent
d9c0231475
commit
592f8d8c1b
4 changed files with 681 additions and 281 deletions
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#include "perf_precomp.hpp" |
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#include "opencv2/imgproc.hpp" |
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#include "opencv2/imgproc/types_c.h" |
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using namespace std; |
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using namespace cv; |
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using namespace perf; |
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PERF_TEST(PerfHoughCircles, Basic) |
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{ |
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string filename = getDataPath("cv/imgproc/stuff.jpg"); |
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const double dp = 1.0; |
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double minDist = 20; |
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double edgeThreshold = 20; |
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double accumThreshold = 30; |
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int minRadius = 20; |
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int maxRadius = 200; |
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Mat img = imread(filename, IMREAD_GRAYSCALE); |
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ASSERT_FALSE(img.empty()) << "Unable to load source image " << filename; |
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GaussianBlur(img, img, Size(9, 9), 2, 2); |
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vector<Vec3f> circles; |
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declare.in(img); |
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TEST_CYCLE() |
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{ |
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HoughCircles(img, circles, CV_HOUGH_GRADIENT, dp, minDist, edgeThreshold, accumThreshold, minRadius, maxRadius); |
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} |
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SANITY_CHECK_NOTHING(); |
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} |
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PERF_TEST(PerfHoughCircles2, ManySmallCircles) |
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{ |
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string filename = getDataPath("cv/imgproc/beads.jpg"); |
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const double dp = 1.0; |
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double minDist = 10; |
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double edgeThreshold = 90; |
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double accumThreshold = 11; |
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int minRadius = 7; |
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int maxRadius = 18; |
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Mat img = imread(filename, IMREAD_GRAYSCALE); |
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ASSERT_FALSE(img.empty()) << "Unable to load source image " << filename; |
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vector<Vec3f> circles; |
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declare.in(img); |
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TEST_CYCLE() |
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{ |
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HoughCircles(img, circles, CV_HOUGH_GRADIENT, dp, minDist, edgeThreshold, accumThreshold, minRadius, maxRadius); |
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} |
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SANITY_CHECK_NOTHING(); |
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} |
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/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
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// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
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// Copyright (C) 2014, Itseez, Inc, all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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//
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// * The name of the copyright holders may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// indirect, incidental, special, exemplary, or consequential damages
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// (including, but not limited to, procurement of substitute goods or services;
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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#include "test_precomp.hpp" |
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#ifndef DEBUG_IMAGES |
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#define DEBUG_IMAGES 0 |
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#endif |
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using namespace cv; |
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using namespace std; |
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static string getTestCaseName(const string& picture_name, double minDist, double edgeThreshold, double accumThreshold, int minRadius, int maxRadius) |
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{ |
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string results_name = format("circles_%s_%.0f_%.0f_%.0f_%d_%d", |
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picture_name.c_str(), minDist, edgeThreshold, accumThreshold, minRadius, maxRadius); |
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string temp(results_name); |
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size_t pos = temp.find_first_of("\\/."); |
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while (pos != string::npos) { |
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temp.replace(pos, 1, "_"); |
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pos = temp.find_first_of("\\/."); |
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} |
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return temp; |
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} |
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#if DEBUG_IMAGES |
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static void highlightCircles(const string& imagePath, const vector<Vec3f>& circles, const string& outputImagePath) |
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{ |
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Mat imgDebug = imread(imagePath, IMREAD_COLOR); |
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const Scalar yellow(0, 255, 255); |
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for (vector<Vec3f>::const_iterator iter = circles.begin(); iter != circles.end(); ++iter) |
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{ |
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const Vec3f& circle = *iter; |
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float x = circle[0]; |
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float y = circle[1]; |
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float r = max(circle[2], 2.0f); |
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cv::circle(imgDebug, Point(int(x), int(y)), int(r), yellow); |
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} |
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imwrite(outputImagePath, imgDebug); |
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} |
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#endif |
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typedef std::tr1::tuple<string, double, double, double, int, int> Image_MinDist_EdgeThreshold_AccumThreshold_MinRadius_MaxRadius_t; |
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class HoughCirclesTestFixture : public testing::TestWithParam<Image_MinDist_EdgeThreshold_AccumThreshold_MinRadius_MaxRadius_t> |
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{ |
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string picture_name; |
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double minDist; |
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double edgeThreshold; |
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double accumThreshold; |
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int minRadius; |
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int maxRadius; |
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public: |
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HoughCirclesTestFixture() |
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{ |
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picture_name = std::tr1::get<0>(GetParam()); |
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minDist = std::tr1::get<1>(GetParam()); |
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edgeThreshold = std::tr1::get<2>(GetParam()); |
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accumThreshold = std::tr1::get<3>(GetParam()); |
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minRadius = std::tr1::get<4>(GetParam()); |
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maxRadius = std::tr1::get<5>(GetParam()); |
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} |
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HoughCirclesTestFixture(const string& picture, double minD, double edge, double accum, int minR, int maxR) : |
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picture_name(picture), minDist(minD), edgeThreshold(edge), accumThreshold(accum), minRadius(minR), maxRadius(maxR) |
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{ |
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} |
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void run_test() |
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{ |
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string test_case_name = getTestCaseName(picture_name, minDist, edgeThreshold, accumThreshold, minRadius, maxRadius); |
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string filename = cvtest::TS::ptr()->get_data_path() + picture_name; |
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Mat src = imread(filename, IMREAD_GRAYSCALE); |
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EXPECT_FALSE(src.empty()) << "Invalid test image: " << filename; |
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GaussianBlur(src, src, Size(9, 9), 2, 2); |
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vector<Vec3f> circles; |
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const double dp = 1.0; |
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HoughCircles(src, circles, CV_HOUGH_GRADIENT, dp, minDist, edgeThreshold, accumThreshold, minRadius, maxRadius); |
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string imgProc = string(cvtest::TS::ptr()->get_data_path()) + "imgproc/"; |
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#if DEBUG_IMAGES |
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highlightCircles(filename, circles, imgProc + test_case_name + ".png"); |
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#endif |
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string xml = imgProc + "HoughCircles.xml"; |
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FileStorage fs(xml, FileStorage::READ); |
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FileNode node = fs[test_case_name]; |
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if (node.empty()) |
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{ |
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fs.release(); |
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fs.open(xml, FileStorage::APPEND); |
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EXPECT_TRUE(fs.isOpened()) << "Cannot open sanity data file: " << xml; |
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fs << test_case_name << circles; |
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fs.release(); |
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fs.open(xml, FileStorage::READ); |
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EXPECT_TRUE(fs.isOpened()) << "Cannot open sanity data file: " << xml; |
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} |
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vector<Vec3f> exp_circles; |
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read(fs[test_case_name], exp_circles, vector<Vec3f>()); |
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fs.release(); |
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EXPECT_EQ(exp_circles.size(), circles.size()); |
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} |
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}; |
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TEST_P(HoughCirclesTestFixture, regression) |
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{ |
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run_test(); |
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} |
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INSTANTIATE_TEST_CASE_P(ImgProc, HoughCirclesTestFixture, testing::Combine( |
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// picture_name:
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testing::Values("imgproc/stuff.jpg"), |
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// minDist:
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testing::Values(20), |
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// edgeThreshold:
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testing::Values(20), |
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// accumThreshold:
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testing::Values(30), |
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// minRadius:
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testing::Values(20), |
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// maxRadius:
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testing::Values(200) |
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)); |
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TEST(HoughCirclesTest, DefaultMaxRadius) |
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{ |
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string picture_name = "imgproc/stuff.jpg"; |
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const double dp = 1.0; |
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double minDist = 20; |
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double edgeThreshold = 20; |
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double accumThreshold = 30; |
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int minRadius = 20; |
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int maxRadius = 0; |
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string filename = cvtest::TS::ptr()->get_data_path() + picture_name; |
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Mat src = imread(filename, IMREAD_GRAYSCALE); |
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EXPECT_FALSE(src.empty()) << "Invalid test image: " << filename; |
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GaussianBlur(src, src, Size(9, 9), 2, 2); |
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vector<Vec3f> circles; |
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HoughCircles(src, circles, CV_HOUGH_GRADIENT, dp, minDist, edgeThreshold, accumThreshold, minRadius, maxRadius); |
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#if DEBUG_IMAGES |
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string imgProc = string(cvtest::TS::ptr()->get_data_path()) + "imgproc/"; |
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highlightCircles(filename, circles, imgProc + "HoughCirclesTest_DefaultMaxRadius.png"); |
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#endif |
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int maxDimension = std::max(src.rows, src.cols); |
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EXPECT_GT(circles.size(), size_t(0)) << "Should find at least some circles"; |
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for (size_t i = 0; i < circles.size(); ++i) |
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{ |
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EXPECT_GE(circles[i][2], minRadius) << "Radius should be >= minRadius"; |
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EXPECT_LE(circles[i][2], maxDimension) << "Radius should be <= max image dimension"; |
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} |
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} |
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TEST(HoughCirclesTest, CentersOnly) |
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{ |
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string picture_name = "imgproc/stuff.jpg"; |
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const double dp = 1.0; |
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double minDist = 20; |
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double edgeThreshold = 20; |
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double accumThreshold = 30; |
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int minRadius = 20; |
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int maxRadius = -1; |
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string filename = cvtest::TS::ptr()->get_data_path() + picture_name; |
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Mat src = imread(filename, IMREAD_GRAYSCALE); |
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EXPECT_FALSE(src.empty()) << "Invalid test image: " << filename; |
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GaussianBlur(src, src, Size(9, 9), 2, 2); |
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vector<Vec3f> circles; |
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HoughCircles(src, circles, CV_HOUGH_GRADIENT, dp, minDist, edgeThreshold, accumThreshold, minRadius, maxRadius); |
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#if DEBUG_IMAGES |
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string imgProc = string(cvtest::TS::ptr()->get_data_path()) + "imgproc/"; |
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highlightCircles(filename, circles, imgProc + "HoughCirclesTest_CentersOnly.png"); |
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#endif |
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EXPECT_GT(circles.size(), size_t(0)) << "Should find at least some circles"; |
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for (size_t i = 0; i < circles.size(); ++i) |
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{ |
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EXPECT_EQ(circles[i][2], 0.0f) << "Did not ask for radius"; |
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} |
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} |
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TEST(HoughCirclesTest, ManySmallCircles) |
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{ |
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string picture_name = "imgproc/beads.jpg"; |
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const double dp = 1.0; |
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double minDist = 10; |
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double edgeThreshold = 90; |
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double accumThreshold = 11; |
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int minRadius = 7; |
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int maxRadius = 18; |
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string filename = cvtest::TS::ptr()->get_data_path() + picture_name; |
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Mat src = imread(filename, IMREAD_GRAYSCALE); |
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EXPECT_FALSE(src.empty()) << "Invalid test image: " << filename; |
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vector<Vec3f> circles; |
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HoughCircles(src, circles, CV_HOUGH_GRADIENT, dp, minDist, edgeThreshold, accumThreshold, minRadius, maxRadius); |
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#if DEBUG_IMAGES |
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string imgProc = string(cvtest::TS::ptr()->get_data_path()) + "imgproc/"; |
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string test_case_name = getTestCaseName(picture_name, minDist, edgeThreshold, accumThreshold, minRadius, maxRadius); |
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highlightCircles(filename, circles, imgProc + test_case_name + ".png"); |
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#endif |
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EXPECT_GT(circles.size(), size_t(3000)) << "Should find a lot of circles"; |
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} |
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