mirror of https://github.com/opencv/opencv.git
cbalint13
10 years ago
parent
b639353193
commit
26997f32c6
10 changed files with 17378 additions and 21 deletions
@ -0,0 +1,40 @@ |
||||
#include "perf_precomp.hpp" |
||||
|
||||
using namespace std; |
||||
using namespace cv; |
||||
using namespace perf; |
||||
using std::tr1::make_tuple; |
||||
using std::tr1::get; |
||||
|
||||
CV_ENUM(AgastType, AgastFeatureDetector::AGAST_5_8, AgastFeatureDetector::AGAST_7_12d, |
||||
AgastFeatureDetector::AGAST_7_12s, AgastFeatureDetector::OAST_9_16) |
||||
|
||||
typedef std::tr1::tuple<string, AgastType> File_Type_t; |
||||
typedef perf::TestBaseWithParam<File_Type_t> agast; |
||||
|
||||
#define AGAST_IMAGES \ |
||||
"cv/detectors_descriptors_evaluation/images_datasets/leuven/img1.png",\
|
||||
"stitching/a3.png" |
||||
|
||||
PERF_TEST_P(agast, detect, testing::Combine( |
||||
testing::Values(AGAST_IMAGES), |
||||
AgastType::all() |
||||
)) |
||||
{ |
||||
string filename = getDataPath(get<0>(GetParam())); |
||||
int type = get<1>(GetParam()); |
||||
Mat frame = imread(filename, IMREAD_GRAYSCALE); |
||||
|
||||
if (frame.empty()) |
||||
FAIL() << "Unable to load source image " << filename; |
||||
|
||||
declare.in(frame); |
||||
|
||||
Ptr<FeatureDetector> fd = AgastFeatureDetector::create(20, true, type); |
||||
ASSERT_FALSE( fd.empty() ); |
||||
vector<KeyPoint> points; |
||||
|
||||
TEST_CYCLE() fd->detect(frame, points); |
||||
|
||||
SANITY_CHECK_KEYPOINTS(points); |
||||
} |
||||
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
@ -0,0 +1,62 @@ |
||||
/* This is AGAST and OAST, an optimal and accelerated corner detector
|
||||
based on the accelerated segment tests |
||||
Below is the original copyright and the references */ |
||||
|
||||
/*
|
||||
Copyright (C) 2010 Elmar Mair |
||||
All rights reserved. |
||||
|
||||
Redistribution and use in source and binary forms, with or without |
||||
modification, are permitted provided that the following conditions |
||||
are met: |
||||
|
||||
*Redistributions of source code must retain the above copyright |
||||
notice, this list of conditions and the following disclaimer. |
||||
|
||||
*Redistributions 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. |
||||
|
||||
*Neither the name of the University of Cambridge nor the names of |
||||
its contributors may 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 COPYRIGHT OWNER 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, OR TORT (INCLUDING |
||||
NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS |
||||
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. |
||||
*/ |
||||
|
||||
/*
|
||||
The references are: |
||||
* Adaptive and Generic Corner Detection Based on the Accelerated Segment Test, |
||||
Elmar Mair and Gregory D. Hager and Darius Burschka |
||||
and Michael Suppa and Gerhard Hirzinger ECCV 2010 |
||||
URL: http://www6.in.tum.de/Main/ResearchAgast
|
||||
*/ |
||||
|
||||
|
||||
#ifndef __OPENCV_FEATURES_2D_AGAST_HPP__ |
||||
#define __OPENCV_FEATURES_2D_AGAST_HPP__ |
||||
|
||||
#ifdef __cplusplus |
||||
|
||||
#include "precomp.hpp" |
||||
namespace cv |
||||
{ |
||||
|
||||
void makeAgastOffsets(int pixel[16], int row_stride, int type); |
||||
|
||||
template<int type> |
||||
int agast_cornerScore(const uchar* ptr, const int pixel[], int threshold); |
||||
|
||||
} |
||||
#endif |
||||
#endif |
||||
@ -0,0 +1,137 @@ |
||||
/*M///////////////////////////////////////////////////////////////////////////////////////
|
||||
//
|
||||
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
|
||||
//
|
||||
// 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,
|
||||
// or tort (including negligence or otherwise) arising in any way out of
|
||||
// the use of this software, even if advised of the possibility of such damage.
|
||||
//
|
||||
//M*/
|
||||
|
||||
#include "test_precomp.hpp" |
||||
|
||||
using namespace std; |
||||
using namespace cv; |
||||
|
||||
class CV_AgastTest : public cvtest::BaseTest |
||||
{ |
||||
public: |
||||
CV_AgastTest(); |
||||
~CV_AgastTest(); |
||||
protected: |
||||
void run(int); |
||||
}; |
||||
|
||||
CV_AgastTest::CV_AgastTest() {} |
||||
CV_AgastTest::~CV_AgastTest() {} |
||||
|
||||
void CV_AgastTest::run( int ) |
||||
{ |
||||
for(int type=0; type <= 2; ++type) { |
||||
Mat image1 = imread(string(ts->get_data_path()) + "inpaint/orig.png"); |
||||
Mat image2 = imread(string(ts->get_data_path()) + "cameracalibration/chess9.png"); |
||||
string xml = string(ts->get_data_path()) + format("agast/result%d.xml", type); |
||||
|
||||
if (image1.empty() || image2.empty()) |
||||
{ |
||||
ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_TEST_DATA ); |
||||
return; |
||||
} |
||||
|
||||
Mat gray1, gray2; |
||||
cvtColor(image1, gray1, COLOR_BGR2GRAY); |
||||
cvtColor(image2, gray2, COLOR_BGR2GRAY); |
||||
|
||||
vector<KeyPoint> keypoints1; |
||||
vector<KeyPoint> keypoints2; |
||||
AGAST(gray1, keypoints1, 30, true, type); |
||||
AGAST(gray2, keypoints2, (type > 0 ? 30 : 20), true, type); |
||||
|
||||
for(size_t i = 0; i < keypoints1.size(); ++i) |
||||
{ |
||||
const KeyPoint& kp = keypoints1[i]; |
||||
cv::circle(image1, kp.pt, cvRound(kp.size/2), Scalar(255, 0, 0)); |
||||
} |
||||
|
||||
for(size_t i = 0; i < keypoints2.size(); ++i) |
||||
{ |
||||
const KeyPoint& kp = keypoints2[i]; |
||||
cv::circle(image2, kp.pt, cvRound(kp.size/2), Scalar(255, 0, 0)); |
||||
} |
||||
|
||||
Mat kps1(1, (int)(keypoints1.size() * sizeof(KeyPoint)), CV_8U, &keypoints1[0]); |
||||
Mat kps2(1, (int)(keypoints2.size() * sizeof(KeyPoint)), CV_8U, &keypoints2[0]); |
||||
|
||||
FileStorage fs(xml, FileStorage::READ); |
||||
if (!fs.isOpened()) |
||||
{ |
||||
fs.open(xml, FileStorage::WRITE); |
||||
if (!fs.isOpened()) |
||||
{ |
||||
ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_TEST_DATA); |
||||
return; |
||||
} |
||||
fs << "exp_kps1" << kps1; |
||||
fs << "exp_kps2" << kps2; |
||||
fs.release(); |
||||
fs.open(xml, FileStorage::READ); |
||||
if (!fs.isOpened()) |
||||
{ |
||||
ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_TEST_DATA); |
||||
return; |
||||
} |
||||
} |
||||
|
||||
Mat exp_kps1, exp_kps2; |
||||
read( fs["exp_kps1"], exp_kps1, Mat() ); |
||||
read( fs["exp_kps2"], exp_kps2, Mat() ); |
||||
fs.release(); |
||||
|
||||
if ( exp_kps1.size != kps1.size || 0 != cvtest::norm(exp_kps1, kps1, NORM_L2) || |
||||
exp_kps2.size != kps2.size || 0 != cvtest::norm(exp_kps2, kps2, NORM_L2)) |
||||
{ |
||||
ts->set_failed_test_info(cvtest::TS::FAIL_MISMATCH); |
||||
return; |
||||
} |
||||
|
||||
/*cv::namedWindow("Img1"); cv::imshow("Img1", image1);
|
||||
cv::namedWindow("Img2"); cv::imshow("Img2", image2); |
||||
cv::waitKey(0);*/ |
||||
} |
||||
|
||||
ts->set_failed_test_info(cvtest::TS::OK); |
||||
} |
||||
|
||||
TEST(Features2d_AGAST, regression) { CV_AgastTest test; test.safe_run(); } |
||||
Loading…
Reference in new issue