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/*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"
#include <string>
#ifdef HAVE_CVCONFIG_H
#include "cvconfig.h"
#endif
#ifdef HAVE_TBB
#include "tbb/task_scheduler_init.h"
#endif
using namespace cv;
const int num_detections = 3;
const float true_scores[3] = {-0.383931f, -0.825876f, -0.959934f};
const float score_thr = 0.05f;
const CvRect true_bounding_boxes[3] = {cvRect(0, 45, 362, 452), cvRect(304, 0, 64, 80), cvRect(236, 0, 108, 59)};
class CV_LatentSVMDetectorTest : public cvtest::BaseTest
{
public:
CV_LatentSVMDetectorTest();
~CV_LatentSVMDetectorTest();
protected:
void run(int);
bool isEqual(CvRect r1, CvRect r2);
};
CV_LatentSVMDetectorTest::CV_LatentSVMDetectorTest()
{
}
CV_LatentSVMDetectorTest::~CV_LatentSVMDetectorTest() {}
bool CV_LatentSVMDetectorTest::isEqual(CvRect r1, CvRect r2)
{
return ((r1.x == r2.x) && (r1.y == r2.y) && (r1.width == r2.width) && (r1.height == r2.height));
}
void CV_LatentSVMDetectorTest::run( int /* start_from */)
{
string img_path = string(ts->get_data_path()) + "latentsvmdetector/cat.jpg";
string model_path = string(ts->get_data_path()) + "latentsvmdetector/models_VOC2007/cat.xml";
int numThreads = -1;
#ifdef HAVE_TBB
numThreads = 2;
tbb::task_scheduler_init init(tbb::task_scheduler_init::deferred);
init.initialize(numThreads);
#endif
IplImage* image = cvLoadImage(img_path.c_str());
if (!image)
{
ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_TEST_DATA );
return;
}
CvLatentSvmDetector* detector = cvLoadLatentSvmDetector(model_path.c_str());
if (!detector)
{
ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_TEST_DATA );
cvReleaseImage(&image);
return;
}
CvMemStorage* storage = cvCreateMemStorage(0);
CvSeq* detections = 0;
detections = cvLatentSvmDetectObjects(image, detector, storage, 0.5f, numThreads);
if (detections->total != num_detections)
{
ts->set_failed_test_info( cvtest::TS::FAIL_MISMATCH );
}
else
{
ts->set_failed_test_info(cvtest::TS::OK);
for (int i = 0; i < detections->total; i++)
{
CvObjectDetection detection = *(CvObjectDetection*)cvGetSeqElem( detections, i );
CvRect bounding_box = detection.rect;
float score = detection.score;
if ((!isEqual(bounding_box, true_bounding_boxes[i])) || (fabs(score - true_scores[i]) > score_thr))
{
ts->set_failed_test_info( cvtest::TS::FAIL_MISMATCH );
break;
}
}
}
#ifdef HAVE_TBB
init.terminate();
#endif
cvReleaseMemStorage( &storage );
cvReleaseLatentSvmDetector( &detector );
cvReleaseImage( &image );
}
// Test for c++ version of Latent SVM
class LatentSVMDetectorTest : public cvtest::BaseTest
{
public:
LatentSVMDetectorTest();
protected:
void run(int);
};
LatentSVMDetectorTest::LatentSVMDetectorTest()
{
}
static void writeDetections( FileStorage& fs, const string& nodeName, const vector<LatentSvmDetector::ObjectDetection>& detections )
{
fs << nodeName << "[";
for( size_t i = 0; i < detections.size(); i++ )
{
const LatentSvmDetector::ObjectDetection& d = detections[i];
fs << d.rect.x << d.rect.y << d.rect.width << d.rect.height
<< d.score << d.classID;
}
fs << "]";
}
static void readDetections( FileStorage fs, const string& nodeName, vector<LatentSvmDetector::ObjectDetection>& detections )
{
detections.clear();
FileNode fn = fs.root()[nodeName];
FileNodeIterator fni = fn.begin();
while( fni != fn.end() )
{
LatentSvmDetector::ObjectDetection d;
fni >> d.rect.x >> d.rect.y >> d.rect.width >> d.rect.height
>> d.score >> d.classID;
detections.push_back( d );
}
}
static inline bool isEqual( const LatentSvmDetector::ObjectDetection& d1, const LatentSvmDetector::ObjectDetection& d2)
{
return ((d1.rect.x == d2.rect.x) && (d1.rect.y == d2.rect.y) && (d1.rect.width == d2.rect.width) && (d1.rect.height == d2.rect.height) &&
(d1.classID == d2.classID) &&
std::abs(d1.score-d2.score) < score_thr );
}
bool compareResults( const vector<LatentSvmDetector::ObjectDetection>& calc, const vector<LatentSvmDetector::ObjectDetection>& valid )
{
if( calc.size() != valid.size() )
return false;
for( size_t i = 0; i < calc.size(); i++ )
{
const LatentSvmDetector::ObjectDetection& c = calc[i];
const LatentSvmDetector::ObjectDetection& v = valid[i];
if( !isEqual(c,v) )
return false;
}
return true;
}
void LatentSVMDetectorTest::run( int /* start_from */)
{
string img_path_cat = string(ts->get_data_path()) + "latentsvmdetector/cat.jpg";
string img_path_cars = string(ts->get_data_path()) + "latentsvmdetector/cars.jpg";
string model_path_cat = string(ts->get_data_path()) + "latentsvmdetector/models_VOC2007/cat.xml";
string model_path_car = string(ts->get_data_path()) + "latentsvmdetector/models_VOC2007/car.xml";
string true_res_path = string(ts->get_data_path()) + "latentsvmdetector/results.xml";
int numThreads = 1;
#ifdef HAVE_TBB
numThreads = 2;
#endif
Mat image_cat = imread( img_path_cat );
Mat image_cars = imread( img_path_cars );
if( image_cat.empty() || image_cars.empty() )
{
ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_TEST_DATA );
return;
}
// We will test 2 cases:
// detector1 - to test case of one class 'cat'
// detector12 - to test case of two (several) classes 'cat' and car
// Load detectors
LatentSvmDetector detector1( vector<string>(1,model_path_cat) );
vector<string> models_pathes(2);
models_pathes[0] = model_path_cat;
models_pathes[1] = model_path_car;
LatentSvmDetector detector12( models_pathes );
if( detector1.empty() || detector12.empty() || detector12.getClassCount() != 2 )
{
ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_TEST_DATA );
return;
}
// 1. Test method detect
// Run detectors
vector<LatentSvmDetector::ObjectDetection> detections1_cat, detections12_cat, detections12_cars;
detector1.detect( image_cat, detections1_cat, 0.5, numThreads );
detector12.detect( image_cat, detections12_cat, 0.5, numThreads );
detector12.detect( image_cars, detections12_cars, 0.5, numThreads );
// Load true results
FileStorage fs( true_res_path, FileStorage::READ );
if( fs.isOpened() )
{
vector<LatentSvmDetector::ObjectDetection> true_detections1_cat, true_detections12_cat, true_detections12_cars;
readDetections( fs, "detections1_cat", true_detections1_cat );
readDetections( fs, "detections12_cat", true_detections12_cat );
readDetections( fs, "detections12_cars", true_detections12_cars );
if( !compareResults(detections1_cat, true_detections1_cat) )
{
std::cerr << "Results of detector1 are invalid on image cat.jpg" << std::endl;
ts->set_failed_test_info( cvtest::TS::FAIL_MISMATCH );
}
if( !compareResults(detections12_cat, true_detections12_cat) )
{
std::cerr << "Results of detector12 are invalid on image cat.jpg" << std::endl;
ts->set_failed_test_info( cvtest::TS::FAIL_MISMATCH );
}
if( !compareResults(detections12_cars, true_detections12_cars) )
{
std::cerr << "Results of detector12 are invalid on image cars.jpg" << std::endl;
ts->set_failed_test_info( cvtest::TS::FAIL_MISMATCH );
}
}
else
{
fs.open( true_res_path, FileStorage::WRITE );
if( fs.isOpened() )
{
writeDetections( fs, "detections1_cat", detections1_cat );
writeDetections( fs, "detections12_cat", detections12_cat );
writeDetections( fs, "detections12_cars", detections12_cars );
}
else
std::cerr << "File " << true_res_path << " cann't be opened to save test results" << std::endl;
}
// 2. Simple tests of other methods
if( detector1.getClassCount() != 1 || detector1.getClassNames()[0] != "cat" )
{
std::cerr << "Incorrect result of method getClassNames() or getClassCount()" << std::endl;
ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT);
}
detector1.clear();
if( !detector1.empty() )
{
std::cerr << "There is a bug in method clear() or empty()" << std::endl;
ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT);
}
ts->set_failed_test_info( cvtest::TS::OK);
}
TEST(Objdetect_LatentSVMDetector_c, regression) { CV_LatentSVMDetectorTest test; test.safe_run(); }
TEST(Objdetect_LatentSVMDetector_cpp, regression) { LatentSVMDetectorTest test; test.safe_run(); }