/*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 #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& 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& 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& calc, const vector& 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(1,model_path_cat) ); vector 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 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 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(); }