308 lines
11 KiB
C++
308 lines
11 KiB
C++
/*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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// 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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#include "opencv2/objdetect/objdetect_c.h"
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#include <string>
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#ifdef HAVE_TBB
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#include "tbb/task_scheduler_init.h"
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#endif
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using namespace std;
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using namespace cv;
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const int num_detections = 3;
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const float true_scores[3] = {-0.383931f, -0.825876f, -0.959934f};
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const float score_thr = 0.05f;
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const CvRect true_bounding_boxes[3] = {cvRect(0, 45, 362, 452), cvRect(304, 0, 64, 80), cvRect(236, 0, 108, 59)};
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class CV_LatentSVMDetectorTest : public cvtest::BaseTest
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{
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protected:
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void run(int);
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bool isEqual(CvRect r1, CvRect r2, int eps);
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};
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bool CV_LatentSVMDetectorTest::isEqual(CvRect r1, CvRect r2, int eps)
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{
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return (std::abs(r1.x - r2.x) <= eps
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&& std::abs(r1.y - r2.y) <= eps
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&& std::abs(r1.width - r2.width) <= eps
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&& std::abs(r1.height - r2.height) <= eps);
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}
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void CV_LatentSVMDetectorTest::run( int /* start_from */)
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{
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string img_path = string(ts->get_data_path()) + "latentsvmdetector/cat.png";
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string model_path = string(ts->get_data_path()) + "latentsvmdetector/models_VOC2007/cat.xml";
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int numThreads = -1;
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#ifdef HAVE_TBB
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numThreads = 2;
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tbb::task_scheduler_init init(tbb::task_scheduler_init::deferred);
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init.initialize(numThreads);
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#endif
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Mat image2 = cv::imread(img_path.c_str());
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IplImage image = image2;
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if (image2.empty())
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{
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ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_TEST_DATA );
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return;
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}
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CvLatentSvmDetector* detector = cvLoadLatentSvmDetector(model_path.c_str());
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if (!detector)
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{
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ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_TEST_DATA );
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return;
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}
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CvMemStorage* storage = cvCreateMemStorage(0);
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CvSeq* detections = 0;
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detections = cvLatentSvmDetectObjects(&image, detector, storage, 0.5f, numThreads);
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if (detections->total != num_detections)
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{
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ts->set_failed_test_info( cvtest::TS::FAIL_MISMATCH );
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}
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else
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{
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ts->set_failed_test_info(cvtest::TS::OK);
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for (int i = 0; i < detections->total; i++)
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{
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CvObjectDetection detection = *(CvObjectDetection*)cvGetSeqElem( detections, i );
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CvRect bounding_box = detection.rect;
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float score = detection.score;
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if ((!isEqual(bounding_box, true_bounding_boxes[i], 1)) || (fabs(score - true_scores[i]) > score_thr))
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{
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ts->set_failed_test_info( cvtest::TS::FAIL_MISMATCH );
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break;
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}
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}
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}
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#ifdef HAVE_TBB
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init.terminate();
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#endif
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cvReleaseMemStorage( &storage );
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cvReleaseLatentSvmDetector( &detector );
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}
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// Test for c++ version of Latent SVM
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class LatentSVMDetectorTest : public cvtest::BaseTest
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{
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protected:
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void run(int);
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};
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static void writeDetections( FileStorage& fs, const string& nodeName, const vector<LatentSvmDetector::ObjectDetection>& detections )
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{
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fs << nodeName << "[";
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for( size_t i = 0; i < detections.size(); i++ )
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{
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const LatentSvmDetector::ObjectDetection& d = detections[i];
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fs << d.rect.x << d.rect.y << d.rect.width << d.rect.height
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<< d.score << d.classID;
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}
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fs << "]";
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}
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static void readDetections( FileStorage fs, const string& nodeName, vector<LatentSvmDetector::ObjectDetection>& detections )
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{
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detections.clear();
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FileNode fn = fs.root()[nodeName];
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FileNodeIterator fni = fn.begin();
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while( fni != fn.end() )
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{
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LatentSvmDetector::ObjectDetection d;
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fni >> d.rect.x >> d.rect.y >> d.rect.width >> d.rect.height
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>> d.score >> d.classID;
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detections.push_back( d );
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}
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}
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static inline bool isEqual( const LatentSvmDetector::ObjectDetection& d1, const LatentSvmDetector::ObjectDetection& d2, int eps, float threshold)
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{
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return (
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std::abs(d1.rect.x - d2.rect.x) <= eps
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&& std::abs(d1.rect.y - d2.rect.y) <= eps
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&& std::abs(d1.rect.width - d2.rect.width) <= eps
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&& std::abs(d1.rect.height - d2.rect.height) <= eps
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&& (d1.classID == d2.classID)
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&& std::abs(d1.score - d2.score) <= threshold
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);
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}
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std::ostream& operator << (std::ostream& os, const CvRect& r)
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{
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return (os << "[x=" << r.x << ", y=" << r.y << ", w=" << r.width << ", h=" << r.height << "]");
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}
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bool compareResults( const vector<LatentSvmDetector::ObjectDetection>& calc, const vector<LatentSvmDetector::ObjectDetection>& valid, int eps, float threshold)
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{
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if( calc.size() != valid.size() )
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return false;
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for( size_t i = 0; i < calc.size(); i++ )
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{
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const LatentSvmDetector::ObjectDetection& c = calc[i];
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const LatentSvmDetector::ObjectDetection& v = valid[i];
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if( !isEqual(c, v, eps, threshold) )
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{
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std::cerr << "Expected: " << v.rect << " class=" << v.classID << " score=" << v.score << std::endl;
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std::cerr << "Actual: " << c.rect << " class=" << c.classID << " score=" << c.score << std::endl;
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return false;
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}
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}
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return true;
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}
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void LatentSVMDetectorTest::run( int /* start_from */)
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{
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string img_path_cat = string(ts->get_data_path()) + "latentsvmdetector/cat.png";
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string img_path_cars = string(ts->get_data_path()) + "latentsvmdetector/cars.png";
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string model_path_cat = string(ts->get_data_path()) + "latentsvmdetector/models_VOC2007/cat.xml";
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string model_path_car = string(ts->get_data_path()) + "latentsvmdetector/models_VOC2007/car.xml";
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string true_res_path = string(ts->get_data_path()) + "latentsvmdetector/results.xml";
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int numThreads = 1;
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#ifdef HAVE_TBB
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numThreads = 2;
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#endif
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Mat image_cat = imread( img_path_cat );
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Mat image_cars = imread( img_path_cars );
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if( image_cat.empty() || image_cars.empty() )
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{
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ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_TEST_DATA );
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return;
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}
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// We will test 2 cases:
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// detector1 - to test case of one class 'cat'
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// detector12 - to test case of two (several) classes 'cat' and car
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// Load detectors
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LatentSvmDetector detector1( vector<String>(1,model_path_cat) );
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vector<String> models_pathes(2);
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models_pathes[0] = model_path_cat;
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models_pathes[1] = model_path_car;
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LatentSvmDetector detector12( models_pathes );
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if( detector1.empty() || detector12.empty() || detector12.getClassCount() != 2 )
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{
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ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_TEST_DATA );
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return;
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}
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// 1. Test method detect
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// Run detectors
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vector<LatentSvmDetector::ObjectDetection> detections1_cat, detections12_cat, detections12_cars;
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detector1.detect( image_cat, detections1_cat, 0.5, numThreads );
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detector12.detect( image_cat, detections12_cat, 0.5, numThreads );
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detector12.detect( image_cars, detections12_cars, 0.5, numThreads );
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// Load true results
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FileStorage fs( true_res_path, FileStorage::READ );
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if( fs.isOpened() )
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{
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vector<LatentSvmDetector::ObjectDetection> true_detections1_cat, true_detections12_cat, true_detections12_cars;
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readDetections( fs, "detections1_cat", true_detections1_cat );
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readDetections( fs, "detections12_cat", true_detections12_cat );
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readDetections( fs, "detections12_cars", true_detections12_cars );
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if( !compareResults(detections1_cat, true_detections1_cat, 1, score_thr) )
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{
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std::cerr << "Results of detector1 are invalid on image cat.png" << std::endl;
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ts->set_failed_test_info( cvtest::TS::FAIL_MISMATCH );
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}
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if( !compareResults(detections12_cat, true_detections12_cat, 1, score_thr) )
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{
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std::cerr << "Results of detector12 are invalid on image cat.png" << std::endl;
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ts->set_failed_test_info( cvtest::TS::FAIL_MISMATCH );
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}
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if( !compareResults(detections12_cars, true_detections12_cars, 1, score_thr) )
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{
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std::cerr << "Results of detector12 are invalid on image cars.png" << std::endl;
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ts->set_failed_test_info( cvtest::TS::FAIL_MISMATCH );
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}
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}
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else
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{
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fs.open( true_res_path, FileStorage::WRITE );
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if( fs.isOpened() )
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{
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writeDetections( fs, "detections1_cat", detections1_cat );
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writeDetections( fs, "detections12_cat", detections12_cat );
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writeDetections( fs, "detections12_cars", detections12_cars );
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}
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else
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std::cerr << "File " << true_res_path << " cann't be opened to save test results" << std::endl;
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}
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// 2. Simple tests of other methods
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if( detector1.getClassCount() != 1 || detector1.getClassNames()[0] != "cat" )
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{
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std::cerr << "Incorrect result of method getClassNames() or getClassCount()" << std::endl;
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ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT);
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}
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detector1.clear();
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if( !detector1.empty() )
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{
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std::cerr << "There is a bug in method clear() or empty()" << std::endl;
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ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT);
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}
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ts->set_failed_test_info( cvtest::TS::OK);
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}
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TEST(Objdetect_LatentSVMDetector_c, DISABLED_regression) { CV_LatentSVMDetectorTest test; test.safe_run(); }
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TEST(Objdetect_LatentSVMDetector_cpp, DISABLED_regression) { LatentSVMDetectorTest test; test.safe_run(); }
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