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465 lines
15 KiB
465 lines
15 KiB
/*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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// Intel License Agreement |
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// For Open Source Computer Vision Library |
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// |
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// Copyright (C) 2000, Intel Corporation, 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 Intel Corporation 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/imgproc/imgproc.hpp" |
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using namespace cv; |
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using namespace std; |
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//#define GET_STAT |
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#define DIST_E "distE" |
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#define S_E "sE" |
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#define NO_PAIR_E "noPairE" |
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//#define TOTAL_NO_PAIR_E "totalNoPairE" |
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#define DETECTOR_NAMES "detector_names" |
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#define DETECTORS "detectors" |
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#define IMAGE_FILENAMES "image_filenames" |
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#define VALIDATION "validation" |
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#define FILENAME "fn" |
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#define C_SCALE_CASCADE "scale_cascade" |
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class CV_DetectorTest : public cvtest::BaseTest |
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{ |
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public: |
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CV_DetectorTest(); |
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protected: |
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virtual int prepareData( FileStorage& fs ); |
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virtual void run( int startFrom ); |
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virtual string& getValidationFilename(); |
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virtual void readDetector( const FileNode& fn ) = 0; |
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virtual void writeDetector( FileStorage& fs, int di ) = 0; |
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int runTestCase( int detectorIdx, vector<vector<Rect> >& objects ); |
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virtual int detectMultiScale( int di, const Mat& img, vector<Rect>& objects ) = 0; |
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int validate( int detectorIdx, vector<vector<Rect> >& objects ); |
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struct |
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{ |
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float dist; |
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float s; |
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float noPair; |
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//float totalNoPair; |
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} eps; |
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vector<string> detectorNames; |
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vector<string> detectorFilenames; |
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vector<string> imageFilenames; |
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vector<Mat> images; |
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string validationFilename; |
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FileStorage validationFS; |
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}; |
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CV_DetectorTest::CV_DetectorTest() |
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{ |
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} |
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string& CV_DetectorTest::getValidationFilename() |
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{ |
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return validationFilename; |
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} |
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int CV_DetectorTest::prepareData( FileStorage& _fs ) |
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{ |
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if( !_fs.isOpened() ) |
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test_case_count = -1; |
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else |
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{ |
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FileNode fn = _fs.getFirstTopLevelNode(); |
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fn[DIST_E] >> eps.dist; |
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fn[S_E] >> eps.s; |
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fn[NO_PAIR_E] >> eps.noPair; |
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// fn[TOTAL_NO_PAIR_E] >> eps.totalNoPair; |
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// read detectors |
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if( fn[DETECTOR_NAMES].node->data.seq != 0 ) |
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{ |
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FileNodeIterator it = fn[DETECTOR_NAMES].begin(); |
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for( ; it != fn[DETECTOR_NAMES].end(); ) |
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{ |
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string _name; |
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it >> _name; |
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detectorNames.push_back(_name); |
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readDetector(fn[DETECTORS][_name]); |
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} |
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} |
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test_case_count = (int)detectorNames.size(); |
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// read images filenames and images |
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string dataPath = ts->get_data_path(); |
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if( fn[IMAGE_FILENAMES].node->data.seq != 0 ) |
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{ |
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for( FileNodeIterator it = fn[IMAGE_FILENAMES].begin(); it != fn[IMAGE_FILENAMES].end(); ) |
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{ |
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string filename; |
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it >> filename; |
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imageFilenames.push_back(filename); |
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Mat img = imread( dataPath+filename, 1 ); |
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images.push_back( img ); |
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} |
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} |
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} |
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return cvtest::TS::OK; |
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} |
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void CV_DetectorTest::run( int ) |
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{ |
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string dataPath = ts->get_data_path(); |
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validationFS.open( dataPath + getValidationFilename(), FileStorage::READ ); |
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int code = prepareData( validationFS ); |
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if( code < 0 ) |
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{ |
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ts->set_failed_test_info( code ); |
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return; |
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} |
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#ifdef GET_STAT |
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validationFS.release(); |
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string filename = ts->get_data_path(); |
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filename += getValidationFilename(); |
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validationFS.open( filename, FileStorage::WRITE ); |
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validationFS << FileStorage::getDefaultObjectName(validationFilename) << "{"; |
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validationFS << DIST_E << eps.dist; |
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validationFS << S_E << eps.s; |
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validationFS << NO_PAIR_E << eps.noPair; |
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// validationFS << TOTAL_NO_PAIR_E << eps.totalNoPair; |
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// write detector names |
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validationFS << DETECTOR_NAMES << "["; |
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vector<string>::const_iterator nit = detectorNames.begin(); |
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for( ; nit != detectorNames.end(); ++nit ) |
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{ |
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validationFS << *nit; |
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} |
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validationFS << "]"; // DETECTOR_NAMES |
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// write detectors |
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validationFS << DETECTORS << "{"; |
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assert( detectorNames.size() == detectorFilenames.size() ); |
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nit = detectorNames.begin(); |
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for( int di = 0; di < detectorNames.size(), nit != detectorNames.end(); ++nit, di++ ) |
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{ |
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validationFS << *nit << "{"; |
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writeDetector( validationFS, di ); |
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validationFS << "}"; |
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} |
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validationFS << "}"; |
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// write image filenames |
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validationFS << IMAGE_FILENAMES << "["; |
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vector<string>::const_iterator it = imageFilenames.begin(); |
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for( int ii = 0; it != imageFilenames.end(); ++it, ii++ ) |
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{ |
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char buf[10]; |
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sprintf( buf, "%s%d", "img_", ii ); |
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cvWriteComment( validationFS.fs, buf, 0 ); |
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validationFS << *it; |
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} |
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validationFS << "]"; // IMAGE_FILENAMES |
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validationFS << VALIDATION << "{"; |
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#endif |
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int progress = 0; |
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for( int di = 0; di < test_case_count; di++ ) |
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{ |
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progress = update_progress( progress, di, test_case_count, 0 ); |
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#ifdef GET_STAT |
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validationFS << detectorNames[di] << "{"; |
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#endif |
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vector<vector<Rect> > objects; |
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int temp_code = runTestCase( di, objects ); |
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#ifndef GET_STAT |
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if (temp_code == cvtest::TS::OK) |
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temp_code = validate( di, objects ); |
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#endif |
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if (temp_code != cvtest::TS::OK) |
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code = temp_code; |
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#ifdef GET_STAT |
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validationFS << "}"; // detectorNames[di] |
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#endif |
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} |
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#ifdef GET_STAT |
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validationFS << "}"; // VALIDATION |
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validationFS << "}"; // getDefaultObjectName |
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#endif |
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if ( test_case_count <= 0 || imageFilenames.size() <= 0 ) |
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{ |
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ts->printf( cvtest::TS::LOG, "validation file is not determined or not correct" ); |
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code = cvtest::TS::FAIL_INVALID_TEST_DATA; |
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} |
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ts->set_failed_test_info( code ); |
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} |
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int CV_DetectorTest::runTestCase( int detectorIdx, vector<vector<Rect> >& objects ) |
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{ |
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string dataPath = ts->get_data_path(), detectorFilename; |
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if( !detectorFilenames[detectorIdx].empty() ) |
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detectorFilename = dataPath + detectorFilenames[detectorIdx]; |
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for( int ii = 0; ii < (int)imageFilenames.size(); ++ii ) |
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{ |
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vector<Rect> imgObjects; |
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Mat image = images[ii]; |
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if( image.empty() ) |
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{ |
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char msg[30]; |
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sprintf( msg, "%s %d %s", "image ", ii, " can not be read" ); |
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ts->printf( cvtest::TS::LOG, msg ); |
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return cvtest::TS::FAIL_INVALID_TEST_DATA; |
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} |
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int code = detectMultiScale( detectorIdx, image, imgObjects ); |
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if( code != cvtest::TS::OK ) |
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return code; |
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objects.push_back( imgObjects ); |
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#ifdef GET_STAT |
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char buf[10]; |
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sprintf( buf, "%s%d", "img_", ii ); |
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string imageIdxStr = buf; |
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validationFS << imageIdxStr << "[:"; |
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for( vector<Rect>::const_iterator it = imgObjects.begin(); |
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it != imgObjects.end(); ++it ) |
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{ |
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validationFS << it->x << it->y << it->width << it->height; |
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} |
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validationFS << "]"; // imageIdxStr |
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#endif |
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} |
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return cvtest::TS::OK; |
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} |
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bool isZero( uchar i ) {return i == 0;} |
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int CV_DetectorTest::validate( int detectorIdx, vector<vector<Rect> >& objects ) |
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{ |
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assert( imageFilenames.size() == objects.size() ); |
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int imageIdx = 0; |
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int totalNoPair = 0, totalValRectCount = 0; |
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for( vector<vector<Rect> >::const_iterator it = objects.begin(); |
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it != objects.end(); ++it, imageIdx++ ) // for image |
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{ |
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Size imgSize = images[imageIdx].size(); |
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float dist = min(imgSize.height, imgSize.width) * eps.dist; |
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float wDiff = imgSize.width * eps.s; |
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float hDiff = imgSize.height * eps.s; |
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int noPair = 0; |
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// read validation rectangles |
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char buf[10]; |
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sprintf( buf, "%s%d", "img_", imageIdx ); |
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string imageIdxStr = buf; |
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FileNode node = validationFS.getFirstTopLevelNode()[VALIDATION][detectorNames[detectorIdx]][imageIdxStr]; |
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vector<Rect> valRects; |
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if( node.node->data.seq != 0 ) |
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{ |
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for( FileNodeIterator it2 = node.begin(); it2 != node.end(); ) |
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{ |
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Rect r; |
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it2 >> r.x >> r.y >> r.width >> r.height; |
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valRects.push_back(r); |
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} |
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} |
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totalValRectCount += (int)valRects.size(); |
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// compare rectangles |
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vector<uchar> map(valRects.size(), 0); |
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for( vector<Rect>::const_iterator cr = it->begin(); |
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cr != it->end(); ++cr ) |
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{ |
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// find nearest rectangle |
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Point2f cp1 = Point2f( cr->x + (float)cr->width/2.0f, cr->y + (float)cr->height/2.0f ); |
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int minIdx = -1, vi = 0; |
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float minDist = (float)norm( Point(imgSize.width, imgSize.height) ); |
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for( vector<Rect>::const_iterator vr = valRects.begin(); |
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vr != valRects.end(); ++vr, vi++ ) |
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{ |
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Point2f cp2 = Point2f( vr->x + (float)vr->width/2.0f, vr->y + (float)vr->height/2.0f ); |
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float curDist = (float)norm(cp1-cp2); |
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if( curDist < minDist ) |
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{ |
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minIdx = vi; |
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minDist = curDist; |
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} |
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} |
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if( minIdx == -1 ) |
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{ |
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noPair++; |
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} |
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else |
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{ |
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Rect vr = valRects[minIdx]; |
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if( map[minIdx] != 0 || (minDist > dist) || (abs(cr->width - vr.width) > wDiff) || |
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(abs(cr->height - vr.height) > hDiff) ) |
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noPair++; |
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else |
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map[minIdx] = 1; |
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} |
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} |
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noPair += (int)count_if( map.begin(), map.end(), isZero ); |
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totalNoPair += noPair; |
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if( noPair > cvRound(valRects.size()*eps.noPair)+1 ) |
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break; |
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} |
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if( imageIdx < (int)imageFilenames.size() ) |
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{ |
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char msg[500]; |
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sprintf( msg, "detector %s has overrated count of rectangles without pair on %s-image\n", |
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detectorNames[detectorIdx].c_str(), imageFilenames[imageIdx].c_str() ); |
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ts->printf( cvtest::TS::LOG, msg ); |
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return cvtest::TS::FAIL_BAD_ACCURACY; |
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} |
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if ( totalNoPair > cvRound(totalValRectCount*eps./*total*/noPair)+1 ) |
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{ |
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ts->printf( cvtest::TS::LOG, "overrated count of rectangles without pair on all images set" ); |
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return cvtest::TS::FAIL_BAD_ACCURACY; |
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} |
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return cvtest::TS::OK; |
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} |
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//----------------------------------------------- CascadeDetectorTest ----------------------------------- |
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class CV_CascadeDetectorTest : public CV_DetectorTest |
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{ |
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public: |
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CV_CascadeDetectorTest(); |
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protected: |
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virtual void readDetector( const FileNode& fn ); |
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virtual void writeDetector( FileStorage& fs, int di ); |
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virtual int detectMultiScale( int di, const Mat& img, vector<Rect>& objects ); |
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vector<int> flags; |
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}; |
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CV_CascadeDetectorTest::CV_CascadeDetectorTest() |
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{ |
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validationFilename = "cascadeandhog/cascade.xml"; |
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} |
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void CV_CascadeDetectorTest::readDetector( const FileNode& fn ) |
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{ |
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string filename; |
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int flag; |
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fn[FILENAME] >> filename; |
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detectorFilenames.push_back(filename); |
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fn[C_SCALE_CASCADE] >> flag; |
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if( flag ) |
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flags.push_back( 0 ); |
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else |
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flags.push_back( CV_HAAR_SCALE_IMAGE ); |
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} |
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void CV_CascadeDetectorTest::writeDetector( FileStorage& fs, int di ) |
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{ |
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int sc = flags[di] & CV_HAAR_SCALE_IMAGE ? 0 : 1; |
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fs << FILENAME << detectorFilenames[di]; |
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fs << C_SCALE_CASCADE << sc; |
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} |
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int CV_CascadeDetectorTest::detectMultiScale( int di, const Mat& img, |
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vector<Rect>& objects) |
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{ |
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string dataPath = ts->get_data_path(), filename; |
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filename = dataPath + detectorFilenames[di]; |
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CascadeClassifier cascade( filename ); |
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if( cascade.empty() ) |
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{ |
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ts->printf( cvtest::TS::LOG, "cascade %s can not be opened"); |
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return cvtest::TS::FAIL_INVALID_TEST_DATA; |
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} |
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Mat grayImg; |
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cvtColor( img, grayImg, CV_BGR2GRAY ); |
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equalizeHist( grayImg, grayImg ); |
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cascade.detectMultiScale( grayImg, objects, 1.1, 3, flags[di] ); |
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return cvtest::TS::OK; |
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} |
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//----------------------------------------------- HOGDetectorTest ----------------------------------- |
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class CV_HOGDetectorTest : public CV_DetectorTest |
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{ |
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public: |
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CV_HOGDetectorTest(); |
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protected: |
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virtual void readDetector( const FileNode& fn ); |
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virtual void writeDetector( FileStorage& fs, int di ); |
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virtual int detectMultiScale( int di, const Mat& img, vector<Rect>& objects ); |
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}; |
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CV_HOGDetectorTest::CV_HOGDetectorTest() |
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{ |
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validationFilename = "cascadeandhog/hog.xml"; |
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} |
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void CV_HOGDetectorTest::readDetector( const FileNode& fn ) |
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{ |
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string filename; |
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if( fn[FILENAME].node->data.seq != 0 ) |
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fn[FILENAME] >> filename; |
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detectorFilenames.push_back( filename); |
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} |
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void CV_HOGDetectorTest::writeDetector( FileStorage& fs, int di ) |
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{ |
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fs << FILENAME << detectorFilenames[di]; |
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} |
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int CV_HOGDetectorTest::detectMultiScale( int di, const Mat& img, |
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vector<Rect>& objects) |
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{ |
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HOGDescriptor hog; |
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if( detectorFilenames[di].empty() ) |
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hog.setSVMDetector(HOGDescriptor::getDefaultPeopleDetector()); |
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else |
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assert(0); |
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hog.detectMultiScale(img, objects); |
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return cvtest::TS::OK; |
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} |
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TEST(Objdetect_CascadeDetector, regression) { CV_CascadeDetectorTest test; test.safe_run(); } |
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TEST(Objdetect_HOGDetector, regression) { CV_HOGDetectorTest test; test.safe_run(); }
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