Visual Servoing Platform  version 3.2.0 under development (2018-12-11)
testImageNormalizedCorrelation.cpp

Test vpImageTools::normalizedCorrelation().

/****************************************************************************
*
* This file is part of the ViSP software.
* Copyright (C) 2005 - 2017 by Inria. All rights reserved.
*
* This software is free software; you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation; either version 2 of the License, or
* (at your option) any later version.
* See the file LICENSE.txt at the root directory of this source
* distribution for additional information about the GNU GPL.
*
* For using ViSP with software that can not be combined with the GNU
* GPL, please contact Inria about acquiring a ViSP Professional
* Edition License.
*
* See http://visp.inria.fr for more information.
*
* This software was developed at:
* Inria Rennes - Bretagne Atlantique
* Campus Universitaire de Beaulieu
* 35042 Rennes Cedex
* France
*
* If you have questions regarding the use of this file, please contact
* Inria at visp@inria.fr
*
* This file is provided AS IS with NO WARRANTY OF ANY KIND, INCLUDING THE
* WARRANTY OF DESIGN, MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE.
*
* Description:
* Test vpImageTools::normalizedCorrelation().
*
*****************************************************************************/
#include <visp3/core/vpImage.h>
#include <visp3/core/vpIoTools.h>
#include <visp3/core/vpImageTools.h>
#include <visp3/io/vpVideoReader.h>
#include <visp3/io/vpParseArgv.h>
#include <visp3/gui/vpDisplayX.h>
#include <visp3/gui/vpDisplayGDI.h>
#include <visp3/gui/vpDisplayOpenCV.h>
// List of allowed command line options
#define GETOPTARGS "cdi:h"
namespace
{
void usage(const char *name, const char *badparam, std::string ipath)
{
fprintf(stdout, "\n\
Test vpImageTools::normalizedCorrelation().\n\
\n\
SYNOPSIS\n\
%s [-i <VISP_IMAGES directory>] \n\
[-h]\n \
", name);
fprintf(stdout, "\n\
OPTIONS: Default\n\
-i <VISP_IMAGES directory> %s\n\
Set VISP_IMAGES input path.\n\
Setting the VISP_INPUT_IMAGE_PATH environment\n\
variable produces the same behaviour than using\n\
this option.\n\
-h\n\
Print the help.\n\n", ipath.c_str());
if (badparam)
fprintf(stdout, "\nERROR: Bad parameter [%s]\n", badparam);
}
bool getOptions(int argc, const char **argv, std::string &ipath)
{
const char *optarg_;
int c;
while ((c = vpParseArgv::parse(argc, argv, GETOPTARGS, &optarg_)) > 1) {
switch (c) {
case 'i':
ipath = optarg_;
break;
case 'h':
usage(argv[0], NULL, ipath);
return false;
break;
case 'c':
case 'd':
break;
default:
usage(argv[0], optarg_, ipath);
return false;
break;
}
}
if ((c == 1) || (c == -1)) {
// standalone param or error
usage(argv[0], NULL, ipath);
std::cerr << "ERROR: " << std::endl;
std::cerr << " Bad argument " << optarg_ << std::endl << std::endl;
return false;
}
return true;
}
void templateMatching(const vpImage<unsigned char> &I, const vpImage<unsigned char> &I_tpl,
vpImage<double> &I_score, const unsigned int step_u,
const unsigned int step_v, const bool useOptimized)
{
unsigned int height_tpl = I_tpl.getHeight(), width_tpl = I_tpl.getWidth();
vpImage<double> I_double, I_tpl_double, I_cur;
vpImageConvert::convert(I_tpl, I_tpl_double);
I_score.resize(I.getHeight() - height_tpl, I.getWidth() - width_tpl, 0.0);
for (unsigned int i = 0; i < I.getHeight()-height_tpl; i += step_v) {
for (unsigned int j = 0; j < I.getWidth()-width_tpl; j += step_u) {
vpRect roi( vpImagePoint(i, j), vpImagePoint(i+height_tpl-1, j+width_tpl-1) );
vpImageTools::crop(I_double, roi, I_cur);
I_score[i][j] = vpImageTools::normalizedCorrelation(I_cur, I_tpl_double, useOptimized);
}
}
}
}
int main(int argc, const char **argv)
{
try {
std::string env_ipath;
std::string opt_ipath;
std::string ipath;
std::string filename;
// Get the visp-images-data package path or VISP_INPUT_IMAGE_PATH
// environment variable value
// Set the default input path
if (!env_ipath.empty()) {
ipath = env_ipath;
}
// Read the command line options
if (!getOptions(argc, argv, opt_ipath)) {
exit(EXIT_FAILURE);
}
// Get the option values
if (!opt_ipath.empty()) {
ipath = opt_ipath;
}
// Compare ipath and env_ipath. If they differ, we take into account
// the input path comming from the command line option
if (!opt_ipath.empty() && !env_ipath.empty()) {
if (ipath != env_ipath) {
std::cout << std::endl << "WARNING: " << std::endl;
std::cout << " Since -i <visp image path=" << ipath << "> "
<< " is different from VISP_IMAGE_PATH=" << env_ipath << std::endl
<< " we skip the environment variable." << std::endl;
}
}
// Test if an input path is set
if (opt_ipath.empty() && env_ipath.empty()) {
usage(argv[0], NULL, ipath);
std::cerr << std::endl << "ERROR:" << std::endl;
std::cerr << " Use -i <visp image path> option or set VISP_INPUT_IMAGE_PATH " << std::endl
<< " environment variable to specify the location of the " << std::endl
<< " image path where test images are located." << std::endl
<< std::endl;
exit(EXIT_FAILURE);
}
//
// Here starts really the test
//
// Load cube sequence
filename = vpIoTools::createFilePath(ipath, "mbt/cube/image%04d.pgm");
vpVideoReader reader;
reader.setFileName(filename);
vpImage<unsigned char> I, I_template;
reader.open(I);
vpRect template_roi( vpImagePoint(201, 310), vpImagePoint(201+152-1, 310+138-1) );
vpImageTools::crop(I, template_roi, I_template);
vpImage<double> I_score, I_score_gold;
const unsigned int step_i = 5, step_j = 5;
double t = vpTime::measureTimeMs();
templateMatching(I, I_template, I_score, step_i, step_j, true);
double t_gold = vpTime::measureTimeMs();
templateMatching(I, I_template, I_score_gold, step_i, step_j, false);
t_gold = vpTime::measureTimeMs() - t_gold;
for (unsigned int i = 0; i < I_score.getHeight(); i++) {
for (unsigned int j = 0; j < I_score.getWidth(); j++) {
if ( !vpMath::equal(I_score[i][j], I_score_gold[i][j], 1e-9) ) {
std::cerr << "Issue with normalizedCorrelation, gold: " << std::setprecision(17)
<< I_score_gold[i][j] << " ; compute: " << I_score[i][j] << std::endl;
return EXIT_FAILURE;
}
}
}
vpImagePoint max_loc, max_loc_gold;
double max_correlation = -1.0, max_correlation_gold = -1.0;
I_score.getMinMaxLoc(NULL, &max_loc, NULL, &max_correlation);
I_score_gold.getMinMaxLoc(NULL, &max_loc_gold, NULL, &max_correlation_gold);
std::cout << "Compare regular and SSE version of vpImageTools::normalizedCorrelation()" << std::endl;
std::cout << "vpImageTools::normalizedCorrelation(): " << max_correlation << " ; " << t << " ms" << std::endl;
std::cout << "Gold normalizedCorrelation(): " << max_correlation_gold << " ; " << t_gold << " ms" << std::endl;
std::cerr << "\nTrue template position: " << template_roi.getTopLeft() << std::endl;
std::cerr << "Found template position: " << max_loc << std::endl;
if ( vpImagePoint::distance(max_loc, template_roi.getTopLeft()) > step_i ) {
std::cerr << "Issue with vpImageTools::normalizedCorrelation:" << std::endl;
return EXIT_FAILURE;
}
} catch (const vpException &e) {
std::cerr << "\nCatch an exception: " << e << std::endl;
return EXIT_FAILURE;
}
return EXIT_SUCCESS;
}