mirrors/opencv_contrib
1
0
Fork 0
Code Pull Requests Packages Releases Activity

vendor: OpenCV 5.0.0 snapshot at 755e50675d97db9b7d449d8bd6b09888646f6c6e

Browse Source
This commit is contained in:
Gitea Mirror Bot
2026-08-22 00:11:13 +08:00
commit 12022378a3
3872 changed files with 2513409 additions and 0 deletions
Download Patch File Download Diff File Expand all files Collapse all files
modules/structured_light/test/test_faps.cpp
+149
View File
@@ -0,0 +1,149 @@
/*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) 2015, OpenCV Foundation, 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 <opencv2/structured_light/graycodepattern.hpp>
#include <opencv2/structured_light/sinusoidalpattern.hpp>
namespace opencv_test { namespace {
const string STRUCTURED_LIGHT_DIR = "structured_light";
const string FOLDER_DATA = "data";
TEST( SinusoidalPattern, unwrapPhaseMap )
{
string folder = cvtest::TS::ptr()->get_data_path() + "/" + STRUCTURED_LIGHT_DIR + "/" + FOLDER_DATA + "/";
Ptr<structured_light::SinusoidalPattern::Params> paramsPsp, paramsFtp, paramsFaps;
paramsPsp = makePtr<structured_light::SinusoidalPattern::Params>();
paramsFtp = makePtr<structured_light::SinusoidalPattern::Params>();
paramsFaps = makePtr<structured_light::SinusoidalPattern::Params>();
paramsFtp->methodId = 0;
paramsPsp->methodId = 1;
paramsFaps->methodId = 2;
Ptr<structured_light::SinusoidalPattern> sinusPsp = structured_light::SinusoidalPattern::create(paramsPsp);
Ptr<structured_light::SinusoidalPattern> sinusFtp = structured_light::SinusoidalPattern::create(paramsFtp);
Ptr<structured_light::SinusoidalPattern> sinusFaps = structured_light::SinusoidalPattern::create(paramsFaps);
vector<Mat> captures(3);
Mat unwrappedPhaseMapPspRef, unwrappedPhaseMapFtpRef, unwrappedPhaseMapFapsRef;
Mat shadowMask;
Mat wrappedPhaseMap, unwrappedPhaseMap, unwrappedPhaseMap8;
captures[0] = imread(folder + "capture_sin_0.jpg", IMREAD_GRAYSCALE);
captures[1] = imread(folder + "capture_sin_1.jpg", IMREAD_GRAYSCALE);
captures[2] = imread(folder + "capture_sin_2.jpg", IMREAD_GRAYSCALE);
unwrappedPhaseMapPspRef = imread(folder + "unwrappedPspTest.jpg", IMREAD_GRAYSCALE);
unwrappedPhaseMapFtpRef = imread(folder + "unwrappedFtpTest.jpg", IMREAD_GRAYSCALE);
unwrappedPhaseMapFapsRef = imread(folder + "unwrappedFapsTest.jpg", IMREAD_GRAYSCALE);
if( !captures[0].data || !captures[1].data || !captures[2].data || !unwrappedPhaseMapFapsRef.data
|| !unwrappedPhaseMapFtpRef.data || !unwrappedPhaseMapPspRef.data )
{
cerr << "invalid test data" << endl;
}
sinusPsp->computePhaseMap(captures, wrappedPhaseMap, shadowMask);
sinusPsp->unwrapPhaseMap(wrappedPhaseMap, unwrappedPhaseMap, Size(captures[0].cols, captures[1].rows), shadowMask);
unwrappedPhaseMap.convertTo(unwrappedPhaseMap8, CV_8U, 1, 128);
int sumOfDiff = 0;
int count = 0;
float ratio = 0;
for( int i = 0; i < unwrappedPhaseMap8.rows; ++i )
{
for( int j = 0; j < unwrappedPhaseMap8.cols; ++j )
{
int ref = unwrappedPhaseMapPspRef.at<uchar>(i, j);
int comp = unwrappedPhaseMap8.at<uchar>(i, j);
sumOfDiff += (ref - comp);
count ++;
}
}
ratio = (float)(sumOfDiff / count);
EXPECT_LE( ratio, 0.003 );
sinusFtp->computePhaseMap(captures, wrappedPhaseMap, shadowMask);
sinusFtp->unwrapPhaseMap(wrappedPhaseMap, unwrappedPhaseMap, Size(captures[0].cols, captures[1].rows), shadowMask);
unwrappedPhaseMap.convertTo(unwrappedPhaseMap8, CV_8U, 1, 128);
sumOfDiff = 0;
count = 0;
ratio = 0;
for( int i = 0; i < unwrappedPhaseMap8.rows; ++i )
{
for( int j = 0; j < unwrappedPhaseMap8.cols; ++j )
{
int ref = unwrappedPhaseMapFtpRef.at<uchar>(i, j);
int comp = unwrappedPhaseMap8.at<uchar>(i, j);
sumOfDiff += (ref - comp);
count ++;
}
}
ratio = (float)(sumOfDiff / count);
EXPECT_LE( ratio, 0.003 );
sinusFaps->computePhaseMap(captures, wrappedPhaseMap, shadowMask);
sinusFaps->unwrapPhaseMap(wrappedPhaseMap, unwrappedPhaseMap, Size(captures[0].cols, captures[1].rows), shadowMask);
unwrappedPhaseMap.convertTo(unwrappedPhaseMap8, CV_8U, 1, 128);
sumOfDiff = 0;
count = 0;
ratio = 0;
for( int i = 0; i < unwrappedPhaseMap8.rows; ++i )
{
for( int j = 0; j < unwrappedPhaseMap8.cols; ++j )
{
int ref = unwrappedPhaseMapFapsRef.at<uchar>(i, j);
int comp = unwrappedPhaseMap8.at<uchar>(i, j);
sumOfDiff += (ref - comp);
count ++;
}
}
ratio = (float)(sumOfDiff / count);
EXPECT_LE( ratio, 0.003 );
}
}} // namespace