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/*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 "precomp.hpp"
namespace cv {
namespace structured_light {
class CV_EXPORTS_W GrayCodePattern_Impl CV_FINAL : public GrayCodePattern
{
public:
// Constructor
explicit GrayCodePattern_Impl( const GrayCodePattern::Params ¶meters = GrayCodePattern::Params() );
// Destructor
virtual ~GrayCodePattern_Impl() CV_OVERRIDE {};
// Generates the gray code pattern as a std::vector<Mat>
bool generate( OutputArrayOfArrays patternImages ) CV_OVERRIDE;
// Decodes the gray code pattern, computing the disparity map
bool decode( const std::vector< std::vector<Mat> >& patternImages, OutputArray disparityMap, InputArrayOfArrays blackImages = noArray(),
InputArrayOfArrays whiteImages = noArray(), int flags = DECODE_3D_UNDERWORLD ) const CV_OVERRIDE;
// Returns the number of pattern images for the graycode pattern
size_t getNumberOfPatternImages() const CV_OVERRIDE;
// Sets the value for black threshold
void setBlackThreshold( size_t val ) CV_OVERRIDE;
// Sets the value for set the value for white threshold
void setWhiteThreshold( size_t val ) CV_OVERRIDE;
// Generates the images needed for shadowMasks computation
void getImagesForShadowMasks( InputOutputArray blackImage, InputOutputArray whiteImage ) const CV_OVERRIDE;
// For a (x,y) pixel of the camera returns the corresponding projector pixel
bool getProjPixel(InputArrayOfArrays patternImages, int x, int y, CV_OUT Point &projPix) const CV_OVERRIDE;
private:
// Parameters
Params params;
// The number of images of the pattern
size_t numOfPatternImages;
// The number of row images of the pattern
size_t numOfRowImgs;
// The number of column images of the pattern
size_t numOfColImgs;
// Number between 0-255 that represents the minimum brightness difference
// between the fully illuminated (white) and the non - illuminated images (black)
size_t blackThreshold;
// Number between 0-255 that represents the minimum brightness difference
// between the gray-code pattern and its inverse images
size_t whiteThreshold;
// Computes the required number of pattern images, allocating the pattern vector
void computeNumberOfPatternImages();
// Computes the shadows occlusion where we cannot reconstruct the model
void computeShadowMasks( InputArrayOfArrays blackImages, InputArrayOfArrays whiteImages,
OutputArrayOfArrays shadowMasks ) const;
// Converts a gray code sequence (~ binary number) to a decimal number
int grayToDec( const std::vector<uchar>& gray ) const;
};
/*
* GrayCodePattern
*/
GrayCodePattern::Params::Params()
{
width = 1024;
height = 768;
}
GrayCodePattern_Impl::GrayCodePattern_Impl( const GrayCodePattern::Params ¶meters ) :
params( parameters )
{
computeNumberOfPatternImages();
blackThreshold = 40; // 3D_underworld default value
whiteThreshold = 5; // 3D_underworld default value
}
bool GrayCodePattern_Impl::generate( OutputArrayOfArrays pattern )
{
std::vector<Mat>& pattern_ = *( std::vector<Mat>* ) pattern.getObj();
pattern_.resize( numOfPatternImages );
for( size_t i = 0; i < numOfPatternImages; i++ )
{
pattern_[i] = Mat( params.height, params.width, CV_8U );
}
uchar flag = 0;
for( int j = 0; j < params.width; j++ ) // rows loop
{
int rem = 0, num = j, prevRem = j % 2;
for( size_t k = 0; k < numOfColImgs; k++ ) // images loop
{
num = num / 2;
rem = num % 2;
if( ( rem == 0 && prevRem == 1 ) || ( rem == 1 && prevRem == 0) )
{
flag = 1;
}
else
{
flag = 0;
}
for( int i = 0; i < params.height; i++ ) // rows loop
{
uchar pixel_color = ( uchar ) flag * 255;
pattern_[2 * numOfColImgs - 2 * k - 2].at<uchar>( i, j ) = pixel_color;
if( pixel_color > 0 )
pixel_color = ( uchar ) 0;
else
pixel_color = ( uchar ) 255;
pattern_[2 * numOfColImgs - 2 * k - 1].at<uchar>( i, j ) = pixel_color; // inverse
}
prevRem = rem;
}
}
for( int i = 0; i < params.height; i++ ) // rows loop
{
int rem = 0, num = i, prevRem = i % 2;
for( size_t k = 0; k < numOfRowImgs; k++ )
{
num = num / 2;
rem = num % 2;
if( (rem == 0 && prevRem == 1) || (rem == 1 && prevRem == 0) )
{
flag = 1;
}
else
{
flag = 0;
}
for( int j = 0; j < params.width; j++ )
{
uchar pixel_color = ( uchar ) flag * 255;
pattern_[2 * numOfRowImgs - 2 * k + 2 * numOfColImgs - 2].at<uchar>( i, j ) = pixel_color;
if( pixel_color > 0 )
pixel_color = ( uchar ) 0;
else
pixel_color = ( uchar ) 255;
pattern_[2 * numOfRowImgs - 2 * k + 2 * numOfColImgs - 1].at<uchar>( i, j ) = pixel_color;
}
prevRem = rem;
}
}
return true;
}
bool GrayCodePattern_Impl::decode( const std::vector< std::vector<Mat> >& patternImages, OutputArray disparityMap,
InputArrayOfArrays blackImages, InputArrayOfArrays whitheImages, int flags ) const
{
const std::vector<std::vector<Mat> >& acquired_pattern = patternImages;
if( flags == DECODE_3D_UNDERWORLD )
{
// Computing shadows mask
std::vector<Mat> shadowMasks;
computeShadowMasks( blackImages, whitheImages, shadowMasks );
int cam_width = acquired_pattern[0][0].cols;
int cam_height = acquired_pattern[0][0].rows;
Point projPixel;
// Storage for the pixels of the two cams that correspond to the same pixel of the projector
std::vector<std::vector<std::vector<Point> > > camsPixels;
camsPixels.resize( acquired_pattern.size() );
// TODO: parallelize for (k and j)
for( size_t k = 0; k < acquired_pattern.size(); k++ )
{
camsPixels[k].resize( params.height * params.width );
for( int i = 0; i < cam_width; i++ )
{
for( int j = 0; j < cam_height; j++ )
{
//if the pixel is not shadowed, reconstruct
if( shadowMasks[k].at<uchar>( j, i ) )
{
//for a (x,y) pixel of the camera returns the corresponding projector pixel by calculating the decimal number
bool error = getProjPixel( acquired_pattern[k], i, j, projPixel );
if( error )
{
continue;
}
camsPixels[k][projPixel.x * params.height + projPixel.y].push_back( Point( i, j ) );
}
}
}
}
std::vector<Point> cam1Pixs, cam2Pixs;
Mat& disparityMap_ = *( Mat* ) disparityMap.getObj();
disparityMap_ = Mat( cam_height, cam_width, CV_64F, double( 0 ) );
double number_of_pixels_cam1 = 0;
double number_of_pixels_cam2 = 0;
for( int i = 0; i < params.width; i++ )
{
for( int j = 0; j < params.height; j++ )
{
cam1Pixs = camsPixels[0][i * params.height + j];
cam2Pixs = camsPixels[1][i * params.height + j];
if( cam1Pixs.size() == 0 || cam2Pixs.size() == 0 )
continue;
Point p1;
Point p2;
double sump1x = 0;
double sump2x = 0;
number_of_pixels_cam1 += cam1Pixs.size();
number_of_pixels_cam2 += cam2Pixs.size();
for( int c1 = 0; c1 < (int) cam1Pixs.size(); c1++ )
{
p1 = cam1Pixs[c1];
sump1x += p1.x;
}
for( int c2 = 0; c2 < (int) cam2Pixs.size(); c2++ )
{
p2 = cam2Pixs[c2];
sump2x += p2.x;
}
sump2x /= cam2Pixs.size();
sump1x /= cam1Pixs.size();
for( int c1 = 0; c1 < (int) cam1Pixs.size(); c1++ )
{
p1 = cam1Pixs[c1];
disparityMap_.at<double>( p1.y, p1.x ) = ( double ) (sump2x - sump1x);
}
sump2x = 0;
sump1x = 0;
}
}
return true;
} // end if flags
return false;
}
// Computes the required number of pattern images
void GrayCodePattern_Impl::computeNumberOfPatternImages()
{
numOfColImgs = ( size_t ) ceil( log( double( params.width ) ) / log( 2.0 ) );
numOfRowImgs = ( size_t ) ceil( log( double( params.height ) ) / log( 2.0 ) );
numOfPatternImages = 2 * numOfColImgs + 2 * numOfRowImgs;
}
// Returns the number of pattern images to project / decode
size_t GrayCodePattern_Impl::getNumberOfPatternImages() const
{
return numOfPatternImages;
}
// Computes the shadows occlusion where we cannot reconstruct the model
void GrayCodePattern_Impl::computeShadowMasks( InputArrayOfArrays blackImages, InputArrayOfArrays whiteImages,
OutputArrayOfArrays shadowMasks ) const
{
std::vector<Mat>& whiteImages_ = *( std::vector<Mat>* ) whiteImages.getObj();
std::vector<Mat>& blackImages_ = *( std::vector<Mat>* ) blackImages.getObj();
std::vector<Mat>& shadowMasks_ = *( std::vector<Mat>* ) shadowMasks.getObj();
shadowMasks_.resize( whiteImages_.size() );
int cam_width = whiteImages_[0].cols;
int cam_height = whiteImages_[0].rows;
// TODO: parallelize for
for( int k = 0; k < (int) shadowMasks_.size(); k++ )
{
shadowMasks_[k] = Mat( cam_height, cam_width, CV_8U );
for( int i = 0; i < cam_width; i++ )
{
for( int j = 0; j < cam_height; j++ )
{
double white = whiteImages_[k].at<uchar>( Point( i, j ) );
double black = blackImages_[k].at<uchar>( Point( i, j ) );
if( abs(white - black) > blackThreshold )
{
shadowMasks_[k].at<uchar>( Point( i, j ) ) = ( uchar ) 1;
}
else
{
shadowMasks_[k].at<uchar>( Point( i, j ) ) = ( uchar ) 0;
}
}
}
}
}
// Generates the images needed for shadowMasks computation
void GrayCodePattern_Impl::getImagesForShadowMasks( InputOutputArray blackImage, InputOutputArray whiteImage ) const
{
Mat& blackImage_ = *( Mat* ) blackImage.getObj();
Mat& whiteImage_ = *( Mat* ) whiteImage.getObj();
blackImage_ = Mat( params.height, params.width, CV_8U, Scalar( 0 ) );
whiteImage_ = Mat( params.height, params.width, CV_8U, Scalar( 255 ) );
}
// For a (x,y) pixel of the camera returns the corresponding projector's pixel
bool GrayCodePattern_Impl::getProjPixel( InputArrayOfArrays patternImages, int x, int y, Point &projPix ) const
{
std::vector<Mat>& _patternImages = *( std::vector<Mat>* ) patternImages.getObj();
std::vector<uchar> grayCol;
std::vector<uchar> grayRow;
bool error = false;
int xDec, yDec;
// process column images
for( size_t count = 0; count < numOfColImgs; count++ )
{
// get pixel intensity for regular pattern projection and its inverse
double val1 = _patternImages[count * 2].at<uchar>( Point( x, y ) );
double val2 = _patternImages[count * 2 + 1].at<uchar>( Point( x, y ) );
// check if the intensity difference between the values of the normal and its inverse projection image is in a valid range
if( abs(val1 - val2) < whiteThreshold )
error = true;
// determine if projection pixel is on or off
if( val1 > val2 )
grayCol.push_back( 1 );
else
grayCol.push_back( 0 );
}
xDec = grayToDec( grayCol );
// process row images
for( size_t count = 0; count < numOfRowImgs; count++ )
{
// get pixel intensity for regular pattern projection and its inverse
double val1 = _patternImages[count * 2 + numOfColImgs * 2].at<uchar>( Point( x, y ) );
double val2 = _patternImages[count * 2 + numOfColImgs * 2 + 1].at<uchar>( Point( x, y ) );
// check if the intensity difference between the values of the normal and its inverse projection image is in a valid range
if( abs(val1 - val2) < whiteThreshold )
error = true;
// determine if projection pixel is on or off
if( val1 > val2 )
grayRow.push_back( 1 );
else
grayRow.push_back( 0 );
}
yDec = grayToDec( grayRow );
if( (yDec >= params.height || xDec >= params.width) )
{
error = true;
}
projPix.x = xDec;
projPix.y = yDec;
return error;
}
// Converts a gray code sequence (~ binary number) to a decimal number
int GrayCodePattern_Impl::grayToDec( const std::vector<uchar>& gray ) const
{
int dec = 0;
uchar tmp = gray[0];
if( tmp )
dec += ( int ) pow( ( float ) 2, int( gray.size() - 1 ) );
for( int i = 1; i < (int) gray.size(); i++ )
{
// XOR operation
tmp = tmp ^ gray[i];
if( tmp )
dec += (int) pow( ( float ) 2, int( gray.size() - i - 1 ) );
}
return dec;
}
// Sets the value for black threshold
void GrayCodePattern_Impl::setBlackThreshold( size_t val )
{
blackThreshold = val;
}
// Sets the value for white threshold
void GrayCodePattern_Impl::setWhiteThreshold( size_t val )
{
whiteThreshold = val;
}
// Creates the GrayCodePattern instance
Ptr<GrayCodePattern> GrayCodePattern::create( const GrayCodePattern::Params& params )
{
return makePtr<GrayCodePattern_Impl>( params );
}
// Creates the GrayCodePattern instance
// alias for scripting
Ptr<GrayCodePattern> GrayCodePattern::create( int width, int height )
{
Params params;
params.width = width;
params.height = height;
return makePtr<GrayCodePattern_Impl>( params );
}
}
}