void FreeSpaceWidget::slotAvailableFreeSpace(const QString& mountPoint, quint64 kBSize,
quint64 kBUsed, quint64 kBAvail)
{
#if KDE_IS_VERSION(4,1,68)
Q_UNUSED(mountPoint);
Q_UNUSED(kBSize);
Q_UNUSED(kBUsed);
Q_UNUSED(kBAvail);
#else
addInformation(kBSize, kBUsed, kBAvail, mountPoint);
#endif /* KDE_IS_VERSION(4,1,68) */
}
void FreeSpaceWidget::slotTimeout()
{
foreach(const QString& path, d->paths)
{
KDiskFreeSpaceInfo info = KDiskFreeSpaceInfo::freeSpaceInfo(path);
if (info.isValid())
{
addInformation((unsigned long)(info.size() / 1024.0),
(unsigned long)(info.used() / 1024.0),
(unsigned long)(info.available() / 1024.0),
info.mountPoint());
}
}
}
void FreeSpaceWidget::slotTimeout()
{
foreach(const QString& path, d->paths)
{
QStorageInfo info(path);
if (info.isValid())
{
addInformation((unsigned long)(info.bytesTotal() / 1024.0),
(unsigned long)((info.bytesTotal()-info.bytesAvailable()) / 1024.0),
(unsigned long)(info.bytesAvailable() / 1024.0),
info.rootPath());
}
}
}
bool IPLIFFT::processInputData(IPLImage* data , int, bool)
{
_complexImage = new IPLComplexImage(*data->toComplexImage());
// delete previous result
delete _result;
_result = NULL;
int width = _complexImage->width();
int height = _complexImage->height();
_result = new IPLImage(IPLData::IMAGE_GRAYSCALE, width, height);
// get properties
//int mode = getProcessPropertyInt("mode");
int progress = 0;
int maxProgress = height;
_complexImage->IFFT();
float dc = _complexImage->real(0,0);
float min = _complexImage->minReal();
float max = _complexImage->maxReal();
float diff = max-min;
for(int y=0; y<height; y++)
{
// progress
notifyProgressEventHandler(100*progress++/maxProgress);
for(int x=0; x<width; x++)
{
float value = (_complexImage->real(x,y) - min) / diff;
value = (value < 0) ? 0 : value;
value = (value > 1) ? 1 : value;
_result->plane(0)->p(x, y) = value;
}
}
std::stringstream s;
s << "DC: ";
s << dc;
addInformation(s.str());
return true;
}
bool IPLBinarizeUnimodal::processInputData(IPLImage* image , int, bool)
{
// delete previous result
delete _result;
_result = NULL;
int width = image->width();
int height = image->height();
if( image->type() == IPL_IMAGE_GRAYSCALE )
_result = new IPLImage( IPL_IMAGE_BW, width, height );
else
_result = new IPLImage( image->type(), width, height );
int progress = 0;
int maxProgress = image->height() * image->getNumberOfPlanes();
int nrOfPlanes = image->getNumberOfPlanes();
#pragma omp parallel for
for( int planeNr=0; planeNr < nrOfPlanes; planeNr++ )
{
IPLImagePlane* plane = image->plane( planeNr );
IPLImagePlane* newplane = _result->plane( planeNr );
int p[256] = { 0 };
for( int y = 0; y < height; ++y )
{
for( int x = 0; x < width; ++x )
{
int index = plane->p(x,y) * 255;
p[index]++;
}
}
// determine maxEntry
int maxBin = 0;
int maxFrequency = 0;
for( int k=1; k<255; ++k )
{
if( p[k] > maxFrequency )
{
maxFrequency = p[k];
maxBin = k;
}
}
// determine zeroEntry
int zeroBin = 0;
int x0, x1;
if( maxBin >= 128 )
{
zeroBin = 0;
while( p[zeroBin]==0 ) ++zeroBin;
x0 = zeroBin;
x1 = maxBin;
}
else
{
zeroBin = 255;
while( p[zeroBin]==0 ) --zeroBin;
x0 = maxBin;
x1 = zeroBin;
}
int y0 = p[x0];
int y1 = p[x1];
double a = y0 - y1;
double b = x1 - x0;
double c = x0*y1 - x1*y0;
double d = sqrt( a*a + b*b );
int T = 0;
if( d != 0.0 )
{
double maxDist = 0.0;
for( int k=x0; k<=x1; ++k )
{
double distance = std::abs( ( a*k + b*p[k] + c ) / d );
if( distance > maxDist )
{
maxDist = distance;
T = k;
}
}
}
ipl_basetype threshold = T * FACTOR_TO_FLOAT;
std::stringstream s;
s << "Automatic Threshold: ";
s << threshold;
addInformation(s.str());
for(int y = 0; y < height; y++)
{ // progress
notifyProgressEventHandler(100*progress++/maxProgress);
for(int x = 0; x < width; x++)
{
newplane->p(x,y)= (plane->p(x,y) > threshold)? 1.0 : 0.0;
}
}
}
return true;
}
bool IPLCanny::processInputData(IPLImage* image , int, bool useOpenCV)
{
// delete previous result
delete _result;
_result = NULL;
delete _binaryImage;
_binaryImage = NULL;
int width = image->width();
int height = image->height();
_result = new IPLImage( image->type(), width, height );
_binaryImage = new IPLImage( IPLData::IMAGE_BW, width, height );
// get properties
int window = getProcessPropertyInt("window");
double sigma = getProcessPropertyDouble("sigma");
double lowThreshold = getProcessPropertyDouble("lowThreshold");
double highThreshold = getProcessPropertyDouble("highThreshold");
std::stringstream s;
s << "Window: ";
s << window;
addInformation(s.str());
//! @todo currently only the opencv implementation works
if(useOpenCV || true)
{
notifyProgressEventHandler(-1);
cv::Mat input;
cv::Mat output;
cvtColor(image->toCvMat(), input, CV_BGR2GRAY);
cv::Canny(input, output, lowThreshold*255, highThreshold*255, window);
delete _result;
_result = new IPLImage(output);
return true;
}
return false;
// Create a Gaussian 1D filter
int N = ceil( sigma * sqrt( 2.0*log( 1.0/0.015 ) ) + 1.0 );
double ssq = sigma*sigma;
double* gau = new double [window];
double* dgau = new double [window];
for( int k = -N; k <= N; ++k )
{
gau[k+N] = gauss ( (double)k, ssq );
dgau[k+N] = dGauss ( (double)k, 0, ssq );
}
// Create a directional derivative of 2D Gaussian (along X-axis)
// Since the result is symmetric along X, we can get the derivative along
// Y-axis simply by transposing the result for X direction.
// DoubleImage* dgau = new DoubleImage( window, window );
// for( int y = -N; y <= N; ++y )
// for( int x = -N; x <= N; ++x )
// dgau->f(x+N, y+N) = dGauss( x, y, ssq );
int progress = 0;
int maxProgress = width * image->getNumberOfPlanes();
int nrOfPlanes = image->getNumberOfPlanes();
//#pragma omp parallel for
for( int planeNr=0; planeNr < nrOfPlanes; planeNr++ )
{
IPLImagePlane* plane = image->plane( planeNr );
IPLImagePlane* newplane = _result->plane( planeNr );
// ******** Gaussian filtering of input image
IPLImagePlane* gI = new IPLImagePlane( width, height );
// horizontal run (normalizing original image)
IPLImagePlane* tmpI = new IPLImagePlane( width, height );
for(int x=0; x<width; x++)
{ // progress
notifyProgressEventHandler(100*progress++/maxProgress);
for(int y=0; y<height; y++)
{
double sum = 0;
int i = 0;
for( int kx=-N; kx<=N; kx++ )
{
double img = (double) plane->bp(x+kx, y);
sum += (img * gau[i++]);
}
tmpI->p(x,y) = (double) (sum);
}
}
// vertiacl run
for(int x=0; x<width; x++)
{
for(int y=0; y<height; y++)
{
double sum = 0;
int i = 0;
for( int ky=-N; ky<=N; ky++ )
{
double img = tmpI->bp(x, y+ky);
sum += (img * gau[i++]);
}
gI->p(x,y) = sum;
}
}
//delete tmpI;
// ******** Apply directional derivatives ...
// ... in x-direction
IPLImagePlane* dx = new IPLImagePlane( width, height );
for(int x=0; x<width; x++)
{
for(int y=0; y<height; y++)
{
dx->p(x,y) = 0.0;
for( int k=1; k<N; k++ )
{
dx->p(x,y) += ( gI->bp(x-k,y) - gI->bp(x+k,y) ) * dgau[k];
}
}
}
// double maxVal = 0.0;
// for(int x=0; x<width; x++)
// for(int y=0; y<height; y++)
// if( dx->f(x,y) > maxVal ) maxVal = dx->f(x,y);
// ... in y-direction
IPLImagePlane* dy = new IPLImagePlane( width, height );
for(int x=0; x<width; x++)
{
for(int y=0; y<height; y++)
{
dy->p(x,y) = 0.0;
for( int k=1; k<N; k++ )
{
dy->p(x,y) += ( gI->bp(x,y-k) - gI->bp(x,y+k) ) * dgau[k];
}
}
}
// ******** Compute magnitude and binarization thresholds
IPLImagePlane* mag = new IPLImagePlane( width, height );
double magMax = 0.0;
double magMin = 999999999.0;
for(int x=0; x<width; x++)
{
for(int y=0; y<height; y++)
{
double val = sqrt( dx->p(x,y)*dx->p(x,y) + dy->p(x,y)*dy->p(x,y) );
mag->p(x,y) = val;
if( val > magMax ) magMax = val;
if( val < magMin ) magMin = val;
}
}
//// ******** Non-maxima suppression - edge pixels should be a local maximum
_orientedImage = new IPLOrientedImage( width, height );
for(int x=0; x<width; x++)
{
for(int y=0; y<height; y++)
{
double ix = dx->p(x,y);
double iy = dy->p(x,y);
double g = mag->p(x,y);
// determine 4-neighbor direction of gradient
int dir4 = 0;
if( (iy<=0.0 && ix>-iy) || (iy>=0.0 && ix<-iy) )
dir4 = 1;
else if( (ix>0.0 && -iy>=ix) || (ix<0.0 && -iy<=ix) )
dir4 = 2;
else if( (ix<=0.0 && ix>iy) || (ix>=0.0 && ix<iy) )
dir4 = 3;
else if( (iy<0.0 && ix<=iy) || (iy>0.0 && ix>=iy) )
dir4 = 4;
else
continue;
double gradmag1, gradmag2, d;
switch(dir4)
{
case 1: d = std::fabs(iy/ix);
gradmag1 = mag->bp(x+1,y)*(1-d) + mag->bp(x+1,y-1)*d;
gradmag2 = mag->bp(x-1,y)*(1-d) + mag->bp(x-1,y+1)*d;
break;
case 2: d = std::fabs(ix/iy);
gradmag1 = mag->bp(x,y-1)*(1-d) + mag->bp(x+1,y-1)*d;
gradmag2 = mag->bp(x,y+1)*(1-d) + mag->bp(x-1,y+1)*d;
break;
case 3: d = std::fabs(ix/iy);
gradmag1 = mag->bp(x,y-1)*(1-d) + mag->bp(x-1,y-1)*d;
gradmag2 = mag->bp(x,y+1)*(1-d) + mag->bp(x+1,y+1)*d;
break;
case 4: d = std::fabs(iy/ix);
gradmag1 = mag->bp(x-1,y)*(1-d) + mag->bp(x-1,y-1)*d;
gradmag2 = mag->bp(x+1,y)*(1-d) + mag->bp(x+1,y+1)*d;
break;
}
if( g > gradmag1 && g > gradmag2 )
{
_orientedImage->magnitude(x,y) = g;
_orientedImage->phase(x,y) = atan2(iy,ix);
}
}
}
for(int x=0; x<width; x++)
{
for(int y=0; y<height; y++)
{
_orientedImage->magnitude(x,y) /= magMax;
double val = _orientedImage->magnitude(x,y)*255.0;
// double val = mag->f(x,y)/magMax*255.0;
if (val > 255.0 ) val = 255.0;
if (val < 0.0 ) val = 0.0;
newplane->p(x,y) = (unsigned char ) val;
}
}
// ******** Binarize with hysteresis threshold
double hist[ 256 ];
for( int i=0; i<256; ++i )
hist[i] = 0;
int pixCount = 0;
for(int x=0; x<width; x++)
{
for(int y=0; y<height; y++)
{
if( _orientedImage->magnitude(x,y) > 0.0 )
{
int index = floor( _orientedImage->magnitude(x,y)*256.0+0.5 );
++hist[ index ];
++pixCount;
}
}
}
double PercentOfPixelsNotEdges = 0.7*pixCount;
double highThresh = 0.0;
double cumsum = 0.0;
for( int i=0; i<256; ++i )
{
cumsum += hist[i];
if( cumsum > PercentOfPixelsNotEdges )
{
highThresh = (double)i / 256.0;
break;
}
}
double lowThresh = 0.4 * highThresh;
IPLImagePlane* binPlane = _binaryImage->plane( 0 );
for(int x=0; x<width; x++)
{
for(int y=0; y<height; y++)
{
if(_orientedImage->magnitude(x,y) >= highThresh)
trace(x, y, lowThresh, _orientedImage, binPlane);
}
}
//delete dx;
//delete dy;
//delete gI;
thinning(_orientedImage, binPlane, newplane );
}
//delete [] gau;
//delete [] dgau;
return true;
}
