void CvMatDataInputPin::checkImageFormat( const CvMatData& mat )
{
if( !supportsDepth( mat.depth()) )
{
QString msg = QString("Depth \"%1\" unsupported by input pin \"%2\"")
.arg( CvMatData::depthToString( mat.depth() ) )
.arg( this->getName() );
throw PlvRuntimeException( msg, __FILE__, __LINE__ );
}
if( !supportsChannels(mat.channels()) )
{
QString msg = "Number of channels " %
QVariant(mat.channels()).toString() %
" unsupported by input pin \"" % this->getName() %
"\". Supports channels (";
QString channelsStr;
channelsStr.reserve( (2 * m_channels.size()) + 2 );
QList<int> channelList = m_channels.toList();
int lastIdx = channelList.size() - 1;
for( int i = 0; i < channelList.size(); ++i )
{
channelsStr += QVariant(channelList.at(i)).toString();
if( i != lastIdx )
channelsStr += ",";
}
msg += channelsStr + ").";
throw PlvRuntimeException( msg, __FILE__, __LINE__ );
}
}
bool ImageThreshold::process()
{
CvMatData in = m_inputPin->get();
CvMatData out = CvMatData::create( in.width(), in.height(), in.type() );
const cv::Mat& src = in;
cv::Mat& dst = out;
// perform threshold operation on the image
cv::threshold( src, dst, m_threshold, m_maxValue, m_method.getSelectedValue() );
// publish the new image
m_outputPin->put( out );
return true;
}
bool ImageFlip::process()
{
CvMatData in = m_inputPin->get();
CvMatData out = CvMatData::create(in.properties());
// open for reading
const cv::Mat& src = in;
// open image for writing
cv::Mat& target = out;
// do a flip of the image
cv::flip( src, target, m_method.getSelectedValue() );
// publish the new image
m_outputPin->put( target );
return true;
}
void DistanceTransform::process()
{
//get the input image
CvMatData img = m_inputPin->get();
// open input images for reading
const cv::Mat& src = img;
if(img.channels() != 1)
qDebug() << "Wrong number of channels";
if(img.depth() != CV_8U && img.depth() != CV_8S)
qDebug() << "Wrong depth in the image";
//get a destination image with the distance values.
CvMatData out = CvMatData::create( img.width(), img.height(), CV_32FC1 );
// open output image for writing
cv::Mat& dst = out;
//DistanceTransform both images
try{
cv::distanceTransform(src, dst, m_distanceType.getSelectedValue(), m_maskSize.getSelectedValue());
}
catch(std::exception &e){
//Don't know why but this try/catch block prevents exception troubles.
qDebug() << "exception: " << e.what();
throw;
}
// publish the new image
m_outputPin->put( out );
}
bool Gray2RGB::process()
{
assert(m_inputPin != 0);
assert(m_outputPin != 0);
CvMatData src = m_inputPin->get();
// allocate a target buffer
CvMatData target;
target.create( src.width(), src.height(), src.type() );
// do a flip of the image
const cv::Mat in = src;
cv::Mat out = target;
cv::flip( in, out, 1);
// publish the new image
m_outputPin->put( out );
// CvMatData in = m_inputPin->get();
//const cv::Mat& inputImage = in;
//m_outputPin->put( inputImage );
return true;
}
/**
* The method in steps:
* - Check if input is initialized and retrieve the image data.
* - Check if the trigger input is active
* # Set doSave corresponding to the value of the trigger
* - Check if the image has to be saved.
* # Build the save path.
* # Save image to the correct file format
* # Check if the suffixNr needs to be increased and increase it.
*/
void SaveImageToFile::process()
{
assert(m_inputImage != 0);
CvMatData img = m_inputImage->get();
if( m_inputTrigger->isConnected() )
{
if( !m_inputTrigger->getConnection()->hasData() )
{
return;
}
//If the trigger has been connected check if the trigger sent an activation.
RefPtr<PlvBoolean> trig = m_inputTrigger->get();
if( trig->getValue() )
setDoSave(true);
}
if(m_doSave)
{
QString fn = m_directory;
//Check if the string ends with a '/' character
if(!fn.endsWith('/'))
fn.append('/');
fn.append(m_filename);
fn.append(QString::number(m_suffixNr));
fn.append(m_fileExt);
const IplImage* saveImg = img->getImage();
if(!cvSaveImage(fn.toAscii(), saveImg))
{
qDebug() << "Something went wrong with writing to a file: " << fn;
}
if(m_autoIncSuf)
setSuffixNr(m_suffixNr+1);
setDoSave(false);
}
}
/**
Calculates the first, second, third or mixed image derivatives using an extended Sobel operator
Parameters:
* src – The source image
* dst – The destination image; will have the same size and the same number of channels as src
* ddepth – The destination image depth
* xorder – Order of the derivative x
* yorder – Order of the derivative y
* ksize – Size of the extended Sobel kernel, must be 1, 3, 5 or 7
* scale – The optional scale factor for the computed derivative values (by default, no scaling is applied, see getDerivKernels() )
* delta – The optional delta value, added to the results prior to storing them in dst
* borderType – The pixel extrapolation method, see borderInterpolate()
*/
void EdgeDetectorSobel::process()
{
CvMatData srcPtr = m_inputPin->get();
CvMatData dstPtr = CvMatData::create( srcPtr.properties() );
// open for reading
const cv::Mat& src = srcPtr;
// open image for writing
cv::Mat& dst = dstPtr;
assert( m_xOrder == 1 || m_xOrder == 0 );
assert( m_yOrder == 1 || m_yOrder == 0 );
assert( m_kernelSize == 1 || m_kernelSize == 3 || m_kernelSize == 5 || m_kernelSize == 7 );
// do sobel operation
cv::Sobel( src, dst, dst.depth() , m_xOrder, m_yOrder,
m_kernelSize, m_scale, m_delta,
m_borderType.getSelectedValue() );
// publish output
m_outputPin->put( dstPtr );
}
void ImageCornerHarris::process()
{
assert(m_inputPin != 0);
assert(m_outputPin != 0);
// get the src image
CvMatData in = m_inputPin->get();
// make a target image
// cv::CornerHarris expects a 32F dst image
CvMatDataProperties props( in.width(), in.height(), CV_32FC1 );
CvMatData out = CvMatData::create( props );
const cv::Mat& src = in;
cv::Mat& dst = out;
// do a canny edge detection operator of the image
cv::cornerHarris( src, dst, m_blockSize, m_kernelSize,
m_k, m_borderType.getSelectedValue() );
// publish the new image
m_outputPin->put( out );
}
bool EdgeDetectorCanny::process()
{
// get the source
CvMatData in = m_inputPin->get();
// get a new target image with the same properties as the src
CvMatData out = CvMatData::create( in.properties() );
// open for reading
const cv::Mat& src = in;
// open image for writing
cv::Mat& edges = out;
// do a canny edge detection operator of the image
// the input should be grayscaled
cv::Canny( src, edges, m_thresholdLow, m_thresholdHigh, m_apertureSize, m_l2Gradient );
// publish the new image
m_outputPin->put( out );
return true;
}
void OpenCVCamera::run()
{
assert( m_state != CAM_UNINITIALIZED );
assert( m_captureDevice != 0 );
while( m_state == CAM_RUNNING || m_state == CAM_PAUSED )
{
// get a frame, blocking call
CvMatData frame;
if( !getFrame(frame) )
{
qWarning() << "Camera failed to grab frame. Exiting camera loop.";
return;
}
// send a signal to subscribers
if( frame.isValid() )
{
emit newFrame( frame );
}
if( m_state == CAM_PAUSED )
{
m_mutex.lock();
// this will let this thread wait on the event
// and unlocks the mutex so no deadlock is created
m_condition.wait(&m_mutex);
// we have woken up
// mutex was relocked by the condition
// unlock it here
m_mutex.unlock();
}
}
}
