本文整理汇总了C++中Global::getMinimumRecognitionWeight方法的典型用法代码示例。如果您正苦于以下问题:C++ Global::getMinimumRecognitionWeight方法的具体用法?C++ Global::getMinimumRecognitionWeight怎么用?C++ Global::getMinimumRecognitionWeight使用的例子?那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类Global
的用法示例。
在下文中一共展示了Global::getMinimumRecognitionWeight方法的2个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的C++代码示例。
示例1: QWidget
SearchPreferences::SearchPreferences(QWidget *parent) :
QWidget(parent)
{
QGridLayout *mainLayout = new QGridLayout(this);
setLayout(mainLayout);
syncAttachments = new QCheckBox(tr("Index Attachments"));
mainLayout->addWidget(syncAttachments,0,0);
syncAttachments->setChecked(global.synchronizeAttachments());
weight = new QSpinBox(this);
mainLayout->addWidget(new QLabel(tr("Minimum Image Recognition Weight")), 1,0);
mainLayout->addWidget(weight,1,1);
weight->setMinimum(1);
weight->setMaximum(100);
weight->setValue(global.getMinimumRecognitionWeight());
this->setFont(global.getGuiFont(font()));
}
示例2: addImageHighlight
/* This function works the same as the addHighlight, but instead of highlighting
text in a note, it highlights the text in an image. */
QString NoteFormatter::addImageHighlight(qint32 resLid, QString imgfile) {
if (highlightWords.size() == 0)
return "";
// Get the image resource recognition data. This tells where to highlight the image
ResourceTable resTable(global.db);
Resource recoResource;
resTable.getResourceRecognition(recoResource, resLid);
Data recognition;
if (recoResource.recognition.isSet())
recognition = recoResource.recognition;
if (!recognition.size.isSet() || !recognition.body.isSet() ||
recognition.size == 0) {
return "";
}
QString filename = global.fileManager.getTmpDirPath() + QString::number(resLid) + ".png";
// Now we have the recognition data. We need to go through it
QByteArray recoData;
if (recognition.body.isSet())
recoData = recognition.body;
QString xml(recoData);
// Create a transparent pixmap. The only non transparent piece is teh
// highlight that will be overlaid on the old image
imgfile = imgfile.replace("file:///", "");
QPixmap originalFile(imgfile);
QPixmap overlayPix(originalFile.size());
overlayPix.fill(Qt::transparent);
QPainter p2(&overlayPix);
p2.setBackgroundMode(Qt::TransparentMode);
p2.setRenderHint(QPainter::Antialiasing,true);
QColor yellow(Qt::yellow);
p2.setBrush(yellow);
// Now, we have the image. We need to go through all the recognition data to highlight
// what we've found.
QDomDocument doc;
doc.setContent(xml);
// Go through the "item" nodes
QDomNodeList anchors = doc.elementsByTagName("item");
for (unsigned int i=0; i<anchors.length(); i++) {
QDomElement element = anchors.at(i).toElement();
int x = element.attribute("x").toInt();
int y = element.attribute("y").toInt();
int w = element.attribute("w").toInt();
int h = element.attribute("h").toInt();
// Get all children ("t" nodes)
QDomNodeList children = element.childNodes();
for (unsigned int j=0; j<children.length(); j++) {
QDomElement child = children.at(j).toElement();
if (child.nodeName().toLower() == "t") {
QString text = child.text();
int weight = child.attribute("w").toInt(); // Image weight
if (weight >= global.getMinimumRecognitionWeight()) {
// Check to see if this word matches something we're looking for
for (int k=0; k<highlightWords.size(); k++) {
QString searchWord = highlightWords[k].toLower();
if (searchWord.endsWith("*"))
searchWord.chop(1);
if (text.toLower().contains(searchWord)) {
p2.drawRect(x,y,w,h);
}
}
}
}
}
}
// Paint the highlight onto the background & save over the original
p2.setOpacity(0.4);
p2.drawPixmap(0,0,overlayPix);
p2.end();
// Create the actual overlay. We do this in two steps to avoid
// constantly painting the same area
QPixmap finalPix(originalFile.size());
finalPix.fill(Qt::transparent);
QPainter p3(&finalPix);
p3.setBackgroundMode(Qt::TransparentMode);
p3.setRenderHint(QPainter::Antialiasing,true);
p3.drawPixmap(0,0,originalFile);
p3.setOpacity(0.4);
p3.drawPixmap(0,0,overlayPix);
p3.end();
finalPix.save(filename);
return "this.src='file://"+filename+"';";
}