void qt_gui_settings::unserialize(core::coll_helper _collection)
{
core::iarray* values_array = _collection.get_value_as_array("values");
if (!values_array)
{
assert(false);
return;
}
for (int i = 0; i < values_array->size(); ++i)
{
const core::ivalue* val = values_array->get_at(i);
gui_coll_helper coll_val(val->get_as_collection(), false);
core::istream* idata = coll_val.get_value_as_stream("value");
int len = idata->size();
set_value_simple_data(coll_val.get_value_as_string("name"), (const char*) idata->read(len), len, false);
}
emit received();
setIsLoaded(true);
}
void TimeSeriesMotion::setDataColumn(int column)
{
if (m_dataColumn != column) {
m_dataColumn = column;
emit dataColumnChanged(column);
setIsLoaded(false);
}
}
void TimeSeriesMotion::setStopLine(int line)
{
if (m_stopLine != line) {
m_stopLine = line;
emit stopLineChanged(line);
setIsLoaded(false);
}
}
void TimeSeriesMotion::setFormat(Format format)
{
if (m_format != format) {
m_format = format;
emit formatChanged(format);
setIsLoaded(false);
}
}
void TimeSeriesMotion::setPointCount(int count)
{
if (m_pointCount != count) {
m_pointCount = count;
emit pointCountChanged(count);
setIsLoaded(false);
}
}
void TimeSeriesMotion::setTimeStep(double timeStep)
{
if (fabs(m_timeStep - timeStep) > DBL_EPSILON) {
m_timeStep = timeStep;
emit timeStepChanged(m_timeStep);
setIsLoaded(false);
}
}
void TimeSeriesMotion::setFileName(const QString & fileName)
{
QFileInfo fileInfo(fileName);
const QString _fileName = QDir::cleanPath(fileInfo.absoluteFilePath());
if (m_fileName != _fileName) {
emit fileNameChanged(_fileName);
}
m_fileName = _fileName;
setIsLoaded(false);
}
void TimeSeriesMotion::setInputUnits(TimeSeriesMotion::InputUnits inputUnits)
{
if (m_inputUnits != inputUnits) {
// Save the previously used conversation and scale factors
const double prevFactor = unitConversionFactor();
const double prevScale = m_scale;
m_inputUnits = inputUnits;
setModified(true);
// Need to modify the scale to correct for the change in units.
// This is done by modifying the m_scale parameter which is then
// used in rescale the appropriate values.
m_scale *= prevFactor / unitConversionFactor();
setScale(prevScale);
emit inputUnitsChanged(inputUnits);
}
setIsLoaded(false);
}
void TensorFlowEngine::load() {
const auto networkFilename = getFilename();
tensorflow::SessionOptions options;
tensorflow::ConfigProto &config = options.config;
tensorflow::GPUOptions* gpuOptions = config.mutable_gpu_options();
gpuOptions->set_allow_growth(true); // Set this so that tensorflow will not use up all GPU memory
//gpuOptions->set_per_process_gpu_memory_fraction(0.5);
mSession.reset(tensorflow::NewSession(options));
tensorflow::GraphDef tensorflow_graph;
{
reportInfo() << "Loading network file: " << networkFilename << reportEnd();
tensorflow::Status s = ReadBinaryProto(tensorflow::Env::Default(), networkFilename, &tensorflow_graph);
if (!s.ok()) {
throw Exception("Could not read TensorFlow graph file " + networkFilename);
}
}
bool nodesSpecified = true;
int inputCounter = 0;
if(mInputNodes.size() == 0) {
nodesSpecified = false;
}
for(int i = 0; i < tensorflow_graph.node_size(); ++i) {
tensorflow::NodeDef node = tensorflow_graph.node(i);
if(mInputNodes.count(node.name()) > 0) {
}
if(node.op() == "Placeholder") {
if(node.name().find("keras_learning_phase") != std::string::npos) {
//mLearningPhaseTensors.insert(node.name());
mLearningPhaseTensors.push_back(node.name());
} else {
// Input node found:
// Get its shape
// Input nodes use the Op Placeholder
reportInfo() << "Found input node: " << i << " with name " << node.name() << reportEnd();
auto shape = getShape(node);
reportInfo() << "Node has shape " << shape.toString() << reportEnd();
if(mInputNodes.count(node.name()) == 0) {
if(nodesSpecified) {
throw Exception("Encountered unknown node " + node.name());
}
reportInfo() << "Node was not specified by user" << reportEnd();
// If node has not been specified by user, we need to add it
// and thus know its type (fast image or tensor)
// It is assumed to be an image if input shape has at least 4 dimensions
NodeType type = NodeType::TENSOR;
if(shape.getKnownDimensions() >= 2) {
reportInfo() << "Assuming node is an image" << reportEnd();
type = NodeType::IMAGE;
} else {
reportInfo() << "Assuming node is a tensor" << reportEnd();
}
addInputNode(inputCounter, tensorflow_graph.node(0).name(), type, shape);
++inputCounter;
}
// Set its shape
mInputNodes[node.name()].shape = shape;
}
}
}
reportInfo() << "Creating session." << reportEnd();
tensorflow::Status s = mSession->Create(tensorflow_graph);
if (!s.ok()) {
throw Exception("Could not create TensorFlow Graph");
}
//tensorflow::graph::SetDefaultDevice("/gpu:0", &tensorflow_graph);
// Clear the proto to save memory space.
tensorflow_graph.Clear();
reportInfo() << "TensorFlow graph loaded from: " << networkFilename << reportEnd();
setIsLoaded(true);
}
bool TimeSeriesMotion::load(const QString &fileName, bool defaults, double scale)
{
m_accel.clear();
setFileName(fileName);
const QString ext = m_fileName.right(3).toUpper();
// Load the file
QFile file(m_fileName);
if (!file.open( QIODevice::ReadOnly | QIODevice::Text )) {
qWarning() << "Unable to open the time series file:" << qPrintable(m_fileName);
return false;
}
QTextStream stream(&file);
if (defaults) {
if (ext == "AT2") {
// Set format
setFormat(Rows);
setStartLine(5);
setStopLine(0);
setScale(scale);
// Read in the header information
Q_UNUSED(stream.readLine());
setDescription(stream.readLine());
Q_UNUSED(stream.readLine());
QStringList parts = stream.readLine().split(QRegExp("\\s+"));
bool b;
const int count = parts.at(0).toInt(&b);
if (b && count > 1) {
// Greater than one condition to catch if an acceleration value is read
setPointCount(count);
} else {
qCritical() << "Unable to parse the point count in AT2 file!";
return false;
}
const double timeStep = parts.at(1).toDouble(&b);
if (b) {
setTimeStep(timeStep);
} else {
qCritical() << "Unable to parse the time step in AT2 file!";
return false;
}
} else {
// Unknown file format can't process with default settings
return false;
}
} else {
// Check the input
if (m_timeStep <= 0) {
qCritical("Time step must be greater than one");
return false;
}
if (m_startLine < 0) {
qCritical("Number of header lines must be positive");
return false;
}
}
// Move back to the start of the stream
stream.seek(0);
int lineNum = 1;
// Skip the header lines
while (lineNum < m_startLine) {
Q_UNUSED(stream.readLine());
++lineNum;
}
// Initialize the length of m_accel
m_accel.resize(m_pointCount);
// Process each of the lines
int index = 0;
// Read the first line
QString line =stream.readLine();
bool finished = false;
bool stopLineReached = false;
// Modify the scale for unit conversion
scale = unitConversionFactor() * m_scale;
while (!finished && !line.isNull()) {
// Stop if line exceeds number of lines. The line number has
// to be increased by one because the user display starts at
// line number 1 instead of 0
if (m_stopLine > 0 && m_stopLine <= lineNum+1) {
stopLineReached = true;
break;
}
// Read the line and split the line
QRegExp rx("(-?\\d*\\.\\d+(?:[eE][+-]?\\d+)?)");
int pos = 0;
QStringList row;
while ((pos = rx.indexIn(line, pos)) != -1) {
row << rx.cap(1);
pos += rx.matchedLength();
}
// Process the row based on the format
bool ok;
switch (m_format) {
case Rows:
// Use all parts of the data
for(int i = 0; i < row.size(); ++i) {
if ( index == m_pointCount ) {
qWarning("Point count reached before end of data!");
finished = true;
break;
}
// Apply the scale factor and read the acceleration
m_accel[index] = scale * row.at(i).trimmed().toDouble(&ok);
// Increment the index
++index;
// Stop if there was an error in the conversion
if (!ok) {
continue;
}
}
break;
case Columns:
// Use only the important column, however at the end of the
// file that column may not exist -- this only happens when the
// row format is applied, but it still causes the program to
// crash.
if ( m_dataColumn - 1 < row.size() ) {
m_accel[index] = scale * row.at(m_dataColumn-1).trimmed().toDouble(&ok);
}
// Increment the index
++index;
break;
}
// Throw an error if there was a problem
if (!ok) {
qCritical() << "Error converting string to double in line: \n\""
<< qPrintable(line) << "\"\nCheck starting line.";
return false;
}
// Read the next line
++lineNum;
line = stream.readLine();
}
if (m_pointCount != index) {
if (stopLineReached) {
qWarning() << "Number of points limited by stop line.";
} else {
qCritical() << "Number of points read does not equal specified point count!";
return false;
}
}
// Compute motion properties
calculate();
setIsLoaded(true);
return true;
}