void MulticlassEvaluator::evaluate(Learner& learner, DataSet& dataSet)
{
if(++iteration % interval == 0)
{
const int N = dataSet.samples();
double e = 0.0;
int correct = 0;
int wrong = 0;
Eigen::VectorXd temporaryOutput(dataSet.outputs());
for(int n = 0; n < N; n++)
{
Eigen::VectorXd y = learner(dataSet.getInstance(n));
temporaryOutput = dataSet.getTarget(n);
e += (y - temporaryOutput).squaredNorm();
int j1 = oneOfCDecoding(temporaryOutput);
int j2 = oneOfCDecoding(y);
if(j1 == j2)
correct++;
else
wrong++;
}
e /= N;
*logger << iteration << " " << e << " " << correct << " " << wrong << " "
<< stopwatch->stop(Stopwatch::MILLISECOND) << "\n";
}
}
void transformsChain::runTransform(
const ptr<image>& inputImage,
std::uint32_t inputTopLeftX, std::uint32_t inputTopLeftY, std::uint32_t inputWidth, std::uint32_t inputHeight,
const ptr<image>& outputImage,
std::uint32_t outputTopLeftX, std::uint32_t outputTopLeftY)
{
if(isEmpty())
{
ptr<transformHighBit> highBit(new transformHighBit);
highBit->runTransform(inputImage, inputTopLeftX, inputTopLeftY, inputWidth, inputHeight, outputImage, outputTopLeftX, outputTopLeftY);
return;
}
if(m_transformsList.size() == 1)
{
m_transformsList.front()->runTransform(inputImage, inputTopLeftX, inputTopLeftY, inputWidth, inputHeight,
outputImage, outputTopLeftX, outputTopLeftY);
return;
}
// Get the position of the last transform
///////////////////////////////////////////////////////////
tTransformsList::iterator lastTransform(m_transformsList.end());
--lastTransform;
std::wstring inputColorSpace(inputImage->getColorSpace());
image::bitDepth inputDepth(inputImage->getDepth());
std::uint32_t inputHighBit(inputImage->getHighBit());
std::wstring outputColorSpace(outputImage->getColorSpace());
image::bitDepth outputDepth(outputImage->getDepth());
std::uint32_t outputHighBit(outputImage->getHighBit());
std::uint32_t allocateRows = 65536 / inputWidth;
if(allocateRows < 1)
{
allocateRows = 1;
}
if(allocateRows > inputHeight)
{
allocateRows = inputHeight;
}
// Allocate temporary images
///////////////////////////////////////////////////////////
if(
m_inputWidth != inputWidth ||
m_inputHeight != inputHeight ||
m_inputColorSpace != inputColorSpace ||
m_inputDepth != inputDepth ||
m_inputHighBit != inputHighBit ||
m_outputColorSpace != outputColorSpace ||
m_outputDepth != outputDepth ||
m_outputHighBit != outputHighBit)
{
m_inputWidth = inputWidth;
m_inputHeight = inputHeight;
m_inputColorSpace = inputColorSpace;
m_inputDepth = inputDepth;
m_inputHighBit = inputHighBit;
m_outputColorSpace = outputColorSpace;
m_outputDepth = outputDepth;
m_outputHighBit = outputHighBit;
m_temporaryImages.clear();
tTransformsList::iterator scanTransforms(m_transformsList.begin());
m_temporaryImages.push_back((*scanTransforms)->allocateOutputImage(inputImage, inputWidth, allocateRows));
while(++scanTransforms != lastTransform)
{
m_temporaryImages.push_back((*scanTransforms)->allocateOutputImage(m_temporaryImages.back(), inputWidth, allocateRows));
}
}
// Run all the transforms. Split the images into several
// parts
///////////////////////////////////////////////////////////
while(inputHeight != 0)
{
std::uint32_t rows = allocateRows;
if(rows > inputHeight)
{
rows = inputHeight;
}
inputHeight -= rows;
tTransformsList::iterator scanTransforms(m_transformsList.begin());
tTemporaryImagesList::iterator scanTemporaryImages(m_temporaryImages.begin());
(*scanTransforms)->runTransform(inputImage, inputTopLeftX, inputTopLeftY, inputWidth, rows, *scanTemporaryImages, 0, 0);
inputTopLeftY += rows;
while(++scanTransforms != lastTransform)
{
ptr<image> temporaryInput(*(scanTemporaryImages++));
ptr<image> temporaryOutput(*scanTemporaryImages);
(*scanTransforms)->runTransform(temporaryInput, 0, 0, inputWidth, rows, temporaryOutput, 0, 0);
}
m_transformsList.back()->runTransform(*scanTemporaryImages, 0, 0, inputWidth, rows, outputImage, outputTopLeftX, outputTopLeftY);
outputTopLeftY += rows;
}
}