Limited log window size

Digits

Layer.cpp

@@ -41,7 +41,7 @@ double Layer::getWeightedSum(size_t outputNeuron) const
 		sum += neuron.getWeightedOutputValue(outputNeuron);
 	}
 
-	return sum;
+    return sum / size();
 }
 
 void Layer::connectTo(const Layer & nextLayer)

gui/NeuroUI/errorplotter.cpp

@@ -28,6 +28,11 @@ void ErrorPlotter::clear()
 
 void ErrorPlotter::addErrorValue(double errorValue)
 {
+    if (m_errorValues.size() == m_bufferSize)
+    {
+        m_errorValues.pop_front();
+    }
+
     m_errorValues.push_back(errorValue);
     m_maxErrorValue = std::max<double>(m_maxErrorValue, errorValue);
 

gui/NeuroUI/errorplotter.h

@@ -11,6 +11,8 @@ private:
     std::list<double> m_errorValues;
     double m_maxErrorValue;
 
+    size_t m_bufferSize = 10000;
+
 public:
     explicit ErrorPlotter(QWidget *parent = 0);
 

gui/NeuroUI/mnistloader.cpp

@@ -8,6 +8,21 @@ void MnistLoader::load(const std::string &databaseFileName, const std::string &l
     loadLabels(labelsFileName);
 }
 
+size_t MnistLoader::getSamleCount() const
+{
+    return samples.size();
+}
+
+const MnistLoader::MnistSample &MnistLoader::getSample(size_t index) const
+{
+    if (index >= samples.size())
+    {
+        throw std::runtime_error("MNIST sample index out of range");
+    }
+
+    return *(samples[index].get());
+}
+
 const MnistLoader::MnistSample &MnistLoader::getRandomSample() const
 {
     size_t sampleIndex = (std::rand() * (samples.size() - 1)) / RAND_MAX;

gui/NeuroUI/mnistloader.h

@@ -6,6 +6,8 @@
 #include <memory>
 #include <inttypes.h>
 
+#include <QImage>
+
 class MnistLoader
 {
 private:
@@ -21,6 +23,11 @@ public:
     public:
         uint8_t label;
         uint8_t data[SAMPLE_WIDTH * SAMPLE_HEIGHT];
+
+        QImage toQImage() const
+        {
+            return QImage(data, SAMPLE_WIDTH, SAMPLE_HEIGHT, QImage::Format_Grayscale8);
+        }
     };
 
     using MnistSample = Sample<SampleWidth, SampleHeight>;
@@ -31,6 +38,8 @@ private:
 public:
     void load(const std::string &databaseFileName, const std::string &labelsFileName);
 
+    size_t getSamleCount() const;
+    const MnistSample &getSample(size_t index) const;
     const MnistSample &getRandomSample() const;
 
 private:

gui/NeuroUI/netlearner.cpp

@@ -24,12 +24,12 @@ void NetLearner::run()
         timer.start();
 
         size_t numIterations = 100000;
-        for (size_t iteration = 0; iteration < numIterations; ++iteration)
+        for (size_t iteration = 0; iteration < numIterations && cancel == false; ++iteration)
         {
             auto trainingSample = mnistLoader.getRandomSample();
 
-            QImage trainingImage(trainingSample.data, 28, 28, QImage::Format_Grayscale8);
+//            emit logMessage(QString("training sample ") + QString::number(trainingSample.label));
-            emit sampleImageLoaded(trainingImage);
+            emit sampleImageLoaded(trainingSample.toQImage());
 
             std::vector<double> targetValues =
             {
@@ -49,12 +49,7 @@ void NetLearner::run()
 
             double error = outputValues[0] - targetValues[0];
 
-            QString logString;
+            emit logMessage(QString("Error: ") + QString::number(std::abs(error)));
-
-            logString.append("Error: ");
-            logString.append(QString::number(std::abs(error)));
-
-            emit logMessage(logString);
             emit currentNetError(error);
             emit progress((double)iteration / (double)numIterations);
 
@@ -76,4 +71,11 @@ void NetLearner::run()
         logString.append(ex.what());
         emit logMessage(logString);
     }
+
+    cancel = false;
+}
+
+void NetLearner::cancelLearning()
+{
+    cancel = true;
 }

gui/NeuroUI/netlearner.h

@@ -7,6 +7,9 @@ class NetLearner : public QThread
 {
     Q_OBJECT
 
+private:
+    bool cancel = false;
+
 private:
     void run() Q_DECL_OVERRIDE;
 
@@ -15,6 +18,9 @@ signals:
     void progress(double progress);
     void currentNetError(double error);
     void sampleImageLoaded(const QImage &image);
+
+public slots:
+    void cancelLearning();
 };
 
 #endif // NETLEARNER_H

gui/NeuroUI/neuroui.cpp

@@ -12,6 +12,12 @@ NeuroUI::NeuroUI(QWidget *parent) :
 
 NeuroUI::~NeuroUI()
 {
+    if (m_netLearner != nullptr)
+    {
+        m_netLearner->cancelLearning();
+        m_netLearner->wait();
+    }
+
     delete ui;
 }
 
@@ -40,6 +46,11 @@ void NeuroUI::on_runButton_clicked()
 
 void NeuroUI::logMessage(const QString &logMessage)
 {
+    if (ui->logView->count() == static_cast<int>(m_logSize))
+    {
+        delete ui->logView->item(0);
+    }
+
     ui->logView->addItem(logMessage);
     ui->logView->scrollToBottom();
 }

gui/NeuroUI/neuroui.h

@@ -17,6 +17,7 @@ class NeuroUI : public QMainWindow
 
 private:
     std::unique_ptr<NetLearner> m_netLearner;
+    size_t m_logSize = 128;
 
 public:
     explicit NeuroUI(QWidget *parent = 0);