[kimageprocess-devel] kimageprocess/src/plugins/fann fann.cpp

[Herton R. K. <he...@us...>]

Update of /cvsroot/kimageprocess/kimageprocess/src/plugins/fann
In directory sc8-pr-cvs1.sourceforge.net:/tmp/cvs-serv1726/plugins/fann

Modified Files:
	fann.cpp 
Log Message:
- Reenabled fann plugin compilation.
- Fixing compiling problems on fann plugin.


Index: fann.cpp
===================================================================
RCS file: /cvsroot/kimageprocess/kimageprocess/src/plugins/fann/fann.cpp,v
retrieving revision 1.6
retrieving revision 1.7
diff -u -d -r1.6 -r1.7
--- fann.cpp	3 Jul 2005 00:31:40 -0000	1.6
+++ fann.cpp	3 Jul 2005 01:09:17 -0000	1.7
@@ -27,6 +27,7 @@
 
 #include <ktimage.h>
 #include <ktpluginmanager.h>
+#include <ktpatternmanager.h>
 
 K_EXPORT_COMPONENT_FACTORY( kimageprocess_fann,
                             KGenericFactory<KTFANNPlugin>( "kimageprocess_fann" ) )
@@ -35,7 +36,6 @@
  : KTClassifBackend(parent, name)
 {
     m_network = 0;
-    m_img = 0;
     m_iterations = 300000;
     m_hiddenLayers = 1;
     m_connectionRate = 1.0;
@@ -60,7 +60,7 @@
 
     //create the network
     unsigned int neurons[m_hiddenLayers + 2];
-    neurons[0] = inputs
+    neurons[0] = inputs;
     for ( int i=1; i < m_hiddenLayers; ++i ) {
         neurons[i] = inputs;
     }
@@ -72,35 +72,40 @@
     fann_set_activation_function_output(m_network, m_activationFunctionOutput);
 
     struct fann_train_data fanndata;
-    float *out;
-    float error = 0.0;
+    float *in, *out;
 
+    in = new float[data.count() * inputs];
     out = new float[data.count() * outputs];
     fanndata.num_data = data.count();
     fanndata.num_input = inputs;
     fanndata.num_output = outputs;
     fanndata.input = new float*[data.count()];
     fanndata.output = new float*[data.count()];
-    for ( int i=0; i < data.count(); ++i )
+    for ( unsigned int i=0; i < data.count(); ++i )
     {
+        fanndata.input[i] = in + i * inputs;
         fanndata.output[i] = out + i * outputs;
-        for ( int j=0; j < m_output; ++j )
+        for ( int j=0; j < outputs; ++j )
         {
             fanndata.output[i][j] = 0;
         }
     }
 
     QValueList<dataEntry>::ConstIterator end = data.constEnd();
+    int c = 0;
 
-    for ( QValueList<dataEntry>::ConstIterator it = data.constBegin(), int c=0; it != end; ++it, ++c )
+    for ( QValueList<dataEntry>::ConstIterator it = data.constBegin(); it != end; ++it )
     {
-        fanndata.inputs[c] = (*it).inputs;
+        for ( int i=0; i < inputs; ++i )
+            fanndata.input[c][i] = (*it).inputs[i];
         fanndata.output[c][(*it).sampleClass-1] = 1;
+        c++;
     }
     fann_init_weights(m_network, &fanndata);
     fann_train_on_data(m_network, &fanndata, m_iterations, m_iterations / 100, m_desiredError);
 
     //clear data
+    delete in;
     delete out;
     delete fanndata.input;
     delete fanndata.output;
@@ -113,23 +118,26 @@
 
     KTImage *c_img = KTImageManager::self()->testingImage();
     QImage *img = new QImage(c_img->width(), c_img->height(), 32);
-    float *outputs;
+    float input[inputs];
+    float *output;
     QValueList<dataEntry>::ConstIterator end = data.constEnd();
-    int x = 0, y = 0;
+    int x = 0, y = 0, i = 0;
     int colorStep = 255 / (outputs - 1);
     int level;
 
-    for ( QValueList<dataEntry>::ConstIterator it = data.constBegin(), int i=0; it != end; ++it, ++i )
+    for ( QValueList<dataEntry>::ConstIterator it = data.constBegin(); it != end; ++it )
     {
-        outputs = fann_run(m_network, (*it).inputs);
+        for ( int j=0; j < inputs; ++j )
+            input[j] = (*it).inputs[j];
+        output = fann_run(m_network, input);
         int maxclass = 0;
-        int maxvalue = outputs[0];
+        float maxvalue = output[0];
         for ( int j=1; j < outputs; ++j )
         {
-            if (outputs[j] > maxvalue)
+            if (output[j] > maxvalue)
             {
                 maxclass = j;
-                maxvalue = outputs[j];
+                maxvalue = output[j];
             }
         }
         level = maxclass * colorStep;
@@ -139,6 +147,7 @@
             x = 0;
             y++;
         }
+        i++;
     }
 
     //save the image
@@ -148,7 +157,7 @@
     {
         KTempFile tmpImg(QString::null, ".pgm");
         tmpImg.close();
-        m_img->save(tmpImg.name(), "PGM");
+        img->save(tmpImg.name(), "PGM");
         KIO::NetAccess::upload(tmpImg.name(), dest, 0);
         KIO::NetAccess::removeTempFile(tmpImg.name());
     }