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Merged the trunk r8589:8653 - all changes related to build warnings

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This commit is contained in:
Andrey Kamaev
2012-06-15 13:04:17 +00:00
parent 73c152abc4
commit bd0e0b5800
438 changed files with 20374 additions and 19674 deletions
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samples/c/mushroom.cpp
+18 -23
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@@ -2,9 +2,9 @@
#include "opencv2/ml/ml.hpp"
#include <stdio.h>
void help()
static void help()
{
printf("\nThis program demonstrated the use of OpenCV's decision tree function for learning and predicting data\n"
printf("\nThis program demonstrated the use of OpenCV's decision tree function for learning and predicting data\n"
"Usage :\n"
"./mushroom <path to agaricus-lepiota.data>\n"
"\n"
@@ -21,7 +21,7 @@ void help()
"// the values are encoded by characters.\n\n");
}
int mushroom_read_database( const char* filename, CvMat** data, CvMat** missing, CvMat** responses )
static int mushroom_read_database( const char* filename, CvMat** data, CvMat** missing, CvMat** responses )
{
const int M = 1024;
FILE* f = fopen( filename, "rt" );
@@ -95,7 +95,7 @@ int mushroom_read_database( const char* filename, CvMat** data, CvMat** missing,
}
CvDTree* mushroom_create_dtree( const CvMat* data, const CvMat* missing,
static CvDTree* mushroom_create_dtree( const CvMat* data, const CvMat* missing,
const CvMat* responses, float p_weight )
{
CvDTree* dtree;
@@ -107,7 +107,7 @@ CvDTree* mushroom_create_dtree( const CvMat* data, const CvMat* missing,
cvSet( var_type, cvScalarAll(CV_VAR_CATEGORICAL) ); // all the variables are categorical
dtree = new CvDTree;
dtree->train( data, CV_ROW_SAMPLE, responses, 0, 0, var_type, missing,
CvDTreeParams( 8, // max depth
10, // min sample count
@@ -179,7 +179,7 @@ static const char* var_desc[] =
};
void print_variable_importance( CvDTree* dtree, const char** var_desc )
static void print_variable_importance( CvDTree* dtree )
{
const CvMat* var_importance = dtree->get_var_importance();
int i;
@@ -201,21 +201,16 @@ void print_variable_importance( CvDTree* dtree, const char** var_desc )
for( i = 0; i < var_importance->cols*var_importance->rows; i++ )
{
double val = var_importance->data.db[i];
if( var_desc )
{
char buf[100];
int len = (int)(strchr( var_desc[i], '(' ) - var_desc[i] - 1);
strncpy( buf, var_desc[i], len );
buf[len] = '\0';
printf( "%s", buf );
}
else
printf( "var #%d", i );
char buf[100];
int len = (int)(strchr( var_desc[i], '(' ) - var_desc[i] - 1);
strncpy( buf, var_desc[i], len );
buf[len] = '\0';
printf( "%s", buf );
printf( ": %g%%\n", val*100. );
}
}
void interactive_classification( CvDTree* dtree, const char** var_desc )
static void interactive_classification( CvDTree* dtree )
{
char input[1000];
const CvDTreeNode* root;
@@ -230,14 +225,14 @@ void interactive_classification( CvDTree* dtree, const char** var_desc )
for(;;)
{
const CvDTreeNode* node;
printf( "Start/Proceed with interactive mushroom classification (y/n): " );
int values_read = scanf( "%1s", input );
CV_Assert(values_read == 1);
if( input[0] != 'y' && input[0] != 'Y' )
break;
printf( "Enter 1-letter answers, '?' for missing/unknown value...\n" );
printf( "Enter 1-letter answers, '?' for missing/unknown value...\n" );
// custom version of predict
node = root;
@@ -245,7 +240,7 @@ void interactive_classification( CvDTree* dtree, const char** var_desc )
{
CvDTreeSplit* split = node->split;
int dir = 0;
if( !node->left || node->Tn <= dtree->get_pruned_tree_idx() || !node->split )
break;
@@ -279,7 +274,7 @@ void interactive_classification( CvDTree* dtree, const char** var_desc )
else
printf( "Error: unrecognized value\n" );
}
if( !dir )
{
printf( "Impossible to classify the sample\n");
@@ -319,8 +314,8 @@ int main( int argc, char** argv )
cvReleaseMat( &missing );
cvReleaseMat( &responses );
print_variable_importance( dtree, var_desc );
interactive_classification( dtree, var_desc );
print_variable_importance( dtree );
interactive_classification( dtree );
delete dtree;
return 0;