generic-library/opencv
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Set stricter warning rules for gcc

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This commit is contained in:
Andrey Kamaev
2012-06-07 17:21:29 +00:00
parent 0395f7c63f
commit 49a1ba6038
241 changed files with 9054 additions and 8947 deletions
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46
modules/ml/src/svm.cpp
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@@ -88,7 +88,7 @@ using namespace cv;
#include <stdarg.h>
#include <ctype.h>
#if _MSC_VER >= 1200
#if defined _MSC_VER && _MSC_VER >= 1200
#pragma warning( disable: 4514 ) /* unreferenced inline functions */
#endif
@@ -1593,7 +1593,7 @@ bool CvSVM::train( const CvMat* _train_data, const CvMat* _responses,
return ok;
}
struct indexedratio
struct indexedratio
{
double val;
int ind;
@@ -1774,7 +1774,7 @@ bool CvSVM::train_auto( const CvMat* _train_data, const CvMat* _responses,
else
CV_SWAP( responses->data.i[i1], responses->data.i[i2], y );
}
if (!is_regression && class_labels->cols==2 && balanced)
{
// count class samples
@@ -1786,13 +1786,13 @@ bool CvSVM::train_auto( const CvMat* _train_data, const CvMat* _responses,
else
++num_1;
}
int label_smallest_class;
int label_biggest_class;
if (num_0 < num_1)
{
label_biggest_class = class_labels->data.i[1];
label_smallest_class = class_labels->data.i[0];
label_smallest_class = class_labels->data.i[0];
}
else
{
@@ -2001,7 +2001,7 @@ float CvSVM::predict( const float* row_sample, int row_len, bool returnDFVal ) c
int var_count = get_var_count();
assert( row_len == var_count );
(void)row_len;
(void)row_len;
int class_count = class_labels ? class_labels->cols :
params.svm_type == ONE_CLASS ? 1 : 0;
@@ -2072,7 +2072,7 @@ float CvSVM::predict( const CvMat* sample, bool returnDFVal ) const
__BEGIN__;
int class_count;
if( !kernel )
CV_ERROR( CV_StsBadArg, "The SVM should be trained first" );
@@ -2082,7 +2082,7 @@ float CvSVM::predict( const CvMat* sample, bool returnDFVal ) const
CV_CALL( cvPreparePredictData( sample, var_all, var_idx,
class_count, 0, &row_sample ));
result = predict( row_sample, get_var_count(), returnDFVal );
__END__;
if( sample && (!CV_IS_MAT(sample) || sample->data.fl != row_sample) )
@@ -2099,12 +2099,12 @@ struct predict_body_svm {
samples = _samples;
results = _results;
}
const CvSVM* pointer;
float* result;
const CvMat* samples;
CvMat* results;
void operator()( const cv::BlockedRange& range ) const
{
for(int i = range.begin(); i < range.end(); i++ )
@@ -2116,15 +2116,15 @@ struct predict_body_svm {
results->data.fl[i] = (float)r;
if (i == 0)
*result = (float)r;
}
}
}
};
float CvSVM::predict(const CvMat* samples, CV_OUT CvMat* results) const
{
float result = 0;
cv::parallel_for(cv::BlockedRange(0, samples->rows),
predict_body_svm(this, &result, samples, results)
cv::parallel_for(cv::BlockedRange(0, samples->rows),
predict_body_svm(this, &result, samples, results)
);
return result;
}
@@ -2141,7 +2141,7 @@ CvSVM::CvSVM( const Mat& _train_data, const Mat& _responses,
kernel = 0;
solver = 0;
default_model_name = "my_svm";
train( _train_data, _responses, _var_idx, _sample_idx, _params );
}
@@ -2166,7 +2166,7 @@ bool CvSVM::train_auto( const Mat& _train_data, const Mat& _responses,
float CvSVM::predict( const Mat& _sample, bool returnDFVal ) const
{
CvMat sample = _sample;
CvMat sample = _sample;
return predict(&sample, returnDFVal);
}
@@ -2648,11 +2648,11 @@ cvTrainSVM_CrossValidation( const CvMat* train_data, int tflag,
__BEGIN__;
double degree_step = 7,
g_step = 15,
coef_step = 14,
C_step = 20,
nu_step = 5,
p_step = 7; // all steps must be > 1
g_step = 15,
coef_step = 14,
C_step = 20,
nu_step = 5,
p_step = 7; // all steps must be > 1
double degree_begin = 0.01, degree_end = 2;
double g_begin = 1e-5, g_end = 0.5;
double coef_begin = 0.1, coef_end = 300;
@@ -2662,12 +2662,12 @@ cvTrainSVM_CrossValidation( const CvMat* train_data, int tflag,
double rate = 0, gamma = 0, C = 0, degree = 0, coef = 0, p = 0, nu = 0;
double best_rate = 0;
double best_rate = 0;
double best_degree = degree_begin;
double best_gamma = g_begin;
double best_coef = coef_begin;
double best_C = C_begin;
double best_nu = nu_begin;
double best_C = C_begin;
double best_nu = nu_begin;
double best_p = p_begin;
CvSVMModelParams svm_params, *psvm_params;