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fixed warnings under win32

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This commit is contained in:
Maria Dimashova
2010-11-26 10:35:48 +00:00
parent 337f1dd2fa
commit dfe4af9e1d
6 changed files with 32 additions and 32 deletions
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22
samples/cpp/bagofwords_classification.cpp
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@@ -861,7 +861,7 @@ void VocData::calcPrecRecall_impl(const vector<char>& ground_truth, const vector
recall[0] = 0;
for (size_t idx = 0; idx < ground_truth.size(); ++idx)
{
if (ground_truth[ranking[idx]] == true) ++retrieved_hits;
if (ground_truth[ranking[idx]] != 0) ++retrieved_hits;
precision[idx+1] = static_cast<float>(retrieved_hits)/static_cast<float>(idx+1);
recall[idx+1] = static_cast<float>(retrieved_hits)/static_cast<float>(recall_norm);
@@ -897,12 +897,12 @@ void VocData::calcPrecRecall_impl(const vector<char>& ground_truth, const vector
for (size_t idx = 0; idx < (recall.size()-1); ++idx)
{
ap += (recall[idx+1] - recall[idx])*precision_monot[idx+1] + //no need to take min of prec - is monotonically decreasing
0.5*(recall[idx+1] - recall[idx])*std::abs(precision_monot[idx+1] - precision_monot[idx]);
0.5f*(recall[idx+1] - recall[idx])*std::abs(precision_monot[idx+1] - precision_monot[idx]);
}
} else {
// FOR BEFORE VOC2010 AP IS CALCULATED BY SAMPLING PRECISION AT RECALL 0.0,0.1,..,1.0
for (float recall_pos = 0.0; recall_pos <= 1.0; recall_pos += 0.1)
for (float recall_pos = 0.f; recall_pos <= 1.f; recall_pos += 0.1f)
{
//find iterator of the precision corresponding to the first recall >= recall_pos
vector<float>::iterator recall_it = recall.begin();
@@ -1037,7 +1037,7 @@ void VocData::calcClassifierConfMatRow(const string& obj_class, const vector<Obd
/* convert iterator to index */
int class_idx = std::distance(output_headers.begin(),class_idx_it);
//add to confusion matrix row in proportion
output_values[class_idx] += 1.0/static_cast<float>(img_objects.size());
output_values[class_idx] += 1.f/static_cast<float>(img_objects.size());
}
}
//check break conditions if breaking on certain level of recall
@@ -1154,16 +1154,16 @@ void VocData::calcDetectorConfMatRow(const string& obj_class, const ObdDatasetTy
//find the ground truth object which has the highest overlap score with the detected object
float maxov = -1.0;
size_t max_gt_obj_idx = -1;
int max_gt_obj_idx = -1;
//-- for each detected object iterate through objects present in ground truth --
for (size_t gt_obj_idx = 0; gt_obj_idx < img_objects.size(); ++gt_obj_idx)
{
//check difficulty flag
if (ignore_difficult || (img_object_data[gt_obj_idx].difficult = false))
if (ignore_difficult || (img_object_data[gt_obj_idx].difficult == false))
{
//if the class matches, then check if the detected object and ground truth object overlap by a sufficient margin
int ov = testBoundingBoxesForOverlap(bounding_boxes_flat[ranking[image_idx]], img_objects[gt_obj_idx].boundingBox);
if (ov != -1.0)
float ov = testBoundingBoxesForOverlap(bounding_boxes_flat[ranking[image_idx]], img_objects[gt_obj_idx].boundingBox);
if (ov != -1.f)
{
//if all conditions are met store the overlap score and index (as objects are assigned to the highest scoring match)
if (ov > maxov)
@@ -1773,7 +1773,7 @@ bool VocData::getClassifierGroundTruthImage(const string& obj_class, const strin
if (it != m_classifier_gt_all_ids.end())
{
//image found, so return corresponding ground truth
return m_classifier_gt_all_present[std::distance(m_classifier_gt_all_ids.begin(),it)];
return m_classifier_gt_all_present[std::distance(m_classifier_gt_all_ids.begin(),it)] != 0;
} else {
string err_msg = "could not find classifier ground truth for image '" + id + "' and class '" + obj_class + "'";
CV_Error(CV_StsError,err_msg.c_str());
@@ -2015,9 +2015,7 @@ struct VocabTrainParams
struct SVMTrainParamsExt
{
SVMTrainParamsExt() : descPercent(0.5f), targetRatio(0.4f), balanceClasses(true) {}
SVMTrainParamsExt( float _descPercent, float _targetRatio, bool _balanceClasses,
int _svmType, int _kernelType, double _degree, double _gamma, double _coef0,
double _C, double _nu, double _p, Mat& _class_weights, TermCriteria _termCrit ) :
SVMTrainParamsExt( float _descPercent, float _targetRatio, bool _balanceClasses ) :
descPercent(_descPercent), targetRatio(_targetRatio), balanceClasses(_balanceClasses) {}
void read( const FileNode& fn )
{