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Code Issues Releases Wiki Activity

Warning fixes

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This commit is contained in:
Vlad Shakhuro
2015-08-07 16:12:59 +03:00
parent 81d44b7e22
commit 4b161803b4
3 changed files with 19 additions and 19 deletions
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22
modules/xobjdetect/src/waldboost.cpp
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@@ -84,7 +84,7 @@ static void compute_min_step(const Mat &data_pos, const Mat &data_neg, size_t n_
max(reduced_pos, reduced_neg, data_max);
data_max += 0.01;
data_step = (data_max - data_min) / (n_bins - 1);
data_step = (data_max - data_min) / (double)(n_bins - 1);
}
static void quantize_data(Mat &data, Mat1f &data_min, Mat1f &data_step)
@@ -132,15 +132,15 @@ void WaldBoost::detect(Ptr<CvFeatureEvaluator> eval,
float scale = scales[i];
resize(img, resized_img, Size(), scale, scale);
eval->setImage(resized_img, 0, 0, feature_indices_);
int n_rows = 24 / scale;
int n_cols = 24 / scale;
int n_rows = (int)(24 / scale);
int n_cols = (int)(24 / scale);
for (int r = 0; r + 24 < resized_img.rows; r += step) {
for (int c = 0; c + 24 < resized_img.cols; c += step) {
//eval->setImage(resized_img(Rect(c, r, 24, 24)), 0, 0);
eval->setWindow(Point(c, r));
if (predict(eval, &h) == +1) {
int row = r / scale;
int col = c / scale;
int row = (int)(r / scale);
int col = (int)(c / scale);
bboxes.push_back(Rect(col, row, n_cols, n_rows));
confidences.push_back(h);
}
@@ -164,14 +164,14 @@ void WaldBoost::detect(Ptr<CvFeatureEvaluator> eval,
float scale = scales[i];
resize(img, resized_img, Size(), scale, scale);
eval->setImage(resized_img, 0, 0, feature_indices_);
int n_rows = 24 / scale;
int n_cols = 24 / scale;
int n_rows = (int)(24 / scale);
int n_cols = (int)(24 / scale);
for (int r = 0; r + 24 < resized_img.rows; r += step) {
for (int c = 0; c + 24 < resized_img.cols; c += step) {
eval->setWindow(Point(c, r));
if (predict(eval, &h) == +1) {
int row = r / scale;
int col = c / scale;
int row = (int)(r / scale);
int col = (int)(c / scale);
bboxes.push_back(Rect(col, row, n_cols, n_rows));
confidences.push_back(h);
}
@@ -233,7 +233,7 @@ void WaldBoost::fit(Mat& data_pos, Mat& data_neg)
compute_cdf(data_pos.row(feat_i), pos_weights, pos_cdf);
compute_cdf(data_neg.row(feat_i), neg_weights, neg_cdf);
float neg_total = sum(neg_weights)[0];
float neg_total = (float)sum(neg_weights)[0];
Mat1f err_direct = pos_cdf + neg_total - neg_cdf;
Mat1f err_backward = 1.0f - err_direct;
@@ -265,7 +265,7 @@ void WaldBoost::fit(Mat& data_pos, Mat& data_neg)
}
float alpha = .5f * log((1 - min_err) / min_err);
float alpha = .5f * (float)log((1 - min_err) / min_err);
alphas_.push_back(alpha);
feature_indices_.push_back(min_feature_ind);
thresholds_.push_back(min_threshold);