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[CCV] Fixed mean fusion function

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Signed-off-by: Jim Martens <github@2martens.de>
This commit is contained in:
Jim Martens
2017-05-30 19:26:45 +02:00
parent e196aea379
commit 958b0b748c
1 changed files with 9 additions and 2 deletions
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11
ccv/saliency/fusion.cpp
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@ -49,15 +49,22 @@ cv::Mat mean_fusion_generic(const std::vector<cv::Mat> feature_maps) {
unsigned long number_of_features = feature_maps.size(); unsigned long number_of_features = feature_maps.size();
cv::Mat sum_of_features; cv::Mat sum_of_features;
double max = -1; double max = -1;
bool first_run = true;
for (auto& f : feature_maps) { for (auto& f : feature_maps) {
sum_of_features += f; if (first_run) {
sum_of_features = f.clone();
first_run = false;
}
else {
sum_of_features = sum_of_features + f;
}
double max_value; double max_value;
cv::minMaxLoc(f, nullptr, &max_value); cv::minMaxLoc(f, nullptr, &max_value);
if (max_value >= max) { if (max_value >= max) {
max = max_value; max = max_value;
} }
} }
cv::Mat C = 1/number_of_features * sum_of_features; cv::Mat C = 1./number_of_features * sum_of_features;
cv::normalize(C, C, 0, max, cv::NORM_MINMAX, -1); cv::normalize(C, C, 0, max, cv::NORM_MINMAX, -1);
return C.clone(); return C.clone();