void ApplyNonMaximumSuppresion(std::vector< kstate >& in_source, float in_nms_threshold)
{
std::vector< kstate > tmp_source = in_source;
if (tmp_source.empty())
return ;
unsigned int size = in_source.size();
std::vector<float> area(size);
std::vector<float> scores(size);
std::vector<int> x1(size);
std::vector<int> y1(size);
std::vector<int> x2(size);
std::vector<int> y2(size);
std::vector<unsigned int> indices(size);
std::vector<bool> is_suppresed(size);
for(unsigned int i = 0; i< in_source.size(); i++)
{
kstate tmp = in_source[i];
area[i] = tmp.pos.width * tmp.pos.height;
indices[i] = i;
is_suppresed[i] = false;
scores[i] = tmp.score;
x1[i] = tmp.pos.x;
y1[i] = tmp.pos.y;
x2[i] = tmp.pos.width + tmp.pos.x;
y2[i] = tmp.pos.height + tmp.pos.y;
}
Sort(scores, indices);//returns indices ordered based on scores
for(unsigned int i=0; i< size; i++)
{
if(!is_suppresed[indices[i]])
{
for(unsigned int j= i+1; j< size; j++)
{
int x1_max = std::max(x1[indices[i]], x1[indices[j]]);
int x2_min = std::min(x2[indices[i]], x2[indices[j]]);
int y1_max = std::max(y1[indices[i]], y1[indices[j]]);
int y2_min = std::min(y2[indices[i]], y2[indices[j]]);
int overlap_width = x2_min - x1_max + 1;
int overlap_height = y2_min - y1_max + 1;
if(overlap_width > 0 && overlap_height>0)
{
float overlap_part = (overlap_width*overlap_height)/area[indices[j]];
if(overlap_part > in_nms_threshold)
{
is_suppresed[indices[j]] = true;
}
}
}
}
}
unsigned int size_out = 0;
for (unsigned int i = 0; i < size; i++)
{
if (!is_suppresed[i])
size_out++;
}
std::vector< kstate > filtered_detections(size_out);
unsigned int index = 0;
for(unsigned int i = 0 ; i < size_out; i++)
{
if(!is_suppresed[indices[i]])
{
filtered_detections[index] = in_source[indices[i]];//x1[indices[i]];
index++;
}
}
in_source = filtered_detections;
}
void ApplyNonMaximumSuppresion(std::vector< LkTracker* >& in_out_source, float in_nms_threshold)
{
if (in_out_source.empty())
return;
unsigned int size = in_out_source.size();
std::vector<float> area(size);
std::vector<float> scores(size);
std::vector<int> x1(size);
std::vector<int> y1(size);
std::vector<int> x2(size);
std::vector<int> y2(size);
std::vector<unsigned int> indices(size);
std::vector<bool> is_suppresed(size);
for(unsigned int i = 0; i< in_out_source.size(); i++)
{
cv::LatentSvmDetector::ObjectDetection tmp = in_out_source[i]->GetTrackedObject();
area[i] = tmp.rect.width * tmp.rect.height;
if (area[i]>0)
is_suppresed[i] = false;
else
{
is_suppresed[i] = true;
in_out_source[i]->NullifyLifespan();
}
indices[i] = i;
scores[i] = tmp.score;
x1[i] = tmp.rect.x;
y1[i] = tmp.rect.y;
x2[i] = tmp.rect.width + tmp.rect.x;
y2[i] = tmp.rect.height + tmp.rect.y;
}
Sort(area, indices);//returns indices ordered based on scores
for(unsigned int i=0; i< size; i++)
{
for(unsigned int j= i+1; j< size; j++)
{
if(is_suppresed[indices[i]] || is_suppresed[indices[j]])
continue;
int x1_max = std::max(x1[indices[i]], x1[indices[j]]);
int x2_min = std::min(x2[indices[i]], x2[indices[j]]);
int y1_max = std::max(y1[indices[i]], y1[indices[j]]);
int y2_min = std::min(y2[indices[i]], y2[indices[j]]);
int overlap_width = x2_min - x1_max + 1;
int overlap_height = y2_min - y1_max + 1;
if(overlap_width > 0 && overlap_height>0)
{
float overlap_part = (overlap_width*overlap_height)/area[indices[j]];
if(overlap_part > in_nms_threshold)
{
is_suppresed[indices[j]] = true;
in_out_source[indices[j]]->NullifyLifespan();
if (in_out_source[indices[j]]->GetFrameCount() > in_out_source[indices[i]]->GetFrameCount())
{
in_out_source[indices[i]]->object_id = in_out_source[indices[j]]->object_id;
}
}
}
}
}
return ;
}
