void QueryClusterer::MergeClusters() {
// Merge two clusters that are within the threshold in similarity
// Iterate from left to right and merge the left one into right one and mark
// the left one for deletion
std::vector<Cluster *> to_delete;
for (auto i = clusters_.begin(); i != clusters_.end(); i++) {
for (auto j = i; ++j != clusters_.end();) {
auto left = *i;
auto right = *j;
auto r_centroid = right->GetCentroid();
auto similarity = left->CosineSimilarity(r_centroid);
if (similarity > threshold_) {
auto templates = left->GetTemplates();
for (auto &fingerprint : templates) {
right->AddTemplate(fingerprint);
template_cluster_[fingerprint] = right;
}
right->UpdateCentroid(features_);
to_delete.push_back(left);
break;
}
}
}
// Delete the clusters that are empty
for (auto cluster : to_delete) {
clusters_.erase(cluster);
delete cluster;
}
// Rebuild the KDTree to account for changed clusters
kd_tree_.Build(clusters_);
}
std::vector<TemplateDescriptor>TemplateDescriptor::GetTemplateList(
const string & userId,
IAuthenticationCallback& authenticationCallback)
{
TIterable<TemplateDescriptor> result;
auto authenticationCallbackImpl =
AuthenticationCallbackImpl { authenticationCallback, userId };
auto pTemplatesClient = ITemplatesClient::Create();
auto response = pTemplatesClient->GetTemplates(
authenticationCallbackImpl,
userId);
for_each(
begin(response.templates),
end(response.templates),
[&](const TemplateResponse& templateResponse)
{
result.push_back(move(TemplateDescriptor(templateResponse.id,
templateResponse.name,
templateResponse.description)));
});
return result;
}
void
GusdOBJ_usdcamera::Register(OP_OperatorTable* table)
{
OP_Operator* op = new OP_Operator("pixar::usdcamera",
"USD Camera",
creator,
GetTemplates(),
#if UT_MAJOR_VERSION_INT >= 16
SOP_TABLE_NAME,
#endif
/* min inputs*/ 0,
/* max inputs*/ 1,
GetVariables());
op->setIconName("pxh_gusdIcon.png");
op->setOpTabSubMenuPath( "Pixar" );
table->addOperator(op);
table->setOpFirstName("pixar::usdcamera", "usdcam");
}
