void Clustering::clusterConfidentIndices() {
int numConfidentIndices = detectionResult->confidentIndices.size();
std::vector<float> distances;
distances.resize(numConfidentIndices*(numConfidentIndices-1)/2);
calcDistances(distances.data());
std::vector<int> clusterIndices;
clusterIndices.resize(numConfidentIndices);
cluster(distances.data(), clusterIndices.data());
if(detectionResult->numClusters == 1) {
calcMeanRect(&detectionResult->confidentIndices);
//TODO: Take the maximum confidence as the result confidence.
}
}
void Clustering::clusterConfidentIndices() {
int numConfidentIndices = detectionResult->confidentIndices->size();
float * distances = new float[numConfidentIndices*(numConfidentIndices-1)/2];
calcDistances(distances);
int * clusterIndices = new int[numConfidentIndices];
cluster(distances, clusterIndices);
if(detectionResult->numClusters == 1) {
calcMeanRect(detectionResult->confidentIndices);
//TODO: Take the maximum confidence as the result confidence.
}
}
void Clustering::clusterConfidentIndices() {
size_t numConfidentIndices = detectionResult->confidentIndices->size();
size_t numDistances = numConfidentIndices * (numConfidentIndices - 1) / 2;
float* distances = new float[numDistances] {};
calcDistances(distances);
cluster(distances);
if (detectionResult->numClusters == 1) {
calcMeanRect(detectionResult->confidentIndices);
//TODO: Take the maximum confidence as the result confidence.
}
delete[]distances;
distances = NULL;
}