void GAB::MiningNeg(int n,DataSet& neg){
const Options& opt = Options::GetInstance();
int pool_size = opt.numThreads;
vector<Mat> region_pool(pool_size);
int st = neg.imgs.size();
int all = 0;
int need = n - st;
double rate;
while(st<n){
#pragma omp parallel for
for(int i = 0;i<pool_size;i++){
region_pool[i] = neg.NextImage(i);
}
#pragma omp parallel for
for (int i = 0; i < pool_size; i++) {
float score = 0;
if(NPDClassify(region_pool[i].clone(),score)){
#pragma omp critical
{
neg.imgs.push_back(region_pool[i].clone());
neg.Fx[st]=score;
if(opt.generate_hd){
char di[256];
sprintf(di,"../data/hd/%d.jpg",st);
imwrite(di,region_pool[i].clone());
}
st++;
}
}
all++;
}
}
neg.size = n;
rate = ((double)(need))/(double)all;
printf("mining success rate %lf\n",rate);
}
