コード例 #1
0
// Training SVM with feature vector X and label Y. 
// Each row of X is a feature vector, with corresponding label in Y.
// Return a CV_32F weight Mat
Mat Objectness::trainSVM(CMat &X1f, const vecI &Y, int sT, double C, double bias, double eps)
{
	// Set SVM parameters
	parameter param; {
		param.solver_type = sT; // L2R_L2LOSS_SVC_DUAL;
		param.C = C;
		param.eps = eps; // see setting below
		param.p = 0.1;
		param.nr_weight = 0;
		param.weight_label = NULL;
		param.weight = NULL;
		set_print_string_function(print_null);
		CV_Assert(X1f.rows == Y.size() && X1f.type() == CV_32F);
	}

	// Initialize a problem
	feature_node *x_space = NULL;
	problem prob;{
		prob.l = X1f.rows;
		prob.bias = bias;
		prob.y = Malloc(double, prob.l);
		prob.x = Malloc(feature_node*, prob.l);
		const int DIM_FEA = X1f.cols;
		prob.n = DIM_FEA + (bias >= 0 ? 1 : 0);
		x_space = Malloc(feature_node, (prob.n + 1) * prob.l);
		int j = 0;
		for (int i = 0; i < prob.l; i++){
			prob.y[i] = Y[i];
			prob.x[i] = &x_space[j];
			const float* xData = X1f.ptr<float>(i);
			for (int k = 0; k < DIM_FEA; k++){
				x_space[j].index = k + 1;
				x_space[j++].value = xData[k];
			}
			if (bias >= 0){
				x_space[j].index = prob.n;
				x_space[j++].value = bias;
			}
			x_space[j++].index = -1;
		}
		CV_Assert(j == (prob.n + 1) * prob.l);
	}

	// Training SVM for current problem
	const char*  error_msg = check_parameter(&prob, &param);
	if(error_msg){
		fprintf(stderr,"ERROR: %s\n",error_msg);
		exit(1);
	}
	model *svmModel = train(&prob, &param);
	Mat wMat(1, prob.n, CV_64F, svmModel->w);
	wMat.convertTo(wMat, CV_32F);
	free_and_destroy_model(&svmModel);
	destroy_param(&param);
	free(prob.y);
	free(prob.x);
	free(x_space);
	return wMat;
}
コード例 #2
0
bool isLucky(vecI mv){
	int cont;
	int n = mv.size();
	for(int  i = 0; i < n; i++)
	{
		if(mv[i]== 4 or mv[i] == 7)
			cont++;
	}
	if(cont == n) return true;
		else return false;
}
コード例 #3
0
ファイル: CmAPCluster.cpp プロジェクト: 20083017/CmCode
int CmAPCluster::ReMapIdx(vecI &mapIdx)
{
	int N = (int)mapIdx.size(), newCount = 0;
	map<int, int> idxCount, oldNewIdx;
	vecI newIdx(N);
	for (int i = 0; i < N; i++){
		if (idxCount.find(mapIdx[i]) == idxCount.end())
			oldNewIdx[mapIdx[i]] = newCount++, idxCount[mapIdx[i]]++;
		mapIdx[i] = oldNewIdx[mapIdx[i]];
	}
	return (int)idxCount.size();
}
コード例 #4
0
ファイル: DataSetVOC.cpp プロジェクト: DraculaIII/Objectness
void DataSetVOC::loadBox(const FileNode &fn, vector<Vec4i> &boxes, vecI &clsIdx){
	string isDifficult;
	fn["difficult"]>>isDifficult;
	if (isDifficult == "1")
		return; 

	string strXmin, strYmin, strXmax, strYmax;
	fn["bndbox"]["xmin"] >> strXmin;
	fn["bndbox"]["ymin"] >> strYmin;
	fn["bndbox"]["xmax"] >> strXmax;
	fn["bndbox"]["ymax"] >> strYmax;
	boxes.push_back(Vec4i(atoi(_S(strXmin)), atoi(_S(strYmin)), atoi(_S(strXmax)), atoi(_S(strYmax))));

	string clsName;
	fn["name"]>>clsName;
	clsIdx.push_back(findFromList(clsName, classNames));	
	CV_Assert_(clsIdx[clsIdx.size() - 1] >= 0, ("Invalidate class name\n"));
}