void MPIErrorValueCalculator::calculateErrorValue(ModelTuningParameters & params) {
vector< ModelTuningParameters > paramList(1);
paramList[0] = params;
calculateParallelErrorValue(paramList);
/// This is necessary because otherwise the error value is not transferred
/// since no reference is passed to calculateParallelErrorValue
params.setErrorValue(paramList[0].getErrorValue());
}
void
clientSimple::call(string const serverUrl,
string const methodName,
value * const resultP) {
carriageParm_http0 carriageParm(serverUrl);
rpcPtr rpcPtr(methodName, paramList());
rpcPtr->call(this->clientP.get(), &carriageParm);
*resultP = rpcPtr->getResult();
}
void invokeHelper(Param0 p0, Param1 p1) const
{
ArgList2<Param0, Param1> paramList(p0, p1);
return invokeDelegate(deleg_, stored_, paramList);
}
void invokeHelper(Param0 p0) const
{
ArgList1<Param0> paramList(p0);
return invokeDelegate(deleg_, stored_, paramList);
}
void invokeHelper(Param0 p0, Param1 p1, Param2 p2, Param3 p3, Param4 p4, Param5 p5, Param6 p6, Param7 p7) const
{
ArgList8<Param0, Param1, Param2, Param3, Param4, Param5, Param6, Param7> paramList(p0, p1, p2, p3, p4, p5, p6, p7);
return invokeDelegate(deleg_, stored_, paramList);
}
void invokeHelper(Param0 p0, Param1 p1, Param2 p2, Param3 p3, Param4 p4, Param5 p5) const
{
ArgList6<Param0, Param1, Param2, Param3, Param4, Param5> paramList(p0, p1, p2, p3, p4, p5);
return invokeDelegate(deleg_, stored_, paramList);
}
void invokeHelper(Param0 p0, Param1 p1, Param2 p2, Param3 p3) const
{
ArgList4<Param0, Param1, Param2, Param3> paramList(p0, p1, p2, p3);
return invokeDelegate(deleg_, stored_, paramList);
}
void invokeHelper(Param0 p0, Param1 p1, Param2 p2) const
{
ArgList3<Param0, Param1, Param2> paramList(p0, p1, p2);
return invokeDelegate(deleg_, stored_, paramList);
}
/************* Main *****************/
int main(int argc, char *argv[]){
try{
if(argc<3){
std::cout << "Wrong number of parameter";
paramList();
return 1;
}
int medianBlurKernelRadius = 1;
int bilateralRadius = 3;
float bilateralDistSigma = 1.5;
float bilateralWeightSigma = 0.03;
float saturationFactor = 1.5f;
float saturationOffset = 0.05f;
for(int p = 3; p < argc; ++p){
std::string param(argv[p]);
if(param.compare("-mr") == 0 && p < argc-1){
++p;
medianBlurKernelRadius = atoi(argv[p]);
}else if(param.compare("-br") == 0 && p < argc-1){
++p;
bilateralRadius = atoi(argv[p]);
}else if(param.compare("-bds") == 0 && p < argc-1){
++p;
bilateralDistSigma = atof(argv[p]);
}else if(param.compare("-bws") == 0 && p < argc-1){
++p;
bilateralWeightSigma = atof(argv[p]);
}else if(param.compare("-sf") == 0 && p < argc-1){
++p;
saturationFactor = atof(argv[p]);
}else if(param.compare("-so") == 0 && p < argc-1){
++p;
saturationOffset = atof(argv[p]);
}else{
std::cout << "Wrong parameter" << std::endl;
paramList();
return 3;
}
}
cv::Mat_<unsigned char> src = cv::imread(argv[1],CV_LOAD_IMAGE_GRAYSCALE);
cv::Mat_<unsigned char> elabImage = src.clone();
if(medianBlurKernelRadius>0){
medianBlurElab(elabImage,medianBlurKernelRadius);
cv::imwrite("medianBlur.png", elabImage);
}
std::vector<float> squaredColorWeight;
computeSquaredColorWeight(elabImage,squaredColorWeight);
logColumnMap(squaredColorWeight,elabImage.rows,"squaredColorWeights.png");
if(bilateralRadius > 0 && bilateralDistSigma > 0 && bilateralWeightSigma > 0){
bilateralFilterOnMap(squaredColorWeight,bilateralRadius,bilateralDistSigma,bilateralWeightSigma);
logColumnMap(squaredColorWeight,elabImage.rows,"bilateralWeights.png");
}
applyColumnMap(elabImage,squaredColorWeight,saturationOffset,saturationFactor);
cv::imwrite(argv[2], elabImage);
}catch(...){
return 2;
}
return 0;
}