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sebastic-guest pushed a commit to branch upstream-master
in repository pktools.
commit 8f2c83b00c79924faa51b65434cc134e42faace4
Author: Pieter Kempeneers <kempe...@gmail.com>
Date: Sat Jan 4 21:36:07 2014 +0100
redundant ilayer loop in readDataImageShape in ImgReaderOgr.cc
---
src/apps/pkclassify_nn.cc | 230 +++++++++++++++++----------------
src/apps/pkclassify_svm.cc | 272 ++++++++++++++++++++-------------------
src/apps/pkextract.cc | 2 +-
src/imageclasses/ImgReaderOgr.cc | 104 +++++++--------
src/imageclasses/ImgReaderOgr.h | 1 +
5 files changed, 315 insertions(+), 294 deletions(-)
diff --git a/src/apps/pkclassify_nn.cc b/src/apps/pkclassify_nn.cc
index e369096..3fadf15 100644
--- a/src/apps/pkclassify_nn.cc
+++ b/src/apps/pkclassify_nn.cc
@@ -981,121 +981,131 @@ int main(int argc, char *argv[])
else
imgWriterOgr.createField("class",OFTString);
}
- OGRFeature *poFeature;
- unsigned int ifeature=0;
- unsigned int nFeatures=imgReaderOgr.getFeatureCount();
- while( (poFeature = imgReaderOgr.getLayer()->GetNextFeature()) != NULL ){
- if(verbose_opt[0]>1)
- cout << "feature " << ifeature << endl;
- if( poFeature == NULL )
- break;
- OGRFeature *poDstFeature = NULL;
- if(output_opt.size()){
- poDstFeature=imgWriterOgr.createFeature();
- if( poDstFeature->SetFrom( poFeature, TRUE ) != OGRERR_NONE ){
- CPLError( CE_Failure, CPLE_AppDefined,
- "Unable to translate feature %d from layer %s.\n",
- poFeature->GetFID(), imgWriterOgr.getLayerName().c_str()
);
- OGRFeature::DestroyFeature( poFeature );
- OGRFeature::DestroyFeature( poDstFeature );
- }
- }
- vector<float> validationPixel;
- vector<float> validationFeature;
+ if(verbose_opt[0])
+ cout << "number of layers in input ogr file: " <<
imgReaderOgr.getLayerCount() << endl;
+ for(int ilayer=0;ilayer<imgReaderOgr.getLayerCount();++ilayer){
+ if(verbose_opt[0])
+ cout << "processing input layer " << ilayer << endl;
+ unsigned int nFeatures=imgReaderOgr.getFeatureCount(ilayer);
+ unsigned int ifeature=0;
+ progress=0;
+ pfnProgress(progress,pszMessage,pProgressArg);
+ OGRFeature *poFeature;
+ while( (poFeature = imgReaderOgr.getLayer(ilayer)->GetNextFeature()) !=
NULL ){
+ if(verbose_opt[0]>1)
+ cout << "feature " << ifeature << endl;
+ if( poFeature == NULL ){
+ cout << "Warning: could not read feature " << ifeature << " in
layer " << imgReaderOgr.getLayerName(ilayer) << endl;
+ continue;
+ }
+ OGRFeature *poDstFeature = NULL;
+ if(output_opt.size()){
+ poDstFeature=imgWriterOgr.createFeature();
+ if( poDstFeature->SetFrom( poFeature, TRUE ) != OGRERR_NONE ){
+ CPLError( CE_Failure, CPLE_AppDefined,
+ "Unable to translate feature %d from layer %s.\n",
+ poFeature->GetFID(),
imgWriterOgr.getLayerName().c_str() );
+ OGRFeature::DestroyFeature( poFeature );
+ OGRFeature::DestroyFeature( poDstFeature );
+ }
+ }
+ vector<float> validationPixel;
+ vector<float> validationFeature;
- imgReaderOgr.readData(validationPixel,OFTReal,fields,poFeature);
- assert(validationPixel.size()==nband);
- vector<float> probOut(nclass);//posterior prob for each class
- for(int iclass=0;iclass<nclass;++iclass)
- probOut[iclass]=0;
- for(int ibag=0;ibag<nbag;++ibag){
- for(int iband=0;iband<nband;++iband){
-
validationFeature.push_back((validationPixel[iband]-offset[ibag][iband])/scale[ibag][iband]);
- if(verbose_opt[0]==2)
- std:: cout << " " << validationFeature.back();
- }
- if(verbose_opt[0]==2)
- std::cout << std:: endl;
- vector<float> result(nclass);
- result=net[ibag].run(validationFeature);
+
imgReaderOgr.readData(validationPixel,OFTReal,fields,poFeature,ilayer);
+ assert(validationPixel.size()==nband);
+ vector<float> probOut(nclass);//posterior prob for each class
+ for(int iclass=0;iclass<nclass;++iclass)
+ probOut[iclass]=0;
+ for(int ibag=0;ibag<nbag;++ibag){
+ for(int iband=0;iband<nband;++iband){
+
validationFeature.push_back((validationPixel[iband]-offset[ibag][iband])/scale[ibag][iband]);
+ if(verbose_opt[0]==2)
+ std:: cout << " " << validationFeature.back();
+ }
+ if(verbose_opt[0]==2)
+ std::cout << std:: endl;
+ vector<float> result(nclass);
+ result=net[ibag].run(validationFeature);
- if(verbose_opt[0]>1){
- for(int iclass=0;iclass<result.size();++iclass)
- std::cout << result[iclass] << " ";
- std::cout << std::endl;
- }
- //calculate posterior prob of bag
- for(int iclass=0;iclass<nclass;++iclass){
- result[iclass]=(result[iclass]+1.0)/2.0;//bring back to scale [0,1]
- switch(comb_opt[0]){
- default:
- case(0)://sum rule
- probOut[iclass]+=result[iclass]*priors[iclass];//add
probabilities for each bag
- break;
- case(1)://product rule
-
probOut[iclass]*=pow(priors[iclass],static_cast<float>(1.0-nbag)/nbag)*result[iclass];//multiply
probabilities for each bag
+ if(verbose_opt[0]>1){
+ for(int iclass=0;iclass<result.size();++iclass)
+ std::cout << result[iclass] << " ";
+ std::cout << std::endl;
+ }
+ //calculate posterior prob of bag
+ for(int iclass=0;iclass<nclass;++iclass){
+ result[iclass]=(result[iclass]+1.0)/2.0;//bring back to scale
[0,1]
+ switch(comb_opt[0]){
+ default:
+ case(0)://sum rule
+ probOut[iclass]+=result[iclass]*priors[iclass];//add
probabilities for each bag
break;
- case(2)://max rule
- if(priors[iclass]*result[iclass]>probOut[iclass])
- probOut[iclass]=priors[iclass]*result[iclass];
- break;
- }
- }
- }//for ibag
- //search for max class prob
- float maxBag=0;
- float normBag=0;
- string classOut="Unclassified";
- for(int iclass=0;iclass<nclass;++iclass){
- if(verbose_opt[0]>1)
- std::cout << probOut[iclass] << " ";
- if(probOut[iclass]>maxBag){
- maxBag=probOut[iclass];
- classOut=nameVector[iclass];
- }
- }
- //look for class name
- if(verbose_opt[0]>1){
- if(classValueMap.size())
- std::cout << "->" << classValueMap[classOut] << std::endl;
- else
- std::cout << "->" << classOut << std::endl;
- }
- if(output_opt.size()){
- if(classValueMap.size())
- poDstFeature->SetField("class",classValueMap[classOut]);
- else
- poDstFeature->SetField("class",classOut.c_str());
- poDstFeature->SetFID( poFeature->GetFID() );
- }
- int labelIndex=poFeature->GetFieldIndex(label_opt[0].c_str());
- if(labelIndex>=0){
- string classRef=poFeature->GetFieldAsString(labelIndex);
- if(classRef!="0"){
+ case(1)://product rule
+
probOut[iclass]*=pow(priors[iclass],static_cast<float>(1.0-nbag)/nbag)*result[iclass];//multiply
probabilities for each bag
+ break;
+ case(2)://max rule
+ if(priors[iclass]*result[iclass]>probOut[iclass])
+ probOut[iclass]=priors[iclass]*result[iclass];
+ break;
+ }
+ }
+ }//for ibag
+ //search for max class prob
+ float maxBag=0;
+ float normBag=0;
+ string classOut="Unclassified";
+ for(int iclass=0;iclass<nclass;++iclass){
+ if(verbose_opt[0]>1)
+ std::cout << probOut[iclass] << " ";
+ if(probOut[iclass]>maxBag){
+ maxBag=probOut[iclass];
+ classOut=nameVector[iclass];
+ }
+ }
+ //look for class name
+ if(verbose_opt[0]>1){
if(classValueMap.size())
-
cm.incrementResult(type2string<short>(classValueMap[classRef]),type2string<short>(classValueMap[classOut]),1);
- else
- cm.incrementResult(classRef,classOut,1);
+ std::cout << "->" << classValueMap[classOut] << std::endl;
+ else
+ std::cout << "->" << classOut << std::endl;
}
- }
- CPLErrorReset();
- if(output_opt.size()){
- if(imgWriterOgr.createFeature( poDstFeature ) != OGRERR_NONE){
- CPLError( CE_Failure, CPLE_AppDefined,
- "Unable to translate feature %d from layer %s.\n",
- poFeature->GetFID(), imgWriterOgr.getLayerName().c_str()
);
- OGRFeature::DestroyFeature( poDstFeature );
- OGRFeature::DestroyFeature( poDstFeature );
- }
- }
- ++ifeature;
- if(!verbose_opt[0]){
- progress=static_cast<float>(ifeature+1.0)/nFeatures;
- pfnProgress(progress,pszMessage,pProgressArg);
- }
- OGRFeature::DestroyFeature( poFeature );
- OGRFeature::DestroyFeature( poDstFeature );
- }
+ if(output_opt.size()){
+ if(classValueMap.size())
+ poDstFeature->SetField("class",classValueMap[classOut]);
+ else
+ poDstFeature->SetField("class",classOut.c_str());
+ poDstFeature->SetFID( poFeature->GetFID() );
+ }
+ int labelIndex=poFeature->GetFieldIndex(label_opt[0].c_str());
+ if(labelIndex>=0){
+ string classRef=poFeature->GetFieldAsString(labelIndex);
+ if(classRef!="0"){
+ if(classValueMap.size())
+
cm.incrementResult(type2string<short>(classValueMap[classRef]),type2string<short>(classValueMap[classOut]),1);
+ else
+ cm.incrementResult(classRef,classOut,1);
+ }
+ }
+ CPLErrorReset();
+ if(output_opt.size()){
+ if(imgWriterOgr.createFeature( poDstFeature ) != OGRERR_NONE){
+ CPLError( CE_Failure, CPLE_AppDefined,
+ "Unable to translate feature %d from layer %s.\n",
+ poFeature->GetFID(),
imgWriterOgr.getLayerName().c_str() );
+ OGRFeature::DestroyFeature( poDstFeature );
+ OGRFeature::DestroyFeature( poDstFeature );
+ }
+ }
+ ++ifeature;
+ if(!verbose_opt[0]){
+ progress=static_cast<float>(ifeature+1.0)/nFeatures;
+ pfnProgress(progress,pszMessage,pProgressArg);
+ }
+ OGRFeature::DestroyFeature( poFeature );
+ OGRFeature::DestroyFeature( poDstFeature );
+ }//get next feature
+ }//next layer
imgReaderOgr.close();
if(output_opt.size())
imgWriterOgr.close();
diff --git a/src/apps/pkclassify_svm.cc b/src/apps/pkclassify_svm.cc
index 8a1512c..1ed2ffa 100644
--- a/src/apps/pkclassify_svm.cc
+++ b/src/apps/pkclassify_svm.cc
@@ -57,7 +57,7 @@ int main(int argc, char *argv[])
Optionpk<short> band_opt("b", "band", "band index (starting from 0, either
use band option or use start to end)");
Optionpk<double> offset_opt("\0", "offset", "offset value for each spectral
band input features: refl[band]=(DN[band]-offset[band])/scale[band]", 0.0);
Optionpk<double> scale_opt("\0", "scale", "scale value for each spectral
band input features: refl=(DN[band]-offset[band])/scale[band] (use 0 if scale
min and max in each band to -1.0 and 1.0)", 0.0);
- Optionpk<double> priors_opt("p", "prior", "prior probabilities for each
class (e.g., -p 0.3 -p 0.3 -p 0.2 )", 0.0);
+ Optionpk<double> priors_opt("p", "prior", "prior probabilities for each
class (e.g., -p 0.3 -p 0.3 -p 0.2 ). Used for input only (ignored for cross
validation)", 0.0);
Optionpk<string> priorimg_opt("pim", "priorimg", "prior probability image
(multi-band img with band for each class");
Optionpk<unsigned short> cv_opt("cv", "cv", "n-fold cross validation
mode",0);
Optionpk<std::string> svm_type_opt("svmt", "svmtype", "type of SVM (C_SVC,
nu_SVC,one_class, epsilon_SVR, nu_SVR)","C_SVC");
@@ -979,144 +979,154 @@ int main(int argc, char *argv[])
else
imgWriterOgr.createField("class",OFTString);
}
- OGRFeature *poFeature;
- unsigned int ifeature=0;
- unsigned int nFeatures=imgReaderOgr.getFeatureCount();
- while( (poFeature = imgReaderOgr.getLayer()->GetNextFeature()) != NULL ){
- if(verbose_opt[0]>1)
- std::cout << "feature " << ifeature << std::endl;
- if( poFeature == NULL )
- break;
- OGRFeature *poDstFeature = NULL;
- if(output_opt.size()){
- poDstFeature=imgWriterOgr.createFeature();
- if( poDstFeature->SetFrom( poFeature, TRUE ) != OGRERR_NONE ){
- CPLError( CE_Failure, CPLE_AppDefined,
- "Unable to translate feature %d from layer %s.\n",
- poFeature->GetFID(), imgWriterOgr.getLayerName().c_str()
);
- OGRFeature::DestroyFeature( poFeature );
- OGRFeature::DestroyFeature( poDstFeature );
+ if(verbose_opt[0])
+ cout << "number of layers in input ogr file: " <<
imgReaderOgr.getLayerCount() << endl;
+ for(int ilayer=0;ilayer<imgReaderOgr.getLayerCount();++ilayer){
+ if(verbose_opt[0])
+ cout << "processing input layer " << ilayer << endl;
+ unsigned int nFeatures=imgReaderOgr.getFeatureCount(ilayer);
+ unsigned int ifeature=0;
+ progress=0;
+ pfnProgress(progress,pszMessage,pProgressArg);
+ OGRFeature *poFeature;
+ while( (poFeature = imgReaderOgr.getLayer(ilayer)->GetNextFeature()) !=
NULL ){
+ if(verbose_opt[0]>1)
+ std::cout << "feature " << ifeature << std::endl;
+ if( poFeature == NULL ){
+ cout << "Warning: could not read feature " << ifeature << " in
layer " << imgReaderOgr.getLayerName(ilayer) << endl;
+ continue;
}
- }
- vector<float> validationPixel;
- vector<float> validationFeature;
+ OGRFeature *poDstFeature = NULL;
+ if(output_opt.size()){
+ poDstFeature=imgWriterOgr.createFeature();
+ if( poDstFeature->SetFrom( poFeature, TRUE ) != OGRERR_NONE ){
+ CPLError( CE_Failure, CPLE_AppDefined,
+ "Unable to translate feature %d from layer %s.\n",
+ poFeature->GetFID(),
imgWriterOgr.getLayerName().c_str() );
+ OGRFeature::DestroyFeature( poFeature );
+ OGRFeature::DestroyFeature( poDstFeature );
+ }
+ }
+ vector<float> validationPixel;
+ vector<float> validationFeature;
- imgReaderOgr.readData(validationPixel,OFTReal,fields,poFeature);
- assert(validationPixel.size()==nband);
- vector<float> probOut(nclass);//posterior prob for each class
- for(short iclass=0;iclass<nclass;++iclass)
- probOut[iclass]=0;
- for(int ibag=0;ibag<nbag;++ibag){
- for(int iband=0;iband<nband;++iband){
-
validationFeature.push_back((validationPixel[iband]-offset[ibag][iband])/scale[ibag][iband]);
- if(verbose_opt[0]==2)
- std::cout << " " << validationFeature.back();
- }
- if(verbose_opt[0]==2)
- std::cout << std::endl;
- vector<double> result(nclass);
- struct svm_node *x;
- x = (struct svm_node *)
malloc((validationFeature.size()+1)*sizeof(struct svm_node));
- for(int i=0;i<validationFeature.size();++i){
- x[i].index=i+1;
- x[i].value=validationFeature[i];
- }
+
imgReaderOgr.readData(validationPixel,OFTReal,fields,poFeature,ilayer);
+ assert(validationPixel.size()==nband);
+ vector<float> probOut(nclass);//posterior prob for each class
+ for(short iclass=0;iclass<nclass;++iclass)
+ probOut[iclass]=0;
+ for(int ibag=0;ibag<nbag;++ibag){
+ for(int iband=0;iband<nband;++iband){
+
validationFeature.push_back((validationPixel[iband]-offset[ibag][iband])/scale[ibag][iband]);
+ if(verbose_opt[0]==2)
+ std::cout << " " << validationFeature.back();
+ }
+ if(verbose_opt[0]==2)
+ std::cout << std::endl;
+ vector<double> result(nclass);
+ struct svm_node *x;
+ x = (struct svm_node *)
malloc((validationFeature.size()+1)*sizeof(struct svm_node));
+ for(int i=0;i<validationFeature.size();++i){
+ x[i].index=i+1;
+ x[i].value=validationFeature[i];
+ }
- x[validationFeature.size()].index=-1;//to end svm feature vector
- double predict_label=0;
- if(!prob_est_opt[0]){
- predict_label = svm_predict(svm[ibag],x);
- for(short iclass=0;iclass<nclass;++iclass){
- if(iclass==static_cast<short>(predict_label))
- result[iclass]=1;
- else
- result[iclass]=0;
- }
- }
- else{
- assert(svm_check_probability_model(svm[ibag]));
- predict_label = svm_predict_probability(svm[ibag],x,&(result[0]));
- }
- if(verbose_opt[0]>1){
- std::cout << "predict_label: " << predict_label << std::endl;
- for(int iclass=0;iclass<result.size();++iclass)
- std::cout << result[iclass] << " ";
- std::cout << std::endl;
- }
+ x[validationFeature.size()].index=-1;//to end svm feature vector
+ double predict_label=0;
+ if(!prob_est_opt[0]){
+ predict_label = svm_predict(svm[ibag],x);
+ for(short iclass=0;iclass<nclass;++iclass){
+ if(iclass==static_cast<short>(predict_label))
+ result[iclass]=1;
+ else
+ result[iclass]=0;
+ }
+ }
+ else{
+ assert(svm_check_probability_model(svm[ibag]));
+ predict_label = svm_predict_probability(svm[ibag],x,&(result[0]));
+ }
+ if(verbose_opt[0]>1){
+ std::cout << "predict_label: " << predict_label << std::endl;
+ for(int iclass=0;iclass<result.size();++iclass)
+ std::cout << result[iclass] << " ";
+ std::cout << std::endl;
+ }
- //calculate posterior prob of bag
- for(short iclass=0;iclass<nclass;++iclass){
- switch(comb_opt[0]){
- default:
- case(0)://sum rule
- probOut[iclass]+=result[iclass]*priors[iclass];//add
probabilities for each bag
- break;
- case(1)://product rule
-
probOut[iclass]*=pow(priors[iclass],static_cast<float>(1.0-nbag)/nbag)*result[iclass];//multiply
probabilities for each bag
- break;
- case(2)://max rule
- if(priors[iclass]*result[iclass]>probOut[iclass])
- probOut[iclass]=priors[iclass]*result[iclass];
- break;
- }
- }
- free(x);
- }//for ibag
+ //calculate posterior prob of bag
+ for(short iclass=0;iclass<nclass;++iclass){
+ switch(comb_opt[0]){
+ default:
+ case(0)://sum rule
+ probOut[iclass]+=result[iclass]*priors[iclass];//add
probabilities for each bag
+ break;
+ case(1)://product rule
+
probOut[iclass]*=pow(priors[iclass],static_cast<float>(1.0-nbag)/nbag)*result[iclass];//multiply
probabilities for each bag
+ break;
+ case(2)://max rule
+ if(priors[iclass]*result[iclass]>probOut[iclass])
+ probOut[iclass]=priors[iclass]*result[iclass];
+ break;
+ }
+ }
+ free(x);
+ }//for ibag
- //search for max class prob
- float maxBag=0;
- float normBag=0;
- string classOut="Unclassified";
- for(short iclass=0;iclass<nclass;++iclass){
- if(verbose_opt[0]>1)
- std::cout << probOut[iclass] << " ";
- if(probOut[iclass]>maxBag){
- maxBag=probOut[iclass];
- classOut=nameVector[iclass];
- }
- }
- //look for class name
- if(verbose_opt[0]>1){
- if(classValueMap.size())
- std::cout << "->" << classValueMap[classOut] << std::endl;
- else
- std::cout << "->" << classOut << std::endl;
- }
- if(output_opt.size()){
- if(classValueMap.size())
- poDstFeature->SetField("class",classValueMap[classOut]);
- else
- poDstFeature->SetField("class",classOut.c_str());
- poDstFeature->SetFID( poFeature->GetFID() );
- }
- int labelIndex=poFeature->GetFieldIndex(label_opt[0].c_str());
- if(labelIndex>=0){
- string classRef=poFeature->GetFieldAsString(labelIndex);
- if(classRef!="0"){
+ //search for max class prob
+ float maxBag=0;
+ float normBag=0;
+ string classOut="Unclassified";
+ for(short iclass=0;iclass<nclass;++iclass){
+ if(verbose_opt[0]>1)
+ std::cout << probOut[iclass] << " ";
+ if(probOut[iclass]>maxBag){
+ maxBag=probOut[iclass];
+ classOut=nameVector[iclass];
+ }
+ }
+ //look for class name
+ if(verbose_opt[0]>1){
if(classValueMap.size())
-
cm.incrementResult(type2string<short>(classValueMap[classRef]),type2string<short>(classValueMap[classOut]),1);
- else
- cm.incrementResult(classRef,classOut,1);
+ std::cout << "->" << classValueMap[classOut] << std::endl;
+ else
+ std::cout << "->" << classOut << std::endl;
}
- }
- CPLErrorReset();
- if(output_opt.size()){
- if(imgWriterOgr.createFeature( poDstFeature ) != OGRERR_NONE){
- CPLError( CE_Failure, CPLE_AppDefined,
- "Unable to translate feature %d from layer %s.\n",
- poFeature->GetFID(), imgWriterOgr.getLayerName().c_str()
);
- OGRFeature::DestroyFeature( poDstFeature );
- OGRFeature::DestroyFeature( poDstFeature );
+ if(output_opt.size()){
+ if(classValueMap.size())
+ poDstFeature->SetField("class",classValueMap[classOut]);
+ else
+ poDstFeature->SetField("class",classOut.c_str());
+ poDstFeature->SetFID( poFeature->GetFID() );
}
- }
- ++ifeature;
- if(!verbose_opt[0]){
- progress=static_cast<float>(ifeature+1.0)/nFeatures;
- pfnProgress(progress,pszMessage,pProgressArg);
- }
- OGRFeature::DestroyFeature( poFeature );
- OGRFeature::DestroyFeature( poDstFeature );
- }
+ int labelIndex=poFeature->GetFieldIndex(label_opt[0].c_str());
+ if(labelIndex>=0){
+ string classRef=poFeature->GetFieldAsString(labelIndex);
+ if(classRef!="0"){
+ if(classValueMap.size())
+
cm.incrementResult(type2string<short>(classValueMap[classRef]),type2string<short>(classValueMap[classOut]),1);
+ else
+ cm.incrementResult(classRef,classOut,1);
+ }
+ }
+ CPLErrorReset();
+ if(output_opt.size()){
+ if(imgWriterOgr.createFeature( poDstFeature ) != OGRERR_NONE){
+ CPLError( CE_Failure, CPLE_AppDefined,
+ "Unable to translate feature %d from layer %s.\n",
+ poFeature->GetFID(),
imgWriterOgr.getLayerName().c_str() );
+ OGRFeature::DestroyFeature( poDstFeature );
+ OGRFeature::DestroyFeature( poDstFeature );
+ }
+ }
+ ++ifeature;
+ if(!verbose_opt[0]){
+ progress=static_cast<float>(ifeature+1.0)/nFeatures;
+ pfnProgress(progress,pszMessage,pProgressArg);
+ }
+ OGRFeature::DestroyFeature( poFeature );
+ OGRFeature::DestroyFeature( poDstFeature );
+ }//get next feature
+ }//next layer
imgReaderOgr.close();
if(output_opt.size())
imgWriterOgr.close();
diff --git a/src/apps/pkextract.cc b/src/apps/pkextract.cc
index a831110..5d6820a 100644
--- a/src/apps/pkextract.cc
+++ b/src/apps/pkextract.cc
@@ -52,7 +52,7 @@ int main(int argc, char *argv[])
Optionpk<string> bufferOutput_opt("bu", "bu", "Buffer output shape file");
Optionpk<short> geo_opt("g", "geo", "geo coordinates", 1);
Optionpk<short> down_opt("down", "down", "down sampling factor. Can be used
to create grid points", 1);
- Optionpk<float> threshold_opt("t", "threshold", "threshold for selecting
samples (randomly). Provide probability in percentage (>0) or absolute (<0).
Use multiple threshold values (e.g. -t 80 -t 60) if more classes are to be
extracted with random selection. Use value 100 to select all pixels for
selected class(es)", 100);
+ Optionpk<float> threshold_opt("t", "threshold", "threshold for selecting
samples (randomly). Provide probability in percentage (>0) or absolute (<0).
Use a single threshold for vector sample files. If using raster land cover maps
as a sample file, you can provide a threshold value for each class (e.g. -t 80
-t 60). Use value 100 to select all pixels for selected class(es)", 100);
Optionpk<double> min_opt("min", "min", "minimum number of samples to select
(0)", 0);
Optionpk<short> boundary_opt("bo", "boundary", "boundary for selecting the
sample", 1);
// Optionpk<short> rbox_opt("rb", "rbox", "rectangular boundary box (total
width in m) to draw around the selected pixel. Can not combined with class
option. Use multiple rbox options for multiple boundary boxes. Use value 0 for
no box)", 0);
diff --git a/src/imageclasses/ImgReaderOgr.cc b/src/imageclasses/ImgReaderOgr.cc
index 09e54c5..7adf657 100644
--- a/src/imageclasses/ImgReaderOgr.cc
+++ b/src/imageclasses/ImgReaderOgr.cc
@@ -230,57 +230,59 @@ unsigned int
ImgReaderOgr::readDataImageShape(std::map<std::string,Vector2d<floa
if(verbose)
std::cout << "reading shape file " << m_filename << std::endl;
try{
- for(int ilayer=0;ilayer<m_datasource->GetLayerCount();++ilayer){
- //only retain bands in fields
- getFields(fields);
- std::vector<std::string>::iterator fit=fields.begin();
- if(verbose>1)
- std::cout << "reading fields: ";
- while(fit!=fields.end()){
- if(verbose)
- std::cout << *fit << " ";
- // size_t
pos=(*fit).find_first_not_of("abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ_
");
- if((*fit).substr(0,1)=="B"||(*fit).substr(0,1)=="b"){
-
if((*fit).substr(1).find_first_not_of("abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ_
")!=std::string::npos){
- int theBand=atoi((*fit).substr(1).c_str());
- if(bands.size()){
- bool validBand=false;
- for(int iband=0;iband<bands.size();++iband){
- if(theBand==bands[iband])
- validBand=true;
- }
- if(validBand)
- ++fit;
- else
- fields.erase(fit);
+ //only retain bands in fields
+ getFields(fields);
+ std::vector<std::string>::iterator fit=fields.begin();
+ if(verbose>1)
+ std::cout << "reading fields: ";
+ while(fit!=fields.end()){
+ if(verbose)
+ std::cout << *fit << " ";
+ // size_t
pos=(*fit).find_first_not_of("abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ_
");
+ if((*fit).substr(0,1)=="B"||(*fit).substr(0,1)=="b"){
+
if((*fit).substr(1).find_first_not_of("abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ_
")!=std::string::npos){
+ int theBand=atoi((*fit).substr(1).c_str());
+ if(bands.size()){
+ bool validBand=false;
+ for(int iband=0;iband<bands.size();++iband){
+ if(theBand==bands[iband])
+ validBand=true;
}
- else
+ if(validBand)
++fit;
+ else
+ fields.erase(fit);
}
- else if((*fit)=="B" || (*fit)=="b" || (*fit)=="Band")//B is only band
+ else
++fit;
}
- else
- fields.erase(fit);
- }
- if(verbose)
- std::cout << std::endl;
- if(verbose){
- std::cout << "fields:";
- for(std::vector<std::string>::iterator
fit=fields.begin();fit!=fields.end();++fit)
- std::cout << " " << *fit;
- std::cout << std::endl;
+ else if((*fit)=="B" || (*fit)=="b" || (*fit)=="Band")//B is only band
+ ++fit;
}
+ else
+ fields.erase(fit);
+ }
+ if(verbose)
+ std::cout << std::endl;
+ if(verbose){
+ std::cout << "fields:";
+ for(std::vector<std::string>::iterator
fit=fields.begin();fit!=fields.end();++fit)
+ std::cout << " " << *fit;
+ std::cout << std::endl;
+ }
+ for(int ilayer=0;ilayer<m_datasource->GetLayerCount();++ilayer){
if(!nband){
if(verbose)
std::cout << "reading data" << std::endl;
- for(int ilayer=0;ilayer<m_datasource->GetLayerCount();++ilayer)
- nband=readData(mapPixels,OFTReal,fields,label,ilayer,true,verbose==2);
+ nband=readData(mapPixels,OFTReal,fields,label,ilayer,true,verbose==2);
}
else{
- for(int ilayer=0;ilayer<m_datasource->GetLayerCount();++ilayer)
-
assert(nband==readData(mapPixels,OFTReal,fields,label,ilayer,true,false));
+
assert(nband==readData(mapPixels,OFTReal,fields,label,ilayer,true,false));
}
+ nsample=getFeatureCount(ilayer);
+ totalSamples+=nsample;
+ if(verbose)
+ std::cout << ": " << nsample << " samples read with " << nband << "
bands" << std::endl;
}
}
catch(std::string e){
@@ -288,10 +290,6 @@ unsigned int
ImgReaderOgr::readDataImageShape(std::map<std::string,Vector2d<floa
estr << e << " " << m_filename;
throw(estr.str());
}
- nsample=getFeatureCount();
- totalSamples+=nsample;
- if(verbose)
- std::cout << ": " << nsample << " samples read with " << nband << " bands"
<< std::endl;
if(verbose)
std::cout << "total number of samples read " << totalSamples << std::endl;
return totalSamples;
@@ -342,15 +340,19 @@ unsigned int
ImgReaderOgr::readDataImageShape(std::map<std::string,Vector2d<floa
std::cout << " " << *fit;
std::cout << std::endl;
}
- if(!nband){
- if(verbose)
- std::cout << "reading data" << std::endl;
- for(int ilayer=0;ilayer<m_datasource->GetLayerCount();++ilayer)
+ for(int ilayer=0;ilayer<m_datasource->GetLayerCount();++ilayer){
+ if(!nband){
+ if(verbose)
+ std::cout << "reading data" << std::endl;
nband=readData(mapPixels,OFTReal,fields,label,ilayer,true,verbose==2);
- }
- else{
- for(int ilayer=0;ilayer<m_datasource->GetLayerCount();++ilayer)
+ }
+ else{
assert(nband==readData(mapPixels,OFTReal,fields,label,ilayer,true,false));
+ }
+ nsample=getFeatureCount(ilayer);
+ totalSamples+=nsample;
+ if(verbose)
+ std::cout << ": " << nsample << " samples read with " << nband << "
bands" << std::endl;
}
}
catch(std::string e){
@@ -358,8 +360,6 @@ unsigned int
ImgReaderOgr::readDataImageShape(std::map<std::string,Vector2d<floa
estr << e << " " << m_filename;
throw(estr.str());
}
- nsample=getFeatureCount();
- totalSamples+=nsample;
if(verbose)
std::cout << ": " << nsample << " samples read with " << nband << " bands"
<< std::endl;
if(verbose)
diff --git a/src/imageclasses/ImgReaderOgr.h b/src/imageclasses/ImgReaderOgr.h
index ea210e4..36653e6 100644
--- a/src/imageclasses/ImgReaderOgr.h
+++ b/src/imageclasses/ImgReaderOgr.h
@@ -73,6 +73,7 @@ public:
int getFields(std::vector<OGRFieldDefn*>& fields, int layer=0) const;
OGRDataSource* getDataSource(void) {return m_datasource;};
OGRSFDriver* getDriver(void) const {return m_datasource->GetDriver();};
+ int getLayerCount(void) const {return m_datasource->GetLayerCount();};
// OGRLayer *executeSql(const std::string& output,const std::string&
sqlStatement, OGRGeometry* spatialFilter=NULL);
template<typename T> int readSql(Vector2d<T>& data, const OGRFieldType&
fieldType, std::vector<std::string>& fields, const std::string& sqlStatement,
OGRGeometry* spatialFilter=NULL, int layer=0, bool pos=false, bool
verbose=false);
template<typename T> int readSql(std::map<int,Vector2d<T> >& data, const
OGRFieldType& fieldType, std::vector<std::string>& fields, const std::string&
label, const std::string& sqlStatement, OGRGeometry* spatialFilter, int
layer=0, bool pos=false, bool verbose=false);
--
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/srv/git.debian.org/git/pkg-grass/pktools.git
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