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sebastic-guest pushed a commit to branch upstream-master
in repository pktools.
commit 97a280093300af4108b79e808014b4b5f892f56b
Author: Pieter Kempeneers <kempe...@gmail.com>
Date: Fri Mar 21 11:55:48 2014 +0100
commit from branch
---
src/apps/pkclassify_nn.cc | 10 ++---
src/apps/pkclassify_svm.cc | 10 ++---
src/apps/pkextract.cc | 12 ++----
src/apps/pkfs_nn.cc | 19 +-------
src/apps/pkfs_svm.cc | 6 +--
src/base/Optionpk.h | 105 ++++++++++++++++++++++++++++++++++++++++++++-
6 files changed, 118 insertions(+), 44 deletions(-)
diff --git a/src/apps/pkclassify_nn.cc b/src/apps/pkclassify_nn.cc
index 01337ad..c4eefd4 100644
--- a/src/apps/pkclassify_nn.cc
+++ b/src/apps/pkclassify_nn.cc
@@ -18,10 +18,6 @@ You should have received a copy of the GNU General Public
License
along with pktools. If not, see <http://www.gnu.org/licenses/>.
***********************************************************************/
#include <stdlib.h>
-#ifdef WIN32
-#define random rand
-#define srandom srand
-#endif
#include <vector>
#include <map>
#include <algorithm>
@@ -46,6 +42,7 @@ int main(int argc, char *argv[])
Optionpk<string> training_opt("t", "training", "training shape file. A
single shape file contains all training features (must be set as: B0, B1,
B2,...) for all classes (class numbers identified by label option). Use
multiple training files for bootstrap aggregation (alternative to the bag and
bsize options, where a random subset is taken from a single training file)");
Optionpk<string> label_opt("label", "label", "identifier for class label in
training shape file.","label");
Optionpk<unsigned int> balance_opt("bal", "balance", "balance the input data
to this number of samples for each class", 0);
+ Optionpk<bool> random_opt("random", "random", "in case of balance, randomize
input data", true);
Optionpk<int> minSize_opt("min", "min", "if number of training pixels is
less then min, do not take this class into account (0: consider all classes)",
0);
Optionpk<double> start_opt("s", "start", "start band sequence number (set to
0)",0);
Optionpk<double> end_opt("e", "end", "end band sequence number (set to 0 for
all bands)", 0);
@@ -88,6 +85,7 @@ int main(int argc, char *argv[])
training_opt.retrieveOption(argc,argv);
label_opt.retrieveOption(argc,argv);
balance_opt.retrieveOption(argc,argv);
+ random_opt.retrieveOption(argc,argv);
minSize_opt.retrieveOption(argc,argv);
start_opt.retrieveOption(argc,argv);
end_opt.retrieveOption(argc,argv);
@@ -266,7 +264,7 @@ int main(int argc, char *argv[])
if(balance_opt[0]>0){
while(balance_opt.size()<nclass)
balance_opt.push_back(balance_opt.back());
- if(random)
+ if(random_opt[0])
srand(time(NULL));
totalSamples=0;
for(int iclass=0;iclass<nclass;++iclass){
@@ -392,7 +390,7 @@ int main(int argc, char *argv[])
int nctraining=0;
if(verbose_opt[0]>=1)
cout << "calculating features for class " << iclass << endl;
- if(random)
+ if(random_opt[0])
srand(time(NULL));
nctraining=(bagSize_opt[iclass]<100)?
trainingPixels[iclass].size()/100.0*bagSize_opt[iclass] :
trainingPixels[iclass].size();//bagSize_opt[iclass] given in % of training size
if(nctraining<=0)
diff --git a/src/apps/pkclassify_svm.cc b/src/apps/pkclassify_svm.cc
index e5d7896..b428f95 100644
--- a/src/apps/pkclassify_svm.cc
+++ b/src/apps/pkclassify_svm.cc
@@ -18,10 +18,6 @@ You should have received a copy of the GNU General Public
License
along with pktools. If not, see <http://www.gnu.org/licenses/>.
***********************************************************************/
#include <stdlib.h>
-#ifdef WIN32
-#define random rand
-#define srandom srand
-#endif
#include <vector>
#include <map>
#include <algorithm>
@@ -56,6 +52,7 @@ int main(int argc, char *argv[])
Optionpk<string> training_opt("t", "training", "training shape file. A
single shape file contains all training features (must be set as: B0, B1,
B2,...) for all classes (class numbers identified by label option). Use
multiple training files for bootstrap aggregation (alternative to the bag and
bsize options, where a random subset is taken from a single training file)");
Optionpk<string> label_opt("label", "label", "identifier for class label in
training shape file.","label");
Optionpk<unsigned int> balance_opt("bal", "balance", "balance the input data
to this number of samples for each class", 0);
+ Optionpk<bool> random_opt("random", "random", "in case of balance, randomize
input data", true);
Optionpk<int> minSize_opt("min", "min", "if number of training pixels is
less then min, do not take this class into account (0: consider all classes)",
0);
Optionpk<double> start_opt("s", "start", "start band sequence number (set to
0)",0);
Optionpk<double> end_opt("e", "end", "end band sequence number (set to 0 for
all bands)", 0);
@@ -104,6 +101,7 @@ int main(int argc, char *argv[])
training_opt.retrieveOption(argc,argv);
label_opt.retrieveOption(argc,argv);
balance_opt.retrieveOption(argc,argv);
+ random_opt.retrieveOption(argc,argv);
minSize_opt.retrieveOption(argc,argv);
start_opt.retrieveOption(argc,argv);
end_opt.retrieveOption(argc,argv);
@@ -316,7 +314,7 @@ int main(int argc, char *argv[])
if(balance_opt[0]>0){
while(balance_opt.size()<nclass)
balance_opt.push_back(balance_opt.back());
- if(random)
+ if(random_opt[0])
srand(time(NULL));
totalSamples=0;
for(short iclass=0;iclass<nclass;++iclass){
@@ -443,7 +441,7 @@ int main(int argc, char *argv[])
int nctraining=0;
if(verbose_opt[0]>=1)
std::cout << "calculating features for class " << iclass << std::endl;
- if(random)
+ if(random_opt[0])
srand(time(NULL));
nctraining=(bagSize_opt[iclass]<100)?
trainingPixels[iclass].size()/100.0*bagSize_opt[iclass] :
trainingPixels[iclass].size();//bagSize_opt[iclass] given in % of training size
if(nctraining<=0)
diff --git a/src/apps/pkextract.cc b/src/apps/pkextract.cc
index d893ee2..889faf4 100644
--- a/src/apps/pkextract.cc
+++ b/src/apps/pkextract.cc
@@ -20,10 +20,6 @@ along with pktools. If not, see
<http://www.gnu.org/licenses/>.
#include <assert.h>
#include <math.h>
#include <stdlib.h>
-#ifdef WIN32
-#define random rand
-#define srandom srand
-#endif
#include <sstream>
#include <string>
#include <algorithm>
@@ -246,7 +242,7 @@ int main(int argc, char *argv[])
void* pProgressArg=NULL;
GDALProgressFunc pfnProgress=GDALTermProgress;
double progress=0;
- srandom(time(NULL));
+ srand(time(NULL));
bool sampleIsRaster=false;
ImgReaderOgr sampleReaderOgr;
@@ -427,7 +423,7 @@ int main(int argc, char *argv[])
}
float
theThreshold=(threshold_opt.size()>1)?threshold_opt[processClass]:threshold_opt[0];
if(theThreshold>0){//percentual value
- double p=static_cast<double>(random())/(RAND_MAX);
+ double p=static_cast<double>(rand())/(RAND_MAX);
p*=100.0;
if(p>theThreshold)
continue;//do not select for now, go to next column
@@ -671,7 +667,7 @@ int main(int argc, char *argv[])
}
float
theThreshold=(threshold_opt.size()>1)?threshold_opt[processClass]:threshold_opt[0];
if(theThreshold>0){//percentual value
- double p=static_cast<double>(random())/(RAND_MAX);
+ double p=static_cast<double>(rand())/(RAND_MAX);
p*=100.0;
if(p>theThreshold)
continue;//do not select for now, go to next column
@@ -891,7 +887,7 @@ int main(int argc, char *argv[])
if(verbose_opt[0]>0)
std::cout << "reading feature " << readFeature->GetFID() << std::endl;
if(threshold_opt[0]>0){//percentual value
- double p=static_cast<double>(random())/(RAND_MAX);
+ double p=static_cast<double>(rand())/(RAND_MAX);
p*=100.0;
if(p>threshold_opt[0]){
if(test_opt.size())
diff --git a/src/apps/pkfs_nn.cc b/src/apps/pkfs_nn.cc
index 6ac56b2..4a8c939 100644
--- a/src/apps/pkfs_nn.cc
+++ b/src/apps/pkfs_nn.cc
@@ -18,10 +18,6 @@ You should have received a copy of the GNU General Public
License
along with pktools. If not, see <http://www.gnu.org/licenses/>.
***********************************************************************/
#include <stdlib.h>
-#ifdef WIN32
-#define random rand
-#define srandom srand
-#endif
#include <vector>
#include <string>
#include <map>
@@ -162,11 +158,6 @@ double getCost(const vector<Vector2d<float> >
&trainingFeatures)
else{//not working yet. please repair...
assert(cv_opt[0]>0);
bool initWeights=true;
- //test
- cout << "tempFeatures.size(): " << tmpFeatures.size() << endl;
- cout << "ntraining: " << ntraining << endl;
- cout << "initWeights: " << initWeights << endl;
- cout << "maxit_opt.size(): " << maxit_opt.size() << endl;
net.train_on_data(tmpFeatures,ntraining,initWeights, maxit_opt[0],
iterations_between_reports, desired_error);
vector<Vector2d<float> > testFeatures(nclass);
@@ -178,8 +169,6 @@ double getCost(const vector<Vector2d<float> >
&trainingFeatures)
for(int ifeature=0;ifeature<nFeatures;++ifeature){
testFeatures[iclass][isample][ifeature]=trainingFeatures[iclass][nctraining[iclass]+isample][ifeature];
}
- //test
- cout << "isample:" << isample<< endl;
result=net.run(testFeatures[iclass][isample]);
string refClassName=nameVector[iclass];
float maxP=-1;
@@ -190,19 +179,13 @@ double getCost(const vector<Vector2d<float> >
&trainingFeatures)
maxClass=ic;
}
}
- //test
- cout << "maxClass:" << maxClass << "(" << nameVector.size() << ")" <<
endl;
string className=nameVector[maxClass];
- //test
- cout << "className:" << nameVector[maxClass] << endl;
if(classValueMap.size())
cm.incrementResult(type2string<short>(classValueMap[refClassName]),type2string<short>(classValueMap[className]),1.0);
else
cm.incrementResult(cm.getClass(referenceVector[isample]),cm.getClass(outputVector[isample]),1.0);
}
}
- //test
- cout << "debug12" << endl;
}
assert(cm.nReference());
return(cm.kappa());
@@ -237,7 +220,7 @@ int main(int argc, char *argv[])
maxFeatures_opt.retrieveOption(argc,argv);
label_opt.retrieveOption(argc,argv);
balance_opt.retrieveOption(argc,argv);
- random_opt.retrieveOption(argc,argv);
+ random_opt.retrieveOption(argc,argv);
minSize_opt.retrieveOption(argc,argv);
start_opt.retrieveOption(argc,argv);
end_opt.retrieveOption(argc,argv);
diff --git a/src/apps/pkfs_svm.cc b/src/apps/pkfs_svm.cc
index 45f8996..65c6cab 100644
--- a/src/apps/pkfs_svm.cc
+++ b/src/apps/pkfs_svm.cc
@@ -18,10 +18,6 @@ You should have received a copy of the GNU General Public
License
along with pktools. If not, see <http://www.gnu.org/licenses/>.
***********************************************************************/
#include <stdlib.h>
-#ifdef WIN32
-#define random rand
-#define srandom srand
-#endif
#include <vector>
#include <string>
#include <map>
@@ -246,7 +242,7 @@ int main(int argc, char *argv[])
maxFeatures_opt.retrieveOption(argc,argv);
label_opt.retrieveOption(argc,argv);
balance_opt.retrieveOption(argc,argv);
- random_opt.retrieveOption(argc,argv);
+ random_opt.retrieveOption(argc,argv);
minSize_opt.retrieveOption(argc,argv);
start_opt.retrieveOption(argc,argv);
end_opt.retrieveOption(argc,argv);
diff --git a/src/base/Optionpk.h b/src/base/Optionpk.h
index 9c07f43..1905978 100644
--- a/src/base/Optionpk.h
+++ b/src/base/Optionpk.h
@@ -31,6 +31,9 @@ along with pktools. If not, see
<http://www.gnu.org/licenses/>.
#include <typeinfo>
#ifndef WIN32
#include <cxxabi.h>
+#define mytypeid(T) abi::__cxa_demangle(typeid(T).name(),0,0,&status)
+#else
+#define mytypeid(T) typeid(T).name()
#endif
#include "ogr_feature.h"
@@ -236,7 +239,7 @@ template<class T> inline std::string
Optionpk<T>::usageDoxygen() const
else
helpss << std::setiosflags(std::ios::left) << " | ";
int status;
- helpss << std::setiosflags(std::ios::left) << std::setw(4) <<
typeid(T).name() << " | ";
+ helpss << std::setiosflags(std::ios::left) << std::setw(4) << mytypeid(T) <<
" | ";
//helpss << std::setiosflags(std::ios::left) << std::setw(4) <<
abi::__cxa_demangle(typeid(T).name(),0,0,&status) << " | ";
if(m_hasDefault)
helpss <<std::setiosflags(std::ios::left) << std::setw(5) <<
type2string<T>(m_defaultValue) << " |";
@@ -345,4 +348,104 @@ template<class T> inline bool
Optionpk<T>::retrieveOption(int argc, char **argv)
//template<class T> typename std::vector<T>::const_iterator
Optionpk<T>::findSubstring(const T& argument) const {std::string
errorString="Error: findSubstring only defined for options of type
std::string"; throw(errorString);}
+//todo: to be put in .cc file
+/////////////////// Specializations /////////////////
+
+///specialization for string
+template<> inline std::string string2type(std::string const& s){
+ return s;
+}
+
+///specialization for OGRFieldType
+template<> inline OGRFieldType string2type(std::string const& s){
+ OGRFieldType ftype;
+ int ogr_typecount=11;//hard coded for now!
+ for(int iType = 0; iType < ogr_typecount; ++iType){
+ if( OGRFieldDefn::GetFieldTypeName((OGRFieldType)iType) != NULL
+ &&
EQUAL(OGRFieldDefn::GetFieldTypeName((OGRFieldType)iType),s.c_str()))
+ ftype=(OGRFieldType) iType;
+ }
+ return ftype;
+}
+
+///specialization for bool
+template<> inline std::string type2string(bool const& value){
+ if(value)
+ return("true");
+ else
+ return("false");
+}
+
+///specialization for string
+template<> inline std::string type2string(std::string const& value){
+ // if(value.empty())
+ // return("<empty string>");
+ // else
+ return(value);
+}
+
+///specialization for float
+template<> inline std::string type2string(float const& value){
+ std::ostringstream oss;
+ // oss.precision(1);
+ // oss.setf(ios::fixed);
+ oss << value;
+ return oss.str();
+}
+
+///specialization for double
+template<> inline std::string type2string(double const& value){
+ std::ostringstream oss;
+ // oss.precision(1);
+ // oss.setf(ios::fixed);
+ oss << value;
+ return oss.str();
+}
+
+///specialization for bool
+template<> inline void Optionpk<bool>::setAll(const std::string& shortName,
const std::string& longName, const std::string& helpInfo)
+{
+ m_shortName=shortName;
+ m_longName=longName;
+ m_hasArgument=false;
+ m_help=helpInfo;
+ m_hide=0;
+}
+
+///specialization for bool
+template<> inline void Optionpk<bool>::setAll(const std::string& shortName,
const std::string& longName, const std::string& helpInfo,const bool&
defaultValue, short hide)
+{
+ m_shortName=shortName;
+ m_longName=longName;
+ m_hasArgument=false;
+ m_help=helpInfo;
+ m_defaultValue=defaultValue;
+ m_hasDefault=true;
+ m_hide=hide;
+}
+
+///specialization for bool
+template<> inline Optionpk<bool>::Optionpk(const std::string& shortName, const
std::string& longName, const std::string& helpInfo)
+{
+ setAll(shortName,longName,helpInfo);
+}
+
+///specialization for bool
+template<> inline Optionpk<bool>::Optionpk(const std::string& shortName, const
std::string& longName, const std::string& helpInfo,const bool& defaultValue,
short hide)
+{
+ setAll(shortName,longName,helpInfo,defaultValue, hide);
+}
+
+//specialization (only makes sense for T=std::string), generic function throws
exception
+//find a substring in string option (e.g., option is of type -co
INTERLEAVE=BAND)
+template<> inline std::vector<std::string>::const_iterator
Optionpk<std::string>::findSubstring(const std::string& argument) const{
+ std::vector<std::string>::const_iterator opit=this->begin();
+ while(opit!=this->end()){
+ if(opit->find(argument)!=std::string::npos)
+ break;
+ ++opit;
+ }
+ return opit;
+}
+
#endif
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