This is an automated email from the git hooks/post-receive script.
sebastic-guest pushed a commit to branch upstream-master
in repository pktools.
commit 009288c132afd04b5b2c76c832f101c544482672
Author: Pieter Kempeneers <kempe...@gmail.com>
Date: Mon Mar 31 10:33:46 2014 +0200
support of layer names
---
src/apps/pkann.cc | 6 +++---
src/apps/pkextract.cc | 12 ++++++++++--
src/apps/pkfsann.cc | 10 +++++-----
src/apps/pkfssvm.cc | 10 +++++-----
src/apps/pkoptsvm.cc | 10 +++++-----
src/apps/pksvm.cc | 6 +++---
src/imageclasses/ImgReaderOgr.cc | 30 +++++++++++++++---------------
src/imageclasses/ImgReaderOgr.h | 22 +++++++++++-----------
8 files changed, 57 insertions(+), 49 deletions(-)
diff --git a/src/apps/pkann.cc b/src/apps/pkann.cc
index 15c1464..fc8104d 100644
--- a/src/apps/pkann.cc
+++ b/src/apps/pkann.cc
@@ -40,7 +40,7 @@ int main(int argc, char *argv[])
//--------------------------- command line options
------------------------------------
Optionpk<string> input_opt("i", "input", "input image");
Optionpk<string> training_opt("t", "training", "training vector file. A
single vector 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> tlayer_opt("tln", "tln", "training layer name","");
+ Optionpk<string> tlayer_opt("tln", "tln", "training layer name(s)");
Optionpk<string> label_opt("label", "label", "identifier for class label in
training vector 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);
@@ -213,9 +213,9 @@ int main(int argc, char *argv[])
try{
ImgReaderOgr trainingReaderBag(training_opt[ibag]);
if(band_opt.size())
-
totalSamples=trainingReaderBag.readDataImageOgr(trainingMap,fields,band_opt,label_opt[0],tlayer_opt[0],verbose_opt[0]);
+
totalSamples=trainingReaderBag.readDataImageOgr(trainingMap,fields,band_opt,label_opt[0],tlayer_opt,verbose_opt[0]);
else
-
totalSamples=trainingReaderBag.readDataImageOgr(trainingMap,fields,start_opt[0],end_opt[0],label_opt[0],tlayer_opt[0],verbose_opt[0]);
+
totalSamples=trainingReaderBag.readDataImageOgr(trainingMap,fields,start_opt[0],end_opt[0],label_opt[0],tlayer_opt,verbose_opt[0]);
if(trainingMap.size()<2){
string errorstring="Error: could not read at least two classes from
training file, did you provide class labels in training sample (see option
label)?";
throw(errorstring);
diff --git a/src/apps/pkextract.cc b/src/apps/pkextract.cc
index 889faf4..fa16986 100644
--- a/src/apps/pkextract.cc
+++ b/src/apps/pkextract.cc
@@ -44,6 +44,7 @@ int main(int argc, char *argv[])
{
Optionpk<string> image_opt("i", "image", "Input image file");
Optionpk<string> sample_opt("s", "sample", "Input sample vector file or
class file (e.g. Corine CLC) if class option is set");
+ Optionpk<string> layer_opt("ln", "ln", "layer name(s) in sample (leave empty
to select all)");
Optionpk<string> mask_opt("m", "mask", "Mask image file");
Optionpk<int> msknodata_opt("msknodata", "msknodata", "Mask value where
image is invalid. If a single mask is used, more nodata values can be set. If
more masks are used, use one value for each mask.", 1);
Optionpk<int> class_opt("c", "class", "Class(es) to extract from input
sample image. Leave empty to extract all valid data pixels from sample file");
@@ -72,6 +73,7 @@ int main(int argc, char *argv[])
try{
doProcess=image_opt.retrieveOption(argc,argv);
sample_opt.retrieveOption(argc,argv);
+ layer_opt.retrieveOption(argc,argv);
mask_opt.retrieveOption(argc,argv);
msknodata_opt.retrieveOption(argc,argv);
class_opt.retrieveOption(argc,argv);
@@ -773,7 +775,11 @@ int main(int argc, char *argv[])
for(int ilayer=0;ilayer<nlayer;++ilayer){
OGRLayer *readLayer=sampleReaderOgr.getLayer(ilayer);
- cout << "processing layer " << readLayer->GetName() << endl;
+ string currentLayername=readLayer->GetName();
+ if(layer_opt.size())
+
if(find(layer_opt.begin(),layer_opt.end(),currentLayername)==layer_opt.end())
+ continue;
+ cout << "processing layer " << currentLayername << endl;
readLayer->ResetReading();
OGRLayer *writeLayer;
OGRLayer *writeTestLayer;
@@ -798,9 +804,11 @@ int main(int argc, char *argv[])
}
}
if(verbose_opt[0])
- std::cout << "copy fields" << std::flush << std::endl;
+ std::cout << "copy fields from layer " << ilayer << std::flush <<
std::endl;
ogrWriter.copyFields(sampleReaderOgr,ilayer);
+ //hiero test: todo does not work
+ cout << "debug0" << endl;
if(test_opt.size()){
if(verbose_opt[0])
std::cout << "copy fields test writer" << std::flush << std::endl;
diff --git a/src/apps/pkfsann.cc b/src/apps/pkfsann.cc
index b115dcb..44ddc5e 100644
--- a/src/apps/pkfsann.cc
+++ b/src/apps/pkfsann.cc
@@ -198,7 +198,7 @@ int main(int argc, char *argv[])
//--------------------------- command line options
------------------------------------
Optionpk<string> input_opt("i", "input", "input test set (leave empty to
perform a cross validation based on training only)");
Optionpk<string> training_opt("t", "training", "training vector file. A
single vector 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> tlayer_opt("tln", "tln", "training layer name","");
+ Optionpk<string> tlayer_opt("tln", "tln", "training layer name(s)");
Optionpk<string> label_opt("\0", "label", "identifier for class label in
training vector file.","label");
Optionpk<unsigned short> maxFeatures_opt("n", "nf", "number of features to
select (0 to select optimal number, see also ecost option)", 0);
Optionpk<unsigned int> balance_opt("\0", "balance", "balance the input data
to this number of samples for each class", 0);
@@ -310,18 +310,18 @@ int main(int argc, char *argv[])
try{
ImgReaderOgr trainingReader(training_opt[0]);
if(band_opt.size()){
-
totalSamples=trainingReader.readDataImageOgr(trainingMap,fields,band_opt,label_opt[0],tlayer_opt[0],verbose_opt[0]);
+
totalSamples=trainingReader.readDataImageOgr(trainingMap,fields,band_opt,label_opt[0],tlayer_opt,verbose_opt[0]);
if(input_opt.size()){
ImgReaderOgr inputReader(input_opt[0]);
-
totalTestSamples=trainingReader.readDataImageOgr(testMap,fields,band_opt,label_opt[0],tlayer_opt[0],verbose_opt[0]);
+
totalTestSamples=trainingReader.readDataImageOgr(testMap,fields,band_opt,label_opt[0],tlayer_opt,verbose_opt[0]);
inputReader.close();
}
}
else{
-
totalSamples=trainingReader.readDataImageOgr(trainingMap,fields,start_opt[0],end_opt[0],label_opt[0],tlayer_opt[0],verbose_opt[0]);
+
totalSamples=trainingReader.readDataImageOgr(trainingMap,fields,start_opt[0],end_opt[0],label_opt[0],tlayer_opt,verbose_opt[0]);
if(input_opt.size()){
ImgReaderOgr inputReader(input_opt[0]);
-
totalTestSamples=trainingReader.readDataImageOgr(testMap,fields,start_opt[0],end_opt[0],label_opt[0],tlayer_opt[0],verbose_opt[0]);
+
totalTestSamples=trainingReader.readDataImageOgr(testMap,fields,start_opt[0],end_opt[0],label_opt[0],tlayer_opt,verbose_opt[0]);
inputReader.close();
}
}
diff --git a/src/apps/pkfssvm.cc b/src/apps/pkfssvm.cc
index 4dcf05b..ed7f282 100644
--- a/src/apps/pkfssvm.cc
+++ b/src/apps/pkfssvm.cc
@@ -222,7 +222,7 @@ int main(int argc, char *argv[])
//--------------------------- command line options
------------------------------------
Optionpk<string> input_opt("i", "input", "input test set (leave empty to
perform a cross validation based on training only)");
Optionpk<string> training_opt("t", "training", "training vector file. A
single vector file contains all training features (must be set as: B0, B1,
B2,...) for all classes (class numbers identified by label option).");
- Optionpk<string> tlayer_opt("tln", "tln", "training layer name","");
+ Optionpk<string> tlayer_opt("tln", "tln", "training layer name(s)");
Optionpk<string> label_opt("\0", "label", "identifier for class label in
training vector file.","label");
Optionpk<unsigned short> maxFeatures_opt("n", "nf", "number of features to
select (0 to select optimal number, see also ecost option)", 0);
Optionpk<unsigned int> balance_opt("\0", "balance", "balance the input data
to this number of samples for each class", 0);
@@ -348,18 +348,18 @@ int main(int argc, char *argv[])
try{
ImgReaderOgr trainingReader(training_opt[0]);
if(band_opt.size()){
-
totalSamples=trainingReader.readDataImageOgr(trainingMap,fields,band_opt,label_opt[0],tlayer_opt[0],verbose_opt[0]);
+
totalSamples=trainingReader.readDataImageOgr(trainingMap,fields,band_opt,label_opt[0],tlayer_opt,verbose_opt[0]);
if(input_opt.size()){
ImgReaderOgr inputReader(input_opt[0]);
-
totalTestSamples=inputReader.readDataImageOgr(testMap,fields,band_opt,label_opt[0],tlayer_opt[0],verbose_opt[0]);
+
totalTestSamples=inputReader.readDataImageOgr(testMap,fields,band_opt,label_opt[0],tlayer_opt,verbose_opt[0]);
inputReader.close();
}
}
else{
-
totalSamples=trainingReader.readDataImageOgr(trainingMap,fields,start_opt[0],end_opt[0],label_opt[0],tlayer_opt[0],verbose_opt[0]);
+
totalSamples=trainingReader.readDataImageOgr(trainingMap,fields,start_opt[0],end_opt[0],label_opt[0],tlayer_opt,verbose_opt[0]);
if(input_opt.size()){
ImgReaderOgr inputReader(input_opt[0]);
-
totalTestSamples=inputReader.readDataImageOgr(testMap,fields,start_opt[0],end_opt[0],label_opt[0],tlayer_opt[0],verbose_opt[0]);
+
totalTestSamples=inputReader.readDataImageOgr(testMap,fields,start_opt[0],end_opt[0],label_opt[0],tlayer_opt,verbose_opt[0]);
inputReader.close();
}
}
diff --git a/src/apps/pkoptsvm.cc b/src/apps/pkoptsvm.cc
index ce77a17..44b2940 100644
--- a/src/apps/pkoptsvm.cc
+++ b/src/apps/pkoptsvm.cc
@@ -232,7 +232,7 @@ int main(int argc, char *argv[])
vector<int> vreclass;
Optionpk<string> input_opt("i", "input", "input image");
Optionpk<string> training_opt("t", "training", "training vector file. A
single vector file contains all training features (must be set as: B0, B1,
B2,...) for all classes (class numbers identified by label option).");
- Optionpk<string> tlayer_opt("tln", "tln", "training layer name","");
+ Optionpk<string> tlayer_opt("tln", "tln", "training layer name(s)");
Optionpk<string> label_opt("\0", "label", "identifier for class label in
training vector file.","label");
// Optionpk<unsigned short> reclass_opt("\0", "rc", "reclass code (e.g.
--rc=12 --rc=23 to reclass first two classes to 12 and 23 resp.).", 0);
Optionpk<unsigned int> balance_opt("\0", "balance", "balance the input data
to this number of samples for each class", 0);
@@ -357,18 +357,18 @@ int main(int argc, char *argv[])
try{
ImgReaderOgr trainingReader(training_opt[0]);
if(band_opt.size()){
-
totalSamples=trainingReader.readDataImageOgr(trainingMap,fields,band_opt,label_opt[0],tlayer_opt[0],verbose_opt[0]);
+
totalSamples=trainingReader.readDataImageOgr(trainingMap,fields,band_opt,label_opt[0],tlayer_opt,verbose_opt[0]);
if(input_opt.size()){
ImgReaderOgr inputReader(input_opt[0]);
-
totalTestSamples=inputReader.readDataImageOgr(testMap,fields,band_opt,label_opt[0],tlayer_opt[0],verbose_opt[0]);
+
totalTestSamples=inputReader.readDataImageOgr(testMap,fields,band_opt,label_opt[0],tlayer_opt,verbose_opt[0]);
inputReader.close();
}
}
else{
-
totalSamples=trainingReader.readDataImageOgr(trainingMap,fields,start_opt[0],end_opt[0],label_opt[0],tlayer_opt[0],verbose_opt[0]);
+
totalSamples=trainingReader.readDataImageOgr(trainingMap,fields,start_opt[0],end_opt[0],label_opt[0],tlayer_opt,verbose_opt[0]);
if(input_opt.size()){
ImgReaderOgr inputReader(input_opt[0]);
-
totalTestSamples=inputReader.readDataImageOgr(testMap,fields,start_opt[0],end_opt[0],label_opt[0],tlayer_opt[0],verbose_opt[0]);
+
totalTestSamples=inputReader.readDataImageOgr(testMap,fields,start_opt[0],end_opt[0],label_opt[0],tlayer_opt,verbose_opt[0]);
inputReader.close();
}
trainingReader.close();
diff --git a/src/apps/pksvm.cc b/src/apps/pksvm.cc
index 38e835f..9e396ed 100644
--- a/src/apps/pksvm.cc
+++ b/src/apps/pksvm.cc
@@ -50,7 +50,7 @@ int main(int argc, char *argv[])
//--------------------------- command line options
------------------------------------
Optionpk<string> input_opt("i", "input", "input image");
Optionpk<string> training_opt("t", "training", "training vector file. A
single vector 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> tlayer_opt("tln", "tln", "training layer name","");
+ Optionpk<string> tlayer_opt("tln", "tln", "training layer name(s)");
Optionpk<string> label_opt("label", "label", "identifier for class label in
training vector 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);
@@ -255,9 +255,9 @@ int main(int argc, char *argv[])
try{
ImgReaderOgr trainingReaderBag(training_opt[ibag]);
if(band_opt.size())
-
totalSamples=trainingReaderBag.readDataImageOgr(trainingMap,fields,band_opt,label_opt[0],tlayer_opt[0],verbose_opt[0]);
+
totalSamples=trainingReaderBag.readDataImageOgr(trainingMap,fields,band_opt,label_opt[0],tlayer_opt,verbose_opt[0]);
else
-
totalSamples=trainingReaderBag.readDataImageOgr(trainingMap,fields,start_opt[0],end_opt[0],tlayer_opt[0],label_opt[0],verbose_opt[0]);
+
totalSamples=trainingReaderBag.readDataImageOgr(trainingMap,fields,start_opt[0],end_opt[0],label_opt[0],tlayer_opt,verbose_opt[0]);
if(trainingMap.size()<2){
string errorstring="Error: could not read at least two classes from
training file, did you provide class labels in training sample (see option
label)?";
throw(errorstring);
diff --git a/src/imageclasses/ImgReaderOgr.cc b/src/imageclasses/ImgReaderOgr.cc
index 8472796..db5d7cc 100644
--- a/src/imageclasses/ImgReaderOgr.cc
+++ b/src/imageclasses/ImgReaderOgr.cc
@@ -218,11 +218,11 @@ std::ostream& operator<<(std::ostream& theOstream,
ImgReaderOgr& theImageReader)
// }
unsigned int
ImgReaderOgr::readDataImageOgr(std::map<std::string,Vector2d<float> >
&mapPixels, //[classNr][pixelNr][bandNr],
- std::vector<std::string>& fields,
- const std::vector<short>& bands,
- const std::string& label,
- const std::string& layername,
- int verbose)
+ std::vector<std::string>& fields,
+ const std::vector<short>& bands,
+ const std::string& label,
+ const std::vector<std::string>&
layers,
+ int verbose)
{
mapPixels.clear();
int nsample=0;
@@ -232,8 +232,8 @@ unsigned int
ImgReaderOgr::readDataImageOgr(std::map<std::string,Vector2d<float>
std::cout << "reading shape file " << m_filename << std::endl;
for(int ilayer=0;ilayer<getLayerCount();++ilayer){
std::string currentLayername=getLayer(ilayer)->GetName();
- if(!layername.empty())
- if(currentLayername!=layername)
+ if(layers.size())
+ if(find(layers.begin(),layers.end(),currentLayername)==layers.end())
continue;
try{
//only retain bands in fields
@@ -301,12 +301,12 @@ unsigned int
ImgReaderOgr::readDataImageOgr(std::map<std::string,Vector2d<float>
}
unsigned int
ImgReaderOgr::readDataImageOgr(std::map<std::string,Vector2d<float> >
&mapPixels, //[classNr][pixelNr][bandNr],
- std::vector<std::string>& fields,
- double start,
- double end,
- const std::string& label,
- const std::string& layername,
- int verbose)
+ std::vector<std::string>& fields,
+ double start,
+ double end,
+ const std::string& label,
+ const std::vector<std::string>&
layers,
+ int verbose)
{
mapPixels.clear();
int nsample=0;
@@ -316,8 +316,8 @@ unsigned int
ImgReaderOgr::readDataImageOgr(std::map<std::string,Vector2d<float>
std::cout << "reading shape file " << m_filename << std::endl;
for(int ilayer=0;ilayer<getLayerCount();++ilayer){
std::string currentLayername=getLayer(ilayer)->GetName();
- if(!layername.empty())
- if(currentLayername!=layername)
+ if(layers.size())
+ if(find(layers.begin(),layers.end(),currentLayername)==layers.end())
continue;
try{
//only retain bands in fields
diff --git a/src/imageclasses/ImgReaderOgr.h b/src/imageclasses/ImgReaderOgr.h
index 12e48c4..f15f905 100644
--- a/src/imageclasses/ImgReaderOgr.h
+++ b/src/imageclasses/ImgReaderOgr.h
@@ -49,19 +49,19 @@ public:
template <typename T> int readData(std::map<int,Vector2d<T> >& data, const
OGRFieldType& fieldType, std::vector<std::string>& fields, const std::string&
label, int layer=0, bool pos=false, bool verbose=false);//default layer 0 and
no pos information in data
template <typename T> int readData(std::map<std::string,Vector2d<T> >& data,
const OGRFieldType& fieldType, std::vector<std::string>& fields, const
std::string& label, int layer=0, bool pos=false, bool verbose=false);//default
layer 0 and no pos information in data
unsigned int readDataImageOgr(std::map<std::string,Vector2d<float> >
&mapPixels, //[classNr][pixelNr][bandNr],
- std::vector<std::string>& fields,
- const std::vector<short>& bands,
- const std::string& label,
- const std::string& layername=std::string(),
- int verbose=false);
+ std::vector<std::string>& fields,
+ const std::vector<short>& bands,
+ const std::string& label,
+ const std::vector<std::string>& layers,
+ int verbose=false);
unsigned int readDataImageOgr(std::map<std::string,Vector2d<float> >
&mapPixels, //[classNr][pixelNr][bandNr],
- std::vector<std::string>& fields,
- double start,
- double end,
- const std::string& label,
- const std::string& layername=std::string(),
- int verbose=false);
+ std::vector<std::string>& fields,
+ double start,
+ double end,
+ const std::string& label,
+ const std::vector<std::string>& layers,
+ int verbose=false);
void shape2ascii(std::ostream& theOstream, const std::string& pointname, int
layer=0, bool verbose=false);
unsigned long int getFeatureCount(int layer=0) const;
--
Alioth's /usr/local/bin/git-commit-notice on
/srv/git.debian.org/git/pkg-grass/pktools.git
_______________________________________________
Pkg-grass-devel mailing list
Pkg-grass-devel@lists.alioth.debian.org
http://lists.alioth.debian.org/cgi-bin/mailman/listinfo/pkg-grass-devel
