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commit 3444cb6cbd3e054eb1450e99eaae6f70b761f6f9
Author: Pieter Kempeneers <kempe...@gmail.com>
Date: Sat Jul 5 11:46:14 2014 +0200
changes in help info while reviewing pktools in book
---
src/apps/Makefile.am | 3 +-
src/apps/pkdiff.cc | 22 +++++++-------
src/apps/pkextract.cc | 22 +++++++-------
src/apps/pkstatogr.cc | 32 ++++++++++-----------
src/apps/pksvm.cc | 80 +++++++++++++++++++++++++--------------------------
5 files changed, 80 insertions(+), 79 deletions(-)
diff --git a/src/apps/Makefile.am b/src/apps/Makefile.am
index 85d7749..6aeeeae 100644
--- a/src/apps/Makefile.am
+++ b/src/apps/Makefile.am
@@ -6,7 +6,7 @@ LDADD = $(GSL_LIBS) $(GDAL_LDFLAGS)
$(top_builddir)/src/algorithms/libalgorithms
###############################################################################
# the program to build and install (the names of the final binaries)
-bin_PROGRAMS = pkinfo pkcrop pkreclass pkgetmask pksetmask pkcreatect
pkdumpimg pkdumpogr pksieve pkstatascii pkstatogr pkegcs pkextract pkfillnodata
pkfilter pkkalman pkfilterdem pkenhance pkfilterascii pkdsm2shadow pkcomposite
pkndvi pkpolygonize pkascii2img pksvm pkfssvm pkascii2ogr pkeditogr
+bin_PROGRAMS = pkinfo pkcrop pkreclass pkdiff pkgetmask pksetmask pkcreatect
pkdumpimg pkdumpogr pksieve pkstatascii pkstatogr pkegcs pkextract pkfillnodata
pkfilter pkkalman pkfilterdem pkenhance pkfilterascii pkdsm2shadow pkcomposite
pkndvi pkpolygonize pkascii2img pksvm pkfssvm pkascii2ogr pkeditogr
# the program to build but not install (the names of the final binaries)
#noinst_PROGRAMS = pkxcorimg pkgeom
@@ -38,6 +38,7 @@ endif
pkinfo_SOURCES = pkinfo.cc
pkcrop_SOURCES = pkcrop.cc
pkreclass_SOURCES = pkreclass.cc
+pkdiff_SOURCES = pkdiff.cc
pkgetmask_SOURCES = pkgetmask.cc
pksetmask_SOURCES = pksetmask.cc
pkcreatect_SOURCES = pkcreatect.cc
diff --git a/src/apps/pkdiff.cc b/src/apps/pkdiff.cc
index 27964e9..bb370be 100644
--- a/src/apps/pkdiff.cc
+++ b/src/apps/pkdiff.cc
@@ -31,7 +31,7 @@ int main(int argc, char *argv[])
{
Optionpk<string> input_opt("i", "input", "Input raster dataset.");
Optionpk<string> reference_opt("ref", "reference", "Reference (raster or
vector) dataset");
- Optionpk<string> layer_opt("ln", "ln", "layer name(s) in sample. Leave empty
to select all (for vector reference datasets only)");
+ Optionpk<string> layer_opt("ln", "ln", "Layer name(s) in sample. Leave empty
to select all (for vector reference datasets only)");
Optionpk<string> output_opt("o", "output", "Output dataset (optional)");
Optionpk<string> ogrformat_opt("f", "f", "OGR format for output vector (for
vector reference datasets only)","SQLite");
Optionpk<string> mask_opt("m", "mask", "Use the first band of the specified
file as a validity mask. Nodata values can be set with the option msknodata.");
@@ -41,17 +41,17 @@ int main(int argc, char *argv[])
Optionpk<short> valueC_opt("\0", "commission", "Value for commission errors:
input label < reference label", 2,1);
Optionpk<short> nodata_opt("nodata", "nodata", "No data value(s) in input or
reference dataset are ignored");
Optionpk<short> band_opt("b", "band", "Input raster band", 0);
- Optionpk<bool> confusion_opt("cm", "confusion", "create confusion matrix (to
std out)", false);
- Optionpk<string> labelref_opt("lr", "lref", "attribute name of the reference
label (for vector reference datasets only)", "label");
- Optionpk<string> labelclass_opt("lc", "lclass", "attribute name of the
classified label (for vector reference datasets only)", "class");
- Optionpk<short> boundary_opt("bnd", "boundary", "boundary for selecting the
sample (for vector reference datasets only)", 1,1);
- Optionpk<bool> homogeneous_opt("hom", "homogeneous", "only take regions with
homogeneous boundary into account (for reference datasets only)", false,1);
- Optionpk<bool> disc_opt("circ", "circular", "use circular boundary (for
vector reference datasets only)", false,1);
- Optionpk<string> classname_opt("c", "class", "list of class names.");
- Optionpk<short> classvalue_opt("r", "reclass", "list of class values (use
same order as in classname opt.");
- Optionpk<string> colorTable_opt("ct", "ct", "color table in ASCII format
having 5 columns: id R G B ALFA (0: transparent, 255: solid).");
+ Optionpk<bool> confusion_opt("cm", "confusion", "Create confusion matrix (to
std out)", false);
+ Optionpk<string> labelref_opt("lr", "lref", "Attribute name of the reference
label (for vector reference datasets only)", "label");
+ Optionpk<string> labelclass_opt("lc", "lclass", "Attribute name of the
classified label (for vector reference datasets only)", "class");
+ Optionpk<short> boundary_opt("bnd", "boundary", "Boundary for selecting the
sample (for vector reference datasets only)", 1,1);
+ Optionpk<bool> homogeneous_opt("hom", "homogeneous", "Only take regions with
homogeneous boundary into account (for reference datasets only)", false,1);
+ Optionpk<bool> disc_opt("circ", "circular", "Use circular boundary (for
vector reference datasets only)", false,1);
+ Optionpk<string> classname_opt("c", "class", "List of class names.");
+ Optionpk<short> classvalue_opt("r", "reclass", "List of class values (use
same order as in classname option).");
+ Optionpk<string> colorTable_opt("ct", "ct", "Color table in ASCII format
having 5 columns: id R G B ALFA (0: transparent, 255: solid).");
Optionpk<string> option_opt("co", "co", "Creation option for output file.
Multiple options can be specified.");
- Optionpk<short> verbose_opt("v", "verbose", "verbose", 0);
+ Optionpk<short> verbose_opt("v", "verbose", "Verbose level", 0);
bool doProcess;//stop process when program was invoked with help option (-h
--help)
try{
diff --git a/src/apps/pkextract.cc b/src/apps/pkextract.cc
index b13781c..51646cc 100644
--- a/src/apps/pkextract.cc
+++ b/src/apps/pkextract.cc
@@ -44,17 +44,17 @@ int main(int argc, char *argv[])
{
Optionpk<string> image_opt("i", "input", "Raster input dataset containing
band information");
Optionpk<string> sample_opt("s", "sample", "OGR vector file with features to
be extracted from input data. Output will contain features with input band
information included. Sample image can also be GDAL raster dataset.");
- Optionpk<string> layer_opt("ln", "ln", "layer name(s) in sample (leave empty
to select all)");
+ Optionpk<string> layer_opt("ln", "ln", "Layer name(s) in sample (leave empty
to select all)");
Optionpk<string> output_opt("o", "output", "Output sample file (image
file)");
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.
Make sure to set classes if rule is set to maxvote or proportion");
- 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<float> threshold_opt("t", "threshold", "Probability 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<string> ogrformat_opt("f", "f", "Output sample file
format","SQLite");
Optionpk<string> ftype_opt("ft", "ftype", "Field type (only Real or
Integer)", "Real");
Optionpk<string> ltype_opt("lt", "ltype", "Label type: In16 or String",
"Integer");
Optionpk<bool> polygon_opt("polygon", "polygon", "Create OGRPolygon as
geometry instead of OGRPoint. Only valid if sample features are polygons.",
false);
- Optionpk<int> band_opt("b", "band", "band index(es) to extract. Use -1 to
use all bands)", -1);
- Optionpk<string> rule_opt("r", "rule", "rule how to report image information
per feature (only for vector sample). point (value at each point or at centroid
if polygon), centroid, mean (of polygon), median (of polygon), proportion,
minimum (of polygon), maximum (of polygon), maxvote, sum.", "point");
- Optionpk<double> srcnodata_opt("srcnodata", "srcnodata", "invalid value(s)
for input image");
+ Optionpk<int> band_opt("b", "band", "Band index(es) to extract. Use -1 to
use all bands)", -1);
+ Optionpk<string> rule_opt("r", "rule", "Rule how to report image information
per feature (only for vector sample). point (value at each point or at centroid
if polygon), centroid, mean (of polygon), median (of polygon), proportion,
minimum (of polygon), maximum (of polygon), maxvote, sum.", "point");
+ Optionpk<double> srcnodata_opt("srcnodata", "srcnodata", "Invalid value(s)
for input image");
Optionpk<int> bndnodata_opt("bndnodata", "bndnodata", "Band(s) in input
image to check if pixel is valid (used for srcnodata)", 0);
// 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);
@@ -62,14 +62,14 @@ int main(int argc, char *argv[])
Optionpk<float> polythreshold_opt("tp", "thresholdPolygon", "(absolute)
threshold for selecting samples in each polygon");
Optionpk<string> test_opt("test", "test", "Test sample file (use this option
in combination with threshold<100 to create a training (output) and test set");
Optionpk<string> fieldname_opt("bn", "bname", "For single band input data,
this extra attribute name will correspond to the raster values. For multi-band
input data, multiple attributes with this prefix will be added (e.g. b0, b1,
b2, etc.)", "b");
- Optionpk<string> label_opt("cn", "cname", "name of the class label in the
output vector file", "label");
- Optionpk<short> geo_opt("g", "geo", "use geo coordinates (set to 0 to use
image coordinates)", 1);
- Optionpk<short> down_opt("down", "down", "down sampling factor (for raster
sample datasets only). Can be used to create grid points", 1);
- Optionpk<short> boundary_opt("bo", "boundary", "boundary for selecting the
sample (for vector sample datasets only) ", 1);
- Optionpk<short> disc_opt("circ", "circular", "circular disc kernel boundary
(for vector sample datasets only, use in combination with boundary option)", 0);
+ Optionpk<string> label_opt("cn", "cname", "Name of the class label in the
output vector file", "label");
+ Optionpk<short> geo_opt("g", "geo", "Use geo coordinates (set to 0 to use
image coordinates)", 1);
+ Optionpk<short> down_opt("down", "down", "Down sampling factor (for raster
sample datasets only). Can be used to create grid points", 1);
+ Optionpk<short> boundary_opt("bo", "boundary", "Boundary for selecting the
sample (for vector sample datasets only) ", 1);
+ Optionpk<short> disc_opt("circ", "circular", "Circular disc kernel boundary
(for vector sample datasets only, use in combination with boundary option)", 0);
// 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);
// Optionpk<short> cbox_opt("cbox", "cbox", "circular boundary (diameter in
m) to draw around the selected pixel. Can not combined with class option. Use
multiple cbox options for multiple boundary boxes. Use value 0 for no box)", 0);
- Optionpk<short> verbose_opt("v", "verbose", "verbose mode if > 0", 0);
+ Optionpk<short> verbose_opt("v", "verbose", "Verbose mode if > 0", 0);
bool doProcess;//stop process when program was invoked with help option (-h
--help)
try{
diff --git a/src/apps/pkstatogr.cc b/src/apps/pkstatogr.cc
index 6cbbefd..88b2a1f 100644
--- a/src/apps/pkstatogr.cc
+++ b/src/apps/pkstatogr.cc
@@ -30,23 +30,23 @@ using namespace std;
int main(int argc, char *argv[])
{
Optionpk<string> input_opt("i", "input", "Input OGR vector file", "");
- Optionpk<string> layer_opt("ln", "lname", "layer name(s) in sample (leave
empty to select all)");
- Optionpk<string> fieldname_opt("n", "fname", "fields on which to calculate
statistics", "");
- Optionpk<double> nodata_opt("nodata","nodata","set nodata value(s)");
- Optionpk<double> src_min_opt("src_min","src_min","set minimum value for
histogram");
- Optionpk<double> src_max_opt("src_max","src_max","set maximum value for
histogram");
- Optionpk<bool> size_opt("s","size","sample size (number of points)",false);
- Optionpk<bool> minmax_opt("mm","minmax","calculate minimum and maximum
value",false);
- Optionpk<bool> min_opt("min","min","calculate minimum value",0);
- Optionpk<bool> max_opt("max","max","calculate maximum value",0);
- Optionpk<bool> mean_opt("mean","mean","calculate mean value",false);
- Optionpk<bool> median_opt("median","median","calculate median value",false);
- Optionpk<bool> stdev_opt("stdev","stdev","calculate standard
deviation",false);
- Optionpk<bool> histogram_opt("hist","hist","calculate histogram",false);
- Optionpk<unsigned int> nbin_opt("nbin", "nbin", "number of bins");
- Optionpk<bool> relative_opt("rel","relative","use percentiles for histogram
to calculate histogram",false);
+ Optionpk<string> layer_opt("ln", "lname", "Layer name(s) in sample (leave
empty to select all)");
+ Optionpk<string> fieldname_opt("n", "fname", "Fields on which to calculate
statistics", "");
+ Optionpk<double> nodata_opt("nodata","nodata","Set nodata value(s)");
+ Optionpk<double> src_min_opt("src_min","src_min","Set minimum value for
histogram");
+ Optionpk<double> src_max_opt("src_max","src_max","Set maximum value for
histogram");
+ Optionpk<bool> size_opt("s","size","Sample size (number of points)",false);
+ Optionpk<bool> minmax_opt("mm","minmax","Calculate minimum and maximum
value",false);
+ Optionpk<bool> min_opt("min","min","Calculate minimum value",0);
+ Optionpk<bool> max_opt("max","max","Calculate maximum value",0);
+ Optionpk<bool> mean_opt("mean","mean","Calculate mean value",false);
+ Optionpk<bool> median_opt("median","median","Calculate median value",false);
+ Optionpk<bool> stdev_opt("stdev","stdev","Calculate standard
deviation",false);
+ Optionpk<bool> histogram_opt("hist","hist","Calculate histogram",false);
+ Optionpk<unsigned int> nbin_opt("nbin", "nbin", "Number of bins");
+ Optionpk<bool> relative_opt("rel","relative","Use percentiles for histogram
to calculate histogram",false);
Optionpk<bool> kde_opt("kde","kde","Use Kernel density estimation when
producing histogram. The standard deviation is estimated based on Silverman's
rule of thumb",false);
- Optionpk<short> verbose_opt("v", "verbose", "verbose mode if > 0", 0);
+ Optionpk<short> verbose_opt("v", "verbose", "Verbose level", 0);
bool doProcess;//stop process when program was invoked with help option (-h
--help)
try{
diff --git a/src/apps/pksvm.cc b/src/apps/pksvm.cc
index 17716eb..12ce0e6 100644
--- a/src/apps/pksvm.cc
+++ b/src/apps/pksvm.cc
@@ -49,52 +49,52 @@ 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(s)");
- Optionpk<string> label_opt("label", "label", "attribute name 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", "randomize training data for
balancing and bagging", true, 2);
- 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",0);
- Optionpk<double> end_opt("e", "end", "end band sequence number (set to 0 to
include all bands)", 0);
- 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 ). 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","",2);
- 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");
- Optionpk<std::string> kernel_type_opt("kt", "kerneltype", "type of kernel
function (linear,polynomial,radial,sigmoid) ","radial");
- Optionpk<unsigned short> kernel_degree_opt("kd", "kd", "degree in kernel
function",3);
- Optionpk<float> gamma_opt("g", "gamma", "gamma in kernel function",1.0);
- Optionpk<float> coef0_opt("c0", "coef0", "coef0 in kernel function",0);
- Optionpk<float> ccost_opt("cc", "ccost", "the parameter C of C_SVC,
epsilon_SVR, and nu_SVR",1000);
- Optionpk<float> nu_opt("nu", "nu", "the parameter nu of nu_SVC, one_class
SVM, and nu_SVR",0.5);
- Optionpk<float> epsilon_loss_opt("eloss", "eloss", "the epsilon in loss
function of epsilon_SVR",0.1);
- Optionpk<int> cache_opt("cache", "cache", "cache memory size in MB",100);
- Optionpk<float> epsilon_tol_opt("etol", "etol", "the tolerance of
termination criterion",0.001);
- Optionpk<bool> shrinking_opt("shrink", "shrink", "whether to use the
shrinking heuristics",false);
- Optionpk<bool> prob_est_opt("pe", "probest", "whether to train a SVC or SVR
model for probability estimates",true,2);
- // Optionpk<bool> weight_opt("wi", "wi", "set the parameter C of class i to
weight*C, for C_SVC",true);
- Optionpk<unsigned short> comb_opt("comb", "comb", "how to combine bootstrap
aggregation classifiers (0: sum rule, 1: product rule, 2: max rule). Also used
to aggregate classes with rc option.",0);
+ 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(s)");
+ Optionpk<string> label_opt("label", "label", "Attribute name 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", "Randomize training data for
balancing and bagging", true, 2);
+ 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",0);
+ Optionpk<double> end_opt("e", "end", "End band sequence number (set to 0 to
include all bands)", 0);
+ 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 ). 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","",2);
+ 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");
+ Optionpk<std::string> kernel_type_opt("kt", "kerneltype", "Type of kernel
function (linear,polynomial,radial,sigmoid) ","radial");
+ Optionpk<unsigned short> kernel_degree_opt("kd", "kd", "Degree in kernel
function",3);
+ Optionpk<float> gamma_opt("g", "gamma", "Gamma in kernel function",1.0);
+ Optionpk<float> coef0_opt("c0", "coef0", "Coef0 in kernel function",0);
+ Optionpk<float> ccost_opt("cc", "ccost", "The parameter C of C_SVC,
epsilon_SVR, and nu_SVR",1000);
+ Optionpk<float> nu_opt("nu", "nu", "The parameter nu of nu_SVC, one_class
SVM, and nu_SVR",0.5);
+ Optionpk<float> epsilon_loss_opt("eloss", "eloss", "The epsilon in loss
function of epsilon_SVR",0.1);
+ Optionpk<int> cache_opt("cache", "cache", "Cache memory size in MB",100);
+ Optionpk<float> epsilon_tol_opt("etol", "etol", "The tolerance of
termination criterion",0.001);
+ Optionpk<bool> shrinking_opt("shrink", "shrink", "Whether to use the
shrinking heuristics",false);
+ Optionpk<bool> prob_est_opt("pe", "probest", "Whether to train a SVC or SVR
model for probability estimates",true,2);
+ // Optionpk<bool> weight_opt("wi", "wi", "Set the parameter C of class i to
weight*C, for C_SVC",true);
+ Optionpk<unsigned short> comb_opt("comb", "comb", "How to combine bootstrap
aggregation classifiers (0: sum rule, 1: product rule, 2: max rule). Also used
to aggregate classes with rc option.",0);
Optionpk<unsigned short> bag_opt("bag", "bag", "Number of bootstrap
aggregations", 1);
Optionpk<int> bagSize_opt("bs", "bsize", "Percentage of features used from
available training features for each bootstrap aggregation (one size for all
classes, or a different size for each class respectively", 100);
- Optionpk<string> classBag_opt("cb", "classbag", "output for each individual
bootstrap aggregation");
+ Optionpk<string> classBag_opt("cb", "classbag", "Output for each individual
bootstrap aggregation");
Optionpk<string> mask_opt("m", "mask", "Use the first band of the specified
file as a validity mask. Nodata values can be set with the option msknodata.");
- Optionpk<short> msknodata_opt("msknodata", "msknodata", "mask value(s) not
to consider for classification (use negative values if only these values should
be taken into account). Values will be taken over in classification image.", 0);
- Optionpk<unsigned short> nodata_opt("nodata", "nodata", "nodata value to put
where image is masked as nodata", 0);
- Optionpk<string> output_opt("o", "output", "output classification image");
+ Optionpk<short> msknodata_opt("msknodata", "msknodata", "Mask value(s) not
to consider for classification (use negative values if only these values should
be taken into account). Values will be taken over in classification image.", 0);
+ Optionpk<unsigned short> nodata_opt("nodata", "nodata", "Nodata value to put
where image is masked as nodata", 0);
+ Optionpk<string> output_opt("o", "output", "Output classification image");
Optionpk<string> oformat_opt("of", "oformat", "Output image format (see
also gdal_translate). Empty string: inherit from input image");
Optionpk<string> option_opt("co", "co", "Creation option for output file.
Multiple options can be specified.");
- Optionpk<string> colorTable_opt("ct", "ct", "color table in ASCII format
having 5 columns: id R G B ALFA (0: transparent, 255: solid)");
- Optionpk<string> prob_opt("prob", "prob", "probability image.");
- Optionpk<string> entropy_opt("entropy", "entropy", "entropy image (measure
for uncertainty of classifier output","",2);
- Optionpk<string> active_opt("active", "active", "ogr output for active
training sample.","",2);
+ Optionpk<string> colorTable_opt("ct", "ct", "Color table in ASCII format
having 5 columns: id R G B ALFA (0: transparent, 255: solid)");
+ Optionpk<string> prob_opt("prob", "prob", "Probability image.");
+ Optionpk<string> entropy_opt("entropy", "entropy", "Entropy image (measure
for uncertainty of classifier output","",2);
+ Optionpk<string> active_opt("active", "active", "Ogr output for active
training sample.","",2);
Optionpk<string> ogrformat_opt("f", "f", "Output ogr format for active
training sample","SQLite");
- Optionpk<unsigned int> nactive_opt("na", "nactive", "number of active
training points",1);
- Optionpk<string> classname_opt("c", "class", "list of class names.");
- Optionpk<short> classvalue_opt("r", "reclass", "list of class values (use
same order as in class opt).");
- Optionpk<short> verbose_opt("v", "verbose", "set to: 0 (results only), 1
(confusion matrix), 2 (debug)",0);
+ Optionpk<unsigned int> nactive_opt("na", "nactive", "Number of active
training points",1);
+ Optionpk<string> classname_opt("c", "class", "List of class names.");
+ Optionpk<short> classvalue_opt("r", "reclass", "List of class values (use
same order as in class opt).");
+ Optionpk<short> verbose_opt("v", "verbose", "Verbose level",0);
bool doProcess;//stop process when program was invoked with help option (-h
--help)
try{
--
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