[pktools] 16/16: Add manpages for new executables.
Bas Couwenberg
sebastic at debian.org
Thu Jun 29 14:25:06 UTC 2017
This is an automated email from the git hooks/post-receive script.
sebastic pushed a commit to branch master
in repository pktools.
commit 7857bdf021c23093708614b917e41e9d0b592f82
Author: Bas Couwenberg <sebastic at xs4all.nl>
Date: Thu Jun 29 16:14:10 2017 +0200
Add manpages for new executables.
---
debian/changelog | 1 +
debian/man/pkannogr.1.xml | 478 +++++++++++++++++++++++++++++++++++++++
debian/man/pkreclassogr.1.xml | 125 +++++++++++
debian/man/pksvmogr.1.xml | 507 ++++++++++++++++++++++++++++++++++++++++++
debian/pktools.manpages | 3 +
5 files changed, 1114 insertions(+)
diff --git a/debian/changelog b/debian/changelog
index b1109d9..6f8c6d6 100644
--- a/debian/changelog
+++ b/debian/changelog
@@ -9,6 +9,7 @@ pktools (2.6.7.1+ds-1) unstable; urgency=medium
* Use pkg-info.mk variables instead of dpkg-parsechangelog output.
* Install pk{ann,reclass,svm}ogr in pktools package.
* Update spelling-errors2.patch to fix new 'columns' typo.
+ * Add manpages for new executables.
-- Bas Couwenberg <sebastic at debian.org> Thu, 29 Jun 2017 07:51:22 +0200
diff --git a/debian/man/pkannogr.1.xml b/debian/man/pkannogr.1.xml
new file mode 100644
index 0000000..9b130ec
--- /dev/null
+++ b/debian/man/pkannogr.1.xml
@@ -0,0 +1,478 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<!DOCTYPE refentry PUBLIC "-//OASIS//DTD DocBook XML V4.4//EN" "http://www.oasis-open.org/docbook/xml/4.4/docbookx.dtd">
+<refentry id='pkannogr'>
+
+ <refmeta>
+ <refentrytitle>pkannogr</refentrytitle>
+ <manvolnum>1</manvolnum>
+ </refmeta>
+
+ <refnamediv>
+ <refname>pkannogr</refname>
+ <refpurpose>classify vector dataset using Artificial Neural Network</refpurpose>
+ </refnamediv>
+
+ <refsynopsisdiv id='synopsis'>
+ <cmdsynopsis>
+ <command>pkannogr</command>
+ <arg choice='plain'><option>-t</option> <replaceable>training</replaceable></arg>
+ <arg choice='opt'><option>-i</option> <replaceable>input</replaceable></arg>
+ <arg choice='opt'><option>-o</option> <replaceable>output</replaceable></arg>
+ <arg choice='opt'><option>-cv</option> <replaceable>value</replaceable></arg>
+ <arg choice='opt'><replaceable>options</replaceable></arg>
+ <arg choice='opt'><replaceable>advanced options</replaceable></arg>
+ </cmdsynopsis>
+ </refsynopsisdiv>
+
+ <refsect1 id='description'>
+ <title>DESCRIPTION</title>
+ <para>
+ <command>pkannogr</command> implements an artificial neural network (ANN) to
+ solve a supervised classification problem.
+ The implementation is based on the open source C++ library
+ (<ulink url="http://leenissen.dk/fann/wp/">fann</ulink>).
+ Both raster and vector files are supported as input.
+ The output will contain the classification result, either in raster or
+ vector format, corresponding to the format of the input.
+ A training sample must be provided as an OGR vector dataset that contains
+ the class labels and the features for each training point.
+ The point locations are not considered in the training step.
+ You can use the same training sample for classifying different images,
+ provided the number of bands of the images are identical.
+ Use the utility
+ <citerefentry>
+ <refentrytitle>pkextract</refentrytitle>
+ <manvolnum>1</manvolnum>
+ </citerefentry>
+ to create a suitable training sample, based on a sample of points or
+ polygons.
+ For raster output maps you can attach a color table using the option
+ <option>-ct</option>.
+ </para>
+ </refsect1>
+
+ <refsect1 id='options'>
+ <title>OPTIONS</title>
+ <variablelist>
+
+ <varlistentry>
+ <term><option>-i</option> <replaceable>filename</replaceable></term>
+ <term><option>--input</option> <replaceable>filename</replaceable></term>
+ <listitem>
+ <para>
+ input image
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-t</option> <replaceable>filename</replaceable></term>
+ <term><option>--training</option> <replaceable>filename</replaceable></term>
+ <listitem>
+ <para>
+ 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 <option>--bag</option> and <option>--bsize</option> options,
+ where a random subset is taken from a single training file)
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-tln</option> <replaceable>layer</replaceable></term>
+ <term><option>--tln</option> <replaceable>layer</replaceable></term>
+ <listitem>
+ <para>
+ training layer name(s)
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-label</option> <replaceable>attribute</replaceable></term>
+ <term><option>--label</option> <replaceable>attribute</replaceable></term>
+ <listitem>
+ <para>
+ identifier for class label in training vector file.
+ (default: label)
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-prior</option> <replaceable>value</replaceable></term>
+ <term><option>--prior</option> <replaceable>value</replaceable></term>
+ <listitem>
+ <para>
+ prior probabilities for each class (e.g., <option>-prior</option>
+ 0.3 <option>-prior</option> 0.3 <option>-prior</option> 0.2 )
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-cv</option> <replaceable>value</replaceable></term>
+ <term><option>--cv</option> <replaceable>value</replaceable></term>
+ <listitem>
+ <para>
+ n-fold cross validation mode (default: 0)
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-nn</option> <replaceable>number</replaceable></term>
+ <term><option>--nneuron</option> <replaceable>number</replaceable></term>
+ <listitem>
+ <para>
+ number of neurons in hidden layers in neural network (multiple
+ hidden layers are set by defining multiple number of neurons:
+ <option>-nn</option> 15 <option>-nn</option> 1, default is one
+ hidden layer with 5 neurons)
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-m</option> <replaceable>filename</replaceable></term>
+ <term><option>--mask</option> <replaceable>filename</replaceable></term>
+ <listitem>
+ <para>
+ Only classify within specified mask (vector or raster).
+ For raster mask, set nodata values with the option
+ <option>--msknodata</option>.
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-msknodata</option> <replaceable>value</replaceable></term>
+ <term><option>--msknodata</option> <replaceable>value</replaceable></term>
+ <listitem>
+ <para>
+ mask value(s) not to consider for classification.
+ Values will be taken over in classification image.
+ Default is 0.
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-nodata</option> <replaceable>value</replaceable></term>
+ <term><option>--nodata</option> <replaceable>value</replaceable></term>
+ <listitem>
+ <para>
+ nodata value to put where image is masked as nodata
+ (default: 0)
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-o</option> <replaceable>filename</replaceable></term>
+ <term><option>--output</option> <replaceable>filename</replaceable></term>
+ <listitem>
+ <para>
+ output classification image
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-ot</option> <replaceable>type</replaceable></term>
+ <term><option>--otype</option> <replaceable>type</replaceable></term>
+ <listitem>
+ <para>
+ Data type for output image
+ ({Byte / Int16 / UInt16 / UInt32 / Int32 / Float32 / Float64 / CInt16 / CInt32 / CFloat32 / CFloat64}).
+ Empty string: inherit type from input image
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-of</option> <replaceable>GDALformat</replaceable></term>
+ <term><option>--oformat</option> <replaceable>GDALformat</replaceable></term>
+ <listitem>
+ <para>
+ Output image format (see also
+ <citerefentry>
+ <refentrytitle>gdal_translate</refentrytitle>
+ <manvolnum>1</manvolnum>
+ </citerefentry>).
+ Empty string: inherit from input image
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-f</option> <replaceable>OGRformat</replaceable></term>
+ <term><option>--f</option> <replaceable>OGRformat</replaceable></term>
+ <listitem>
+ <para>
+ Output ogr format for active training sample
+ (default: SQLite)
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-ct</option> <replaceable>filename</replaceable></term>
+ <term><option>--ct</option> <replaceable>filename</replaceable></term>
+ <listitem>
+ <para>
+ colour table in ASCII format having 5 columns: id R G B ALFA
+ (0: transparent, 255: solid)
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-co</option> <replaceable>NAME=VALUE</replaceable></term>
+ <term><option>--co</option> <replaceable>NAME=VALUE</replaceable></term>
+ <listitem>
+ <para>
+ Creation option for output file.
+ Multiple options can be specified.
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-c</option> <replaceable>name</replaceable></term>
+ <term><option>--class</option> <replaceable>name</replaceable></term>
+ <listitem>
+ <para>
+ list of class names.
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-r</option> <replaceable>value</replaceable></term>
+ <term><option>--reclass</option> <replaceable>value</replaceable></term>
+ <listitem>
+ <para>
+ list of class values (use same order as in
+ <option>--class</option> option).
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-v</option> <replaceable>0|1|2</replaceable></term>
+ <term><option>--verbose</option> <replaceable>0|1|2</replaceable></term>
+ <listitem>
+ <para>
+ set to: 0 (results only), 1 (confusion matrix), 2 (debug)
+ </para>
+ </listitem>
+ </varlistentry>
+
+ </variablelist>
+
+ <para>Advanced options</para>
+ <variablelist>
+
+ <varlistentry>
+ <term><option>-bal</option> <replaceable>size</replaceable></term>
+ <term><option>--balance</option> <replaceable>size</replaceable></term>
+ <listitem>
+ <para>
+ balance the input data to this number of samples for each class
+ (default: 0)
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-min</option> <replaceable>number</replaceable></term>
+ <term><option>--min</option> <replaceable>number</replaceable></term>
+ <listitem>
+ <para>
+ if number of training pixels is less then min, do not take this
+ class into account (0: consider all classes)
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-b</option> <replaceable>band</replaceable></term>
+ <term><option>--band</option> <replaceable>band</replaceable></term>
+ <listitem>
+ <para>
+ band index (starting from 0, either use <option>--band</option>
+ option or use <option>--start</option> to <option>--end</option>)
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-sband</option> <replaceable>band</replaceable></term>
+ <term><option>--startband</option> <replaceable>band</replaceable></term>
+ <listitem>
+ <para>
+ start band sequence number
+ (default: 0)
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-eband</option> <replaceable>band</replaceable></term>
+ <term><option>--endband</option> <replaceable>band</replaceable></term>
+ <listitem>
+ <para>
+ end band sequence number
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-offset</option> <replaceable>value</replaceable></term>
+ <term><option>--offset</option> <replaceable>value</replaceable></term>
+ <listitem>
+ <para>
+ offset value for each spectral band input features:
+ <literal>refl[band]=(DN[band]-offset[band])/scale[band]</literal>
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-scale</option> <replaceable>value</replaceable></term>
+ <term><option>--scale</option> <replaceable>value</replaceable></term>
+ <listitem>
+ <para>
+ scale value for each spectral band input features:
+ <literal>refl=(DN[band]-offset[band])/scale[band]</literal>
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-a</option> <replaceable>1|2</replaceable></term>
+ <term><option>--aggreg</option> <replaceable>1|2</replaceable></term>
+ <listitem>
+ <para>
+ how to combine aggregated classifiers, see also
+ <option>--rc</option> option (1: sum rule, 2: max rule).
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>--connection</option> <replaceable>0|1</replaceable></term>
+ <listitem>
+ <para>
+ connection rate (default: 1.0 for a fully connected network)
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-w</option> <replaceable>weights</replaceable></term>
+ <term><option>--weights</option> <replaceable>weights</replaceable></term>
+ <listitem>
+ <para>
+ weights for neural network.
+ Apply to fully connected network only, starting from first input
+ neuron to last output neuron, including the bias neurons (last
+ neuron in each but last layer)
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-l</option> <replaceable>rate</replaceable></term>
+ <term><option>--learning</option> <replaceable>rate</replaceable></term>
+ <listitem>
+ <para>
+ learning rate (default: 0.7)
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>--maxit</option> <replaceable>number</replaceable></term>
+ <listitem>
+ <para>
+ number of maximum iterations (epoch) (default: 500)
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-comb</option> <replaceable>rule</replaceable></term>
+ <term><option>--comb</option> <replaceable>rule</replaceable></term>
+ <listitem>
+ <para>
+ how to combine bootstrap aggregation classifiers
+ (0: sum rule, 1: product rule, 2: max rule).
+ Also used to aggregate classes with <option>--rc</option> option.
+ Default is sum rule (0)
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-bag</option> <replaceable>value</replaceable></term>
+ <term><option>--bag</option> <replaceable>value</replaceable></term>
+ <listitem>
+ <para>
+ Number of bootstrap aggregations (default is no bagging: 1)
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-bs</option> <replaceable>value</replaceable></term>
+ <term><option>--bsize</option> <replaceable>value</replaceable></term>
+ <listitem>
+ <para>
+ 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. default: 100)
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-cb</option> <replaceable>filename</replaceable></term>
+ <term><option>--classbag</option> <replaceable>filename</replaceable></term>
+ <listitem>
+ <para>
+ output for each individual bootstrap aggregation (default is blank)
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>--prob</option> <replaceable>filename</replaceable></term>
+ <listitem>
+ <para>
+ probability image.
+ Default is no probability image
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-na</option> <replaceable>number</replaceable></term>
+ <term><option>--na</option> <replaceable>number</replaceable></term>
+ <listitem>
+ <para>
+ number of active training points
+ (default: 1)
+ </para>
+ </listitem>
+ </varlistentry>
+
+ </variablelist>
+
+ </refsect1>
+
+</refentry>
diff --git a/debian/man/pkreclassogr.1.xml b/debian/man/pkreclassogr.1.xml
new file mode 100644
index 0000000..72af485
--- /dev/null
+++ b/debian/man/pkreclassogr.1.xml
@@ -0,0 +1,125 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<!DOCTYPE refentry PUBLIC "-//OASIS//DTD DocBook XML V4.4//EN" "http://www.oasis-open.org/docbook/xml/4.4/docbookx.dtd">
+<refentry id='pkreclassogr'>
+
+ <refmeta>
+ <refentrytitle>pkreclassogr</refentrytitle>
+ <manvolnum>1</manvolnum>
+ </refmeta>
+
+ <refnamediv>
+ <refname>pkreclassogr</refname>
+ <refpurpose>replace field values of attributes in vector datasets</refpurpose>
+ </refnamediv>
+
+ <refsynopsisdiv id='synopsis'>
+ <cmdsynopsis>
+ <command>pkreclassogr</command>
+ <arg choice='plain'><option>-i</option> <replaceable>input</replaceable></arg>
+ <arg choice='opt'>
+ <option>-c</option> <replaceable>from</replaceable>
+ <option>-r</option> <replaceable>to</replaceable>
+ </arg>
+ <arg choice='plain'><option>-o</option> <replaceable>output</replaceable></arg>
+ <arg choice='opt'><replaceable>options</replaceable></arg>
+ </cmdsynopsis>
+ </refsynopsisdiv>
+
+ <refsect1 id='description'>
+ <title>DESCRIPTION</title>
+ <para>
+ <command>pkreclassogr</command> is a program to replace field values of
+ attributes in vector datasets.
+ </para>
+ </refsect1>
+
+ <refsect1 id='options'>
+ <title>OPTIONS</title>
+ <variablelist>
+
+ <varlistentry>
+ <term><option>-i</option> <replaceable>filename</replaceable></term>
+ <term><option>--input</option> <replaceable>filename</replaceable></term>
+ <listitem>
+ <para>
+ Input vector dataset
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-o</option> <replaceable>filename</replaceable></term>
+ <term><option>--output</option> <replaceable>filename</replaceable></term>
+ <listitem>
+ <para>
+ Output file
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-nodata</option> <replaceable>value</replaceable></term>
+ <term><option>--nodata</option> <replaceable>value</replaceable></term>
+ <listitem>
+ <para>
+ nodata value to put in vector dataset if not valid (0)
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-code</option> <replaceable>filename</replaceable></term>
+ <term><option>--code</option> <replaceable>filename</replaceable></term>
+ <listitem>
+ <para>
+ Recode text file (2 columns: from to)
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-c</option> <replaceable>classes</replaceable></term>
+ <term><option>--class</option> <replaceable>classes</replaceable></term>
+ <listitem>
+ <para>
+ list of classes to reclass (in combination with reclass option)
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-r</option> <replaceable>classes</replaceable></term>
+ <term><option>--reclass</option> <replaceable>classes</replaceable></term>
+ <listitem>
+ <para>
+ list of recoded classes (in combination with class option)
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-n</option> <replaceable>name</replaceable></term>
+ <term><option>--fname</option> <replaceable>name</replaceable></term>
+ <listitem>
+ <para>
+ field name of the shape file to be replaced
+ default: label
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-v</option> <replaceable>level</replaceable></term>
+ <term><option>--verbose</option> <replaceable>level</replaceable></term>
+ <listitem>
+ <para>
+ Verbose mode if > 0
+ </para>
+ </listitem>
+ </varlistentry>
+
+ </variablelist>
+
+ </refsect1>
+
+</refentry>
diff --git a/debian/man/pksvmogr.1.xml b/debian/man/pksvmogr.1.xml
new file mode 100644
index 0000000..015fbaf
--- /dev/null
+++ b/debian/man/pksvmogr.1.xml
@@ -0,0 +1,507 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<!DOCTYPE refentry PUBLIC "-//OASIS//DTD DocBook XML V4.4//EN" "http://www.oasis-open.org/docbook/xml/4.4/docbookx.dtd">
+<refentry id='pksvmogr'>
+
+ <refmeta>
+ <refentrytitle>pksvmogr</refentrytitle>
+ <manvolnum>1</manvolnum>
+ </refmeta>
+
+ <refnamediv>
+ <refname>pksvmogr</refname>
+ <refpurpose>classify vector dataset using Support Vector Machine</refpurpose>
+ </refnamediv>
+
+ <refsynopsisdiv id='synopsis'>
+ <cmdsynopsis>
+ <command>pksvmogr</command>
+ <arg choice='plain'><option>-t</option> <replaceable>training</replaceable></arg>
+ <arg choice='opt'><option>-i</option> <replaceable>input</replaceable></arg>
+ <arg choice='opt'><option>-o</option> <replaceable>output</replaceable></arg>
+ <arg choice='opt'><option>-cv</option> <replaceable>value</replaceable></arg>
+ <arg choice='opt'><replaceable>options</replaceable></arg>
+ <arg choice='opt'><replaceable>advanced options</replaceable></arg>
+ </cmdsynopsis>
+ </refsynopsisdiv>
+
+ <refsect1 id='description'>
+ <title>DESCRIPTION</title>
+ <para>
+ <command>pksvmogr</command> implements a support vector machine (SVM) to
+ solve a supervised classification problem.
+ The implementation is based on the open source C++ library libSVM
+ (http://www.csie.ntu.edu.tw/~cjlin/libsvm).
+ Both raster and vector files are supported as input.
+ The output will contain the classification result, either in raster or
+ vector format, corresponding to the format of the input.
+ A training sample must be provided as an OGR vector dataset that
+ contains the class labels and the features for each training point.
+ The point locations are not considered in the training step.
+ You can use the same training sample for classifying different images,
+ provided the number of bands of the images are identical.
+ Use the utility pkextract to create a suitable training sample, based
+ on a sample of points or polygons.
+ For raster output maps you can attach a color table using the option
+ <option>-ct</option>.
+ </para>
+ </refsect1>
+
+ <refsect1 id='options'>
+ <title>OPTIONS</title>
+ <variablelist>
+
+ <varlistentry>
+ <term><option>-t</option> <replaceable>filename</replaceable></term>
+ <term><option>--training</option> <replaceable>filename</replaceable></term>
+ <listitem>
+ <para>
+ 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 <option>--bag</option> and
+ <option>--bagsize</option> options, where a random subset
+ is taken from a single training file)
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-i</option> <replaceable>filename</replaceable></term>
+ <term><option>--input</option> <replaceable>filename</replaceable></term>
+ <listitem>
+ <para>
+ input image
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-o</option> <replaceable>filename</replaceable></term>
+ <term><option>--output</option> <replaceable>filename</replaceable></term>
+ <listitem>
+ <para>
+ Output classification image
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-cv</option> <replaceable>value</replaceable></term>
+ <term><option>--cv</option> <replaceable>value</replaceable></term>
+ <listitem>
+ <para>
+ N-fold cross validation mode (default: 0)
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-tln</option> <replaceable>layer</replaceable></term>
+ <term><option>--tln</option> <replaceable>layer</replaceable></term>
+ <listitem>
+ <para>
+ Training layer name(s)
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-c</option> <replaceable>name</replaceable></term>
+ <term><option>--class</option> <replaceable>name</replaceable></term>
+ <listitem>
+ <para>
+ List of class names.
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-r</option> <replaceable>value</replaceable></term>
+ <term><option>--reclass</option> <replaceable>value</replaceable></term>
+ <listitem>
+ <para>
+ List of class values (use same order as in
+ <option>--class</option> option).
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-of</option> <replaceable>GDALformat</replaceable></term>
+ <term><option>--oformat</option> <replaceable>GDALformat</replaceable></term>
+ <listitem>
+ <para>
+ Output image format (see also
+ <citerefentry>
+ <refentrytitle>gdal_translate</refentrytitle>
+ <manvolnum>1</manvolnum>
+ </citerefentry>).
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-f</option> <replaceable>format</replaceable></term>
+ <term><option>--f</option> <replaceable>format</replaceable></term>
+ <listitem>
+ <para>
+ Output ogr format for active training sample
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-co</option> <replaceable>NAME=VALUE</replaceable></term>
+ <term><option>--co</option> <replaceable>NAME=VALUE</replaceable></term>
+ <listitem>
+ <para>
+ Creation option for output file.
+ Multiple options can be specified.
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-ct</option> <replaceable>filename</replaceable></term>
+ <term><option>--ct</option> <replaceable>filename</replaceable></term>
+ <listitem>
+ <para>
+ Color table in ASCII format having 5 columns:
+ id R G B ALFA (0: transparent, 255: solid)
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-label</option> <replaceable>attribute</replaceable></term>
+ <term><option>--label</option> <replaceable>attribute</replaceable></term>
+ <listitem>
+ <para>
+ Identifier for class label in training vector file.
+ (default: label)
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-prior</option> <replaceable>value</replaceable></term>
+ <term><option>--prior</option> <replaceable>value</replaceable></term>
+ <listitem>
+ <para>
+ Prior probabilities for each class (e.g.,
+ <option>-prior</option> 0.3 <option>-prior</option> 0.3
+ <option>-prior</option> 0.2)
+ Used for input only (ignored for cross validation)
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-g</option> <replaceable>gamma</replaceable></term>
+ <term><option>--gamma</option> <replaceable>gamma</replaceable></term>
+ <listitem>
+ <para>
+ Gamma in kernel function
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-cc</option> <replaceable>cost</replaceable></term>
+ <term><option>--ccost</option> <replaceable>cost</replaceable></term>
+ <listitem>
+ <para>
+ The parameter C of C_SVC, epsilon_SVR, and nu_SVR
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-m</option> <replaceable>filename</replaceable></term>
+ <term><option>--mask</option> <replaceable>filename</replaceable></term>
+ <listitem>
+ <para>
+ Only classify within specified mask (vector or raster).
+ For raster mask, set nodata values with the option
+ <option>--msknodata</option>.
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-msknodata</option> <replaceable>value</replaceable></term>
+ <term><option>--msknodata</option> <replaceable>value</replaceable></term>
+ <listitem>
+ <para>
+ Mask value(s) not to consider for classification.
+ Values will be taken over in classification image.
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-nodata</option> <replaceable>value</replaceable></term>
+ <term><option>--nodata</option> <replaceable>value</replaceable></term>
+ <listitem>
+ <para>
+ Nodata value to put where image is masked as nodata
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-v</option> <replaceable>level</replaceable></term>
+ <term><option>--verbose</option> <replaceable>level</replaceable></term>
+ <listitem>
+ <para>
+ Verbose level
+ </para>
+ </listitem>
+ </varlistentry>
+
+ </variablelist>
+
+ <para>Advanced options</para>
+ <variablelist>
+
+ <varlistentry>
+ <term><option>-b</option> <replaceable>band</replaceable></term>
+ <term><option>--band</option> <replaceable>band</replaceable></term>
+ <listitem>
+ <para>
+ Band index (starting from 0, either use <option>--band</option>
+ option or use <option>--startband</option> to
+ <option>--endband</option>)
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-sband</option> <replaceable>band</replaceable></term>
+ <term><option>--startband</option> <replaceable>band</replaceable></term>
+ <listitem>
+ <para>
+ Start band sequence number
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-eband</option> <replaceable>band</replaceable></term>
+ <term><option>--endband</option> <replaceable>band</replaceable></term>
+ <listitem>
+ <para>
+ End band sequence number
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-bal</option> <replaceable>size</replaceable></term>
+ <term><option>--balance</option> <replaceable>size</replaceable></term>
+ <listitem>
+ <para>
+ Balance the input data to this number of samples for each class
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-min</option> <replaceable>number</replaceable></term>
+ <term><option>--min</option> <replaceable>number</replaceable></term>
+ <listitem>
+ <para>
+ If number of training pixels is less then min, do not take this
+ class into account (0: consider all classes)
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-bag</option> <replaceable>value</replaceable></term>
+ <term><option>--bag</option> <replaceable>value</replaceable></term>
+ <listitem>
+ <para>
+ Number of bootstrap aggregations (default is no bagging: 1)
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-bagsize</option> <replaceable>value</replaceable></term>
+ <term><option>--bagsize</option> <replaceable>value</replaceable></term>
+ <listitem>
+ <para>
+ 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
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-comb</option> <replaceable>rule</replaceable></term>
+ <term><option>--comb</option> <replaceable>rule</replaceable></term>
+ <listitem>
+ <para>
+ How to combine bootstrap aggregation classifiers
+ (0: sum rule, 1: product rule, 2: max rule).
+ Also used to aggregate classes with rc option.
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-cb</option> <replaceable>filename</replaceable></term>
+ <term><option>--classbag</option> <replaceable>filename</replaceable></term>
+ <listitem>
+ <para>
+ Output for each individual bootstrap aggregation
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-prob</option> <replaceable>filename</replaceable></term>
+ <term><option>--prob</option> <replaceable>filename</replaceable></term>
+ <listitem>
+ <para>
+ Probability image.
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-offset</option> <replaceable>value</replaceable></term>
+ <term><option>--offset</option> <replaceable>value</replaceable></term>
+ <listitem>
+ <para>
+ Offset value for each spectral band input features:
+ <literal>refl[band]=(DN[band]-offset[band])/scale[band]</literal>
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-scale</option> <replaceable>value</replaceable></term>
+ <term><option>--scale</option> <replaceable>value</replaceable></term>
+ <listitem>
+ <para>
+ Scale value for each spectral band input features:
+ <literal>refl=(DN[band]-offset[band])/scale[band]</literal>
+ (use <literal>0</literal> if scale min and max in each band to
+ <literal>-1.0</literal> and <literal>1.0</literal>)
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-svmt</option> <replaceable>type</replaceable></term>
+ <term><option>--svmtype</option> <replaceable>type</replaceable></term>
+ <listitem>
+ <para>
+ Type of SVM (C_SVC, nu_SVC,one_class, epsilon_SVR, nu_SVR)
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-kt</option> <replaceable>type</replaceable></term>
+ <term><option>--kerneltype</option> <replaceable>type</replaceable></term>
+ <listitem>
+ <para>
+ Type of kernel function (linear,polynomial,radial,sigmoid)
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-kd</option> <replaceable>value</replaceable></term>
+ <term><option>--kd</option> <replaceable>value</replaceable></term>
+ <listitem>
+ <para>
+ Degree in kernel function
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-c0</option> <replaceable>value</replaceable></term>
+ <term><option>--coef0</option> <replaceable>value</replaceable></term>
+ <listitem>
+ <para>
+ Coef0 in kernel function
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-nu</option> <replaceable>value</replaceable></term>
+ <term><option>--nu</option> <replaceable>value</replaceable></term>
+ <listitem>
+ <para>
+ The parameter nu of nu-SVC, one-class SVM, and nu-SVR
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-eloss</option> <replaceable>value</replaceable></term>
+ <term><option>--eloss</option> <replaceable>value</replaceable></term>
+ <listitem>
+ <para>
+ The epsilon in loss function of epsilon-SVR
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-cache</option> <replaceable>number</replaceable></term>
+ <term><option>--cache</option> <replaceable>number</replaceable></term>
+ <listitem>
+ <para>
+ <ulink url="http://pktools.nongnu.org/html/classCache.html">Cache</ulink>
+ memory size in MB
+ (default: 100)
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-etol</option> <replaceable>value</replaceable></term>
+ <term><option>--etol</option> <replaceable>value</replaceable></term>
+ <listitem>
+ <para>
+ the tolerance of termination criterion
+ (default: 0.001)
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-shrink</option></term>
+ <term><option>--shrink</option></term>
+ <listitem>
+ <para>
+ Whether to use the shrinking heuristics
+ </para>
+ </listitem>
+ </varlistentry>
+
+ <varlistentry>
+ <term><option>-na</option> <replaceable>number</replaceable></term>
+ <term><option>--nactive</option> <replaceable>number</replaceable></term>
+ <listitem>
+ <para>
+ Number of active training points
+ </para>
+ </listitem>
+ </varlistentry>
+
+ </variablelist>
+
+ </refsect1>
+
+</refentry>
diff --git a/debian/pktools.manpages b/debian/pktools.manpages
index 88a5ddc..ec40e68 100644
--- a/debian/pktools.manpages
+++ b/debian/pktools.manpages
@@ -1,4 +1,5 @@
debian/man/pkann.1
+debian/man/pkannogr.1
debian/man/pkascii2img.1
debian/man/pkascii2ogr.1
debian/man/pkcomposite.1
@@ -24,6 +25,7 @@ debian/man/pklas2img.1
debian/man/pkoptsvm.1
debian/man/pkpolygonize.1
debian/man/pkreclass.1
+debian/man/pkreclassogr.1
debian/man/pkregann.1
debian/man/pksetmask.1
debian/man/pksieve.1
@@ -32,3 +34,4 @@ debian/man/pkstatascii.1
debian/man/pkstatogr.1
debian/man/pkstatprofile.1
debian/man/pksvm.1
+debian/man/pksvmogr.1
--
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