1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
|
<root>
<key>SOMClassification</key>
<exec>otbcli_SOMClassification</exec>
<longname>SOM Classification</longname>
<group>Learning</group>
<description>SOM image classification.</description>
<parameter>
<parameter_type source_parameter_type="ParameterType_InputImage">ParameterRaster</parameter_type>
<key>in</key>
<name>InputImage</name>
<description>Input image to classify.</description>
<optional>False</optional>
</parameter>
<parameter>
<parameter_type source_parameter_type="ParameterType_OutputImage">OutputRaster</parameter_type>
<key>out</key>
<name>OutputImage</name>
<description>Output classified image (each pixel contains the index of its corresponding vector in the SOM).</description>
<hidden />
</parameter>
<parameter>
<parameter_type source_parameter_type="ParameterType_InputImage">ParameterRaster</parameter_type>
<key>vm</key>
<name>ValidityMask</name>
<description>Validity mask (only pixels corresponding to a mask value greater than 0 will be used for learning)</description>
<optional>True</optional>
</parameter>
<parameter>
<parameter_type source_parameter_type="ParameterType_Float">ParameterNumber</parameter_type>
<key>tp</key>
<name>TrainingProbability</name>
<description>Probability for a sample to be selected in the training set</description>
<minValue />
<maxValue />
<default>1</default>
</parameter>
<parameter>
<parameter_type source_parameter_type="ParameterType_Int">ParameterNumber</parameter_type>
<key>ts</key>
<name>TrainingSetSize</name>
<description>Maximum training set size (in pixels)</description>
<minValue />
<maxValue />
<default>0</default>
</parameter>
<parameter>
<parameter_type source_parameter_type="ParameterType_Int">ParameterNumber</parameter_type>
<key>sl</key>
<name>StreamingLines</name>
<description>Number of lines in each streaming block (used during data sampling)</description>
<minValue />
<maxValue />
<default>0</default>
</parameter>
<parameter>
<parameter_type source_parameter_type="ParameterType_OutputImage">OutputRaster</parameter_type>
<key>som</key>
<name>SOM Map</name>
<description>Output image containing the Self-Organizing Map</description>
<hidden />
</parameter>
<parameter>
<parameter_type source_parameter_type="ParameterType_Int">ParameterNumber</parameter_type>
<key>sx</key>
<name>SizeX</name>
<description>X size of the SOM map</description>
<minValue />
<maxValue />
<default>32</default>
</parameter>
<parameter>
<parameter_type source_parameter_type="ParameterType_Int">ParameterNumber</parameter_type>
<key>sy</key>
<name>SizeY</name>
<description>Y size of the SOM map</description>
<minValue />
<maxValue />
<default>32</default>
</parameter>
<parameter>
<parameter_type source_parameter_type="ParameterType_Int">ParameterNumber</parameter_type>
<key>nx</key>
<name>NeighborhoodX</name>
<description>X size of the initial neighborhood in the SOM map</description>
<minValue />
<maxValue />
<default>10</default>
</parameter>
<parameter>
<parameter_type source_parameter_type="ParameterType_Int">ParameterNumber</parameter_type>
<key>ny</key>
<name>NeighborhoodY</name>
<description>Y size of the initial neighborhood in the SOM map</description>
<minValue />
<maxValue />
<default>10</default>
</parameter>
<parameter>
<parameter_type source_parameter_type="ParameterType_Int">ParameterNumber</parameter_type>
<key>ni</key>
<name>NumberIteration</name>
<description>Number of iterations for SOM learning</description>
<minValue />
<maxValue />
<default>5</default>
</parameter>
<parameter>
<parameter_type source_parameter_type="ParameterType_Float">ParameterNumber</parameter_type>
<key>bi</key>
<name>BetaInit</name>
<description>Initial learning coefficient</description>
<minValue />
<maxValue />
<default>1</default>
</parameter>
<parameter>
<parameter_type source_parameter_type="ParameterType_Float">ParameterNumber</parameter_type>
<key>bf</key>
<name>BetaFinal</name>
<description>Final learning coefficient</description>
<minValue />
<maxValue />
<default>0.1</default>
</parameter>
<parameter>
<parameter_type source_parameter_type="ParameterType_Float">ParameterNumber</parameter_type>
<key>iv</key>
<name>InitialValue</name>
<description>Maximum initial neuron weight</description>
<minValue />
<maxValue />
<default>0</default>
</parameter>
<parameter>
<parameter_type source_parameter_type="ParameterType_RAM">ParameterNumber</parameter_type>
<key>ram</key>
<name>Available RAM (Mb)</name>
<description>Available memory for processing (in MB)</description>
<minValue />
<maxValue />
<default>128</default>
</parameter>
<parameter>
<parameter_type source_parameter_type="ParameterType_Int">ParameterNumber</parameter_type>
<key>rand</key>
<name>set user defined seed</name>
<description>Set specific seed. with integer value.</description>
<minValue />
<maxValue />
<default>0</default>
</parameter>
</root>
|
