Tool Normal Bayes Classification (OpenCV)

Integration of the OpenCV Machine Learning library for Normal Bayes classification of gridded features.

References

Open Source Computer Vision

Author: O.Conrad (c) 2016
Menu: Imagery|Classification|Machine Learning

Parameters

	Name	Type	Identifier	Description	Constraints
Input	Features	Grid list (input)	`FEATURES`	-	-
Input	Training Areas	Shapes (input)	`TRAIN_AREAS`	-	-
Output	Probability (*)	Grid (optional output)	`PROBABILITY`	-	-
Output	Classification	Grid (output)	`CLASSES`	-	-
Options	Grid System	Grid system	`PARAMETERS_GRID_SYSTEM`	-	-
	Normalize	Boolean	`NORMALIZE`	-	Default: 0
	Update Colors from Features	Boolean	`RGB_COLORS`	Use the first three features in list to obtain blue, green, red components for class colour in look-up table.	Default: 1
	Load Model	File path	`MODEL_LOAD`	Use a model previously stored to file.	-
	Class Identifier	Table field	`TRAIN_CLASS`	-	-
	Buffer Size	Floating point	`TRAIN_BUFFER`	For non-polygon type training areas, creates a buffer with a diameter of specified size.	Minimum: 0.000000 Default: 1.000000
	Save Model	File path	`MODEL_SAVE`	Stores model to file to be used for subsequent classifications instead of training areas.	-
(*) optional

Command-line

Usage: saga_cmd imagery_opencv 5 [-FEATURES <str>] [-NORMALIZE <str>] [-PROBABILITY <str>] [-CLASSES <str>] [-MODEL_LOAD <str>] [-TRAIN_AREAS <str>] [-TRAIN_CLASS <str>] [-TRAIN_BUFFER <double>] [-MODEL_SAVE <str>]
  -FEATURES:<str>       	Features
	Grid list (input)
  -NORMALIZE:<str>      	Normalize
	Boolean
	Default: 0
  -PROBABILITY:<str>    	Probability
	Grid (optional output)
  -CLASSES:<str>        	Classification
	Grid (output)
  -MODEL_LOAD:<str>     	Load Model
	File path
  -TRAIN_AREAS:<str>    	Training Areas
	Shapes (input)
  -TRAIN_CLASS:<str>    	Class Identifier
	Table field
  -TRAIN_BUFFER:<double>	Buffer Size
	Floating point
	Minimum: 0.000000
	Default: 1.000000
  -MODEL_SAVE:<str>     	Save Model
	File path