perClass Documentation
version 5.4 (7-Dec-2018)
SDCONVERT  Convert alg into a pipeline or create type conversion pipeline

 To convert algorithm ALG into a pipeline:

 To add type conversion to an existing pipline:
   P2=SDCONVERT('uint8-double',P)  % P2 starts from uint8 data

 To create only the conversion pipeline including feature selection
   P=SDCONVERT('uint8-double','input',3,'select',[2 3])

   ALG      trained SDALG object

   OUT      converted pipeline

   'uint8-double'  - convert uint8 into double
   'uint16-double' - convert uint16 into double
   'input',D       - input dimensionality
   'select',ind    - indices of features to pass through

 SDCONVERT transforms trained object into a pipeline.
 For example, algorithm ALG may be converted (provided that the algorithm
 function must has a toconvert section defining the conversion)

 SDCONVERT can also create a type conversion pipeline which type-casts the
 input data in uint8 (or uint16) into double. This is useful to create
 exported pipelines that directly operate on byte/integer image data.  By
 default, specify conversion and provide pipeline object. SDCONVERT will
 add a conversion step and return the complete pipeline.
   pfull=SDCONVERT('uint8-double',p); % pfull can be applied to uint8 buffer

 Feature selection on the integer inputs may be specified with 'select'
 option. In this setup, we create a separate conversion pipeline and join
 later. Input dimensionality must be specified. Example of classifier on G
 and B bands:
  >> pc=sdconvert('uint8-double','input',3,'select',2:3)
  Type conversion pipeline  3x2  uint8-double
  >> p=sdfisher( data(:,{'G','B'} )  % our data contains R,G,B feature names
  >> pall=pc*p   % complete pipeline starting from R,G,B uint8 image data

sdconvert is referenced in examples: