Public Member Functions
InferenceEngine::PreProcessInfo Class Reference

This class stores pre-process information for the input. More...

#include <ie_preprocess.hpp>

Public Member Functions

PreProcessChannel::Ptr operator[] (size_t index)
  Overloaded [] operator to safely get the channel by an index. Throws an exception if channels are empty. More...
 
const PreProcessChannel::Ptr operator[] (size_t index) const
  operator [] to safely get the channel preprocessing information by index. Throws exception if channels are empty or index is out of border More...
 
size_t  getNumberOfChannels () const
  Returns a number of channels to preprocess. More...
 
void  init (const size_t numberOfChannels)
  Initializes with given number of channels. More...
 
void  setMeanImage (const Blob::Ptr &meanImage)
  Sets mean image values if operation is applicable. Also sets the mean type to MEAN_IMAGE for all channels. More...
 
void  setMeanImageForChannel (const Blob::Ptr &meanImage, const size_t channel)
  Sets mean image values if operation is applicable. Also sets the mean type to MEAN_IMAGE for a particular channel. More...
 
void  setVariant (const MeanVariant &variant)
  Sets a type of mean operation. More...
 
MeanVariant  getMeanVariant () const
  Gets a type of mean operation. More...
 
void  setResizeAlgorithm (const ResizeAlgorithm &alg)
  Sets resize algorithm to be used during pre-processing. More...
 
ResizeAlgorithm  getResizeAlgorithm () const
  Gets preconfigured resize algorithm. More...
 

Detailed Description

This class stores pre-process information for the input.

Member Function Documentation

§ getMeanVariant()

MeanVariant InferenceEngine::PreProcessInfo::getMeanVariant ( ) const
inline

Gets a type of mean operation.

Returns
The type of mean operation

§ getNumberOfChannels()

size_t InferenceEngine::PreProcessInfo::getNumberOfChannels ( ) const
inline

Returns a number of channels to preprocess.

Returns
The number of channels

§ getResizeAlgorithm()

ResizeAlgorithm InferenceEngine::PreProcessInfo::getResizeAlgorithm ( ) const
inline

Gets preconfigured resize algorithm.

Returns
Resize algorithm.

§ init()

void InferenceEngine::PreProcessInfo::init ( const size_t  numberOfChannels )
inline

Initializes with given number of channels.

Parameters
numberOfChannels Number of channels to initialize

§ operator[]() [1/2]

PreProcessChannel::Ptr& InferenceEngine::PreProcessInfo::operator[] ( size_t  index )
inline

Overloaded [] operator to safely get the channel by an index. Throws an exception if channels are empty.

Parameters
index Index of the channel to get
Returns
The pre-process channel instance

§ operator[]() [2/2]

const PreProcessChannel::Ptr& InferenceEngine::PreProcessInfo::operator[] ( size_t  index ) const
inline

operator [] to safely get the channel preprocessing information by index. Throws exception if channels are empty or index is out of border

Parameters
index Index of the channel to get
Returns
The const preprocess channel instance

§ setMeanImage()

void InferenceEngine::PreProcessInfo::setMeanImage ( const Blob::Ptr meanImage )
inline

Sets mean image values if operation is applicable. Also sets the mean type to MEAN_IMAGE for all channels.

Parameters
meanImage Blob with a mean image

§ setMeanImageForChannel()

void InferenceEngine::PreProcessInfo::setMeanImageForChannel ( const Blob::Ptr meanImage,
const size_t  channel 
)
inline

Sets mean image values if operation is applicable. Also sets the mean type to MEAN_IMAGE for a particular channel.

Parameters
meanImage Blob with a mean image
channel Index of a particular channel

§ setResizeAlgorithm()

void InferenceEngine::PreProcessInfo::setResizeAlgorithm ( const ResizeAlgorithm alg )
inline

Sets resize algorithm to be used during pre-processing.

Parameters
alg Resize algorithm.

§ setVariant()

void InferenceEngine::PreProcessInfo::setVariant ( const MeanVariant variant )
inline

Sets a type of mean operation.

Parameters
variant Type of mean operation to set

The documentation for this class was generated from the following file: