OpenCV  4.5.1-pre
Open Source Computer Vision
Namespaces | Classes | Typedefs | Enumerations | Functions
cv::gapi::ie Namespace Reference

Namespaces

 detail
 

Classes

class  Params
 
class  Params< cv::gapi::Generic >
 
struct  PortCfg
 
class  PyParams
 

Typedefs

using IEConfig = std::map< std::string, std::string >
 

Enumerations

enum  TraitAs : int {
  TraitAs::TENSOR,
  TraitAs::IMAGE
}
 

Functions

cv::gapi::GBackend backend ()
 
PyParams params (const std::string &tag, const std::string &model, const std::string &weights, const std::string &device)
 
PyParams params (const std::string &tag, const std::string &model, const std::string &device)
 

Typedef Documentation

◆ IEConfig

using cv::gapi::ie::IEConfig = typedef std::map<std::string, std::string>

Enumeration Type Documentation

◆ TraitAs

enum cv::gapi::ie::TraitAs : int
strong

Specify how G-API and IE should trait input data

In OpenCV, the same cv::Mat is used to represent both image and tensor data. Sometimes those are hardly distinguishable, so this extra parameter is used to give G-API a hint.

This hint controls how G-API reinterprets the data when converting it to IE Blob format (and which layout/etc is assigned to this data).

Enumerator
TENSOR 

G-API traits an associated cv::Mat as a raw tensor and passes dimensions as-is.

IMAGE 

G-API traits an associated cv::Mat as an image so creates an "image" blob (NCHW/NHWC, etc)

Function Documentation

◆ backend()

cv::gapi::GBackend cv::gapi::ie::backend ( )

◆ params() [1/2]

PyParams cv::gapi::ie::params ( const std::string &  tag,
const std::string &  model,
const std::string &  weights,
const std::string &  device 
)
Python:
retval=cv.gapi.ie.params(tag, model, weights, device)
retval=cv.gapi.ie.params(tag, model, device)

◆ params() [2/2]

PyParams cv::gapi::ie::params ( const std::string &  tag,
const std::string &  model,
const std::string &  device 
)
Python:
retval=cv.gapi.ie.params(tag, model, weights, device)
retval=cv.gapi.ie.params(tag, model, device)