Compilation arguments: data structures controlling the compilation process. More...

Classes
struct	cv::gapi::plaidml::config
	This structure represents the basic parameters for the experimental PlaidML backend. More...

struct	cv::GCompileArg
	Represents an arbitrary compilation argument. More...

struct	cv::GFluidOutputRois
	This structure allows to control the output image region which Fluid backend will produce in the graph. More...

struct	cv::GFluidParallelFor
	This structure allows to customize the way how Fluid executes parallel regions. More...

struct	cv::GFluidParallelOutputRois
	This structure forces Fluid backend to generate multiple parallel output regions in the graph. These regions execute in parallel. More...

class	cv::gapi::GKernelPackage
	A container class for heterogeneous kernel implementation collections and graph transformations. More...

struct	cv::gapi::GNetPackage
	A container class for network configurations. Similar to GKernelPackage.Use cv::gapi::networks() to construct this object. More...

struct	cv::graph_dump_path
	Ask G-API to dump compiled graph in Graphviz format under the given file name. More...

struct	cv::gapi::use_only
	cv::use_only() is a special combinator which hints G-API to use only kernels specified in cv::GComputation::compile() (and not to extend kernels available by default with that package). More...

Typedefs
using	cv::GCompileArgs = std::vector< GCompileArg >

Functions
template<typename... Ts>
GCompileArgs	cv::compile_args (Ts &&... args)

template<typename... KK>
GKernelPackage	cv::gapi::kernels ()
	Create a kernel package object containing kernels and transformations specified in variadic template argument. More...

template<typename... FF>
GKernelPackage	cv::gapi::kernels (FF &... functors)

Detailed Description

Compilation arguments: data structures controlling the compilation process.

G-API comes with a number of graph compilation options which can be passed to cv::GComputation::apply() or cv::GComputation::compile(). Known compilation options are listed in this page, while extra backends may introduce their own compilation options (G-API transparently accepts everything which can be passed to cv::compile_args(), it depends on underlying backends if an option would be interpreted or not).

For example, if an example computation is executed like this:

cv::GComputation sobelEdge(cv::GIn(in), cv::GOut(out));

sobelEdge.apply(input, output);

Extra parameter specifying which kernels to compile with can be passed like this:

    cv::gapi::GKernelPackage kernels = cv::gapi::combine
        (cv::gapi::core::fluid::kernels(),
         cv::gapi::imgproc::fluid::kernels());
    sobelEdge.apply(input, output, cv::compile_args(kernels));

Typedef Documentation

◆ GCompileArgs

using cv::GCompileArgs = typedef std::vector<GCompileArg>

#include <opencv2/gapi/gcommon.hpp>

Function Documentation

◆ compile_args()

template<typename... Ts>

GCompileArgs cv::compile_args ( Ts &&... args )

#include <opencv2/gapi/gcommon.hpp>

Wraps a list of arguments (a parameter pack) into a vector of compilation arguments (cv::GCompileArg).

◆ kernels() [1/2]

template<typename... KK>

GKernelPackage cv::gapi::kernels ( )

#include <opencv2/gapi/gkernel.hpp>

Create a kernel package object containing kernels and transformations specified in variadic template argument.

In G-API, kernel implementations and transformations are types. Every backend has its own kernel API (like GAPI_OCV_KERNEL() and GAPI_FLUID_KERNEL()) but all of that APIs define a new type for each kernel implementation.

Use this function to pass kernel implementations (defined in either way) and transformations to the system. Example:

    cv::gapi::GKernelPackage pkg = cv::gapi::kernels
        < CustomAdd
        , CustomFilter2D
        , CustomRGB2YUV
        >();

Note that kernels() itself is a function returning object, not a type, so having () at the end is important – it must be a function call.

◆ kernels() [2/2]

template<typename... FF>

GKernelPackage cv::gapi::kernels ( FF &... functors )