OpenCV  4.2.0
Open Source Computer Vision
Classes | Typedefs | Functions
G-API Graph Compilation Arguments

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


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...


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


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...

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:

sobelEdge.apply(input, output, cv::compile_args(kernels));

Typedef Documentation

◆ GCompileArgs

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

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()

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:

< 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.