OpenCV
4.10.0-dev
Open Source Computer Vision
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Compilation arguments: data structures controlling the compilation process. More...
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:
Extra parameter specifying which kernels to compile with can be passed like this:
Namespaces | |
namespace | cv::gapi |
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::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::gapi::use_only |
cv::gapi::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) |
Wraps a list of arguments (a parameter pack) into a vector of compilation arguments (cv::GCompileArg). | |
template<typename... KK> | |
GKernelPackage | cv::gapi::kernels () |
Create a kernel package object containing kernels and transformations specified in variadic template argument. | |
template<typename... FF> | |
GKernelPackage | cv::gapi::kernels (FF &... functors) |
cv::GCompileArgs & | cv::operator+= (cv::GCompileArgs &lhs, const cv::GCompileArgs &rhs) |
using cv::GCompileArgs = typedef std::vector<GCompileArg> |
#include <opencv2/gapi/gcommon.hpp>
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).
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:
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.
GKernelPackage cv::gapi::kernels | ( | FF &... | functors | ) |
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inline |
#include <opencv2/gapi/gcommon.hpp>