onnx.hpp File Reference

#include <unordered_map>
#include <string>
#include <array>
#include <tuple>
#include <opencv2/gapi/opencv_includes.hpp>
#include <opencv2/gapi/util/any.hpp>
#include <opencv2/core/cvdef.h>
#include <opencv2/gapi/gkernel.hpp>
#include <opencv2/gapi/infer.hpp>

Classes
struct	cv::gapi::onnx::ep::CUDA
	This structure provides functions that fill inference options for CUDA Execution Provider. Please follow https://onnxruntime.ai/docs/execution-providers/CUDA-ExecutionProvider.html#cuda-execution-provider. More...
class	cv::gapi::onnx::ep::DirectML
	This structure provides functions that fill inference options for ONNX DirectML Execution Provider. Please follow https://onnxruntime.ai/docs/execution-providers/DirectML-ExecutionProvider.html#directml-execution-provider. More...
struct	cv::gapi::onnx::ep::OpenVINO
	This structure provides functions that fill inference options for ONNX OpenVINO Execution Provider. Please follow https://onnxruntime.ai/docs/execution-providers/OpenVINO-ExecutionProvider.html#summary-of-options. More...
struct	cv::gapi::onnx::detail::ParamDesc
	This structure contains description of inference parameters which is specific to ONNX models. More...
class	cv::gapi::onnx::Params< Net >
class	cv::gapi::onnx::Params< cv::gapi::Generic >
struct	cv::gapi::onnx::PortCfg< Net >
struct	cv::gapi::onnx::ep::TensorRT
	This structure provides functions that fill inference options for TensorRT Execution Provider. Please follow https://onnxruntime.ai/docs/execution-providers/TensorRT-ExecutionProvider.html#tensorrt-execution-provider. More...

Namespaces
namespace	cv
	"black box" representation of the file storage associated with a file on disk.
namespace	cv::gapi
namespace	cv::gapi::onnx
	This namespace contains G-API ONNX Runtime backend functions, structures, and symbols.
namespace	cv::gapi::onnx::detail
namespace	cv::gapi::onnx::ep
	This namespace contains Execution Providers structures for G-API ONNX Runtime backend.

Typedefs
using	cv::gapi::onnx::ep::EP = cv::util::variant< cv::util::monostate, OpenVINO, DirectML, CUDA, TensorRT >
using	cv::gapi::onnx::PostProc = std::function< void(const std::unordered_map< std::string, cv::Mat > &, std::unordered_map< std::string, cv::Mat > &)>

Enumerations
enum class	cv::gapi::onnx::TraitAs : int {   cv::gapi::onnx::TENSOR ,   cv::gapi::onnx::IMAGE }

Functions
cv::gapi::GBackend	cv::gapi::onnx::backend ()