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https://github.com/opencv/opencv.git
synced 2026-07-30 07:43:03 +04:00
Merge branch 4.x
This commit is contained in:
Alexander Smorkalov
@@ -0,0 +1,29 @@
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// This file is part of OpenCV project.
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// It is subject to the license terms in the LICENSE file found in the top-level directory
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// of this distribution and at http://opencv.org/license.html.
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//
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// Copyright (C) 2018 Intel Corporation
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#ifndef OPENCV_GAPI_CPU_OT_API_HPP
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#define OPENCV_GAPI_CPU_OT_API_HPP
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#include <opencv2/core/cvdef.h> // GAPI_EXPORTS
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#include <opencv2/gapi/gkernel.hpp> // GKernelPackage
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namespace cv {
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namespace gapi {
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/**
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* @brief This namespace contains G-API Operation Types for
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* VAS Object Tracking module functionality.
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*/
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namespace ot {
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namespace cpu {
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GAPI_EXPORTS_W GKernelPackage kernels();
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} // namespace cpu
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} // namespace ot
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} // namespace gapi
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} // namespace cv
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#endif // OPENCV_GAPI_CPU_OT_API_HPP
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@@ -39,6 +39,9 @@ public:
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GAPI_WRAP
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PyParams& cfgAddExecutionProvider(ep::DirectML ep);
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GAPI_WRAP
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PyParams& cfgAddExecutionProvider(ep::CoreML ep);
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GAPI_WRAP
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PyParams& cfgAddExecutionProvider(ep::CUDA ep);
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@@ -32,6 +32,65 @@ namespace onnx {
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*/
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namespace ep {
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/**
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* @brief This structure provides functions
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* that fill inference options for ONNX CoreML Execution Provider.
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* Please follow https://onnxruntime.ai/docs/execution-providers/CoreML-ExecutionProvider.html#coreml-execution-provider
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*/
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struct GAPI_EXPORTS_W_SIMPLE CoreML {
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/** @brief Class constructor.
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Constructs CoreML parameters.
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*/
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GAPI_WRAP
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CoreML() = default;
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/** @brief Limit CoreML Execution Provider to run on CPU only.
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This function is used to limit CoreML to run on CPU only.
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Please follow: https://onnxruntime.ai/docs/execution-providers/CoreML-ExecutionProvider.html#coreml_flag_use_cpu_only
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@return reference to this parameter structure.
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*/
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GAPI_WRAP
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CoreML& cfgUseCPUOnly() {
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use_cpu_only = true;
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return *this;
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}
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/** @brief Enable CoreML EP to run on a subgraph in the body of a control flow ONNX operator (i.e. a Loop, Scan or If operator).
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This function is used to enable CoreML EP to run on
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a subgraph of a control flow of ONNX operation.
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Please follow: https://onnxruntime.ai/docs/execution-providers/CoreML-ExecutionProvider.html#coreml_flag_enable_on_subgraph
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@return reference to this parameter structure.
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*/
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GAPI_WRAP
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CoreML& cfgEnableOnSubgraph() {
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enable_on_subgraph = true;
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return *this;
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}
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/** @brief Enable CoreML EP to run only on Apple Neural Engine.
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This function is used to enable CoreML EP to run only on Apple Neural Engine.
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Please follow: https://onnxruntime.ai/docs/execution-providers/CoreML-ExecutionProvider.html#coreml_flag_only_enable_device_with_ane
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@return reference to this parameter structure.
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*/
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GAPI_WRAP
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CoreML& cfgEnableOnlyNeuralEngine() {
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enable_only_ane = true;
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return *this;
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}
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bool use_cpu_only = false;
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bool enable_on_subgraph = false;
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bool enable_only_ane = false;
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};
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/**
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* @brief This structure provides functions
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* that fill inference options for CUDA Execution Provider.
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@@ -189,13 +248,23 @@ public:
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GAPI_WRAP
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explicit DirectML(const int device_id) : ddesc(device_id) { };
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using DeviceDesc = cv::util::variant<int>;
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/** @brief Class constructor.
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Constructs DirectML parameters based on adapter name.
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@param adapter_name Target adapter_name to use.
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*/
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GAPI_WRAP
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explicit DirectML(const std::string &adapter_name) : ddesc(adapter_name) { };
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using DeviceDesc = cv::util::variant<int, std::string>;
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DeviceDesc ddesc;
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};
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using EP = cv::util::variant< cv::util::monostate
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, OpenVINO
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, DirectML
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, CoreML
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, CUDA
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, TensorRT>;
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@@ -487,6 +556,20 @@ public:
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/** @brief Adds execution provider for runtime.
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The function is used to add ONNX Runtime CoreML Execution Provider options.
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@param ep CoreML Execution Provider options.
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@see cv::gapi::onnx::ep::CoreML.
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@return the reference on modified object.
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*/
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Params<Net>& cfgAddExecutionProvider(ep::CoreML&& ep) {
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desc.execution_providers.emplace_back(std::move(ep));
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return *this;
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}
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/** @brief Adds execution provider for runtime.
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The function is used to add ONNX Runtime CUDA Execution Provider options.
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@param ep CUDA Execution Provider options.
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@@ -573,6 +656,11 @@ public:
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desc.execution_providers.emplace_back(std::move(ep));
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}
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/** @see onnx::Params::cfgAddExecutionProvider. */
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void cfgAddExecutionProvider(ep::CoreML&& ep) {
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desc.execution_providers.emplace_back(std::move(ep));
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}
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/** @see onnx::Params::cfgAddExecutionProvider. */
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void cfgAddExecutionProvider(ep::CUDA&& ep) {
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desc.execution_providers.emplace_back(std::move(ep));
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@@ -679,7 +679,32 @@ protected:
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};
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} // namespace ov
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namespace wip { namespace ov {
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/**
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* @brief Ask G-API OpenVINO backend to run only inference of model provided.
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*
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* G-API OpenVINO backend will perform only the inference of the model provided
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* without populating input and copying back output data.
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* This mode is used to evaluate the pure inference performance of the model without
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* taking into account the i/o data transfer.
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*/
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struct benchmark_mode { };
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/** @} */
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} // namespace ov
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} // namespace wip
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} // namespace gapi
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namespace detail
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{
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template<> struct CompileArgTag<cv::gapi::wip::ov::benchmark_mode>
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{
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static const char* tag() { return "gapi.wip.ov.benchmark_mode"; }
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};
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}
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} // namespace cv
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#endif // OPENCV_GAPI_INFER_OV_HPP
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@@ -0,0 +1,194 @@
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// This file is part of OpenCV project.
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// It is subject to the license terms in the LICENSE file found in the top-level directory
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// of this distribution and at http://opencv.org/license.html.
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//
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// Copyright (C) 2023 Intel Corporation
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#ifndef OPENCV_GAPI_OT_HPP
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#define OPENCV_GAPI_OT_HPP
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#include <opencv2/gapi.hpp>
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#include <opencv2/gapi/s11n.hpp>
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#include <opencv2/gapi/gkernel.hpp>
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namespace cv {
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namespace gapi {
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/**
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* @brief This namespace contains G-API Operation Types for
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* VAS Object Tracking module functionality.
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*/
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namespace ot {
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/**
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* @enum TrackingStatus
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*
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* Tracking status twin for vas::ot::TrackingStatus
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*/
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enum TrackingStatus
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{
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NEW = 0, /**< The object is newly added. */
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TRACKED, /**< The object is being tracked. */
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LOST /**< The object gets lost now. The object can be tracked again
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by specifying detected object manually. */
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};
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struct GAPI_EXPORTS_W_SIMPLE ObjectTrackerParams
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{
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/**
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* Maximum number of trackable objects in a frame.
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* Valid range: 1 <= max_num_objects. Or it can be -1 if there is no limitation
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* of maximum number in X86. KMB/TBH has limitation up to 1024.
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* Default value is -1 which means there is no limitation in X86. KMB/TBH is -1 means 200.
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*/
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GAPI_PROP_RW int32_t max_num_objects = -1;
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/**
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* Input color format. Supports 0(BGR), 1(NV12), 2(BGRX) and 4(I420)
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*/
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GAPI_PROP_RW int32_t input_image_format = 0;
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/**
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* Specifies whether tracker to use detection class for keeping id of an object.
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* If it is true, new detection will be associated from previous tracking only when
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* those two have same class.
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* class id of an object is fixed across video frames.
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* If it is false, new detection can be associated across different-class objects.
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* In this case, the class id of an object may change across video frames depending on the tracker input.
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* It is recommended to turn this option off when it is likely that detector confuses the class of object.
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* For example, when detector confuses bicycle and motorbike. Turning this option off will increase
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* the tracking reliability as tracker will ignore the class label of detector.
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* @n
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* Default value is true.
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*/
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GAPI_PROP_RW bool tracking_per_class = true;
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bool operator==(const ObjectTrackerParams& other) const
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{
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return max_num_objects == other.max_num_objects
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&& input_image_format == other.input_image_format
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&& tracking_per_class == other.tracking_per_class;
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}
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};
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using GTrackedInfo = std::tuple<cv::GArray<cv::Rect>, cv::GArray<int32_t>, cv::GArray<uint64_t>, cv::GArray<int>>;
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G_API_OP(GTrackFromMat, <GTrackedInfo(cv::GMat, cv::GArray<cv::Rect>, cv::GArray<int32_t>, float)>, "com.intel.track_from_mat")
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{
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static std::tuple<cv::GArrayDesc, cv::GArrayDesc,
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cv::GArrayDesc, cv::GArrayDesc> outMeta(cv::GMatDesc, cv::GArrayDesc, cv::GArrayDesc, float)
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{
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return std::make_tuple(cv::empty_array_desc(), cv::empty_array_desc(),
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cv::empty_array_desc(), cv::empty_array_desc());
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}
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};
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G_API_OP(GTrackFromFrame, <GTrackedInfo(cv::GFrame, cv::GArray<cv::Rect>, cv::GArray<int32_t>, float)>, "com.intel.track_from_frame")
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{
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static std::tuple<cv::GArrayDesc, cv::GArrayDesc,
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cv::GArrayDesc, cv::GArrayDesc> outMeta(cv::GFrameDesc, cv::GArrayDesc, cv::GArrayDesc, float)
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{
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return std::make_tuple(cv::empty_array_desc(), cv::empty_array_desc(),
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cv::empty_array_desc(), cv::empty_array_desc());
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}
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};
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/**
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* @brief Tracks objects with video frames.
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* If a detected object is overlapped enough with one of tracked object, the tracked object's
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* informationis updated with the input detected object.
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* On the other hand, if a detected object is overlapped with none of tracked objects,
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* the detected object is newly added and ObjectTracker starts to track the object.
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* In zero term tracking type, ObjectTracker clears tracked objects in case that empty
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* list of detected objects is passed in.
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*
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* @param mat Input frame.
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* @param detected_rects Detected objects rectangles in the input frame.
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* @param detected_class_labels Detected objects class labels in the input frame.
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* @param delta Frame_delta_t Delta time between two consecutive tracking in seconds.
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* The valid range is [0.005 ~ 0.5].
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* @return Tracking results of target objects.
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* cv::GArray<cv::Rect> Array of rectangles for tracked objects.
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* cv::GArray<int32_t> Array of detected objects labels.
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* cv::GArray<uint64_t> Array of tracking IDs for objects.
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* Numbering sequence starts from 1.
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* The value 0 means the tracking ID of this object has
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* not been assigned.
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* cv::GArray<int> Array of tracking statuses for objects.
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*/
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GAPI_EXPORTS_W std::tuple<cv::GArray<cv::Rect>,
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cv::GArray<int>,
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cv::GArray<uint64_t>,
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cv::GArray<int>>
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track(const cv::GMat& mat,
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const cv::GArray<cv::Rect>& detected_rects,
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const cv::GArray<int>& detected_class_labels,
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float delta);
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/**
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@overload
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* @brief Tracks objects with video frames. Overload of track(...) for frame as GFrame.
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*
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* @param frame Input frame.
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* @param detected_rects Detected objects rectangles in the input frame.
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* @param detected_class_labels Detected objects class labels in the input frame.
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* @param delta Frame_delta_t Delta time between two consecutive tracking in seconds.
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* The valid range is [0.005 ~ 0.5].
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* @return Tracking results of target objects.
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* @return Tracking results of target objects.
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* cv::GArray<cv::Rect> Array of rectangles for tracked objects.
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* cv::GArray<int32_t> Array of detected objects labels.
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* cv::GArray<uint64_t> Array of tracking IDs for objects.
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* Numbering sequence starts from 1.
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* The value 0 means the tracking ID of this object has
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* not been assigned.
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* cv::GArray<int> Array of tracking statuses for objects.
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*/
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GAPI_EXPORTS_W std::tuple<cv::GArray<cv::Rect>,
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cv::GArray<int>,
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cv::GArray<uint64_t>,
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cv::GArray<int>>
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track(const cv::GFrame& frame,
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const cv::GArray<cv::Rect>& detected_rects,
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const cv::GArray<int>& detected_class_labels,
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float delta);
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} // namespace ot
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} // namespace gapi
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} // namespace cv
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// FIXME: move to a separate file?
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namespace cv
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{
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namespace detail
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{
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template<> struct CompileArgTag<cv::gapi::ot::ObjectTrackerParams>
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{
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static const char* tag()
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{
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return "cv.gapi.ot.object_tracker_params";
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}
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};
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} // namespace detail
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namespace gapi
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{
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namespace s11n
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{
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namespace detail
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{
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template<> struct S11N<cv::gapi::ot::ObjectTrackerParams> {
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static void serialize(IOStream &os, const cv::gapi::ot::ObjectTrackerParams &p) {
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os << p. max_num_objects << p.input_image_format << p.tracking_per_class;
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}
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static cv::gapi::ot::ObjectTrackerParams deserialize(IIStream &is) {
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cv::gapi::ot::ObjectTrackerParams p;
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is >> p. max_num_objects >> p.input_image_format >> p.tracking_per_class;
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return p;
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}
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};
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} // namespace detail
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} // namespace s11n
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} // namespace gapi
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} // namespace cv
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#endif // OPENCV_GAPI_OT_HPP
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