This structure provides functions that fill inference parameters for "OpenVINO Toolkit" model.
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#include <opencv2/gapi/infer/ov.hpp>
template<typename Net>
struct cv::gapi::ov::Params< Net >
This structure provides functions that fill inference parameters for "OpenVINO Toolkit" model.
◆ Params() [1/2]
template<typename Net >
cv::gapi::ov::Params< Net >::Params |
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const std::string & |
model_path, |
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const std::string & |
bin_path, |
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const std::string & |
device |
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) |
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inline |
Class constructor.
Constructs Params based on model information and specifies default values for other inference description parameters. Model is loaded and compiled using "OpenVINO Toolkit".
- Parameters
-
model_path | Path to a model. |
bin_path | Path to a data file. For IR format (*.bin): If path is empty, will try to read a bin file with the same name as xml. If the bin file with the same name is not found, will load IR without weights. For PDPD (*.pdmodel) and ONNX (*.onnx) formats bin_path isn't used. |
device | target device to use. |
◆ Params() [2/2]
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts. Use this constructor to work with pre-compiled network. Model is imported from a pre-compiled blob.
- Parameters
-
blob_path | path to the compiled model (*.blob). |
device | target device to use. |
◆ backend()
◆ cfgInputLayers()
Specifies sequence of network input layers names for inference.
The function is used to associate cv::gapi::infer<> inputs with the model inputs. Number of names has to match the number of network inputs as defined in G_API_NET(). In case a network has only single input layer, there is no need to specify name manually.
- Parameters
-
layer_names | std::array<std::string, N> where N is the number of inputs as defined in the G_API_NET. Contains names of input layers. |
- Returns
- reference to this parameter structure.
◆ cfgInputModelLayout() [1/2]
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
- Parameters
-
layout_map | Map of pairs: name of corresponding input layer and its model layout ("NCHW", "NHWC", etc) |
- Returns
- reference to this parameter structure.
◆ cfgInputModelLayout() [2/2]
Specifies model layout for an input layer.
The function is used to set model layout for an input layer.
- Parameters
-
layout | Model layout ("NCHW", "NHWC", etc) will be applied to all input layers. |
- Returns
- reference to this parameter structure.
◆ cfgInputTensorLayout() [1/2]
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
- Parameters
-
layout_map | Map of pairs: name of corresponding input layer and its tensor layout represented in std::string ("NCHW", "NHWC", etc) |
- Returns
- reference to this parameter structure.
◆ cfgInputTensorLayout() [2/2]
Specifies tensor layout for an input layer.
The function is used to set tensor layout for an input layer.
- Parameters
-
layout | Tensor layout ("NCHW", "NWHC", etc) will be applied to all input layers. |
- Returns
- reference to this parameter structure.
◆ cfgMean() [1/2]
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
- Parameters
-
mean_map | Map of pairs: name of corresponding input layer and its mean values. |
- Returns
- reference to this parameter structure.
◆ cfgMean() [2/2]
Specifies mean values for preprocessing.
The function is used to set mean values for input layer preprocessing.
- Parameters
-
mean_values | Float vector contains mean values |
- Returns
- reference to this parameter structure.
◆ cfgNumRequests()
Specifies number of asynchronous inference requests.
- Parameters
-
nireq | Number of inference asynchronous requests. |
- Returns
- reference to this parameter structure.
◆ cfgOutputLayers()
Specifies sequence of network output layers names for inference.
The function is used to associate cv::gapi::infer<> outputs with the model outputs. Number of names has to match the number of network outputs as defined in G_API_NET(). In case a network has only single output layer, there is no need to specify name manually.
- Parameters
-
layer_names | std::array<std::string, N> where N is the number of outputs as defined in the G_API_NET. Contains names of output layers. |
- Returns
- reference to this parameter structure.
◆ cfgOutputModelLayout() [1/2]
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
- Parameters
-
layout_map | Map of pairs: name of corresponding output layer and its model layout ("NCHW", "NHWC", etc) |
- Returns
- reference to this parameter structure.
◆ cfgOutputModelLayout() [2/2]
Specifies model layout for an output layer.
The function is used to set model layout for an output layer.
- Parameters
-
layout | Model layout ("NCHW", "NHWC", etc) will be applied to all output layers. |
- Returns
- reference to this parameter structure.
◆ cfgOutputTensorLayout() [1/2]
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
- Parameters
-
layout_map | Map of pairs: name of corresponding output layer and its tensor layout represented in std::string ("NCHW", "NHWC", etc) |
- Returns
- reference to this parameter structure.
◆ cfgOutputTensorLayout() [2/2]
Specifies tensor layout for an output layer.
The function is used to set tensor layout for an output layer.
- Parameters
-
layout | Tensor layout ("NCHW", "NWHC", etc) will be applied to all output layers. |
- Returns
- reference to this parameter structure.
◆ cfgOutputTensorPrecision() [1/2]
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
- Parameters
-
precision_map | Map of pairs: name of corresponding output layer and its precision in OpenCV format (CV_8U, CV_32F, ...) |
- Returns
- reference to this parameter structure.
◆ cfgOutputTensorPrecision() [2/2]
Specifies tensor precision for an output layer.
The function is used to set tensor precision for an output layer..
- Parameters
-
precision | Precision in OpenCV format (CV_8U, CV_32F, ...) will be applied to all output layers. |
- Returns
- reference to this parameter structure.
◆ cfgPluginConfig()
Specifies OpenVINO plugin configuration.
The function is used to set configuration for OpenVINO plugin. Some parameters can be different for each plugin. Please follow https://docs.openvinotoolkit.org/latest/index.html to check information about specific plugin.
- Parameters
-
config | Map of pairs: (config parameter name, config parameter value). |
- Returns
- reference to this parameter structure.
◆ cfgReshape() [1/2]
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
- Parameters
-
new_shape_map | Map of pairs: name of corresponding output layer and its new shape. |
- Returns
- reference to this parameter structure.
◆ cfgReshape() [2/2]
Specifies the new shape for input layers.
The function is used to set new shape for input layers.
- Parameters
-
new_shape | New shape will be applied to all input layers. |
- Returns
- reference to this parameter structure.
◆ cfgResize() [1/2]
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
- Parameters
-
interpolation | Map of pairs: name of corresponding input layer and its resize algorithm. |
- Returns
- reference to this parameter structure.
◆ cfgResize() [2/2]
Specifies resize interpolation algorithm.
The function is used to configure resize preprocessing for input layer.
- Parameters
-
- Returns
- reference to this parameter structure.
◆ cfgScale() [1/2]
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
- Parameters
-
scale_map | Map of pairs: name of corresponding input layer and its mean values. |
- Returns
- reference to this parameter structure.
◆ cfgScale() [2/2]
Specifies scale values for preprocessing.
The function is used to set scale values for input layer preprocessing.
- Parameters
-
scale_values | Float vector contains scale values |
- Returns
- reference to this parameter structure.
◆ params()
◆ tag()
◆ m_desc
The documentation for this struct was generated from the following file: