class ov::op::v1::NonMaxSuppression¶

Overview¶

Elementwise addition operation. More…

#include <non_max_suppression.hpp>

class NonMaxSuppression: public ov::op::Op
{
public:
    // enums

    enum BoxEncodingType;

    // construction

    NonMaxSuppression();
    NonMaxSuppression(, , , , , , );
    NonMaxSuppression(, , , );

    // methods

    "NonMaxSuppression""opset1"op::Op OPENVINO_OP(, , );
    virtual boolAttributeVisitor& visit_attributes();
    virtual void validate_and_infer_types();
    virtual std::shared_ptr<Node>const OutputVector& clone_with_new_inputs() const;
    BoxEncodingType get_box_encoding() const;
    voidconst BoxEncodingType set_box_encoding();
    bool get_sort_result_descending() const;
    voidconst bool set_sort_result_descending();
};

Inherited Members¶

public:
    // typedefs

    typedef DiscreteTypeInfo type_info_t;
    typedef std::map<std::string, Any> RTMap;

    // methods

    virtual void validate_and_infer_types();
    void constructor_validate_and_infer_types();
    virtual boolAttributeVisitor& visit_attributes();
    virtual const ov::op::AutoBroadcastSpec& get_autob() const;
    virtual bool has_evaluate() const;
    virtual boolconst ov::HostTensorVector&const ov::HostTensorVector& evaluate(, ) const;

    virtual boolconst ov::HostTensorVector&const ov::HostTensorVector&const EvaluationContext& evaluate(
        ,
        ,

        ) const;

    virtual boolov::TensorVector&const ov::TensorVector& evaluate(, ) const;

    virtual boolov::TensorVector&const ov::TensorVector&const ov::EvaluationContext& evaluate(
        ,
        ,

        ) const;

    virtual boolov::TensorVector& evaluate_lower() const;
    virtual boolov::TensorVector& evaluate_upper() const;
    virtual boolTensorLabelVector& evaluate_label() const;
    virtual boolOutputVector&const OutputVector& constant_fold(, );
    virtual OutputVector decompose_op() const;
    virtual const type_info_t& get_type_info() const = 0;
    const char \* get_type_name() const;
    voidconst NodeVector& set_arguments();
    voidconst OutputVector& set_arguments();
    voidsize_tconst Output<Node>& set_argument(, );
    voidsize_tconst element::Type&const PartialShape& set_output_type(, , );
    voidsize_t set_output_size();
    void invalidate_values();
    virtual void revalidate_and_infer_types();
    virtual std::string description() const;
    const std::string& get_name() const;
    voidconst std::string& set_friendly_name();
    const std::string& get_friendly_name() const;
    virtual bool is_dynamic() const;
    size_t get_instance_id() const;
    virtual std::ostream&std::ostream&uint32_t write_description(, ) const;
    const std::vector<std::shared_ptr<Node>>& get_control_dependencies() const;
    const std::vector<Node \*>& get_control_dependents() const;
    voidstd::shared_ptr<Node> add_control_dependency();
    voidstd::shared_ptr<Node> remove_control_dependency();
    void clear_control_dependencies();
    void clear_control_dependents();
    voidconst std::shared_ptr<const Node>& add_node_control_dependencies();
    voidconst std::shared_ptr<const Node>& add_node_control_dependents();
    voidstd::shared_ptr<Node> transfer_control_dependents();
    size_t get_output_size() const;
    const element::Type&size_t get_output_element_type() const;
    const element::Type& get_element_type() const;
    const Shape&size_t get_output_shape() const;
    const PartialShape&size_t get_output_partial_shape() const;
    Output<const Node> get_default_output() const;
    Output<Node> get_default_output();
    virtual size_t get_default_output_index() const;
    size_t no_default_index() const;
    const Shape& get_shape() const;
    descriptor::Tensor&size_t get_output_tensor() const;
    descriptor::Tensor&size_t get_input_tensor() const;
    std::set<Input<Node>>size_t get_output_target_inputs() const;
    size_t get_input_size() const;
    const element::Type&size_t get_input_element_type() const;
    const Shape&size_t get_input_shape() const;
    const PartialShape&size_t get_input_partial_shape() const;
    Node \*size_t get_input_node_ptr() const;
    std::shared_ptr<Node>size_t get_input_node_shared_ptr() const;
    Output<Node>size_t get_input_source_output() const;
    virtual std::shared_ptr<Node>const OutputVector& clone_with_new_inputs() const = 0;
    std::shared_ptr<Node>const OutputVector& copy_with_new_inputs() const;

    std::shared_ptr<Node>const OutputVector&const std::vector<std::shared_ptr<Node>>& copy_with_new_inputs(
        ,

        ) const;

    boolstd::shared_ptr<const Node> has_same_type() const;
    RTMap& get_rt_info();
    const RTMap& get_rt_info() const;
    NodeVectorbool get_users() const;
    boolconst Node& operator < () const;
    std::vector<Input<Node>> inputs();
    std::vector<Input<const Node>> inputs() const;
    std::vector<Output<Node>> input_values() const;
    std::vector<Output<Node>> outputs();
    std::vector<Output<const Node>> outputs() const;
    Input<Node>size_t input();
    Input<const Node>size_t input() const;
    Output<Node>size_t input_value() const;
    Output<Node>size_t output();
    Output<const Node>size_t output() const;

    virtual boolov::pass::pattern::Matcher \*const Output<Node>&const Output<Node>& match_value(
        ,
        ,

        );

    virtual boolov::pass::pattern::Matcher \*const Output<Node>& match_node(, );
    static _OPENVINO_HIDDEN_METHODconst ::ov::Node::type_info_t& get_type_info_static();
    virtual const ::ov::Node::type_info_t& get_type_info() const;

Detailed Documentation¶

Elementwise addition operation.

Construction¶

NonMaxSuppression(, , , , , , )

Constructs a NonMaxSuppression operation.

Parameters:

boxes	Node producing the box coordinates
scores	Node producing the box scores
max_output_boxes_per_class	Node producing maximum number of boxes to be selected per class
iou_threshold	Node producing intersection over union threshold
score_threshold	Node producing minimum score threshold
box_encoding	Specifies the format of boxes data encoding

NonMaxSuppression(, , , )

Constructs a NonMaxSuppression operation with default values for the last 3 inputs.

Parameters:

boxes	Node producing the box coordinates
scores	Node producing the box coordinates
box_encoding	Specifies the format of boxes data encoding
sort_result_descending	Specifies whether it is necessary to sort selected boxes across batches
output_type	Specifies the output tensor type

Methods¶

virtual void validate_and_infer_types()

Verifies that attributes and inputs are consistent and computes output shapes and element types. Must be implemented by concrete child classes so that it can be run any number of times.

Throws if the node is invalid.