class ov::op::v0::DetectionOutput¶
Overview¶
Layer which performs non-max suppression to generate detection output using location and confidence predictions. More…
#include <detection_output.hpp>
class DetectionOutput: public ov::op::util::DetectionOutputBase
{
public:
// structs
struct Attributes;
// fields
BWDCMP_RTTI_DECLARATION;
// construction
DetectionOutput();
DetectionOutput(
const Output<Node>& box_logits,
const Output<Node>& class_preds,
const Output<Node>& proposals,
const Output<Node>& aux_class_preds,
const Output<Node>& aux_box_preds,
const Attributes& attrs
);
DetectionOutput(
const Output<Node>& box_logits,
const Output<Node>& class_preds,
const Output<Node>& proposals,
const Attributes& attrs
);
// methods
OPENVINO_OP("DetectionOutput", "opset1", op::util::DetectionOutputBase);
virtual void validate_and_infer_types();
virtual std::shared_ptr<Node> clone_with_new_inputs(const OutputVector& new_args) const;
const Attributes& get_attrs() const;
virtual bool visit_attributes(AttributeVisitor& visitor);
};Inherited Members¶
public:
// typedefs
typedef DiscreteTypeInfo type_info_t;
typedef std::map<std::string, Any> RTMap;
// structs
struct AttributesBase;
// methods
virtual void validate_and_infer_types();
void constructor_validate_and_infer_types();
virtual bool visit_attributes(AttributeVisitor&);
virtual const ov::op::AutoBroadcastSpec& get_autob() const;
virtual bool has_evaluate() const;
virtual bool evaluate(
const ov::HostTensorVector& output_values,
const ov::HostTensorVector& input_values
) const;
virtual bool evaluate(
const ov::HostTensorVector& output_values,
const ov::HostTensorVector& input_values,
const EvaluationContext& evaluationContext
) const;
virtual bool evaluate_lower(const ov::HostTensorVector& output_values) const;
virtual bool evaluate_upper(const ov::HostTensorVector& output_values) const;
virtual bool evaluate(
ov::TensorVector& output_values,
const ov::TensorVector& input_values
) const;
virtual bool evaluate(
ov::TensorVector& output_values,
const ov::TensorVector& input_values,
const ov::EvaluationContext& evaluationContext
) const;
virtual bool evaluate_lower(ov::TensorVector& output_values) const;
virtual bool evaluate_upper(ov::TensorVector& output_values) const;
virtual bool evaluate_label(TensorLabelVector& output_labels) const;
virtual bool constant_fold(
OutputVector& output_values,
const OutputVector& inputs_values
);
virtual OutputVector decompose_op() const;
virtual const type_info_t& get_type_info() const = 0;
const char \* get_type_name() const;
void set_arguments(const NodeVector& arguments);
void set_arguments(const OutputVector& arguments);
void set_argument(size_t position, const Output<Node>& argument);
void set_output_type(
size_t i,
const element::Type& element_type,
const PartialShape& pshape
);
void set_output_size(size_t output_size);
void invalidate_values();
virtual void revalidate_and_infer_types();
virtual std::string description() const;
const std::string& get_name() const;
void set_friendly_name(const std::string& name);
const std::string& get_friendly_name() const;
virtual bool is_dynamic() const;
size_t get_instance_id() const;
virtual std::ostream& write_description(std::ostream& os, uint32_t depth = 0) const;
const std::vector<std::shared_ptr<Node>>& get_control_dependencies() const;
const std::vector<Node \*>& get_control_dependents() const;
void add_control_dependency(std::shared_ptr<Node> node);
void remove_control_dependency(std::shared_ptr<Node> node);
void clear_control_dependencies();
void clear_control_dependents();
void add_node_control_dependencies(std::shared_ptr<Node> source_node);
void add_node_control_dependents(std::shared_ptr<Node> source_node);
void transfer_control_dependents(std::shared_ptr<Node> replacement);
size_t get_output_size() const;
const element::Type& get_output_element_type(size_t i) const;
const element::Type& get_element_type() const;
const Shape& get_output_shape(size_t i) const;
const PartialShape& get_output_partial_shape(size_t i) 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& get_output_tensor(size_t i) const;
descriptor::Tensor& get_input_tensor(size_t i) const;
const std::string& get_output_tensor_name(size_t i) const;
std::set<Input<Node>> get_output_target_inputs(size_t i) const;
size_t get_input_size() const;
const element::Type& get_input_element_type(size_t i) const;
const Shape& get_input_shape(size_t i) const;
const PartialShape& get_input_partial_shape(size_t i) const;
const std::string& get_input_tensor_name(size_t i) const;
Node \* get_input_node_ptr(size_t index) const;
std::shared_ptr<Node> get_input_node_shared_ptr(size_t index) const;
Output<Node> get_input_source_output(size_t i) const;
virtual std::shared_ptr<Node> clone_with_new_inputs(const OutputVector& inputs) const = 0;
std::shared_ptr<Node> copy_with_new_inputs(const OutputVector& new_args) const;
std::shared_ptr<Node> copy_with_new_inputs(
const OutputVector& inputs,
const std::vector<std::shared_ptr<Node>>& control_dependencies
) const;
bool has_same_type(std::shared_ptr<const Node> node) const;
RTMap& get_rt_info();
const RTMap& get_rt_info() const;
NodeVector get_users(bool check_is_used = false) const;
virtual size_t get_version() const;
virtual std::shared_ptr<Node> get_default_value() const;
bool operator < (const Node& other) 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> input(size_t input_index);
Input<const Node> input(size_t input_index) const;
Output<Node> input_value(size_t input_index) const;
Output<Node> output(size_t output_index);
Output<const Node> output(size_t output_index) const;
OPENVINO_SUPPRESS_DEPRECATED_START void set_op_annotations(std::shared_ptr<ngraph::op::util::OpAnnotations> op_annotations);
std::shared_ptr<ngraph::op::util::OpAnnotations> get_op_annotations() const;
virtual OPENVINO_SUPPRESS_DEPRECATED_END bool match_value(
ov::pass::pattern::Matcher \* matcher,
const Output<Node>& pattern_value,
const Output<Node>& graph_value
);
virtual bool match_node(
ov::pass::pattern::Matcher \* matcher,
const Output<Node>& graph_value
);
static _OPENVINO_HIDDEN_METHODconst ::ov::Node::type_info_t& get_type_info_static();
virtual const ::ov::Node::type_info_t& get_type_info() const;
OPENVINO_OP("DetectionOutputBase", "util");
void validate_base(const AttributesBase& attrs);
bool visit_attributes_base(AttributeVisitor& visitor, AttributesBase& attrs);
Dimension compute_num_classes(const AttributesBase& attrs);Detailed Documentation¶
Layer which performs non-max suppression to generate detection output using location and confidence predictions.
Construction¶
Constructs a DetectionOutput operation.
Parameters:
box_logits |
Box logits |
class_preds |
Class predictions |
proposals |
Proposals |
aux_class_preds |
Auxilary class predictions |
aux_box_preds |
Auxilary box predictions |
attrs |
Detection Output attributes |
Constructs a DetectionOutput operation.
Parameters:
box_logits |
Box logits |
class_preds |
Class predictions |
proposals |
Proposals |
attrs |
Detection Output attributes |
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.