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// Copyright (C) 2018-2025 Intel Corporation
// SPDX-License-Identifier: Apache-2.0
//
#pragma once
#include "openvino/op/op.hpp"
namespace ov {
namespace op {
namespace v0 {
/// \brief Layer which generates prior boxes of specified sizes
/// normalized to input image size
/// \ingroup ov_ops_cpp_api
class OPENVINO_API PriorBox : public Op {
public:
OPENVINO_OP("PriorBox", "opset1");
struct Attributes {
// min_size Desired min_size of prior boxes
// max_size Desired max_size of prior boxes
// aspect_ratio Aspect ratios of prior boxes
// clip Clip output to [0,1]
// flip Flip aspect ratios
// step Distance between prior box centers
// offset Box offset relative to top center of image
// variance Values to adjust prior boxes with
// scale_all_sizes Scale all sizes
std::vector<float> min_size;
std::vector<float> max_size;
std::vector<float> aspect_ratio;
std::vector<float> density;
std::vector<float> fixed_ratio;
std::vector<float> fixed_size;
bool clip = false;
bool flip = false;
float step = 0.0f;
float offset = 0.0f;
std::vector<float> variance;
bool scale_all_sizes = true;
};
PriorBox() = default;
/// \brief Constructs a PriorBox operation
///
/// \param layer_shape Shape of layer for which prior boxes are computed
/// \param image_shape Shape of image to which prior boxes are scaled
/// \param attrs PriorBox attributes
PriorBox(const Output<Node>& layer_shape, const Output<Node>& image_shape, const Attributes& attrs);
void validate_and_infer_types() override;
std::shared_ptr<Node> clone_with_new_inputs(const OutputVector& new_args) const override;
static int64_t number_of_priors(const Attributes& attrs);
static std::vector<float> normalized_aspect_ratio(const std::vector<float>& aspect_ratio, bool flip);
const Attributes& get_attrs() const {
return m_attrs;
}
void set_attrs(Attributes&& attrs);
void set_attrs(const Attributes& attrs);
bool visit_attributes(AttributeVisitor& visitor) override;
bool evaluate(TensorVector& outputs, const TensorVector& inputs) const override;
bool has_evaluate() const override;
private:
Attributes m_attrs;
};
} // namespace v0
namespace v8 {
/// \brief Layer which generates prior boxes of specified sizes
/// normalized to input image size
/// \ingroup ov_ops_cpp_api
class OPENVINO_API PriorBox : public Op {
public:
OPENVINO_OP("PriorBox", "opset8");
struct Attributes {
// min_size Desired min_size of prior boxes
// max_size Desired max_size of prior boxes
// aspect_ratio Aspect ratios of prior boxes
// clip Clip output to [0,1]
// flip Flip aspect ratios
// step Distance between prior box centers
// offset Box offset relative to top center of image
// variance Values to adjust prior boxes with
// scale_all_sizes Scale all sizes
// min_max_aspect_ratios_order Order of output prior box
std::vector<float> min_size;
std::vector<float> max_size;
std::vector<float> aspect_ratio;
std::vector<float> density;
std::vector<float> fixed_ratio;
std::vector<float> fixed_size;
bool clip = false;
bool flip = false;
float step = 0.0f;
float offset = 0.0f;
std::vector<float> variance;
bool scale_all_sizes = true;
bool min_max_aspect_ratios_order = true;
};
PriorBox() = default;
/// \brief Constructs a PriorBox operation
///
/// \param layer_shape Shape of layer for which prior boxes are computed
/// \param image_shape Shape of image to which prior boxes are scaled
/// \param attrs PriorBox attributes
PriorBox(const Output<Node>& layer_shape, const Output<Node>& image_shape, const Attributes& attrs);
void validate_and_infer_types() override;
std::shared_ptr<Node> clone_with_new_inputs(const OutputVector& new_args) const override;
static int64_t number_of_priors(const Attributes& attrs);
static std::vector<float> normalized_aspect_ratio(const std::vector<float>& aspect_ratio, bool flip);
const Attributes& get_attrs() const {
return m_attrs;
}
void set_attrs(Attributes&& attrs);
void set_attrs(const Attributes& attrs);
bool visit_attributes(AttributeVisitor& visitor) override;
bool evaluate(TensorVector& outputs, const TensorVector& inputs) const override;
bool has_evaluate() const override;
private:
Attributes m_attrs;
};
} // namespace v8
} // namespace op
} // namespace ov