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diff --git a/python/openvino/runtime/dla_benchmark/average_precision.hpp b/python/openvino/runtime/dla_benchmark/average_precision.hpp
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+// Copyright (C) 2018-2023 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+// Description: The file defines functions calculate mAP and COCO AP metrics. See average_precision.cpp for a
+// detailed explaination.
+
+#ifndef DLA_BENCHMARK_OBJECT_DETECTION_H_
+#define DLA_BENCHMARK_OBJECT_DETECTION_H_
+
+#pragma once
+
+#include <map>
+#include <set>
+#include <string>
+#include <vector>
+#include <utility>
+
+#include <inference_engine.hpp>
+
+#undef UNICODE
+
+// Indexes for raw bounding box.
+#define BBOX_X 0
+#define BBOX_Y 1
+#define BBOX_W 2
+#define BBOX_H 3
+#define BBOX_CONFIDENCE 4
+
+// Indices for input image shapes.
+#define IMG_W 0
+#define IMG_H 1
+
+// Indices for parsed bounding boxes.
+#define X_MAX 0
+#define X_MIN 1
+#define Y_MAX 2
+#define Y_MIN 3
+
+// Convenient aliases.
+template <typename T>
+using Box = std::vector<T>;
+
+template <typename T>
+using Tensor2d = std::vector<std::vector<T>>;
+
+template <typename T>
+using Tensor3d = std::vector<std::vector<std::vector<T>>>;
+
+using Blob_t = std::vector<InferenceEngine::BlobMap>;
+
+// A set of supported YOLO graphs and its variants.
+static std::set<std::string> supported_yolo_versions = {"yolo-v3-tf", "yolo-v3-tiny-tf"};
+
+// Each image will have a prediction entry containing coordinates,
+// class scores of prediction boxes, predicted class, and size.
+typedef struct prediction_entry_t {
+  std::vector<double> x_max;
+  std::vector<double> x_min;
+  std::vector<double> y_max;
+  std::vector<double> y_min;
+  // scores for highest class
+  std::vector<double> cls_score;
+  // class with highest probability
+  std::vector<int> cls;
+  unsigned size;
+
+  Box<double> box_at(unsigned idx) { return {x_max[idx], x_min[idx], y_max[idx], y_min[idx]}; }
+} PredictionEntry;
+
+// Each image will have an annotation entry containing coordinates and
+// the true label specified in `cls`.
+typedef struct annotation_entry_t {
+  std::vector<double> x_max;
+  std::vector<double> x_min;
+  std::vector<double> y_max;
+  std::vector<double> y_min;
+  std::vector<int> cls;
+  unsigned size;
+
+  Box<double> box_at(unsigned idx) { return {x_max[idx], x_min[idx], y_max[idx], y_min[idx]}; }
+} AnnotationEntry;
+
+// Stores runtime variables.
+static struct runtime_const_t {
+  // Actually means number of validation image.
+  unsigned niter;
+  unsigned batch_size;
+  std::string name;
+  std::string groundtruth_loc;
+  std::string input_loc;
+  std::string report_folder;
+  const std::string gt_extension = "txt";
+
+  Tensor2d<std::string> input_image_path;
+  Tensor2d<double> source_image_sizes;
+} runtime_vars;
+
+// Stores constants for evaluation.
+static struct meta_t {
+  // Filtering parameters,
+  const double confidence_threshold = 0.001;
+  const double iou_threshold = 0.5;
+
+  // Parameters for parsing and resizing.
+  const unsigned num_classes = 80;
+  const unsigned channel = 255;
+  const unsigned box_per_channel = 3;
+  const unsigned pbox_size = 85;
+  const std::vector<double> dst_image_size = {416, 416};
+
+  // Dimensions of grid cells and anchor boxes.
+  const std::map<std::string, std::map<unsigned, std::vector<double>>> anchor_sizes{
+      {
+          "yolo-v3-tiny-tf",
+          {{13, {81, 82, 135, 169, 344, 319}}, {26, {23, 27, 37, 58, 81, 82}}},
+      },
+      {
+          "yolo-v3-tf",
+          {{13, {116, 90, 156, 198, 373, 326}}, {26, {30, 61, 62, 45, 59, 119}}, {52, {10, 13, 16, 30, 33, 23}}},
+      }};
+  const std::map<std::string, std::vector<unsigned>> grid_sizes = {
+      {"yolo-v3-tiny-tf", {26, 13}},
+      {"yolo-v3-tf", {13, 26, 52}},
+  };
+
+  // Use of `boundary` in IoU calculation.
+  const int boundary = 1;
+
+  // IoU threshold for metrics calculation.
+  const double strict_metric = 0.75;
+  const double pascal_voc_metric = 0.5;
+  const std::vector<double> coco_metric = {0.5, 0.55, 0.6, 0.65, 0.7, 0.75, 0.8, 0.85, 0.9, 0.95};
+
+  // AP calculation
+  const unsigned ap_interval = 11;
+  const unsigned coco_interval = 101;
+} yolo_meta;
+
+// Returns `true` if the given YOLO graph, `name`, is supported. Else, `false` is returned.
+bool inline is_yolo_supported(std::string &name) {
+  return (supported_yolo_versions.find(name) != supported_yolo_versions.end());
+}
+
+// Sets runtime variables.
+void set_runtime(std::string name,
+                 unsigned niter,
+                 unsigned batch_size,
+                 const std::string &input_loc,
+                 const std::string &annotation_loc);
+
+// Entry point of this subroutine.
+std::pair<double, double> validate_yolo_wrapper(std::map<std::string, ov::TensorVector> &raw_results,
+                                                const std::vector<ov::Output<const ov::Node>> &result_layout,
+                                                std::vector<std::string> input_files);
+
+#endif  // DLA_BENCHMARK__OBJECT_DETECTION_H_