/*
// Copyright (C) 2020-2024 Intel Corporation
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
//      http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
*/

#pragma once
#include <stddef.h>
#include <stdint.h>

#include <map>
#include <memory>
#include <string>
#include <vector>

#include <openvino/op/region_yolo.hpp>
#include <openvino/openvino.hpp>

#include "models/detection_model.h"

struct DetectedObject;
struct InferenceResult;
struct ResultBase;

class ModelYolo : public DetectionModel {
protected:
    class Region {
    public:
        int num = 0;
        size_t classes = 0;
        int coords = 0;
        std::vector<float> anchors;
        size_t outputWidth = 0;
        size_t outputHeight = 0;

        Region(const std::shared_ptr<ov::op::v0::RegionYolo>& regionYolo);
        Region(size_t classes,
               int coords,
               const std::vector<float>& anchors,
               const std::vector<int64_t>& masks,
               size_t outputWidth,
               size_t outputHeight);
    };

public:
    enum YoloVersion { YOLO_V1V2, YOLO_V3, YOLO_V4, YOLO_V4_TINY, YOLOF };

    /// Constructor.
    /// @param modelFileName name of model to load
    /// @param confidenceThreshold - threshold to eliminate low-confidence detections.
    /// Any detected object with confidence lower than this threshold will be ignored.
    /// @param useAutoResize - if true, image will be resized by openvino.
    /// Otherwise, image will be preprocessed and resized using OpenCV routines.
    /// @param useAdvancedPostprocessing - if true, an advanced algorithm for filtering/postprocessing will be used
    /// (with better processing of multiple crossing objects). Otherwise, classic algorithm will be used.
    /// @param boxIOUThreshold - threshold to treat separate output regions as one object for filtering
    /// during postprocessing (only one of them should stay). The default value is 0.5
    /// @param labels - array of labels for every class. If this array is empty or contains less elements
    /// than actual classes number, default "Label #N" will be shown for missing items.
    /// @param anchors - vector of anchors coordinates. Required for YOLOv4, for other versions it may be omitted.
    /// @param masks - vector of masks values. Required for YOLOv4, for other versions it may be omitted.
    /// @param layout - model input layout
    ModelYolo(const std::string& modelFileName,
              float confidenceThreshold,
              bool useAutoResize,
              bool useAdvancedPostprocessing = true,
              float boxIOUThreshold = 0.5,
              const std::vector<std::string>& labels = std::vector<std::string>(),
              const std::vector<float>& anchors = std::vector<float>(),
              const std::vector<int64_t>& masks = std::vector<int64_t>(),
              const std::string& layout = "");

    std::unique_ptr<ResultBase> postprocess(InferenceResult& infResult) override;

protected:
    void prepareInputsOutputs(std::shared_ptr<ov::Model>& model) override;

    void parseYOLOOutput(const std::string& output_name,
                         const ov::Tensor& tensor,
                         const unsigned long resized_im_h,
                         const unsigned long resized_im_w,
                         const unsigned long original_im_h,
                         const unsigned long original_im_w,
                         std::vector<DetectedObject>& objects);

    static int calculateEntryIndex(int entriesNum, int lcoords, size_t lclasses, int location, int entry);
    static double intersectionOverUnion(const DetectedObject& o1, const DetectedObject& o2);

    std::map<std::string, Region> regions;
    double boxIOUThreshold;
    bool useAdvancedPostprocessing;
    bool isObjConf = 1;
    YoloVersion yoloVersion;
    const std::vector<float> presetAnchors;
    const std::vector<int64_t> presetMasks;
    ov::Layout yoloRegionLayout = "NCHW";
};