/*
 * Copyright(C) 2020. Huawei Technologies Co.,Ltd. All rights reserved.
 *
 * 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.
 */

#ifndef YOLOV3_POST_PROCESS_H
#define YOLOV3_POST_PROCESS_H
#include "MxBase/PostProcessBases/ObjectPostProcessBase.h"

namespace
{
const float DEFAULT_OBJECTNESS_THRESH = 0.3;
const float DEFAULT_IOU_THRESH = 0.45;
const int DEFAULT_ANCHOR_DIM = 3;
const int DEFAULT_BIASES_NUM = 18;
const int DEFAULT_YOLO_TYPE = 3;
const int DEFAULT_YOLO_VERSION = 3;
const int YOLOV3_VERSION = 3;
const int YOLOV4_VERSION = 4;
const int YOLOV5_VERSION = 5;

struct OutputLayer
{
    size_t width;
    size_t height;
    float anchors[6];
};

struct NetInfo
{
    int anchorDim;
    int classNum;
    int bboxDim;
    int netWidth;
    int netHeight;
};
}  // namespace

namespace MxBase
{
class Yolov3PostProcess : public ObjectPostProcessBase
{
   public:
    Yolov3PostProcess() = default;

    ~Yolov3PostProcess() = default;

    Yolov3PostProcess(const Yolov3PostProcess &other) = default;

    Yolov3PostProcess &operator=(const Yolov3PostProcess &other);

    APP_ERROR Init(const std::map<std::string, std::string> &postConfig) override;

    APP_ERROR DeInit() override;

    APP_ERROR Process(const std::vector<MxBase::TensorBase> &tensors,
                      std::vector<std::vector<MxBase::ObjectInfo>> &objectInfos,
                      const std::vector<MxBase::ResizedImageInfo> &resizedImageInfos = {},
                      const std::map<std::string, std::shared_ptr<void>> &paramMap = {}) override;

   protected:
    bool IsValidTensors(const std::vector<MxBase::TensorBase> &tensors) const;

    void ObjectDetectionOutput(const std::vector<MxBase::TensorBase> &tensors,
                               std::vector<std::vector<MxBase::ObjectInfo>> &objectInfos,
                               const std::vector<MxBase::ResizedImageInfo> &resizedImageInfos = {});

    void CompareProb(int &classID, float &maxProb, float classProb, int classNum);

    void SelectClassNCHW(std::shared_ptr<void> netout, NetInfo info, std::vector<MxBase::ObjectInfo> &detBoxes,
                         int stride, OutputLayer layer);

    void SelectClassNHWC(std::shared_ptr<void> netout, NetInfo info, std::vector<MxBase::ObjectInfo> &detBoxes,
                         int stride, OutputLayer layer);

    void SelectClassNCHWC(std::shared_ptr<void> netout, NetInfo info, std::vector<MxBase::ObjectInfo> &detBoxes,
                          int stride, OutputLayer layer);

    void GenerateBbox(std::vector<std::shared_ptr<void>> featLayerData, std::vector<MxBase::ObjectInfo> &detBoxes,
                      const std::vector<std::vector<size_t>> &featLayerShapes, const int netWidth, const int netHeight);

    APP_ERROR GetBiases(std::string &strBiases);

   protected:
    float objectnessThresh_ = DEFAULT_OBJECTNESS_THRESH;  // Threshold of objectness value
    float iouThresh_ = DEFAULT_IOU_THRESH;                // Non-Maximum Suppression threshold
    int anchorDim_ = DEFAULT_ANCHOR_DIM;
    int biasesNum_ = DEFAULT_BIASES_NUM;  // Yolov3 anchors, generate from train data, coco dataset
    int yoloType_ = DEFAULT_YOLO_TYPE;
    int modelType_ = 0;
    int yoloVersion_ = DEFAULT_YOLO_VERSION;
    int inputType_ = 0;
    std::vector<float> biases_ = {};
};
extern "C"
{
    std::shared_ptr<MxBase::Yolov3PostProcess> GetObjectInstance();
}
}  // namespace MxBase
#endif