// Copyright (c) 2022 PaddlePaddle Authors. 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.

#pragma once
#include "ultra_infer/ultra_infer_model.h"
#include "ultra_infer/vision/common/processors/transform.h"
#include "ultra_infer/vision/common/result.h"

namespace ultra_infer {

namespace vision {

namespace headpose {
/*! @brief FSANet model object used when to load a FSANet model exported by
 * FSANet.
 */
class ULTRAINFER_DECL FSANet : public UltraInferModel {
public:
  /** \brief  Set path of model file and the configuration of runtime.
   *
   * \param[in] model_file Path of model file, e.g ./fsanet-var.onnx
   * \param[in] params_file Path of parameter file, e.g ppyoloe/model.pdiparams,
   * if the model format is ONNX, this parameter will be ignored \param[in]
   * custom_option RuntimeOption for inference, the default will use cpu, and
   * choose the backend defined in "valid_cpu_backends" \param[in] model_format
   * Model format of the loaded model, default is ONNX format
   */
  FSANet(const std::string &model_file, const std::string &params_file = "",
         const RuntimeOption &custom_option = RuntimeOption(),
         const ModelFormat &model_format = ModelFormat::ONNX);

  std::string ModelName() const { return "FSANet"; }
  /** \brief Predict the face detection result for an input image
   *
   * \param[in] im The input image data, comes from cv::imread(), is a 3-D array
   * with layout HWC, BGR format \param[in] result The output face detection
   * result will be written to this structure \return true if the prediction
   * succeeded, otherwise false
   */
  virtual bool Predict(cv::Mat *im, HeadPoseResult *result);

  /// tuple of (width, height), default (64, 64)
  std::vector<int> size;

private:
  bool Initialize();

  bool Preprocess(Mat *mat, FDTensor *outputs,
                  std::map<std::string, std::array<int, 2>> *im_info);

  bool Postprocess(FDTensor &infer_result, HeadPoseResult *result,
                   const std::map<std::string, std::array<int, 2>> &im_info);
};

} // namespace headpose
} // namespace vision
} // namespace ultra_infer