// 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 "fastdeploy/fastdeploy_model.h"
#include "fastdeploy/vision/common/processors/transform.h"
#include "fastdeploy/vision/common/result.h"

namespace fastdeploy {

namespace vision {

namespace facedet {

class FASTDEPLOY_DECL YOLOv5Face : public FastDeployModel {
 public:
  YOLOv5Face(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 "yolov5-face"; }

  virtual bool Predict(cv::Mat* im, FaceDetectionResult* result,
                       float conf_threshold = 0.25,
                       float nms_iou_threshold = 0.5);

  // tuple of (width, height)
  std::vector<int> size;
  // padding value, size should be same with Channels
  std::vector<float> padding_value;
  // only pad to the minimum rectange which height and width is times of stride
  bool is_mini_pad;
  // while is_mini_pad = false and is_no_pad = true, will resize the image to
  // the set size
  bool is_no_pad;
  // if is_scale_up is false, the input image only can be zoom out, the maximum
  // resize scale cannot exceed 1.0
  bool is_scale_up;
  // padding stride, for is_mini_pad
  int stride;
  // setup the number of landmarks for per face (if have), default 5 in
  // official yolov5face note that, the outupt tensor's shape must be:
  // (1,n,4+1+2*landmarks_per_face+1=box+obj+landmarks+cls)
  int landmarks_per_face;

 private:
  bool Initialize();

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

  bool Postprocess(FDTensor& infer_result, FaceDetectionResult* result,
                   const std::map<std::string, std::array<float, 2>>& im_info,
                   float conf_threshold, float nms_iou_threshold);

  bool IsDynamicInput() const { return is_dynamic_input_; }

  bool is_dynamic_input_;
};

}  // namespace facedet
}  // namespace vision
}  // namespace fastdeploy