// Copyright (c) 2020 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 "paddle_api.h"
#include "paddle_inference_api.h"

#include <include/preprocess_op.h>
#include <include/utility.h>

namespace PaddleOCR {

class Classifier {
public:
  explicit Classifier(const std::string &model_dir, const bool &use_gpu,
                      const int &gpu_id, const int &gpu_mem,
                      const int &cpu_math_library_num_threads,
                      const bool &use_mkldnn, const double &cls_thresh,
                      const bool &use_tensorrt, const std::string &precision,
                      const int &cls_batch_num) {
    this->use_gpu_ = use_gpu;
    this->gpu_id_ = gpu_id;
    this->gpu_mem_ = gpu_mem;
    this->cpu_math_library_num_threads_ = cpu_math_library_num_threads;
    this->use_mkldnn_ = use_mkldnn;

    this->cls_thresh = cls_thresh;
    this->use_tensorrt_ = use_tensorrt;
    this->precision_ = precision;
    this->cls_batch_num_ = cls_batch_num;

    LoadModel(model_dir);
  }
  double cls_thresh = 0.9;

  // Load Paddle inference model
  void LoadModel(const std::string &model_dir);

  void Run(std::vector<cv::Mat> img_list, std::vector<int> &cls_labels,
           std::vector<float> &cls_scores, std::vector<double> &times);

private:
  std::shared_ptr<paddle_infer::Predictor> predictor_;

  bool use_gpu_ = false;
  int gpu_id_ = 0;
  int gpu_mem_ = 4000;
  int cpu_math_library_num_threads_ = 4;
  bool use_mkldnn_ = false;

  std::vector<float> mean_ = {0.5f, 0.5f, 0.5f};
  std::vector<float> scale_ = {1 / 0.5f, 1 / 0.5f, 1 / 0.5f};
  bool is_scale_ = true;
  bool use_tensorrt_ = false;
  std::string precision_ = "fp32";
  int cls_batch_num_ = 1;
  // pre-process
  ClsResizeImg resize_op_;
  Normalize normalize_op_;
  PermuteBatch permute_op_;

}; // class Classifier

} // namespace PaddleOCR
