// 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/vision/common/result.h"
#include "opencv2/imgproc/imgproc.hpp"
#include "fastdeploy/vision/tracking/pptracking/model.h"

namespace fastdeploy {
/** \brief All C++ FastDeploy Vision Models APIs are defined inside this namespace
*
*/
namespace vision {

class FASTDEPLOY_DECL Visualize {
 public:
  static int num_classes_;
  static std::vector<int> color_map_;
  static const std::vector<int>& GetColorMap(int num_classes = 1000);
  static cv::Mat VisDetection(const cv::Mat& im, const DetectionResult& result,
                              float score_threshold = 0.0, int line_size = 1,
                              float font_size = 0.5f);
  static cv::Mat VisFaceDetection(const cv::Mat& im,
                                  const FaceDetectionResult& result,
                                  int line_size = 1, float font_size = 0.5f);
  static cv::Mat VisSegmentation(const cv::Mat& im,
                                 const SegmentationResult& result);
  static cv::Mat VisMattingAlpha(const cv::Mat& im, const MattingResult& result,
                                 bool remove_small_connected_area = false);
  static cv::Mat RemoveSmallConnectedArea(const cv::Mat& alpha_pred,
                                          float threshold);
  static cv::Mat SwapBackgroundMatting(
      const cv::Mat& im, const cv::Mat& background, const MattingResult& result,
      bool remove_small_connected_area = false);
  static cv::Mat SwapBackgroundSegmentation(const cv::Mat& im,
                                            const cv::Mat& background,
                                            int background_label,
                                            const SegmentationResult& result);
  static cv::Mat VisOcr(const cv::Mat& srcimg, const OCRResult& ocr_result);
};

std::vector<int> GenerateColorMap(int num_classes = 1000);
cv::Mat RemoveSmallConnectedArea(const cv::Mat& alpha_pred, float threshold);
/** \brief Show the visualized results for detection models
 *
 * \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 result produced by model
 * \param[in] score_threshold threshold for result scores, the bounding box will not be shown if the score is less than score_threshold
 * \param[in] line_size line size for bounding boxes
 * \param[in] font_size font size for text
 * \return cv::Mat type stores the visualized results
 */
FASTDEPLOY_DECL cv::Mat VisDetection(const cv::Mat& im,
                                     const DetectionResult& result,
                                     float score_threshold = 0.0,
                                     int line_size = 1, float font_size = 0.5f);
/** \brief Show the visualized results with custom labels for detection models
 *
 * \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 result produced by model
 * \param[in] labels the visualized result will show the bounding box contain class label
 * \param[in] score_threshold threshold for result scores, the bounding box will not be shown if the score is less than score_threshold
 * \param[in] line_size line size for bounding boxes
 * \param[in] font_size font size for text
 * \return cv::Mat type stores the visualized results
 */
FASTDEPLOY_DECL cv::Mat VisDetection(const cv::Mat& im,
                                     const DetectionResult& result,
                                     const std::vector<std::string>& labels,
                                     float score_threshold = 0.0,
                                     int line_size = 1, float font_size = 0.5f);
/** \brief Show the visualized results for classification models
 *
 * \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 result produced by model
 * \param[in] top_k the length of return values, e.g., if topk==2, the result will include the 2 most possible class label for input image.
 * \param[in] score_threshold threshold for top_k scores, the class will not be shown if the score is less than score_threshold
 * \param[in] font_size font size
 * \return cv::Mat type stores the visualized results
 */
FASTDEPLOY_DECL cv::Mat VisClassification(
  const cv::Mat& im, const ClassifyResult& result, int top_k = 5,
  float score_threshold = 0.0f, float font_size = 0.5f);
/** \brief Show the visualized results with custom labels for classification models
 *
 * \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 result produced by model
 * \param[in] labels custom labels for user, the visualized result will show the corresponding custom labels
 * \param[in] top_k the length of return values, e.g., if topk==2, the result will include the 2 most possible class label for input image.
 * \param[in] score_threshold threshold for top_k scores, the class will not be shown if the score is less than score_threshold
 * \param[in] font_size font size
 * \return cv::Mat type stores the visualized results
 */
FASTDEPLOY_DECL cv::Mat VisClassification(
  const cv::Mat& im, const ClassifyResult& result,
  const std::vector<std::string>& labels, int top_k = 5,
  float score_threshold = 0.0f, float font_size = 0.5f);
/** \brief Show the visualized results for face detection models
 *
 * \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 result produced by model
 * \param[in] line_size line size for bounding boxes
 * \param[in] font_size font size for text
 * \return cv::Mat type stores the visualized results
 */
FASTDEPLOY_DECL cv::Mat VisFaceDetection(const cv::Mat& im,
                                         const FaceDetectionResult& result,
                                         int line_size = 1,
                                         float font_size = 0.5f);
/** \brief Show the visualized results for face alignment models
 *
 * \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 result produced by model
 * \param[in] line_size line size for circle point
 * \return cv::Mat type stores the visualized results
 */
FASTDEPLOY_DECL cv::Mat VisFaceAlignment(const cv::Mat& im,
                                         const FaceAlignmentResult& result,
                                         int line_size = 1);
/** \brief Show the visualized results for segmentation models
 *
 * \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 result produced by model
 * \param[in] weight transparent weight of visualized result image
 * \return cv::Mat type stores the visualized results
 */
FASTDEPLOY_DECL cv::Mat VisSegmentation(const cv::Mat& im,
                                        const SegmentationResult& result,
                                        float weight = 0.5);
/** \brief Show the visualized results for matting models
 *
 * \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 result produced by model
 * \param[in] remove_small_connected_area if remove_small_connected_area==true, the visualized result will not include the small connected areas
 * \return cv::Mat type stores the visualized results
 */
FASTDEPLOY_DECL cv::Mat VisMatting(const cv::Mat& im,
                                   const MattingResult& result,
                                   bool remove_small_connected_area = false);
/** \brief Show the visualized results for Ocr models
 *
 * \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 result produced by model
 * \return cv::Mat type stores the visualized results
 */
FASTDEPLOY_DECL cv::Mat VisOcr(const cv::Mat& im, const OCRResult& ocr_result);

FASTDEPLOY_DECL cv::Mat VisMOT(const cv::Mat& img, const MOTResult& results,
                               float score_threshold = 0.0f,
                               tracking::TrailRecorder* recorder = nullptr);
/** \brief Swap the image background with MattingResult
 *
 * \param[in] im the input image data, comes from cv::imread(), is a 3-D array with layout HWC, BGR format
 * \param[in] background the background image data, comes from cv::imread(), is a 3-D array with layout HWC, BGR format
 * \param[in] result the MattingResult produced by model
 * \param[in] remove_small_connected_area if remove_small_connected_area==true, the visualized result will not include the small connected areas
 * \return cv::Mat type stores the visualized results
 */
FASTDEPLOY_DECL cv::Mat SwapBackground(const cv::Mat& im,
                                      const cv::Mat& background,
                                      const MattingResult& result,
                                      bool remove_small_connected_area = false);
/** \brief Swap the image background with SegmentationResult
 *
 * \param[in] im the input image data, comes from cv::imread(), is a 3-D array with layout HWC, BGR format
 * \param[in] background the background image data, comes from cv::imread(), is a 3-D array with layout HWC, BGR format
 * \param[in] result the SegmentationResult produced by model
 * \param[in] background_label the background label number in SegmentationResult
 * \return cv::Mat type stores the visualized results
 */
FASTDEPLOY_DECL cv::Mat SwapBackground(const cv::Mat& im,
                                       const cv::Mat& background,
                                       const SegmentationResult& result,
                                       int background_label);
/** \brief Show the visualized results for key point detection models
 *
 * \param[in] im the input image data, comes from cv::imread(), is a 3-D array with layout HWC, BGR format
 * \param[in] results the result produced by model
 * \param[in] conf_threshold threshold for result scores, the result will not be shown if the score is less than conf_threshold
 * \return cv::Mat type stores the visualized results
 */
FASTDEPLOY_DECL cv::Mat VisKeypointDetection(const cv::Mat& im,
                        const KeyPointDetectionResult& results,
                        float conf_threshold = 0.5f);
FASTDEPLOY_DECL cv::Mat VisHeadPose(const cv::Mat& im,
                                    const HeadPoseResult& result,
                                    int size = 50,
                                    int line_size = 1);

}  // namespace vision
}  // namespace fastdeploy