code: # 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.
  
  import codecs
  import argparse
  
  import cv2
  import numpy as np
  import geojson
  from geojson import Polygon, Feature, FeatureCollection
  
  from utils import Raster, Timer
  
  
  def _gt_convert(x, y, geotf):
      x_geo = geotf[0] + x * geotf[1] + y * geotf[2]
      y_geo = geotf[3] + x * geotf[4] + y * geotf[5]
      return x_geo, y_geo
  
  
  @Timer
  def convert_data(mask_path, save_path, epsilon=0):
      raster = Raster(mask_path)
      img = raster.getArray()
      ext = save_path.split(".")[-1]
      if ext != "json" and ext != "geojson":
          raise ValueError("The ext of `save_path` must be `json` or `geojson`, not {}.".format(ext))
      geo_writer = codecs.open(save_path, "w", encoding="utf-8")
      clas = np.unique(img)
      cv2_v = (cv2.__version__.split(".")[0] == "3")
      feats = []
      if not isinstance(epsilon, (int, float)):
          epsilon = 0
      for iclas in range(1, len(clas)):
          tmp = np.zeros_like(img).astype("uint8")
          tmp[img == iclas] = 1
          # TODO: Detect internal and external contour
          results = cv2.findContours(tmp, cv2.RETR_EXTERNAL,
                                     cv2.CHAIN_APPROX_TC89_KCOS)
          contours = results[1] if cv2_v else results[0]
          # hierarchys = results[2] if cv2_v else results[1]
          if len(contours) == 0:
              continue
          for contour in contours:
              contour = cv2.approxPolyDP(contour, epsilon, True)
              polys = []
              for point in contour:
                  x, y = point[0]
                  xg, yg = _gt_convert(x, y, raster.geot)
                  polys.append((xg, yg))
              polys.append(polys[0])
              feat = Feature(
                  geometry=Polygon([polys]), properties={"class": int(iclas)})
              feats.append(feat)
      gjs = FeatureCollection(feats)
      geo_writer.write(geojson.dumps(gjs))
      geo_writer.close()
  
  
  parser = argparse.ArgumentParser(description="input parameters")
  parser.add_argument("--mask_path", type=str, required=True, \
                      help="The path of mask tif.")
  parser.add_argument("--save_path", type=str, required=True, \
                      help="The path to save the results, file suffix is `*.json/geojson`.")
  parser.add_argument("--epsilon", type=float, default=0, \
                      help="The CV2 simplified parameters, `0` is the default.")
  
  if __name__ == "__main__":
      args = parser.parse_args()
      convert_data(args.mask_path, args.save_path, args.epsilon)
  
apis: numpy.zeros_like numpy.unique