text: # Copyright The PyTorch Lightning team.
  #
  # 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.
  
  from flash.core.data.utils import download_data
  from flash.core.utilities.flash_cli import FlashCLI
  from flash.image import SemanticSegmentation, SemanticSegmentationData
  
  __all__ = ["semantic_segmentation"]
  
  
  def from_carla(
      num_classes: int = 21,
      val_split: float = 0.1,
      batch_size: int = 4,
      num_workers: int = 0,
      **preprocess_kwargs,
  ) -> SemanticSegmentationData:
      """Downloads and loads the CARLA capture data set."""
      download_data(
          "https://github.com/ongchinkiat/LyftPerceptionChallenge/releases/download/v0.1/carla-capture-20180513A.zip",
          "./data",
      )
      return SemanticSegmentationData.from_folders(
          train_folder="data/CameraRGB",
          train_target_folder="data/CameraSeg",
          val_split=val_split,
          batch_size=batch_size,
          num_workers=num_workers,
          num_classes=num_classes,
          **preprocess_kwargs,
      )
  
  
  def semantic_segmentation():
      """Segment objects in images."""
      cli = FlashCLI(
          SemanticSegmentation,
          SemanticSegmentationData,
          default_datamodule_builder=from_carla,
          default_arguments={
              "trainer.max_epochs": 3,
          },
      )
  
      cli.trainer.save_checkpoint("semantic_segmentation_model.pt")
  
  
  if __name__ == "__main__":
      semantic_segmentation()
  