config_4class.yaml

# Deep learning configuration file ------------------------------------------------
# This config is to use massachusetts_buildings image out of the box WITH ONLY MANDATORY PARAMETERS.
# For that, unzip the file data/massachusetts_buildings.zip before running images_to_samples.py or other command.
# Five sections :
#   1) Global parameters; those are re-used amongst the next three operations
#   2) Inference parameters

# Global parameters
global:
  task: 'segmentation'
  number_of_bands: 4  # Number of bands in input imagery
  # Set to True if the first three channels of imagery are blue, green, red. Set to False if Red, Green, Blue
  BGR_to_RGB: True
  classes:
    1: 'forests'
    2: 'hydro'
    3: 'roads'
    4: 'buildings'

# Inference parameters; used in inference.py --------
inference:
  img_dir_or_csv_file: #/path/to/img_dir_or_csv_file
  state_dict_path: # /path/to/model/weights/for/inference/checkpoint.pth.tar