super-gradients/src/super_gradients/recipes/dataset_params/mapillary_dataset_params.yaml

config_version: '1.2'

config_ignore_values:
  '1.2': 65
  '2.0': 123

mask_fill_value: ${getitem:${dataset_params.config_ignore_values},${dataset_params.config_version}}

train_dataset_params:
  root_dir: /data/mapillary-vistas-dataset_public_v2.0
  config_file: config_v${..config_version}.json
  samples_sub_directory: training/images
  targets_sub_directory: training/v${..config_version}/labels
  cache_labels: False
  cache_images: False
  transforms:
    - SegRescale:
        long_size: 2048

    - SegColorJitter:
        brightness: 0.5
        contrast: 0.5
        saturation: 0.5

    - SegRandomFlip:
        prob: 0.5

    - SegRandomRescale:
        scales: [ 0.5, 2.0 ]

    - SegPadShortToCropSize:
        crop_size: 1024
        fill_mask: ${dataset_params.mask_fill_value}

    - SegCropImageAndMask:
        crop_size: 1024
        mode: random

val_dataset_params:
  root_dir: /data/mapillary-vistas-dataset_public_v2.0
  config_file: config_v${..config_version}.json
  samples_sub_directory: validation/images
  targets_sub_directory: validation/v${..config_version}/labels
  cache_labels: False
  cache_images: False
  transforms:
    - SegRescale:
        long_size: 2048

    - SegPadToDivisible:
        divisible_value: 32
        fill_mask: ${dataset_params.mask_fill_value}

train_dataloader_params:
  shuffle: True
  batch_size: 4
  num_workers: 8
  drop_last: True
  pin_memory: True

val_dataloader_params:
  # Mapillary validation set include various image sizes.
  # It is recommended to Rescale the long size to 2048 then perform validation.
  # Unless the default transformation hasn't modified, it is not possible to batch the images to a common size.
  batch_size: 1
  num_workers: 8
  drop_last: False
  pin_memory: True