deeplabv3p.yml

batch_size: 2
iters: 500

train_dataset:
  type: Cityscapes
  dataset_root: data/cityscapes
  transforms:
    - type: ResizeStepScaling
      min_scale_factor: 0.5
      max_scale_factor: 2.0
      scale_step_size: 0.25
    - type: RandomPaddingCrop
      crop_size: [1024, 512]
    - type: RandomHorizontalFlip
    - type: RandomDistort
    - type: Normalize
  mode: train

val_dataset:
  type: Cityscapes
  dataset_root: data/cityscapes
  transforms:
    - type: Normalize
  mode: val

model:
  type: DeepLabV3P
  backbone:
    type: ResNet50_vd
    output_stride: 8
    multi_grid: [1, 2, 4]
  num_classes: 19
  backbone_indices: [0, 3]
  aspp_ratios: [1, 12, 24, 36]

optimizer:
  type: sgd
  weight_decay: 0.00004

learning_rate:
  value: 0.01
  decay:
    type: poly
    power: 0.9
    end_lr: 0.0

loss:
  types:
    - type: CrossEntropyLoss
      ignore_index: 255
  coef: [1]