dual-hrnet.yaml

OUTPUT_DIR: ''
LOG_DIR: ''
GPUS: [0,]
WORKERS: 4
PRINT_FREQ: 20
AUTO_RESUME: False
PIN_MEMORY: True
RANK: 0

# Cudnn related params
CUDNN:
  BENCHMARK: True
  DETERMINISTIC: False
  ENABLED: True

# common params for NETWORK
MODEL:
  NAME: 'dual-hrnet'
  PRETRAINED: './Checkpoints/HRNet/hrnetv2_w32_imagenet_pretrained.pth'
  USE_FPN: False
  IS_DISASTER_PRED: False
  IS_SPLIT_LOSS: True
  FUSE_CONV_K_SIZE: 1

  # high_resoluton_net related params for segmentation
  EXTRA:
    PRETRAINED_LAYERS: ['*']
    STEM_INPLANES: 64
    FINAL_CONV_KERNEL: 1
    WITH_HEAD: True

    STAGE1:
      NUM_MODULES: 1
      NUM_BRANCHES: 1
      NUM_BLOCKS: [4]
      NUM_CHANNELS: [64]
      BLOCK: 'BOTTLENECK'
      FUSE_METHOD: 'SUM'

    STAGE2:
      NUM_MODULES: 1
      NUM_BRANCHES: 2
      NUM_BLOCKS: [4, 4]
      NUM_CHANNELS: [32, 64]
      BLOCK: 'BASIC'
      FUSE_METHOD: 'SUM'

    STAGE3:
      NUM_MODULES: 4
      NUM_BRANCHES: 3
      NUM_BLOCKS: [4, 4, 4]
      NUM_CHANNELS: [32, 64, 128]
      BLOCK: 'BASIC'
      FUSE_METHOD: 'SUM'

    STAGE4:
      NUM_MODULES: 3
      NUM_BRANCHES: 4
      NUM_BLOCKS: [4, 4, 4, 4]
      NUM_CHANNELS: [32, 64, 128, 256]
      BLOCK: 'BASIC'
      FUSE_METHOD: 'SUM'

#_C.MODEL.EXTRA= CN(new_allowed=True)

LOSS:
  CLASS_BALANCE: True

# DATASET related params
DATASET:
  NUM_CLASSES: 4

# training
TRAIN:
  # Augmentation
  FLIP: True
  MULTI_SCALE: [0.8, 1.2]
  CROP_SIZE: [512, 512]

  LR_FACTOR: 0.1
  LR_STEP: [90, 110]
  LR: 0.05
  EXTRA_LR: 0.001

  OPTIMIZER: 'sgd'
  MOMENTUM: 0.9
  WD: 0.0001
  NESTEROV: False
  IGNORE_LABEL: -1

  NUM_EPOCHS: 500
  RESUME: False

  BATCH_SIZE_PER_GPU: 16
  SHUFFLE: True
# only using some training samples
  NUM_SAMPLES: 0
  CLASS_WEIGHTS: [0.4, 1.2, 1.2, 1.2]

# testing
TEST:
  BATCH_SIZE_PER_GPU: 32
# only testing some samples
  NUM_SAMPLES: 0

  MODEL_FILE: ''
  FLIP_TEST: False
  MULTI_SCALE: False
  CENTER_CROP_TEST: False
  SCALE_LIST: [1]

# debug
DEBUG:
  DEBUG: False
  SAVE_BATCH_IMAGES_GT: False
  SAVE_BATCH_IMAGES_PRED: False
  SAVE_HEATMAPS_GT: False
  SAVE_HEATMAPS_PRED: False