hrnet_config.yaml

CUDNN:
  BENCHMARK: true
  DETERMINISTIC: false
  ENABLED: true
GPUS: (0,)
OUTPUT_DIR: 'output'
LOG_DIR: 'log'
WORKERS: 1
PRINT_FREQ: 100

MODEL:
  NAME: seg_hrnet
  EXTRA:
    FINAL_CONV_KERNEL: 1
    STAGE1:
      NUM_MODULES: 1
      NUM_RANCHES: 1
      BLOCK: BOTTLENECK
      NUM_BLOCKS:
      - 4
      NUM_CHANNELS:
      - 64
      FUSE_METHOD: SUM
    STAGE2:
      NUM_MODULES: 1
      NUM_BRANCHES: 2
      BLOCK: BASIC
      NUM_BLOCKS:
      - 4
      - 4
      NUM_CHANNELS:
      - 48
      - 96
      FUSE_METHOD: SUM
    STAGE3:
      NUM_MODULES: 4
      NUM_BRANCHES: 3
      BLOCK: BASIC
      NUM_BLOCKS:
      - 4
      - 4
      - 4
      NUM_CHANNELS:
      - 48
      - 96
      - 192
      FUSE_METHOD: SUM
    STAGE4:
      NUM_MODULES: 3
      NUM_BRANCHES: 4
      BLOCK: BASIC
      NUM_BLOCKS:
      - 4
      - 4
      - 4
      - 4
      NUM_CHANNELS:
      - 48
      - 96
      - 192
      - 384
      FUSE_METHOD: SUM
LOSS:
  USE_OHEM: false
  OHEMTHRES: 0.9
  OHEMKEEP: 131072
TRAIN:
  IMAGE_SIZE:
  - 256
  - 306
  BASE_SIZE: 2048
  BATCH_SIZE_PER_GPU: 3
  SHUFFLE: true
  BEGIN_EPOCH: 0
  END_EPOCH: 484
  RESUME: true
  OPTIMIZER: sgd
  LR: 0.01
  WD: 0.0005
  MOMENTUM: 0.9
  NESTEROV: false
  FLIP: true
  MULTI_SCALE: true
  DOWNSAMPLERATE: 1
  IGNORE_LABEL: 255
  SCALE_FACTOR: 16
TEST:
  IMAGE_SIZE:
  - 2048
  - 1024
  BASE_SIZE: 2048
  BATCH_SIZE_PER_GPU: 4
  FLIP_TEST: false
  MULTI_SCALE: false