w32_256x256_adam_lr1e-3.yaml

AUTO_RESUME: true
CUDNN:
  BENCHMARK: true
  DETERMINISTIC: false
  ENABLED: true
DATA_DIR: ''
GPUS: (0,1,2,3)
OUTPUT_DIR: 'output'
LOG_DIR: 'log'
WORKERS: 24
PRINT_FREQ: 100

DATASET:
  COLOR_RGB: true
  DATASET: mpii
  DATA_FORMAT: jpg
  FLIP: true
  NUM_JOINTS_HALF_BODY: 8
  PROB_HALF_BODY: -1.0
  ROOT: 'data/mpii/'
  ROT_FACTOR: 30
  SCALE_FACTOR: 0.25
  TEST_SET: valid
  TRAIN_SET: train
MODEL:
  INIT_WEIGHTS: true
  NAME: pose_hrnet
  NUM_JOINTS: 16
  PRETRAINED: 'models/pytorch/imagenet/hrnet_w32-36af842e.pth'
  TARGET_TYPE: gaussian
  IMAGE_SIZE:
  - 256
  - 256
  HEATMAP_SIZE:
  - 64
  - 64
  SIGMA: 2
  EXTRA:
    PRETRAINED_LAYERS:
    - 'conv1'
    - 'bn1'
    - 'conv2'
    - 'bn2'
    - 'layer1'
    - 'transition1'
    - 'stage2'
    - 'transition2'
    - 'stage3'
    - 'transition3'
    - 'stage4'
    FINAL_CONV_KERNEL: 1
    STAGE2:
      NUM_MODULES: 1
      NUM_BRANCHES: 2
      BLOCK: BASIC
      NUM_BLOCKS:
      - 4
      - 4
      NUM_CHANNELS:
      - 32
      - 64
      FUSE_METHOD: SUM
    STAGE3:
      NUM_MODULES: 4
      NUM_BRANCHES: 3
      BLOCK: BASIC
      NUM_BLOCKS:
      - 4
      - 4
      - 4
      NUM_CHANNELS:
      - 32
      - 64
      - 128
      FUSE_METHOD: SUM
    STAGE4:
      NUM_MODULES: 3
      NUM_BRANCHES: 4
      BLOCK: BASIC
      NUM_BLOCKS:
      - 4
      - 4
      - 4
      - 4
      NUM_CHANNELS:
      - 32
      - 64
      - 128
      - 256
      FUSE_METHOD: SUM
LOSS:
  USE_TARGET_WEIGHT: true
TRAIN:
  BATCH_SIZE_PER_GPU: 32
  SHUFFLE: true
  BEGIN_EPOCH: 0
  END_EPOCH: 210
  OPTIMIZER: adam
  LR: 0.001
  LR_FACTOR: 0.1
  LR_STEP:
  - 170
  - 200
  WD: 0.0001
  GAMMA1: 0.99
  GAMMA2: 0.0
  MOMENTUM: 0.9
  NESTEROV: false
TEST:
  BATCH_SIZE_PER_GPU: 32
  MODEL_FILE: ''
  FLIP_TEST: true
  POST_PROCESS: true
  SHIFT_HEATMAP: true
DEBUG:
  DEBUG: true
  SAVE_BATCH_IMAGES_GT: true
  SAVE_BATCH_IMAGES_PRED: true
  SAVE_HEATMAPS_GT: true
  SAVE_HEATMAPS_PRED: true