default.yaml

DATASET:
  TRAIN_CSV: './data/nyu2_train.csv'
  TEST_CSV: './data/nyu2_test.csv'
MODEL:
  # model type: ['resnet', 'densenet', 'senet']
  NAME: 'resnet'
SOLVER:
  BASE_LR: 0.0001
  BATCHSIZE: 8
  NUM_WORKERS: 4
  MOMENTUM: 0.9
  WEIGHT_DECAY: 0.0001
  LR_STEP_SIZE: 5
  LR_GAMMA: 0.1
  EPOCH: 20
  SAVE_INTERVAL: 1
DATA:
  NORMALIZE_MEAN: [0.485, 0.456, 0.406]
  NORMALIZE_STD: [0.229, 0.224, 0.225]
  PCA_LIGHTING: 0.1
  PCA_EIGVAL: [0.2175, 0.0188, 0.0045]
  PCA_EIGVEC: [[-0.5675,  0.7192,  0.4009],
               [-0.5808, -0.0045, -0.8140],
               [-0.5836, -0.6948,  0.4203]]
  SCALE_SIZE_MIN: 240
  RANDOM_ROT_DEGREE: 5
  CENTER_CROP_SIZE: [304, 228]
  OUTPUT_SIZE: [152, 114]
  RANDOM_BRIGHTNESS: 0.4
  RANDOM_CONTRAST: 0.4
  RANDOM_SATURATION: 0.4
LOSS:
  ALPHA: 0.5
  LAMBDA: 1
  MU: 1
SEED: 1
TEST:
  BATCHSIZE: 1
  THRESHOLD_EDGE: 0.25
DEVICE: 'cuda'
OUTPUT_DIR: 'results'