centernet_res50_layout_analysis.yaml

MODEL:
  #WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-50.pkl"
  WEIGHTS: '' #'exp_results/layout_exp_R50_SGD/model_final.pth'

  META_ARCHITECTURE: "CenterNet"
  BN_TYPE: "BN"
  BACKBONE:
    NAME: "build_resnet"
    DEPTH: 50
    PRETRAIN: True
  PIXEL_MEAN: [0.485, 0.456, 0.406]
  PIXEL_STD: [0.229, 0.224, 0.225]

  DETNET:
    DECONV_CHANNEL: [2048, 256, 128, 64]
    DECONV_KERNEL: [4, 4, 4]
    NUM_CLASSES: 5
    MODULATE_DEFORM: True
    BIAS_VALUE: -2.19
    DOWN_SCALE: 4
    MIN_OVERLAP: 0.3
    TENSOR_DIM: 128

TEST:
  EVAL_PERIOD: 100 
DATALOADER:
  NUM_WORKERS: 20 

DATASETS:
  TRAIN: ("layout_train",)
  TEST: ("layout_val",)

SOLVER:
  IMS_PER_BATCH: 2
  WARMUP_ITERS: 1
  STEPS: (20, 30)
  MAX_ITER: 40
  BASE_LR: 0.005 #5e-4
  LR_SCHEDULER_NAME: "WarmupCosineAnnealingLR"
  COSINE_DECAY_ITER: 0.6
  OPTIM_NAME: "SGD"
  CLIP_GRADIENTS:
    ENABLED: True
    CLIP_TYPE: "value"
    CLIP_VALUE: 1.0

INPUT:
  FORMAT: 'RGB'
  MIN_SIZE_TEST: 0
  MIN_SIZE_TRAIN: (384, 448, 512,)
  MAX_SIZE_TRAIN: 512
  CROP:
    ENABLED: True
    TYPE: "relative_range"
    SIZE: [0.6, 0.6]

OUTPUT_DIR: "exp_results/layout_exp_R50"
VERSION: 2