models/configs/vanilla_regnet.yaml

_BASE_: "Base-RCNN-FPN.yaml"
MODEL:
  PIXEL_STD: [57.375, 57.120, 58.395]
  BACKBONE:
    NAME: "build_regnetx_fpn_backbone"
  META_ARCHITECTURE: "GeneralizedRCNN"
  WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-50.pkl"
#  WEIGHTS: "./data/VOC-Detection/faster-rcnn/faster_rcnn_R_50_FPN_all_logistic/random_seed_0/model_final.pth"

#  PROPOSAL_GENERATOR:
#    NAME: "RPNLogistic"
  FPN:
    IN_FEATURES: ["s1", "s2", "s3", "s4"]
  MASK_ON: False
  RESNETS:
    DEPTH: 50
  ROI_HEADS:
    NAME: "StandardROIHeads"
    NUM_CLASSES: 10
INPUT:
  MIN_SIZE_TRAIN: (480, 512, 544, 576, 608, 640, 672, 704, 736, 768, 800)
  MIN_SIZE_TEST: 800
DATASETS:
  TRAIN: ('bdd_custom_train',)
  TEST: ('bdd_custom_val',)
SOLVER:
  IMS_PER_BATCH: 16
  BASE_LR: 0.02
  STEPS: (60000, 80000)
  MAX_ITER: 90000  # 17.4 epochs
  WARMUP_ITERS: 100
DATALOADER:
    NUM_WORKERS: 8  # Depends on the available memory