Base-CenterNet2.yaml

MODEL:
  META_ARCHITECTURE: "GeneralizedRCNN"
  PROPOSAL_GENERATOR:
    NAME: "CenterNet"
  BACKBONE:
    NAME: "build_p67_resnet_fpn_backbone"
  WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-50.pkl"
  RESNETS:
    DEPTH: 50
    OUT_FEATURES: ["res3", "res4", "res5"]
  FPN:
    IN_FEATURES: ["res3", "res4", "res5"]
  ROI_HEADS:
    NAME: CustomCascadeROIHeads
    IN_FEATURES: ["p3", "p4", "p5", "p6", "p7"]
    IOU_THRESHOLDS: [0.6]
    NMS_THRESH_TEST: 0.7
  ROI_BOX_CASCADE_HEAD:
    IOUS: [0.6, 0.7, 0.8]
  ROI_BOX_HEAD:
    NAME: "FastRCNNConvFCHead"
    NUM_FC: 2
    POOLER_RESOLUTION: 7
    CLS_AGNOSTIC_BBOX_REG: True
    MULT_PROPOSAL_SCORE: True
  CENTERNET:
    REG_WEIGHT: 1.
    NOT_NORM_REG: True
    ONLY_PROPOSAL: True
    WITH_AGN_HM: True
    INFERENCE_TH: 0.0001
    PRE_NMS_TOPK_TRAIN: 4000
    POST_NMS_TOPK_TRAIN: 2000
    PRE_NMS_TOPK_TEST: 1000
    POST_NMS_TOPK_TEST: 256
    NMS_TH_TRAIN: 0.9
    NMS_TH_TEST: 0.9
    POS_WEIGHT: 0.5
    NEG_WEIGHT: 0.5
    IGNORE_HIGH_FP: 0.85
DATASETS:
  TRAIN: ("coco_2017_train",)
  TEST: ("coco_2017_val",)
SOLVER:
  IMS_PER_BATCH: 16
  BASE_LR: 0.02
  STEPS: (60000, 80000)
  MAX_ITER: 90000
  CHECKPOINT_PERIOD: 1000000000
  WARMUP_ITERS: 4000
  WARMUP_FACTOR: 0.00025
  CLIP_GRADIENTS:
    ENABLED: True
INPUT:
  MIN_SIZE_TRAIN: (640, 672, 704, 736, 768, 800)
OUTPUT_DIR: "./output/CenterNet2/auto"