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MODEL:
BACKBONE:
FREEZE_AT: 0
NAME: "build_resnet_backbone"
WEIGHTS: "detectron2://ImageNetPretrained/torchvision/R-50.pkl"
PIXEL_MEAN: [123.675, 116.280, 103.530]
PIXEL_STD: [58.395, 57.120, 57.375]
RESNETS:
DEPTH: 50
STEM_TYPE: "basic" # not used
STEM_OUT_CHANNELS: 64
STRIDE_IN_1X1: False
OUT_FEATURES: ["res2", "res3", "res4", "res5"]
# NORM: "SyncBN"
RES5_MULTI_GRID: [1, 1, 1] # not used
DATASETS:
TRAIN: ("ade20k_instance_train",)
TEST: ("ade20k_instance_val",)
SOLVER:
IMS_PER_BATCH: 16
BASE_LR: 0.0001
MAX_ITER: 160000
WARMUP_FACTOR: 1.0
WARMUP_ITERS: 0
WEIGHT_DECAY: 0.05
OPTIMIZER: "ADAMW"
LR_SCHEDULER_NAME: "WarmupPolyLR"
BACKBONE_MULTIPLIER: 0.1
CLIP_GRADIENTS:
ENABLED: True
CLIP_TYPE: "full_model"
CLIP_VALUE: 0.01
NORM_TYPE: 2.0
AMP:
ENABLED: True
INPUT:
MIN_SIZE_TRAIN: !!python/object/apply:eval ["[int(x * 0.1 * 640) for x in range(5, 21)]"]
MIN_SIZE_TRAIN_SAMPLING: "choice"
MIN_SIZE_TEST: 640
MAX_SIZE_TRAIN: 2560
MAX_SIZE_TEST: 2560
CROP:
ENABLED: True
TYPE: "absolute"
SIZE: (640, 640)
SINGLE_CATEGORY_MAX_AREA: 1.0
COLOR_AUG_SSD: True
SIZE_DIVISIBILITY: 640 # used in dataset mapper
FORMAT: "RGB"
DATASET_MAPPER_NAME: "mask_former_instance"
TEST:
EVAL_PERIOD: 5000
AUG:
ENABLED: False
MIN_SIZES: [320, 480, 640, 800, 960, 1120]
MAX_SIZE: 4480
FLIP: True
DATALOADER:
FILTER_EMPTY_ANNOTATIONS: True
NUM_WORKERS: 4
VERSION: 2
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