Mask-Adapter / configs /ground-truth-warmup /Base-COCO-PanopticSegmentation.yaml
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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
SOLVER:
IMS_PER_BATCH: 8
BASE_LR: 0.0001
STEPS: (260231, 283888)
MAX_ITER: 295717
WARMUP_FACTOR: 1.0
WARMUP_ITERS: 10
CHECKPOINT_PERIOD: 10000
WEIGHT_DECAY: 0.05
OPTIMIZER: "ADAMW"
BACKBONE_MULTIPLIER: 0.1
CLIP_GRADIENTS:
ENABLED: True
CLIP_TYPE: "full_model"
CLIP_VALUE: 1.0
NORM_TYPE: 2.0
AMP:
ENABLED: True
INPUT:
IMAGE_SIZE: 768
MIN_SCALE: 0.1
MAX_SCALE: 2.0
FORMAT: "RGB"
MIN_SIZE_TRAIN: (1024,)
MAX_SIZE_TRAIN: 1024
DATASET_MAPPER_NAME: "coco_combine_lsj"
MASK_FORMAT: "bitmask"
COLOR_AUG_SSD: True
DATASETS:
TRAIN: ("openvocab_coco_2017_train_panoptic_with_sem_seg",)
TEST: ("openvocab_ade20k_panoptic_val",) # to evaluate instance and semantic performance as well
DATALOADER:
SAMPLER_TRAIN: "MultiDatasetSampler"
USE_DIFF_BS_SIZE: False
DATASET_RATIO: [1.0]
DATASET_BS: [2]
USE_RFS: [False]
NUM_WORKERS: 8
DATASET_ANN: ['mask']
ASPECT_RATIO_GROUPING: True
TEST:
EVAL_PERIOD: 10000
VERSION: 2