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# ----------------------------------------------------------------------------- | |
# Train a Mask R-CNN R50-FPN backbone on LVIS instance segmentation with any of | |
# these weight init: random, virtex or MoCo. (ImageNet init config is separate) | |
# ----------------------------------------------------------------------------- | |
_BASE_: "_base_mask_rcnn_R_50_FPN.yaml" | |
DATASETS: | |
TRAIN: ("lvis_v1_train",) | |
TEST: ("lvis_v1_val",) | |
DATALOADER: | |
SAMPLER_TRAIN: "RepeatFactorTrainingSampler" | |
REPEAT_THRESHOLD: 0.001 | |
TEST: | |
DETECTIONS_PER_IMAGE: 300 # LVIS allows up to 300. | |
MODEL: | |
MASK_ON: True | |
# FPN also has SyncBN, as opposed to no norm (usually). | |
FPN: | |
NORM: "SyncBN" | |
ROI_HEADS: | |
NUM_CLASSES: 1203 | |
SCORE_THRESH_TEST: 0.0001 | |
# This will be ignored, weights will be loaded manually in the script. | |
WEIGHTS: "" | |
SOLVER: | |
STEPS: (120000, 160000) | |
MAX_ITER: 180000 | |
VERSION: 2 | |