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_BASE_: "Base-RCNN-FPN.yaml"
MODEL:
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"
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