26 lines
720 B
YAML
26 lines
720 B
YAML
MODEL:
|
|
META_ARCHITECTURE: "RetinaNet"
|
|
BACKBONE:
|
|
NAME: "build_retinanet_resnet_fpn_backbone"
|
|
RESNETS:
|
|
OUT_FEATURES: ["res3", "res4", "res5"]
|
|
ANCHOR_GENERATOR:
|
|
SIZES: !!python/object/apply:eval ["[[x, x * 2**(1.0/3), x * 2**(2.0/3) ] for x in [32, 64, 128, 256, 512 ]]"]
|
|
FPN:
|
|
IN_FEATURES: ["res3", "res4", "res5"]
|
|
RETINANET:
|
|
IOU_THRESHOLDS: [0.4, 0.5]
|
|
IOU_LABELS: [0, -1, 1]
|
|
SMOOTH_L1_LOSS_BETA: 0.0
|
|
DATASETS:
|
|
TRAIN: ("coco_2017_train",)
|
|
TEST: ("coco_2017_val",)
|
|
SOLVER:
|
|
IMS_PER_BATCH: 16
|
|
BASE_LR: 0.01 # Note that RetinaNet uses a different default learning rate
|
|
STEPS: (60000, 80000)
|
|
MAX_ITER: 90000
|
|
INPUT:
|
|
MIN_SIZE_TRAIN: (640, 672, 704, 736, 768, 800)
|
|
VERSION: 2
|