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config.py
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config.py
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import os.path as osp
from cvpods.configs.fcos_config import FCOSConfig
_config_dict = dict(
MODEL=dict(
WEIGHTS="detectron2://ImageNetPretrained/MSRA/R-50.pkl",
RESNETS=dict(DEPTH=50),
FCOS=dict(
PRIOR_PROB=0.02,
NORM_REG_TARGETS=True,
NMS_THRESH_TEST=0.6,
BBOX_REG_WEIGHTS=(1.0, 1.0, 1.0, 1.0),
FOCAL_LOSS_GAMMA=2.0,
FOCAL_LOSS_ALPHA=0.25,
IOU_LOSS_TYPE="giou",
REG_WEIGHT=5.0,
),
),
DATASETS=dict(
TRAIN=("coco_2017_train",),
TEST=("coco_2017_val",),
),
SOLVER=dict(
IMS_PER_BATCH=16,
CHECKPOINT_PERIOD=10000,
LR_SCHEDULER=dict(
STEPS=(60000, 80000),
MAX_ITER=90000,
),
OPTIMIZER=dict(
BASE_LR=0.01,
),
),
INPUT=dict(
AUG=dict(
TRAIN_PIPELINES=[
("ResizeShortestEdge", dict(
short_edge_length=(800,), max_size=1333, sample_style="choice")),
("RandomFlip", dict()),
],
TEST_PIPELINES=[
("ResizeShortestEdge", dict(
short_edge_length=800, max_size=1333, sample_style="choice")),
],
)
),
TEST=dict(
EVAL_PERIOD=10000,
),
OUTPUT_DIR=osp.join(
'/data/Outputs/model_logs/cvpods_playground',
osp.split(osp.realpath(__file__))[0].split("playground/")[-1]),
)
class AutoAssignConfig(FCOSConfig):
def __init__(self):
super(AutoAssignConfig, self).__init__()
self._register_configuration(_config_dict)
config = AutoAssignConfig()