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model = dict(
type='FAST',
backbone=dict(
type='fast_backbone',
config='config/fast/nas-configs/fast_base.config'
),
neck=dict(
type='fast_neck',
config='config/fast/nas-configs/fast_base.config'
),
detection_head=dict(
type='fast_head',
config='config/fast/nas-configs/fast_base.config',
pooling_size=9,
loss_text=dict(
type='DiceLoss',
loss_weight=0.5
),
loss_kernel=dict(
type='DiceLoss',
loss_weight=1.0
),
loss_emb=dict(
type='EmbLoss_v1',
feature_dim=4,
loss_weight=0.25
)
)
)
repeat_times = 10
data = dict(
batch_size=16,
train=dict(
type='FAST_IC17MLT',
split='train',
is_transform=True,
img_size=640,
short_size=640,
pooling_size=9,
read_type='cv2',
repeat_times=repeat_times
),
test=dict(
type='FAST_IC17MLT',
split='test',
short_size=640,
read_type='cv2'
)
)
train_cfg = dict(
lr=1e-3,
schedule='polylr',
epoch=300 // repeat_times,
optimizer='Adam',
save_interval=10 // repeat_times,
pretrain='pretrained/fast_base_in1k_epoch_299.pth'
# https://github.com/czczup/FAST/releases/download/release/fast_base_in1k_epoch_299.pth
)
test_cfg = dict(
result_path='outputs/submit_ctw/',
min_area=250,
min_score=0.88,
bbox_type='rect',
)
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