Upload 3 files
Browse files- fast_base_ic17mlt_640.py +64 -0
- fast_small_ic17mlt_640.py +64 -0
- fast_tiny_ic17mlt_640.py +64 -0
fast_base_ic17mlt_640.py
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model = dict(
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type='FAST',
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backbone=dict(
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type='fast_backbone',
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config='config/fast/nas-configs/fast_base.config'
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),
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neck=dict(
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type='fast_neck',
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config='config/fast/nas-configs/fast_base.config'
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),
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detection_head=dict(
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type='fast_head',
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config='config/fast/nas-configs/fast_base.config',
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pooling_size=9,
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loss_text=dict(
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type='DiceLoss',
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loss_weight=0.5
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),
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loss_kernel=dict(
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type='DiceLoss',
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loss_weight=1.0
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),
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loss_emb=dict(
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type='EmbLoss_v1',
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feature_dim=4,
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loss_weight=0.25
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)
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)
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)
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repeat_times = 10
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data = dict(
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batch_size=16,
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train=dict(
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type='FAST_IC17MLT',
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split='train',
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is_transform=True,
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img_size=640,
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short_size=640,
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pooling_size=9,
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read_type='cv2',
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repeat_times=repeat_times
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),
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test=dict(
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type='FAST_IC17MLT',
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split='test',
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short_size=640,
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read_type='cv2'
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)
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)
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train_cfg = dict(
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lr=1e-3,
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schedule='polylr',
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epoch=300 // repeat_times,
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optimizer='Adam',
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save_interval=10 // repeat_times,
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pretrain='pretrained/fast_base_in1k_epoch_299.pth'
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# https://github.com/czczup/FAST/releases/download/release/fast_base_in1k_epoch_299.pth
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)
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test_cfg = dict(
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result_path='outputs/submit_ctw/',
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min_area=250,
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min_score=0.88,
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bbox_type='rect',
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)
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fast_small_ic17mlt_640.py
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model = dict(
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type='FAST',
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backbone=dict(
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type='fast_backbone',
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config='config/fast/nas-configs/fast_small.config'
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),
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neck=dict(
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type='fast_neck',
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config='config/fast/nas-configs/fast_small.config'
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),
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detection_head=dict(
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type='fast_head',
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config='config/fast/nas-configs/fast_small.config',
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pooling_size=9,
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loss_text=dict(
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type='DiceLoss',
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loss_weight=0.5
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),
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loss_kernel=dict(
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type='DiceLoss',
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loss_weight=1.0
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),
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loss_emb=dict(
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type='EmbLoss_v1',
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feature_dim=4,
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loss_weight=0.25
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)
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)
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)
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repeat_times = 10
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data = dict(
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batch_size=16,
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train=dict(
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type='FAST_IC17MLT',
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split='train',
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is_transform=True,
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img_size=640,
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short_size=640,
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pooling_size=9,
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read_type='cv2',
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repeat_times=repeat_times,
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),
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test=dict(
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type='FAST_IC17MLT',
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split='test',
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short_size=640,
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read_type='cv2'
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)
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)
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train_cfg = dict(
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lr=1e-3,
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schedule='polylr',
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epoch=300 // repeat_times,
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optimizer='Adam',
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save_interval=10 // repeat_times,
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pretrain='pretrained/fast_small_in1k_epoch_299.pth'
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# https://github.com/czczup/FAST/releases/download/release/fast_small_in1k_epoch_299.pth
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)
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test_cfg = dict(
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result_path='outputs/submit_ctw/',
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min_area=250,
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min_score=0.88,
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bbox_type='rect',
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)
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fast_tiny_ic17mlt_640.py
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@@ -0,0 +1,64 @@
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model = dict(
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type='FAST',
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+
backbone=dict(
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type='fast_backbone',
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config='config/fast/nas-configs/fast_tiny.config'
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),
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neck=dict(
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type='fast_neck',
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config='config/fast/nas-configs/fast_tiny.config'
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),
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detection_head=dict(
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type='fast_head',
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config='config/fast/nas-configs/fast_tiny.config',
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pooling_size=9,
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loss_text=dict(
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type='DiceLoss',
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loss_weight=0.5
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),
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loss_kernel=dict(
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type='DiceLoss',
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loss_weight=1.0
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),
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loss_emb=dict(
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type='EmbLoss_v1',
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feature_dim=4,
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loss_weight=0.25
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)
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+
)
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)
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repeat_times = 10
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data = dict(
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batch_size=16,
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+
train=dict(
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type='FAST_IC17MLT',
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split='train',
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+
is_transform=True,
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+
img_size=640,
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+
short_size=640,
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pooling_size=9,
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read_type='cv2',
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repeat_times=repeat_times,
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),
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test=dict(
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type='FAST_IC17MLT',
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split='valid',
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short_size=640,
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read_type='cv2'
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)
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)
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train_cfg = dict(
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lr=1e-3,
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schedule='polylr',
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epoch=300 // repeat_times,
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optimizer='Adam',
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save_interval=10 // repeat_times,
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pretrain='/Users/eaxxkra/Downloads/fast_tiny_ic17mlt_640.pth'
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# https://github.com/czczup/FAST/releases/download/release/fast_tiny_in1k_epoch_299.pth
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)
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test_cfg = dict(
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result_path='outputs/submit_ctw/',
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min_area=250,
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min_score=0.88,
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bbox_type='rect',
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)
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