model = dict( type='FAST', backbone=dict( type='fast_backbone', config='config/fast/nas-configs/fast_tiny.config' ), neck=dict( type='fast_neck', config='config/fast/nas-configs/fast_tiny.config' ), detection_head=dict( type='fast_head', config='config/fast/nas-configs/fast_tiny.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='valid', 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='/Users/eaxxkra/Downloads/fast_tiny_ic17mlt_640.pth' # https://github.com/czczup/FAST/releases/download/release/fast_tiny_in1k_epoch_299.pth ) test_cfg = dict( result_path='outputs/submit_ctw/', min_area=250, min_score=0.88, bbox_type='rect', )