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| # model settings | |
| norm_cfg = dict(type='SyncBN', requires_grad=True) | |
| data_preprocessor = dict( | |
| type='SegDataPreProcessor', | |
| mean=[123.675, 116.28, 103.53], | |
| std=[58.395, 57.12, 57.375], | |
| bgr_to_rgb=True, | |
| pad_val=0, | |
| seg_pad_val=255) | |
| model = dict( | |
| type='EncoderDecoder', | |
| data_preprocessor=data_preprocessor, | |
| pretrained=None, | |
| backbone=dict( | |
| type='ERFNet', | |
| in_channels=3, | |
| enc_downsample_channels=(16, 64, 128), | |
| enc_stage_non_bottlenecks=(5, 8), | |
| enc_non_bottleneck_dilations=(2, 4, 8, 16), | |
| enc_non_bottleneck_channels=(64, 128), | |
| dec_upsample_channels=(64, 16), | |
| dec_stages_non_bottleneck=(2, 2), | |
| dec_non_bottleneck_channels=(64, 16), | |
| dropout_ratio=0.1, | |
| init_cfg=None), | |
| decode_head=dict( | |
| type='FCNHead', | |
| in_channels=16, | |
| channels=128, | |
| num_convs=1, | |
| concat_input=False, | |
| dropout_ratio=0.1, | |
| num_classes=19, | |
| norm_cfg=norm_cfg, | |
| align_corners=False, | |
| loss_decode=dict( | |
| type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)), | |
| # model training and testing settings | |
| train_cfg=dict(), | |
| test_cfg=dict(mode='whole')) | |