loss_decode = self._decode_head_forward_train(x, img_metas, gt_semantic_seg) losses.update(loss_decode) if self.with_auxiliary_head: loss_aux = self._auxiliary_head_forward_train( x, img_metas, gt_semantic_seg) losses.update(loss_aux) return losses 1. 2. 3. 4. 5. 6. 7. 8. ...
loss_decode=dict(# 解码头(decode_head)里的损失函数的配置项。type='CrossEntropyLoss',# 在分割里使用的损失函数的类别。use_sigmoid=False,# 在分割里是否使用 sigmoid 激活。loss_weight=1.0)),# 解码头里损失的权重。auxiliary_head=dict(type='FCNHead',# 辅助头(auxiliary head)的种类。可用选项请参考...
loss_decode=dict( type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)), # model training and testing settings train_cfg=dict(), test_cfg=dict(mode='whole')) 这个文件是网络架构配置,type 是用 register 注册过类,根据 type 可以找到对应的类,也可以自己定义模型后使用 Registor 进行注册...
losses_decode = [self.loss_decode] else: losses_decode = self.loss_decode loss = dict() for loss_decode in losses_decode: if 'loss_cls' in loss_decode.loss_name: if loss_decode.loss_name == 'loss_cls_ce': loss[loss_decode.loss_name] = loss_decode( ...
loss_decode=dict( loss_weight=0.4, type='CrossEntropyLoss', use_sigmoid=False), norm_cfg=dict(requires_grad=True, type='BN'), num_classes=6, num_convs=1, type='FCNHead'), backbone=dict( contract_dilation=True, depth=50, dilations=( ...
( type='FCNHead', in_channels=1024, in_index=2, channels=256, num_convs=1, concat_input=False, dropout_ratio=0.1, num_classes=150, norm_cfg=norm_cfg, align_corners=False, loss_decode=dict( type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)), # model training and testing...
loss_se_decode (dict): Config of decode loss. Default: dict(type='CrossEntropyLoss', use_sigmoid=True). """ def__init__(self, num_codes=32, use_se_loss=True, add_lateral=False, loss_se_decode=dict( type='CrossEntropyLoss', ...
mmseg apis core datasets models backbones decode_heads losses necks segmentors uda utils __init__.py builder.py ops utils __init__.py version.py resources tools .gitignore .pre-commit-config.yaml LICENSE LICENSES.md README.md experiments.py requirements.txt run_experiments.py setup.cfg test...
loss_decode=dict( type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)), dict( type='FCNHead', in_channels=32, channels=64, num_convs=2, num_classes=12, in_index=2, norm_cfg=norm_cfg, concat_input=False, align_corners=False, loss_decode=dict( type='CrossEntropyLoss', use...
loss_decode(dict): Config of loss type and some relevant additional options. dw_act_cfg (dict):Activation config of depthwise ConvModule. If it is 'default', it will be the same as `act_cfg`. Default: None. """ def __init__(self, dw_act_cfg=None, **kwargs): super()....