from .decode_head import BaseDecodeHead class MLPMaskDecoder(nn.Module): """Module for decoding query and visual features with MLP layers to generate the attention biases and the mask proposals.""" def __init__( self, *, in_channels: int, ...
class DPTHead(BaseDecodeHead): """Vision Transformers for Dense Prediction. This head is implemented of `DPT <https://arxiv.org/abs/2103.13413>`_. Args: embed_dims (int): The embed dimension of the ViT backbone. Default: 768. post_process_channels (List): Out channels of post proces...
| |--fixmatch_ours.py // 配置文件 mmcv_custom |--runner | |--__init__.py | |--custom_runner.py mmseg_custom |--datasets | |--pipelines | | |--__init__.py | | |--transform.py |--models | |--decode_heads | | |--uper_head_semi.py | |--segmentors | | |--encoder_...
decode_head=dict( type='FCNHead', in_channels=128, in_index=0, channels=1024, num_convs=1, concat_input=False, dropout_ratio=0.1, num_classes=12, norm_cfg=norm_cfg, align_corners=False, loss_decode=dict( type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)), auxiliary_head...
在模型的配置文件中,修改decode_head和auxiliary_head(如果存在)中的num_classes参数,使其与自定义数据集中的类别数一致。 使用MMSegmentation进行训练: 运行训练脚本(tools/train.py),并指定自定义的模型配置文件和数据集配置文件。 监控训练过程和结果,根据需要进行调整,如学习率、优化器等。 以下是一个简单的示例...
decode_head=dict( type='ASPPHead', in_channels=2048, in_index=3, channels=512, dilations=(1, 12, 24, 36), dropout_ratio=0.1, num_classes=150, norm_cfg=norm_cfg, align_corners=False, loss_decode=dict( type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)), auxiliary_head...
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) ...
decode_head=dict( align_corners=False, channels=512, dropout_ratio=0.1, in_channels=2048, in_index=3, loss_decode=dict( loss_weight=1.0, type='CrossEntropyLoss', use_sigmoid=False), norm_cfg=dict(requires_grad=True, type='BN'), ...
python tools/analysis_tools/visualization_cam.py'Pathto img''Pathto Config file''Pathto Checkpoint file'--out-file'Pathto output prediction file,如1.png'--cam-file'Pathto output cam file,如2.png'--target-layers'Targetlayers to visualize CAM,可参考log file,如decode_head.align.conv’--cate...
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...