Comments (1)
Both can be, which determines the number of parameters and the representational power of the network
from swin-transformer-semantic-segmentation.
Related Issues (20)
- How to load pre-trained weights in classification into semantic segmentation
- How can I get the predict result of each pixel?
- How to convert pytorch to onnx? HOT 1
- key, val = kv.split('=', maxsplit=1) ValueError: not enough values to unpack (expected 2, got 1)
- where is get_started.md ? how to install the environment? HOT 4
- 如何将训练好的swin.pth文件转成tensortRT并进行推理,目标检测有这个脚本,分割没有该脚本嘛?
- question about the weight decay
- How to specify dataset path for training and validation
- 我有一个问题,紧急求助!
- KeyError: "EncoderDecoder: 'SwinTransformer is not in the backbone registry'",hope help
- Error:lib2to3.pgen2.parse.ParseError: bad input: type=20, value='<', context=('', (61, 4)) HOT 3
- I can not train swinTransformer on ADE datasets with multi-gpus
- size
- When will SwinV2 be supported for segmentation?
- remote sensing image HOT 1
- if the input and output file is 'png', 'tif' format, what do I need to modify? And what about 16bit file?
- The training results can not reach the author's effect HOT 1
- Training a model with a new dataset HOT 2
- Welcome update to OpenMMLab 2.0
- Why this Segmentation task related code,
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