|
1234567891011121314151617181920212223242526272829 |
- """High-Resolution Representations for Semantic Segmentation"""
- import torch
- import torch.nn as nn
- import torch.nn.functional as F
-
- class HRNet(nn.Module):
- """HRNet
-
- Parameters
- ----------
- nclass : int
- Number of categories for the training dataset.
- backbone : string
- Pre-trained dilated backbone network type (default:'resnet50'; 'resnet50',
- 'resnet101' or 'resnet152').
- norm_layer : object
- Normalization layer used in backbone network (default: :class:`nn.BatchNorm`;
- for Synchronized Cross-GPU BachNormalization).
- aux : bool
- Auxiliary loss.
- Reference:
- Ke Sun. "High-Resolution Representations for Labeling Pixels and Regions."
- arXiv preprint arXiv:1904.04514 (2019).
- """
- def __init__(self, nclass, backbone='', aux=False, pretrained_base=False, **kwargs):
- super(HRNet, self).__init__()
-
- def forward(self, x):
- pass
|