Update comments

own
Bobholamovic 2 years ago
parent 6c582195e2
commit 5dc93677ba
  1. 8
      paddlers/rs_models/cd/backbones/resnet.py
  2. 2
      paddlers/rs_models/cd/cdnet.py
  3. 8
      paddlers/rs_models/cd/changeformer.py
  4. 10
      paddlers/rs_models/cd/fccdn.py
  5. 20
      paddlers/rs_models/seg/farseg.py

@ -168,10 +168,12 @@ class ResNet(nn.Layer):
Args:
Block (BasicBlock|BottleneckBlock): block module of model.
depth (int): layers of resnet, default: 50.
num_classes (int): output dim of last fc layer. If num_classes <=0, last fc
depth (int): layers of resnet.
num_classes (int, optional): output dim of last fc layer. If num_classes <=0, last fc
layer will not be defined. Default: 1000.
with_pool (bool): use pool before the last fc layer or not. Default: True.
with_pool (bool, optional): use pool before the last fc layer or not. Default: True.
strides (tuple[int], optional): Strides to use in each stage. Default: (1, 1, 2, 2, 2).
norm_layer (nn.Layer|None): Type of normalization layer. Default: None.
Examples:
.. code-block:: python

@ -32,7 +32,7 @@ class CDNet(nn.Layer):
num_classes (int): Number of target classes.
"""
def __init__(self, in_channels=6, num_classes=2):
def __init__(self, in_channels, num_classes):
super(CDNet, self).__init__()
self.conv1 = Conv7x7(in_channels, 64, norm=True, act=True)
self.pool1 = nn.MaxPool2D(2, 2, return_mask=True)

@ -178,15 +178,15 @@ class ChangeFormer(nn.Layer):
(https://arxiv.org/pdf/2201.01293.pdf).
Args:
in_channels (int): Number of bands of the input images. Default: 3.
num_classes (int): Number of target classes. Default: 2.
in_channels (int): Number of bands of the input images.
num_classes (int): Number of target classes.
decoder_softmax (bool, optional): Use softmax after decode or not. Default: False.
embed_dim (int, optional): Embedding dimension of each decoder head. Default: 256.
"""
def __init__(self,
in_channels=3,
num_classes=2,
in_channels,
num_classes,
decoder_softmax=False,
embed_dim=256):
super(ChangeFormer, self).__init__()

@ -361,13 +361,13 @@ class FCCDN(nn.Layer):
(https://arxiv.org/pdf/2105.10860.pdf).
Args:
in_channels (int): Number of input channels. Default: 3.
num_classes (int): Number of target classes. Default: 2.
os (int): Number of output stride. Default: 16.
use_se (bool): Whether to use SEModule. Default: True.
in_channels (int): Number of input channels.
num_classes (int): Number of target classes.
os (int, optional): Number of output stride. Default: 16.
use_se (bool, optional): Whether to use SEModule. Default: True.
"""
def __init__(self, in_channels=3, num_classes=2, os=16, use_se=True):
def __init__(self, in_channels, num_classes, os=16, use_se=True):
super(FCCDN, self).__init__()
if os >= 16:
dilation_list = [1, 1, 1, 1]

@ -236,19 +236,19 @@ class FarSeg(nn.Layer):
and pattern recognition. 2020: 4096-4105.
Args:
in_channels (int): The number of image channels for the input model. Default: 3.
num_classes (int): The unique number of target classes. Default: 16.
backbone (str): A backbone network, models available in `paddle.vision.models.resnet`. Default: resnet50.
backbone_pretrained (bool): Whether the backbone network uses IMAGENET pretrained weights. Default: True.
fpn_out_channels (int): The number of channels output by the feature pyramid network. Default: 256.
fsr_out_channels (int): The number of channels output by the F-S relation module. Default: 256.
scale_aware_proj (bool): Whether to use scale awareness in F-S relation module. Default: True.
decoder_out_channels (int): The number of channels output by the decoder. Default: 128.
in_channels (int): Number of input channels.
num_classes (int): Unique number of target classes.
backbone (str, optional): Backbone network, one of models available in `paddle.vision.models.resnet`. Default: resnet50.
backbone_pretrained (bool, optional): Whether the backbone network uses IMAGENET pretrained weights. Default: True.
fpn_out_channels (int, optional): Number of channels output by the feature pyramid network. Default: 256.
fsr_out_channels (int, optional): Number of channels output by the F-S relation module. Default: 256.
scale_aware_proj (bool, optional): Whether to use scale awareness in F-S relation module. Default: True.
decoder_out_channels (int, optional): Number of channels output by the decoder. Default: 128.
"""
def __init__(self,
in_channels=3,
num_classes=16,
in_channels,
num_classes,
backbone='resnet50',
backbone_pretrained=True,
fpn_out_channels=256,

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