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