53 lines
1.5 KiB
Python
53 lines
1.5 KiB
Python
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#!/usr/bin/env python
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# -*- coding: utf-8 -*-
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"""
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@project:
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@File : manet
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@Author : qiqq
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@create_time : 2023/9/17 16:46
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"""
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import torch
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from torch import nn
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import torch.nn.functional as F
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import numpy as np
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from taihuyuan_roof.manet.model.mit_backbone import mit_b1
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from taihuyuan_roof.manet.model.decoder import *
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class MitUnet(nn.Module):
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'''可以滚了...pv iou最高不到88.。怎么也得到90才可以啊'''
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def __init__(self,pretrained="/home/qiqq/q3dl/code/pretrain_weight/pretrained/segformer_mit/mit_b1.pth"):
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super(MitUnet, self).__init__()
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self.bacbone=mit_b1()
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self.bacbone.init_weights(pretrained)
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self.decoder=unetDecoder()
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def forward(self,x):
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feaureslist=self.bacbone(x)
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out =self.decoder(feaureslist)
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out= F.interpolate(out, size=x.size()[2:], mode='bilinear', align_corners=True)
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return out
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class MitCAB0Unet(nn.Module):
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def __init__(self,pretrained="/home/qiqq/q3dl/code/pretrain_weight/pretrained/segformer_mit/mit_b1.pth"):
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super(MitCAB0Unet, self).__init__()
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self.bacbone=mit_b1()
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self.bacbone.init_weights(pretrained)
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self.decoder=unetCAB0Decoder()
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def forward(self,x):
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feaureslist=self.bacbone(x)
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out =self.decoder(feaureslist)
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out= F.interpolate(out, size=x.size()[2:], mode='bilinear', align_corners=True)
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return out
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if __name__ == '__main__':
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inpp=torch.randn(2,3,512,512)
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model=MitCAB0Unet()
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out=model(inpp)
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