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39 lines
1.3 KiB
39 lines
1.3 KiB
import paddle.fluid as fluid
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from 口罩检测.ConvPool import ConvPool
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class VGGNet(fluid.dygraph.Layer):
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def __init__(self):
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super(VGGNet,self).__init__()
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#通道数，卷积核个数，卷积核大小，池化核大小，池化步长，连续卷积个数
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self.convpool01 = ConvPool(3,64,3,2,2,2,act='relu')
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self.convpool02 = ConvPool(64,128,3,2,2,2,act='relu')
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self.convpool03 = ConvPool(128,256,3,2,2,3,act='relu')
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self.convpool04 = ConvPool(256,512,3,2,2,3,act='relu')
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self.convpool05 = ConvPool(512,512,3,2,2,3,act='relu')
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self.pool5_shape = 512*7*7
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self.fc01 = fluid.dygraph.Linear(self.pool5_shape,4096,act='relu')
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self.fc02 =fluid.dygraph.Linear(4096,4096,act='relu')
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self.fc03= fluid.dygraph.Linear(4096,2,act='softmax')
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def forward(self, input,label=None):
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x= self.convpool01(input)
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x= self.convpool02(x)
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x = self.convpool03(x)
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x= self.convpool04(x)
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x = self.convpool05(x)
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result =fluid.layers.reshape(x,shape=[-1,512*7*7])
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out = self.fc01(result)
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out = self.fc02(out)
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out = self.fc03(out)
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if label is not None:
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acc = fluid.layers.accuracy(input =out,label=label)
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return out,acc
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else:
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return out |