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AOD-Net_最好加入后处理/test/test_template.prototxt

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+name:"DirectDehazing"
+input: "data"
+input_dim: 1
+input_dim: 3
+input_dim:{height}
+input_dim:{width}
+
+input: "label"
+input_dim: 1
+input_dim: 3
+input_dim:{height}
+input_dim:{width}
+
+
+layer {{
+  name: "conv1"
+  type: "Convolution"
+  bottom: "data"
+  top: "conv1"
+  convolution_param {{
+    num_output: 3
+    kernel_size: 1
+  }}
+}}
+
+layer {{
+   name: "relu1"
+   type: "ReLU"
+   bottom: "conv1"
+   top: "conv1"
+ }}
+
+ layer {{
+  name: "conv2"
+  type: "Convolution"
+  bottom: "conv1"
+  top: "conv2"
+  convolution_param {{
+    num_output: 3
+    kernel_size: 3
+    pad:1
+  }}
+}}
+
+layer {{
+   name: "relu2"
+   type: "ReLU"
+   bottom: "conv2"
+   top: "conv2"
+ }}
+
+layer {{
+  name: "Concat1"
+  type: "Concat"
+  bottom: "conv1"
+  bottom: "conv2"
+  top: "Concat1"
+  concat_param {{
+    axis: 1
+  }}
+}}
+
+ layer {{
+  name: "conv3"
+  type: "Convolution"
+  bottom: "Concat1"
+  top: "conv3"
+  convolution_param {{
+    num_output: 3
+    kernel_size: 5
+    pad:2
+  }}
+}}
+layer {{
+   name: "relu3"
+   type: "ReLU"
+   bottom: "conv3"
+   top: "conv3"
+ }}
+
+layer {{
+  name: "Concat2"
+  type: "Concat"
+  bottom: "conv2"
+  bottom: "conv3"
+  top: "Concat2"
+  concat_param {{
+    axis: 1
+  }}
+}}
+ layer {{
+  name: "conv4"
+  type: "Convolution"
+  bottom: "Concat2"
+  top: "conv4"
+  convolution_param {{
+    num_output: 3
+    kernel_size: 7
+    pad:3
+  }}
+}}
+layer {{
+   name: "relu4"
+   type: "ReLU"
+   bottom: "conv4"
+   top: "conv4"
+ }}
+ layer {{
+  name: "Concat3"
+  type: "Concat"
+  bottom: "conv1"
+  bottom: "conv2"
+  bottom: "conv3"
+  bottom: "conv4"
+  top: "Concat3"
+  concat_param {{
+    axis: 1
+  }}
+}}
+layer {{
+  name: "conv5"
+  type: "Convolution"
+  bottom: "Concat3"
+  top: "conv5"
+  convolution_param {{
+    num_output: 3
+    kernel_size: 3
+    pad:1
+  }}
+}}
+
+layer {{
+   name: "relu5"
+   type: "ReLU"
+   bottom: "conv5"
+   top: "K"
+ }}
+
+layer {{
+  name: "prod"
+  type: "Eltwise"
+  bottom: "data"
+  bottom: "K"
+  top: "prod"
+  eltwise_param {{
+    operation: PROD
+  }}
+}}
+
+layer {{
+ name:"eltwise_layer"
+ type:"Eltwise"
+ bottom:"prod"
+ bottom:"K"
+ top:"eltwise_layer"
+ eltwise_param{{
+   operation:SUM
+   coeff:1
+   coeff:-1
+ }}
+}}
+
+
+layer {{
+  name: "sum"
+  bottom: "eltwise_layer"
+  top: "sum"
+  type: "Power"
+  power_param {{
+    power: 1
+    scale: 1
+    shift: 1
+  }}
+}}
+layer {{
+   name: "clip"
+   type: "ReLU"
+   bottom: "sum"
+   top: "sum"
+ }}
+layer {{
+  name: "loss"
+  type: "EuclideanLoss"
+  bottom: "sum"
+  bottom: "label"
+  top: "loss"
+}}
+
+