| 123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154155156157158159160161162163164165166167168169170171172173174175176177178179180181182183184185186187188 | 
							- name: "upconv_7"
 
- layer {
 
-   name: "input"
 
-   type: "Input"
 
-   top: "input"
 
-   input_param { shape: { dim: 1 dim: 3 dim: 142 dim: 142 } }
 
- }
 
- layer {
 
-   name: "conv1_layer"
 
-   type: "Convolution"
 
-   bottom: "input"
 
-   top: "conv1"
 
-   convolution_param {
 
-     num_output: 16
 
-     kernel_size: 3
 
-     stride: 1
 
-     weight_filler {
 
-       type: "gaussian"
 
-       std: 0.01
 
-     }
 
-   }
 
- }
 
- layer {
 
-   name: "conv1_relu_layer"
 
-   type: "ReLU"
 
-   bottom: "conv1"
 
-   top: "conv1"
 
-   relu_param {
 
-     negative_slope: 0.1
 
-   }
 
- }
 
- layer {
 
-   name: "conv2_layer"
 
-   type: "Convolution"
 
-   bottom: "conv1"
 
-   top: "conv2"
 
-   convolution_param {
 
-     num_output: 32
 
-     kernel_size: 3
 
-     stride: 1
 
-     weight_filler {
 
-       type: "gaussian"
 
-       std: 0.01
 
-     }
 
-   }
 
- }
 
- layer {
 
-   name: "conv2_relu_layer"
 
-   type: "ReLU"
 
-   bottom: "conv2"
 
-   top: "conv2"
 
-   relu_param {
 
-     negative_slope: 0.1
 
-   }
 
- }
 
- layer {
 
-   name: "conv3_layer"
 
-   type: "Convolution"
 
-   bottom: "conv2"
 
-   top: "conv3"
 
-   convolution_param {
 
-     num_output: 64
 
-     kernel_size: 3
 
-     stride: 1
 
-     weight_filler {
 
-       type: "gaussian"
 
-       std: 0.01
 
-     }
 
-   }
 
- }
 
- layer {
 
-   name: "conv3_relu_layer"
 
-   type: "ReLU"
 
-   bottom: "conv3"
 
-   top: "conv3"
 
-   relu_param {
 
-     negative_slope: 0.1
 
-   }
 
- }
 
- layer {
 
-   name: "conv4_layer"
 
-   type: "Convolution"
 
-   bottom: "conv3"
 
-   top: "conv4"
 
-   convolution_param {
 
-     num_output: 128
 
-     kernel_size: 3
 
-     stride: 1
 
-     weight_filler {
 
-       type: "gaussian"
 
-       std: 0.01
 
-     }
 
-   }
 
- }
 
- layer {
 
-   name: "conv4_relu_layer"
 
-   type: "ReLU"
 
-   bottom: "conv4"
 
-   top: "conv4"
 
-   relu_param {
 
-     negative_slope: 0.1
 
-   }
 
- }
 
- layer {
 
-   name: "conv5_layer"
 
-   type: "Convolution"
 
-   bottom: "conv4"
 
-   top: "conv5"
 
-   convolution_param {
 
-     num_output: 128
 
-     kernel_size: 3
 
-     stride: 1
 
-     weight_filler {
 
-       type: "gaussian"
 
-       std: 0.01
 
-     }
 
-   }
 
- }
 
- layer {
 
-   name: "conv5_relu_layer"
 
-   type: "ReLU"
 
-   bottom: "conv5"
 
-   top: "conv5"
 
-   relu_param {
 
-     negative_slope: 0.1
 
-   }
 
- }
 
- layer {
 
-   name: "conv6_layer"
 
-   type: "Convolution"
 
-   bottom: "conv5"
 
-   top: "conv6"
 
-   convolution_param {
 
-     num_output: 256
 
-     kernel_size: 3
 
-     stride: 1
 
-     weight_filler {
 
-       type: "gaussian"
 
-       std: 0.01
 
-     }
 
-   }
 
- }
 
- layer {
 
-   name: "conv6_relu_layer"
 
-   type: "ReLU"
 
-   bottom: "conv6"
 
-   top: "conv6"
 
-   relu_param {
 
-     negative_slope: 0.1
 
-   }
 
- }
 
- layer {
 
-   name: "conv7_layer"
 
-   type: "Deconvolution"
 
-   bottom: "conv6"
 
-   top: "conv7"
 
-   convolution_param {
 
-     num_output: 3
 
-     kernel_size: 4
 
-     stride: 2
 
-     pad: 3
 
-     weight_filler {
 
-       type: "gaussian"
 
-       std: 0.01
 
-     }
 
-   }
 
- }
 
- layer {
 
-   name: "target"
 
-   type: "MemoryData"
 
-   top: "target"
 
-   top: "dummy_label2"
 
-   memory_data_param {
 
-     batch_size: 1
 
-     channels: 3
 
-     height: 142
 
-     width: 142
 
-   }
 
-   include: { phase: TRAIN }
 
- }
 
- layer {
 
-   name: "loss"
 
-   type: "EuclideanLoss"
 
-   bottom: "conv7"
 
-   bottom: "target"
 
-   top: "loss"
 
-   include: { phase: TRAIN }
 
- }
 
 
  |