det2_relu.prototxt

name: "RNet"
layer
{
   name: "data"
   type: "Input"
   top:  "data"
   input_param{shape:{dim:1 dim:3 dim:24 dim:24}}
}

layer {
  name: "conv1"
  type: "Convolution"
  bottom: "data"
  top: "conv1"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  convolution_param {
    num_output: 28
    kernel_size: 3
    stride: 1
     weight_filler {
      type: "xavier"
	}
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu1_1"
  type: "ReLU"
  bottom: "conv1"
  top: "conv1_1"
  propagate_down: true
}

layer {
	name: "scale1_1"
	bottom: "conv1"
	top: "conv1_2"
	type: "Scale"
	scale_param {
		axis: 1
		bias_term:false
	}
}
layer {
  name: "ReLU1_2"
  type: "ReLU"
  bottom: "conv1_2"
  top: "conv1_2"
}
layer {
	name: "scale1_2"
	bottom: "conv1_2"
	top: "conv1_2"
	type: "Scale"
	scale_param {
		axis: 1
		bias_term:false
	}
}
layer {
  name: "eltwise-sum1"
  type: "Eltwise"
  bottom: "conv1_1"
  bottom: "conv1_2"
  top: "conv1_3"
  eltwise_param { operation: SUM }
}
layer {
  name: "pool1"
  type: "Pooling"
  bottom: "conv1_3"
  top: "pool1"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}

layer {
  name: "conv2"
  type: "Convolution"
  bottom: "pool1"
  top: "conv2"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  convolution_param {
    num_output: 48
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
	}
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu2_1"
  type: "ReLU"
  bottom: "conv2"
  top: "conv2_1"
  propagate_down: true
}

layer {
	name: "scale2_1"
	bottom: "conv2"
	top: "conv2_2"
	type: "Scale"
	scale_param {
		axis: 1
		bias_term:false
	}
}
layer {
  name: "ReLU2_2"
  type: "ReLU"
  bottom: "conv2_2"
  top: "conv2_2"
}
layer {
	name: "scale2_2"
	bottom: "conv2_2"
	top: "conv2_2"
	type: "Scale"
	scale_param {
		axis: 1
		bias_term:false
	}
}
layer {
  name: "eltwise-sum2"
  type: "Eltwise"
  bottom: "conv2_1"
  bottom: "conv2_2"
  top: "conv2_3"
  eltwise_param { operation: SUM }
}

layer {
  name: "pool2"
  type: "Pooling"
  bottom: "conv2_3"
  top: "pool2"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
####################################

##################################
layer {
  name: "conv3"
  type: "Convolution"
  bottom: "pool2"
  top: "conv3"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    kernel_size: 2
    stride: 1
    weight_filler {
      type: "xavier"
	}
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}

layer {
	name: "scale3_1"
	bottom: "conv3"
	top: "conv3_2"
	type: "Scale"
	scale_param {
		axis: 1
		bias_term:false
	}
}
layer {
  name: "ReLU3_2"
  type: "ReLU"
  bottom: "conv3_2"
  top: "conv3_2"
}
layer {
	name: "scale3_2"
	bottom: "conv3_2"
	top: "conv3_2"
	type: "Scale"
	scale_param {
		axis: 1
		bias_term:false
	}
}
layer {
  name: "relu3"
  type: "ReLU"
  bottom: "conv3"
  top: "conv3_1"
  propagate_down: true
}
layer {
  name: "eltwise-sum3"
  type: "Eltwise"
  bottom: "conv3_1"
  bottom: "conv3_2"
  top: "conv3_3"
  eltwise_param { operation: SUM }
}

###############################

###############################

layer {
  name: "conv4"
  type: "InnerProduct"
  bottom: "conv3_3"
  top: "conv4"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  inner_product_param {
    num_output: 128
    weight_filler {
      type: "xavier"
	}
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu4_1"
  type: "ReLU"
  bottom: "conv4"
  top: "conv4_1"
}

layer {
	name: "scale4_1"
	bottom: "conv4"
	top: "conv4_2"
	type: "Scale"
	scale_param {
		axis: 1
		bias_term:false
	}
}
layer {
  name: "ReLU4_2"
  type: "ReLU"
  bottom: "conv4_2"
  top: "conv4_2"
}
layer {
	name: "scale4_2"
	bottom: "conv4_2"
	top: "conv4_2"
	type: "Scale"
	scale_param {
		axis: 1
		bias_term:false
	}
}
layer {
  name: "eltwise-sum4"
  type: "Eltwise"
  bottom: "conv4_1"
  bottom: "conv4_2"
  top: "conv4_3"
  eltwise_param { operation: SUM }
}


layer {
  name: "conv5-1"
  type: "InnerProduct"
  bottom: "conv4_3"
  top: "conv5-1"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  inner_product_param {
    num_output: 2
    #kernel_size: 1
    #stride: 1
    weight_filler {
      type: "xavier"
	}
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "conv5-2"
  type: "InnerProduct"
  bottom: "conv4_3"
  top: "conv5-2"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 1
  }
  inner_product_param {
    num_output: 4
    #kernel_size: 1
    #stride: 1
     weight_filler {
      type: "xavier"
	}
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "prob1"
  type: "Softmax"
  bottom: "conv5-1"
  top: "prob1"
}