name: "skeleton_mask_320x240"
input: "image"
input_dim: 1
input_dim: 3
input_dim: 240
input_dim: 320
##############################################all the same###############################################

layer {
    bottom: "image"
    top: "conv1"
    name: "conv1"
    type: "Convolution"

	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }

    convolution_param {
        num_output: 32
        kernel_size: 7
        pad: 3
        stride: 2
        weight_filler {
            type: "msra"
        }
        bias_term: false

    }
}


layer {
    bottom: "conv1"
    top: "conv1"
    name: "conv1_relu"
    type: "ReLU"
}



layer {
  name: "res1a_branch1_1x1"
  type: "Convolution"
  bottom: "conv1"
  top: "res1a_branch1_1x1"
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }

  convolution_param {
    num_output: 16
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}

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

layer {
    bottom: "res1a_branch1_1x1"
    top: "res1a_branch1"
    name: "res1a_branch1"
    type: "Convolution"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
    convolution_param {
        num_output: 32
        kernel_size: 1
        pad: 0
        stride: 2
        weight_filler {
            type: "msra"
        }
        bias_term: false

    }
}


layer {
    bottom: "res1a_branch1"
    top: "res1a_branch1"
    name: "bn1a_branch1"
    type: "BatchNorm"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
    batch_norm_param {
      moving_average_fraction: 0.9 
	use_global_stats: true
    }
    
}

layer {
    bottom: "res1a_branch1"
    top: "res1a_branch1"
    name: "scale1a_branch1"
    type: "Scale"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
    scale_param {
        bias_term: true
    }
}

###############1x1###############
layer {
  name: "res1a_branch2_1x1"
  type: "Convolution"
  bottom: "conv1"
  top: "res1a_branch2_1x1"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
  convolution_param {
    num_output: 16
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}

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


layer {
    bottom: "res1a_branch2_1x1"
    top: "res1a_branch2a"
    name: "res1a_branch2a"
    type: "Convolution"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
    convolution_param {
        num_output: 32
        kernel_size: 3
        pad: 1
        stride: 2
        weight_filler {
            type: "msra"
        }
        bias_term: false

    }
}

layer {
    bottom: "res1a_branch2a"
    top: "res1a_branch2a"
    name: "bn1a_branch2a"
    type: "BatchNorm"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
    batch_norm_param {
      moving_average_fraction: 0.9 
	use_global_stats: true
    }
    
}

layer {
    bottom: "res1a_branch2a"
    top: "res1a_branch2a"
    name: "scale1a_branch2a"
    type: "Scale"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
    scale_param {
        bias_term: true
    }
}

layer {
    bottom: "res1a_branch2a"
    top: "res1a_branch2a"
    name: "res1a_branch2a_relu"
    type: "ReLU"
}

layer {
    bottom: "res1a_branch2a"
    top: "res1a_branch2b"
    name: "res1a_branch2b"
    type: "Convolution"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
    convolution_param {
        num_output: 32
        kernel_size: 3
        pad: 1
        stride: 1
        weight_filler {
            type: "msra"
        }
        bias_term: false

    }
}

layer {
    bottom: "res1a_branch2b"
    top: "res1a_branch2b"
    name: "bn1a_branch2b"
    type: "BatchNorm"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
    batch_norm_param {
      moving_average_fraction: 0.9 
	use_global_stats: true
    }
    
}

layer {
    bottom: "res1a_branch2b"
    top: "res1a_branch2b"
    name: "scale1a_branch2b"
    type: "Scale"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
    scale_param {
        bias_term: true
    }
}

layer {
    bottom: "res1a_branch1"
    bottom: "res1a_branch2b"
    top: "res1a"
    name: "res1a"
    type: "Eltwise"
    eltwise_param {
        operation: SUM
    }
}

layer {
    bottom: "res1a"
    top: "res1a"
    name: "res1a_relu"
    type: "ReLU"
}


################end#######################
###############1x1###############
layer {
  name: "res2a_branch1_1x1"
  type: "Convolution"
  bottom: "res1a"
  top: "res2a_branch1_1x1"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
  convolution_param {
    num_output: 16
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
###############################




layer {
    bottom: "res2a_branch1_1x1"
    top: "res2a_branch1"
    name: "res2a_branch1"
    type: "Convolution"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
    convolution_param {
        num_output: 32
        kernel_size: 1
        pad: 0
        stride: 1
        weight_filler {
            type: "msra"
        }
        bias_term: false

    }
}


layer {
    bottom: "res2a_branch1"
    top: "res2a_branch1"
    name: "bn2a_branch1"
    type: "BatchNorm"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
    batch_norm_param {
      moving_average_fraction: 0.9 
	use_global_stats: true
    }
    
}

layer {
    bottom: "res2a_branch1"
    top: "res2a_branch1"
    name: "scale2a_branch1"
    type: "Scale"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
    scale_param {
        bias_term: true
    }
}



###############1x1###############
layer {
  name: "res2a_branch2_1x1"
  type: "Convolution"
  bottom: "res1a"
  top: "res2a_branch2_1x1"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
  convolution_param {
    num_output: 16
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
###############################

layer {
    bottom: "res2a_branch2_1x1"
    top: "res2a_branch2a"
    name: "res2a_branch2a"
    type: "Convolution"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
    convolution_param {
        num_output: 32
        kernel_size: 3
        pad: 1
        stride: 1
        weight_filler {
            type: "msra"
        }
        bias_term: false

    }
}

layer {
    bottom: "res2a_branch2a"
    top: "res2a_branch2a"
    name: "bn2a_branch2a"
    type: "BatchNorm"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
    batch_norm_param {
      moving_average_fraction: 0.9 
	use_global_stats: true
    }
    
}

layer {
    bottom: "res2a_branch2a"
    top: "res2a_branch2a"
    name: "scale2a_branch2a"
    type: "Scale"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
    scale_param {
        bias_term: true
    }
}

layer {
    bottom: "res2a_branch2a"
    top: "res2a_branch2a"
    name: "res2a_branch2a_relu"
    type: "ReLU"
}



layer {
    bottom: "res2a_branch2a"
    top: "res2a_branch2b"
    name: "res2a_branch2b"
    type: "Convolution"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
    convolution_param {
        num_output: 32
        kernel_size: 3
        pad: 1
        stride: 1
        weight_filler {
            type: "msra"
        }
        bias_term: false

    }
}

layer {
    bottom: "res2a_branch2b"
    top: "res2a_branch2b"
    name: "bn2a_branch2b"
    type: "BatchNorm"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
    batch_norm_param {
      moving_average_fraction: 0.9 
	use_global_stats: true
    }
    
}

layer {
    bottom: "res2a_branch2b"
    top: "res2a_branch2b"
    name: "scale2a_branch2b"
    type: "Scale"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
    scale_param {
        bias_term: true
    }
}

layer {
    bottom: "res2a_branch1"
    bottom: "res2a_branch2b"
    top: "res2a"
    name: "res2a"
    type: "Eltwise"
    eltwise_param {
        operation: SUM
    }
}

layer {
    bottom: "res2a"
    top: "res2a"
    name: "res2a_relu"
    type: "ReLU"
}


###############1x1###############
layer {
  name: "res2b_branch2a_1x1"
  type: "Convolution"
  bottom: "res2a"
  top: "res2b_branch2a_1x1"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
  convolution_param {
    num_output: 16
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
###############################


layer {
    bottom: "res2b_branch2a_1x1"
    top: "res2b_branch2a"
    name: "res2b_branch2a"
    type: "Convolution"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
    convolution_param {
        num_output: 32
        kernel_size: 3
        pad: 1
        stride: 1
        weight_filler {
            type: "msra"
        }
        bias_term: false

    }
}

layer {
    bottom: "res2b_branch2a"
    top: "res2b_branch2a"
    name: "bn2b_branch2a"
    type: "BatchNorm"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
    batch_norm_param {
      moving_average_fraction: 0.9 
	use_global_stats: true
    }
    
}

layer {
    bottom: "res2b_branch2a"
    top: "res2b_branch2a"
    name: "scale2b_branch2a"
    type: "Scale"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
    scale_param {
        bias_term: true
    }
}

layer {
    bottom: "res2b_branch2a"
    top: "res2b_branch2a"
    name: "res2b_branch2a_relu"
    type: "ReLU"
}

layer {
    bottom: "res2b_branch2a"
    top: "res2b_branch2b"
    name: "res2b_branch2b"
    type: "Convolution"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
    convolution_param {
        num_output: 32
        kernel_size: 3
        pad: 1
        stride: 1
        weight_filler {
            type: "msra"
        }
        bias_term: false

    }
}

layer {
    bottom: "res2b_branch2b"
    top: "res2b_branch2b"
    name: "bn2b_branch2b"
    type: "BatchNorm"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
    batch_norm_param {
      moving_average_fraction: 0.9 
	use_global_stats: true
    }
    
}

layer {
    bottom: "res2b_branch2b"
    top: "res2b_branch2b"
    name: "scale2b_branch2b"
    type: "Scale"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
    scale_param {
        bias_term: true
    }
}

layer {
    bottom: "res2a"
    bottom: "res2b_branch2b"
    top: "res2b"
    name: "res2b"
    type: "Eltwise"
    eltwise_param {
        operation: SUM
    }
}

layer {
    bottom: "res2b"
    top: "res2b"
    name: "res2b_relu"
    type: "ReLU"
}

###############1x1###############
layer {
  name: "res3a_branch1_1x1"
  type: "Convolution"
  bottom: "res2b"
  top: "res3a_branch1_1x1"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
  convolution_param {
    num_output: 32
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
###############################

layer {
    bottom: "res3a_branch1_1x1"
    top: "res3a_branch1"
    name: "res3a_branch1"
    type: "Convolution"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
    convolution_param {
        num_output: 64
        kernel_size: 1
        pad: 0
        stride: 2
        weight_filler {
            type: "msra"
        }
        bias_term: false

    }
}

layer {
    bottom: "res3a_branch1"
    top: "res3a_branch1"
    name: "bn3a_branch1"
    type: "BatchNorm"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
    batch_norm_param {
      moving_average_fraction: 0.9 
	use_global_stats: true
    }
    
}

layer {
    bottom: "res3a_branch1"
    top: "res3a_branch1"
    name: "scale3a_branch1"
    type: "Scale"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
    scale_param {
        bias_term: true
    }
}

###############1x1###############
layer {
  name: "res3a_branch2a_1x1"
  type: "Convolution"
  bottom: "res2b"
  top: "res3a_branch2a_1x1"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
  convolution_param {
    num_output: 32
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
###############################

layer {
    bottom: "res3a_branch2a_1x1"
    top: "res3a_branch2a"
    name: "res3a_branch2a"
    type: "Convolution"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
    convolution_param {
        num_output: 64
        kernel_size: 3
        pad: 1
        stride: 2
        weight_filler {
            type: "msra"
        }
        bias_term: false

    }
}

layer {
    bottom: "res3a_branch2a"
    top: "res3a_branch2a"
    name: "bn3a_branch2a"
    type: "BatchNorm"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
    batch_norm_param {
      moving_average_fraction: 0.9 
	use_global_stats: true
    }
    
}

layer {
    bottom: "res3a_branch2a"
    top: "res3a_branch2a"
    name: "scale3a_branch2a"
    type: "Scale"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
    scale_param {
        bias_term: true
    }
}

layer {
    bottom: "res3a_branch2a"
    top: "res3a_branch2a"
    name: "res3a_branch2a_relu"
    type: "ReLU"
}

layer {
    bottom: "res3a_branch2a"
    top: "res3a_branch2b"
    name: "res3a_branch2b"
    type: "Convolution"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
    convolution_param {
        num_output: 64
        kernel_size: 3
        pad: 1
        stride: 1
        weight_filler {
            type: "msra"
        }
        bias_term: false

    }
}

layer {
    bottom: "res3a_branch2b"
    top: "res3a_branch2b"
    name: "bn3a_branch2b"
    type: "BatchNorm"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
    batch_norm_param {
      moving_average_fraction: 0.9 
	use_global_stats: true
    }
    
}

layer {
    bottom: "res3a_branch2b"
    top: "res3a_branch2b"
    name: "scale3a_branch2b"
    type: "Scale"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
    scale_param {
        bias_term: true
    }
}

layer {
    bottom: "res3a_branch1"
    bottom: "res3a_branch2b"
    top: "res3a"
    name: "res3a"
    type: "Eltwise"
    eltwise_param {
        operation: SUM
    }
}

layer {
    bottom: "res3a"
    top: "res3a"
    name: "res3a_relu"
    type: "ReLU"
}

###############1x1###############
layer {
  name: "res3b_branch2a_1x1"
  type: "Convolution"
  bottom: "res3a"
  top: "res3b_branch2a_1x1"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
  convolution_param {
    num_output: 32
    bias_term: false
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
###############################

layer {
    bottom: "res3b_branch2a_1x1"
    top: "res3b_branch2a"
    name: "res3b_branch2a"
    type: "Convolution"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
    convolution_param {
        num_output: 64
        kernel_size: 3
        pad: 1
        stride: 1
        weight_filler {
            type: "msra"
        }
        bias_term: false

    }
}

layer {
    bottom: "res3b_branch2a"
    top: "res3b_branch2a"
    name: "bn3b_branch2a"
    type: "BatchNorm"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
    batch_norm_param {
      moving_average_fraction: 0.9 
	use_global_stats: true
    }
    
}

layer {
    bottom: "res3b_branch2a"
    top: "res3b_branch2a"
    name: "scale3b_branch2a"
    type: "Scale"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
    scale_param {
        bias_term: true
    }
}

layer {
    bottom: "res3b_branch2a"
    top: "res3b_branch2a"
    name: "res3b_branch2a_relu"
    type: "ReLU"
}

layer {
    bottom: "res3b_branch2a"
    top: "res3b_branch2b"
    name: "res3b_branch2b"
    type: "Convolution"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
    convolution_param {
        num_output: 64
        kernel_size: 3
        pad: 1
        stride: 1
        weight_filler {
            type: "msra"
        }
        bias_term: false

    }
}

layer {
    bottom: "res3b_branch2b"
    top: "res3b_branch2b"
    name: "bn3b_branch2b"
    type: "BatchNorm"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
    batch_norm_param {
      moving_average_fraction: 0.9 
	use_global_stats: true
    }
    
}

layer {
    bottom: "res3b_branch2b"
    top: "res3b_branch2b"
    name: "scale3b_branch2b"
    type: "Scale"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
    scale_param {
        bias_term: true
    }
}

layer {
    bottom: "res3a"
    bottom: "res3b_branch2b"
    top: "res3b"
    name: "res3b"
    type: "Eltwise"
    eltwise_param {
        operation: SUM
    }
}

layer {
    bottom: "res3b"
    top: "res3b"
    name: "res3b_relu"
    type: "ReLU"
}









######################################################all the same###############################################
layer {
  name: "conv4_3_CPM"
  type: "Convolution"
  bottom: "res3b"
  top: "conv4_3_CPM"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
  convolution_param {
    num_output: 256
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "relu4_3_CPM"
  type: "ReLU"
  bottom: "conv4_3_CPM"
  top: "conv4_3_CPM"
}
layer {
  name: "conv4_4_CPM"
  type: "Convolution"
  bottom: "conv4_3_CPM"
  top: "conv4_4_CPM"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "relu4_4_CPM"
  type: "ReLU"
  bottom: "conv4_4_CPM"
  top: "conv4_4_CPM"
}
layer {
  name: "conv5_1_CPM_L1"
  type: "Convolution"
  bottom: "conv4_4_CPM"
  top: "conv5_1_CPM_L1"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "relu5_1_CPM_L1"
  type: "ReLU"
  bottom: "conv5_1_CPM_L1"
  top: "conv5_1_CPM_L1"
}
layer {
  name: "conv5_1_CPM_L2"
  type: "Convolution"
  bottom: "conv4_4_CPM"
  top: "conv5_1_CPM_L2"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "relu5_1_CPM_L2"
  type: "ReLU"
  bottom: "conv5_1_CPM_L2"
  top: "conv5_1_CPM_L2"
}
layer {
  name: "conv5_2_CPM_L1"
  type: "Convolution"
  bottom: "conv5_1_CPM_L1"
  top: "conv5_2_CPM_L1"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "relu5_2_CPM_L1"
  type: "ReLU"
  bottom: "conv5_2_CPM_L1"
  top: "conv5_2_CPM_L1"
}
layer {
  name: "conv5_2_CPM_L2"
  type: "Convolution"
  bottom: "conv5_1_CPM_L2"
  top: "conv5_2_CPM_L2"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "relu5_2_CPM_L2"
  type: "ReLU"
  bottom: "conv5_2_CPM_L2"
  top: "conv5_2_CPM_L2"
}
layer {
  name: "conv5_3_CPM_L1"
  type: "Convolution"
  bottom: "conv5_2_CPM_L1"
  top: "conv5_3_CPM_L1"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "relu5_3_CPM_L1"
  type: "ReLU"
  bottom: "conv5_3_CPM_L1"
  top: "conv5_3_CPM_L1"
}
layer {
  name: "conv5_3_CPM_L2"
  type: "Convolution"
  bottom: "conv5_2_CPM_L2"
  top: "conv5_3_CPM_L2"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "relu5_3_CPM_L2"
  type: "ReLU"
  bottom: "conv5_3_CPM_L2"
  top: "conv5_3_CPM_L2"
}
layer {
  name: "conv5_4_CPM_L1"
  type: "Convolution"
  bottom: "conv5_3_CPM_L1"
  top: "conv5_4_CPM_L1"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
  convolution_param {
    num_output: 512
    pad: 0
    kernel_size: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "relu5_4_CPM_L1"
  type: "ReLU"
  bottom: "conv5_4_CPM_L1"
  top: "conv5_4_CPM_L1"
}
layer {
  name: "conv5_4_CPM_L2"
  type: "Convolution"
  bottom: "conv5_3_CPM_L2"
  top: "conv5_4_CPM_L2"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
  convolution_param {
    num_output: 512
    pad: 0
    kernel_size: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "relu5_4_CPM_L2"
  type: "ReLU"
  bottom: "conv5_4_CPM_L2"
  top: "conv5_4_CPM_L2"
}
layer {
  name: "conv5_5_CPM_L1"
  type: "Convolution"
  bottom: "conv5_4_CPM_L1"
  top: "conv5_5_CPM_L1"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
  convolution_param {
    num_output: 32
    pad: 0
    kernel_size: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "conv5_5_CPM_L2"
  type: "Convolution"
  bottom: "conv5_4_CPM_L2"
  top: "conv5_5_CPM_L2"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
  convolution_param {
    num_output: 16
    pad: 0
    kernel_size: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}


layer {
  name: "concat_stage2"
  type: "Concat"
  bottom: "conv5_5_CPM_L1"
  bottom: "conv5_5_CPM_L2"
  bottom: "conv4_4_CPM"
  top: "concat_stage2"
  concat_param {
    axis: 1
  }
}
layer {
  name: "Mconv1_stage2_L1"
  type: "Convolution"
  bottom: "concat_stage2"
  top: "Mconv1_stage2_L1"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "Mrelu1_stage2_L1"
  type: "ReLU"
  bottom: "Mconv1_stage2_L1"
  top: "Mconv1_stage2_L1"
}
layer {
  name: "Mconv1_stage2_L2"
  type: "Convolution"
  bottom: "concat_stage2"
  top: "Mconv1_stage2_L2"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "Mrelu1_stage2_L2"
  type: "ReLU"
  bottom: "Mconv1_stage2_L2"
  top: "Mconv1_stage2_L2"
}
layer {
  name: "Mconv2_stage2_L1"
  type: "Convolution"
  bottom: "Mconv1_stage2_L1"
  top: "Mconv2_stage2_L1"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "Mrelu2_stage2_L1"
  type: "ReLU"
  bottom: "Mconv2_stage2_L1"
  top: "Mconv2_stage2_L1"
}
layer {
  name: "Mconv2_stage2_L2"
  type: "Convolution"
  bottom: "Mconv1_stage2_L2"
  top: "Mconv2_stage2_L2"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "Mrelu2_stage2_L2"
  type: "ReLU"
  bottom: "Mconv2_stage2_L2"
  top: "Mconv2_stage2_L2"
}
layer {
  name: "Mconv3_stage2_L1"
  type: "Convolution"
  bottom: "Mconv2_stage2_L1"
  top: "Mconv3_stage2_L1"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "Mrelu3_stage2_L1"
  type: "ReLU"
  bottom: "Mconv3_stage2_L1"
  top: "Mconv3_stage2_L1"
}
layer {
  name: "Mconv3_stage2_L2"
  type: "Convolution"
  bottom: "Mconv2_stage2_L2"
  top: "Mconv3_stage2_L2"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "Mrelu3_stage2_L2"
  type: "ReLU"
  bottom: "Mconv3_stage2_L2"
  top: "Mconv3_stage2_L2"
}
layer {
  name: "Mconv4_stage2_L1"
  type: "Convolution"
  bottom: "Mconv3_stage2_L1"
  top: "Mconv4_stage2_L1"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "Mrelu4_stage2_L1"
  type: "ReLU"
  bottom: "Mconv4_stage2_L1"
  top: "Mconv4_stage2_L1"
}
layer {
  name: "Mconv4_stage2_L2"
  type: "Convolution"
  bottom: "Mconv3_stage2_L2"
  top: "Mconv4_stage2_L2"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "Mrelu4_stage2_L2"
  type: "ReLU"
  bottom: "Mconv4_stage2_L2"
  top: "Mconv4_stage2_L2"
}
layer {
  name: "Mconv5_stage2_L1"
  type: "Convolution"
  bottom: "Mconv4_stage2_L1"
  top: "Mconv5_stage2_L1"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "Mrelu5_stage2_L1"
  type: "ReLU"
  bottom: "Mconv5_stage2_L1"
  top: "Mconv5_stage2_L1"
}
layer {
  name: "Mconv5_stage2_L2"
  type: "Convolution"
  bottom: "Mconv4_stage2_L2"
  top: "Mconv5_stage2_L2"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "Mrelu5_stage2_L2"
  type: "ReLU"
  bottom: "Mconv5_stage2_L2"
  top: "Mconv5_stage2_L2"
}
layer {
  name: "Mconv6_stage2_L1"
  type: "Convolution"
  bottom: "Mconv5_stage2_L1"
  top: "Mconv6_stage2_L1"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
  convolution_param {
    num_output: 64
    pad: 0
    kernel_size: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "Mrelu6_stage2_L1"
  type: "ReLU"
  bottom: "Mconv6_stage2_L1"
  top: "Mconv6_stage2_L1"
}
layer {
  name: "Mconv6_stage2_L2"
  type: "Convolution"
  bottom: "Mconv5_stage2_L2"
  top: "Mconv6_stage2_L2"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
  convolution_param {
    num_output: 64
    pad: 0
    kernel_size: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "Mrelu6_stage2_L2"
  type: "ReLU"
  bottom: "Mconv6_stage2_L2"
  top: "Mconv6_stage2_L2"
}
layer {
  name: "Mconv7_stage2_L1"
  type: "Convolution"
  bottom: "Mconv6_stage2_L1"
  top: "Mconv7_stage2_L1"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
  convolution_param {
    num_output: 32
    pad: 0
    kernel_size: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "Mconv7_stage2_L2"
  type: "Convolution"
  bottom: "Mconv6_stage2_L2"
  top: "Mconv7_stage2_L2"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
  convolution_param {
    num_output: 16
    pad: 0
    kernel_size: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}



layer {
  name: "concat_stage3"
  type: "Concat"
  bottom: "Mconv7_stage2_L1"
  bottom: "Mconv7_stage2_L2"
  bottom: "conv4_4_CPM"
  top: "concat_stage3"
  concat_param {
    axis: 1
  }
}
layer {
  name: "Mconv1_stage3_L1"
  type: "Convolution"
  bottom: "concat_stage3"
  top: "Mconv1_stage3_L1"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "Mrelu1_stage3_L1"
  type: "ReLU"
  bottom: "Mconv1_stage3_L1"
  top: "Mconv1_stage3_L1"
}
layer {
  name: "Mconv1_stage3_L2"
  type: "Convolution"
  bottom: "concat_stage3"
  top: "Mconv1_stage3_L2"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "Mrelu1_stage3_L2"
  type: "ReLU"
  bottom: "Mconv1_stage3_L2"
  top: "Mconv1_stage3_L2"
}
layer {
  name: "Mconv2_stage3_L1"
  type: "Convolution"
  bottom: "Mconv1_stage3_L1"
  top: "Mconv2_stage3_L1"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "Mrelu2_stage3_L1"
  type: "ReLU"
  bottom: "Mconv2_stage3_L1"
  top: "Mconv2_stage3_L1"
}
layer {
  name: "Mconv2_stage3_L2"
  type: "Convolution"
  bottom: "Mconv1_stage3_L2"
  top: "Mconv2_stage3_L2"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "Mrelu2_stage3_L2"
  type: "ReLU"
  bottom: "Mconv2_stage3_L2"
  top: "Mconv2_stage3_L2"
}
layer {
  name: "Mconv3_stage3_L1"
  type: "Convolution"
  bottom: "Mconv2_stage3_L1"
  top: "Mconv3_stage3_L1"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "Mrelu3_stage3_L1"
  type: "ReLU"
  bottom: "Mconv3_stage3_L1"
  top: "Mconv3_stage3_L1"
}
layer {
  name: "Mconv3_stage3_L2"
  type: "Convolution"
  bottom: "Mconv2_stage3_L2"
  top: "Mconv3_stage3_L2"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "Mrelu3_stage3_L2"
  type: "ReLU"
  bottom: "Mconv3_stage3_L2"
  top: "Mconv3_stage3_L2"
}
layer {
  name: "Mconv4_stage3_L1"
  type: "Convolution"
  bottom: "Mconv3_stage3_L1"
  top: "Mconv4_stage3_L1"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "Mrelu4_stage3_L1"
  type: "ReLU"
  bottom: "Mconv4_stage3_L1"
  top: "Mconv4_stage3_L1"
}
layer {
  name: "Mconv4_stage3_L2"
  type: "Convolution"
  bottom: "Mconv3_stage3_L2"
  top: "Mconv4_stage3_L2"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "Mrelu4_stage3_L2"
  type: "ReLU"
  bottom: "Mconv4_stage3_L2"
  top: "Mconv4_stage3_L2"
}
layer {
  name: "Mconv5_stage3_L1"
  type: "Convolution"
  bottom: "Mconv4_stage3_L1"
  top: "Mconv5_stage3_L1"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "Mrelu5_stage3_L1"
  type: "ReLU"
  bottom: "Mconv5_stage3_L1"
  top: "Mconv5_stage3_L1"
}
layer {
  name: "Mconv5_stage3_L2"
  type: "Convolution"
  bottom: "Mconv4_stage3_L2"
  top: "Mconv5_stage3_L2"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "Mrelu5_stage3_L2"
  type: "ReLU"
  bottom: "Mconv5_stage3_L2"
  top: "Mconv5_stage3_L2"
}
layer {
  name: "Mconv6_stage3_L1"
  type: "Convolution"
  bottom: "Mconv5_stage3_L1"
  top: "Mconv6_stage3_L1"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
  convolution_param {
    num_output: 64
    pad: 0
    kernel_size: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "Mrelu6_stage3_L1"
  type: "ReLU"
  bottom: "Mconv6_stage3_L1"
  top: "Mconv6_stage3_L1"
}
layer {
  name: "Mconv6_stage3_L2"
  type: "Convolution"
  bottom: "Mconv5_stage3_L2"
  top: "Mconv6_stage3_L2"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
  convolution_param {
    num_output: 64
    pad: 0
    kernel_size: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "Mrelu6_stage3_L2"
  type: "ReLU"
  bottom: "Mconv6_stage3_L2"
  top: "Mconv6_stage3_L2"
}
layer {
  name: "Mconv7_stage3_L1"
  type: "Convolution"
  bottom: "Mconv6_stage3_L1"
  top: "Mconv7_stage3_L1"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
  convolution_param {
    num_output: 32
    pad: 0
    kernel_size: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "Mconv7_stage3_L2"
  type: "Convolution"
  bottom: "Mconv6_stage3_L2"
  top: "Mconv7_stage3_L2"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
  convolution_param {
    num_output: 16
    pad: 0
    kernel_size: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}




layer {
  name: "concat_stage4"
  type: "Concat"
  bottom: "Mconv7_stage3_L1"
  bottom: "Mconv7_stage3_L2"
  bottom: "conv4_4_CPM"
  top: "concat_stage4"
  concat_param {
    axis: 1
  }
}
layer {
  name: "Mconv1_stage4_L1"
  type: "Convolution"
  bottom: "concat_stage4"
  top: "Mconv1_stage4_L1"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "Mrelu1_stage4_L1"
  type: "ReLU"
  bottom: "Mconv1_stage4_L1"
  top: "Mconv1_stage4_L1"
}
layer {
  name: "Mconv1_stage4_L2"
  type: "Convolution"
  bottom: "concat_stage4"
  top: "Mconv1_stage4_L2"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "Mrelu1_stage4_L2"
  type: "ReLU"
  bottom: "Mconv1_stage4_L2"
  top: "Mconv1_stage4_L2"
}
layer {
  name: "Mconv2_stage4_L1"
  type: "Convolution"
  bottom: "Mconv1_stage4_L1"
  top: "Mconv2_stage4_L1"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "Mrelu2_stage4_L1"
  type: "ReLU"
  bottom: "Mconv2_stage4_L1"
  top: "Mconv2_stage4_L1"
}
layer {
  name: "Mconv2_stage4_L2"
  type: "Convolution"
  bottom: "Mconv1_stage4_L2"
  top: "Mconv2_stage4_L2"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "Mrelu2_stage4_L2"
  type: "ReLU"
  bottom: "Mconv2_stage4_L2"
  top: "Mconv2_stage4_L2"
}
layer {
  name: "Mconv3_stage4_L1"
  type: "Convolution"
  bottom: "Mconv2_stage4_L1"
  top: "Mconv3_stage4_L1"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "Mrelu3_stage4_L1"
  type: "ReLU"
  bottom: "Mconv3_stage4_L1"
  top: "Mconv3_stage4_L1"
}
layer {
  name: "Mconv3_stage4_L2"
  type: "Convolution"
  bottom: "Mconv2_stage4_L2"
  top: "Mconv3_stage4_L2"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "Mrelu3_stage4_L2"
  type: "ReLU"
  bottom: "Mconv3_stage4_L2"
  top: "Mconv3_stage4_L2"
}
layer {
  name: "Mconv4_stage4_L1"
  type: "Convolution"
  bottom: "Mconv3_stage4_L1"
  top: "Mconv4_stage4_L1"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "Mrelu4_stage4_L1"
  type: "ReLU"
  bottom: "Mconv4_stage4_L1"
  top: "Mconv4_stage4_L1"
}
layer {
  name: "Mconv4_stage4_L2"
  type: "Convolution"
  bottom: "Mconv3_stage4_L2"
  top: "Mconv4_stage4_L2"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "Mrelu4_stage4_L2"
  type: "ReLU"
  bottom: "Mconv4_stage4_L2"
  top: "Mconv4_stage4_L2"
}
layer {
  name: "Mconv5_stage4_L1"
  type: "Convolution"
  bottom: "Mconv4_stage4_L1"
  top: "Mconv5_stage4_L1"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "Mrelu5_stage4_L1"
  type: "ReLU"
  bottom: "Mconv5_stage4_L1"
  top: "Mconv5_stage4_L1"
}
layer {
  name: "Mconv5_stage4_L2"
  type: "Convolution"
  bottom: "Mconv4_stage4_L2"
  top: "Mconv5_stage4_L2"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "Mrelu5_stage4_L2"
  type: "ReLU"
  bottom: "Mconv5_stage4_L2"
  top: "Mconv5_stage4_L2"
}
layer {
  name: "Mconv6_stage4_L1"
  type: "Convolution"
  bottom: "Mconv5_stage4_L1"
  top: "Mconv6_stage4_L1"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
  convolution_param {
    num_output: 64
    pad: 0
    kernel_size: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "Mrelu6_stage4_L1"
  type: "ReLU"
  bottom: "Mconv6_stage4_L1"
  top: "Mconv6_stage4_L1"
}
layer {
  name: "Mconv6_stage4_L2"
  type: "Convolution"
  bottom: "Mconv5_stage4_L2"
  top: "Mconv6_stage4_L2"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
  convolution_param {
    num_output: 64
    pad: 0
    kernel_size: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "Mrelu6_stage4_L2"
  type: "ReLU"
  bottom: "Mconv6_stage4_L2"
  top: "Mconv6_stage4_L2"
}
layer {
  name: "Mconv7_stage4_L1"
  type: "Convolution"
  bottom: "Mconv6_stage4_L1"
  top: "Mconv7_stage4_L1"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
  convolution_param {
    num_output: 32
    pad: 0
    kernel_size: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "Mconv7_stage4_L2"
  type: "Convolution"
  bottom: "Mconv6_stage4_L2"
  top: "Mconv7_stage4_L2"
		  param {
		    lr_mult: 0
		    decay_mult: 0
		  }
	  param {
	    lr_mult: 0
	    decay_mult: 0
	  }
  convolution_param {
    num_output: 16
    pad: 0
    kernel_size: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}


##########################output#########################

layer {
  name: "net_output"
  type: "Concat"
  bottom: "Mconv7_stage4_L1"
  bottom: "Mconv7_stage4_L2"
  # top: "concat_stage7"
  top: "net_output"
  concat_param {
    axis: 1
  }
}


####################################################all the same#########################

##########################ALL THE SAME##########################################


layer {
  name: "concat_stage8"
  type: "Concat"
  bottom: "Mconv7_stage4_L1"
  bottom: "Mconv7_stage4_L2"
  bottom: "conv4_4_CPM"
  top: "concat_stage8"
  concat_param {
    axis: 1
  }
}

layer {
    bottom: "concat_stage8"
    top: "conv_concat_stage8"
    name: "conv_concat_stage8"
    type: "Convolution"
    convolution_param {
        num_output: 64
        kernel_size: 3
	pad: 1
        stride: 1
        weight_filler {
            type: "gaussian"
	    std: 0.01
        }
        bias_term: false
    }
}

layer {
  name: "relu_conv_concat_stage8"
  type: "ReLU"
  bottom: "conv_concat_stage8"
  top: "conv_concat_stage8"
}

layer {
    bottom: "conv_concat_stage8"
    top: "conv_concat_stage8_1"
    name: "conv_concat_stage8_1"
    type: "Convolution"
    convolution_param {
        num_output: 64
        kernel_size: 3
	pad: 1
        stride: 1
        weight_filler {
            type: "gaussian"
	    std: 0.01
        }
        bias_term: false
    }
}

layer {
  name: "relu_conv_concat_stage8_1"
  type: "ReLU"
  bottom: "conv_concat_stage8_1"
  top: "conv_concat_stage8_1"
}


layer {
  name: "upconv_1"
  type: "Deconvolution"
  bottom: "conv_concat_stage8_1"
  top: "upconv_1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    pad: 0
    kernel_size: 2
    stride: 2
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "relu_u2a"
  type: "ReLU"
  bottom: "upconv_1"
  top: "upconv_1"
}



layer {
  name: "concat_stage_upconv1"
  type: "Concat"
  bottom: "upconv_1"
  bottom: "res2b"
  bottom: "res1a"
  top: "concat_stage_upconv1"
  concat_param {
    axis: 1
  }
}


layer {
    bottom: "concat_stage_upconv1"
    top: "conv_concat_stage9"
    name: "conv_concat_stage9"
    type: "Convolution"
    convolution_param {
        num_output: 64
        kernel_size: 3
	pad: 1
        stride: 1
        weight_filler {
            type: "gaussian"
	    std: 0.01
        }
        bias_term: false
    }
}

layer {
  name: "relu_conv_concat_stage9"
  type: "ReLU"
  bottom: "conv_concat_stage9"
  top: "conv_concat_stage9"
}



layer {
    bottom: "conv_concat_stage9"
    top: "conv_concat_stage9_1"
    name: "conv_concat_stage9_1"
    type: "Convolution"
    convolution_param {
        num_output: 64
        kernel_size: 3
	pad: 1
        stride: 1
        weight_filler {
            type: "gaussian"
	    std: 0.01
        }
        bias_term: false
    }
}

layer {
  name: "relu_conv_concat_stage9_1"
  type: "ReLU"
  bottom: "conv_concat_stage9_1"
  top: "conv_concat_stage9_1"
}


layer {
  name: "upconv_2"
  type: "Deconvolution"
  bottom: "conv_concat_stage9_1"
  top: "upconv_2"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    pad: 0
    kernel_size: 2
    stride: 2
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "relu_u2a_upconv_2"
  type: "ReLU"
  bottom: "upconv_2"
  top: "upconv_2"
}

layer {
  name: "concat_stage_160x160"
  type: "Concat"
  bottom: "upconv_2"
  bottom: "conv1"
  top: "concat_stage_160x160"
  concat_param {
    axis: 1
  }
}


layer {
    bottom: "concat_stage_160x160"
    top: "conv_stage_160x160"
    name: "conv_stage_160x160"
    type: "Convolution"
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
	pad: 1
        weight_filler {
            type: "gaussian"
	    std: 0.01
        }
        bias_term: false
    }
}

layer {
  name: "relu_conv_stage_160x160"
  type: "ReLU"
  bottom: "conv_stage_160x160"
  top: "conv_stage_160x160"
}


layer {
    bottom: "conv_stage_160x160"
    top: "concat_stage_160x160_1"
    name: "concat_stage_160x160_1"
    type: "Convolution"
    convolution_param {
        num_output: 64
        kernel_size: 3
	pad: 1
        stride: 1
        weight_filler {
            type: "gaussian"
	    std: 0.01
        }
        bias_term: false
    }
}

layer {
  name: "relu_concat_stage_160x160_1"
  type: "ReLU"
  bottom: "concat_stage_160x160_1"
  top: "concat_stage_160x160_1"
}



layer {
    bottom: "concat_stage_160x160_1"
    top: "conv2_stage_160x160"
    name: "conv2_stage_160x160"
    type: "Convolution"
    convolution_param {
        num_output: 2
        kernel_size: 1
        stride: 1
        weight_filler {
            type: "gaussian"
	    std: 0.01
        }
        bias_term: false
    }
}


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