tlr_yolov2_deconv_resnet101_focalloss4_4.prototxt

layer {
  name: 'data'
  type: 'MinibatchData'
  top: 'data_bosch'
  top: 'label_bosch_pos'
  top: 'bbox_bosch'#
  include: { phase: TRAIN}#
  data_param {
    #source: "D:/DB/traffic_light/bosch/lmdb/bosch_train_add_shuffle/"
    #source: "D:/DB/traffic_light/bosch/lmdb/bosch_train_add_allsize_shuffle_augmented/"
    #source: "D:/DB/traffic_light/bosch/lmdb/bosch_test_shuffle/"
    #source: "D:/DB/traffic_light/bosch/multi_scale/pos_only_lmdb/"
    source: "C:/Users/jylee/Desktop/TLR/pos_only_lmdb(train)"
    batch_size: 1
    backend: LMDB
  }#
  augmentation_param{
    rand_resize_param {
      p: 0.8
      w_min: 0.9
      w_max: 1.1
      h_min: 0.9
      h_max: 1.1
    }#
    gauss_noise_param {
      p: 0.3
      mean: 0
      stddev: 0.01
    }#
    mirror_param {
      p: 0.5
    }#
    blur_param {
      p: 0.1
      kernel_size: 3
      sigma: 0.2
    }
  }#
  minibatch_data_param {
    num_batch: 3
    width: 224
    height: 224
    num_gt: 15
    max_num_patch: 4
  }
}

#layer {
#	name: "data"
#	type: "SubwinData2"
#	top: "data_bosch"
#	top: "label_bosch_pos"
#	top: "bbox_bosch"
#	#top: "whole_data"#
#	include: {phase: TRAIN}#
#  	data_param {
#    	#source: "D:/DB/traffic_light/bosch/lmdb/bosch_test_shuffle/"
#    	source: "D:/DB/traffic_light/bosch/multi_scale/pos_only_lmdb/"
#    	batch_size: 3
#    	backend: LMDB
#  	}#
#    augmentation_param{
#    	rand_resize_param {
#			p: 0.8
#			w_min: 0.9
#			w_max: 1.1
#			h_min: 0.9
#			h_max: 1.1
#		}#
#		gauss_noise_param {
#			p: 0.3
#			mean: 0
#			stddev: 0.01
#		}#
#		mirror_param {
#			p: 0.5
#		}#
#		blur_param {
#			p: 0.1
#			kernel_size: 3
#			sigma: 0.2
#		}
#    }##
#  	subwin_offset_param {
#  		global_detection: false#
#  		win_size {
#  			width: 224
#  			height: 224
#  		}#
#  		win_offset {
#  			x: 0
#  			y: 0
#  		}
#  		win_offset {
#  			x: 211
#  			y: 0
#  		}
#  		win_offset {
#  			x: 422
#  			y: 0
#  		}
#  		win_offset {
#  			x: 633
#  			y: 0
#  		}
#  		win_offset {
#  			x: 844
#  			y:0
#  		}
#  		win_offset {
#  			x: 1055
#  			y: 0
#  		}
#  		win_offset {
#  			x: 0
#  			y: 211
#  		}
#  		win_offset {
#  			x: 211
#  			y: 211
#  		}
#  		win_offset {
#  			x: 422
#  			y: 211
#  		}
#  		win_offset {
#  			x: 633
#  			y: 211
#  		}
#  		win_offset {
#  			x: 844
#  			y: 211
#  		}
#  		win_offset {
#  			x: 1055
#  			y: 211
#  		}#
#  	}
#}

layer {
	name: "neg_data"
	type: "ImageData"
	top: "neg_data"
	top: "dummy_label"
	include: { phase: TRAIN}
	image_data_param {
		source: "C:/Users/jylee/Desktop/TLR/tl-background/list.txt"
		root_folder: "C:/Users/jylee/Desktop/TLR/tl-background"
		batch_size: 2
		shuffle: true
		new_height: 224
		new_width: 224
	}

	#transform_param {
	#	mirror: true
	#}
}

layer {
	name: "dummy_label_ignore"
	type: "Silence"
	bottom: "dummy_label"
	include: { phase: TRAIN}
}

layer {
	name: "neg_gt"
	type: "NegGT"
	bottom: "label_bosch_pos"
	bottom: "bbox_bosch"
	top: "neg_label"
	top: "neg_bbox"
	include: {phase: TRAIN}
	neg_gt_param {
		batch_size: 2
		num_gt: 15
	}
}

layer {
	name: "data_concat"
	type: "Concat"
	bottom: "data_bosch"
	bottom: "neg_data"
	top: "data"

	include: { phase: TRAIN}

	concat_param {
		axis: 0
	}
}

layer {
	name: "label_concat"
	type: "Concat"
	bottom: "label_bosch_pos"
	bottom: "neg_label"
	top: "label_bosch"

	include: { phase: TRAIN}

	concat_param {
		axis: 0
	}
}

layer {
	name: "bbox_concat"
	type: "Concat"
	bottom: "bbox_bosch"
	bottom: "neg_bbox"
	top: "bbox"

	include: { phase: TRAIN}

	concat_param {
		axis: 0
	}
}



layer {
  name: 'data'
  type: 'MinibatchData'
  top: 'data'
  top: 'label_bosch'
  top: 'bbox'

  include: { phase: TEST}

  data_param {
    #source: "D:/DB/traffic_light/bosch/lmdb/bosch_test_shuffle/"
    source: "D:/DB/traffic_light/lisa-traffic-light-dataset/lmdb/test_shuffle/"
    batch_size: 1
    backend: LMDB
  }

  minibatch_data_param {
    num_batch: 3
    width: 224
    height: 224
    num_gt: 15
    max_num_patch: 10
  }
}

#layer{
#  name: "train_label_to_test_label"
#  type: "LabelRemap"
#  bottom: "label_bosch"
#  top: "label"
#
#  label_remap_param {
#    src: 5 # red_left
#    src: 6 # red_right
#    src: 7 # red_straight
#    src: 8 # red_straight_left
#    src: 9 # red_straight_right
#    src: 10 # green_left
#    src: 11 # green_right
#    src: 12 # green_straight
#    src: 13 # green_straight_left
#    src: 14 # green_straight_right  
#    src: 15 # red_occluded
#    src: 16 # yellow_occluded
#    src: 17 # green_occluded
#    src: 18 # off_occluded
#    src: 19 # red_left_occluded
#    src: 20 # red_right_occluded
#    src: 21 # red_straight_occluded
#    src: 22 # red_straight_left_occluded
#    src: 23 # red_straight_right_occluded
#    src: 24 # green_right_occluded
#    src: 25 # green_left_occluded
#    src: 26 # green_straight_occluded
#    src: 27 # green_straight_left_occluded
#
#    dst: 1 # red_left
#    dst: 1 # red_right
#    dst: 1 # red_straight
#    dst: 1 # red_straight_left
#    dst: 1 # red_straight_right
#    dst: 3 # green_left
#    dst: 3 # green_right
#    dst: 3 # green_straight
#    dst: 3 # green_straight_left
#    dst: 3 # green_straight_right  
#    dst: 1 # red_occluded
#    dst: 2 # yellow_occluded
#    dst: 3 # green_occluded
#    dst: 4 # off_occluded
#    dst: 1 # red_left_occluded
#    dst: 1 # red_right_occluded
#    dst: 1 # red_straight_occluded
#    dst: 1 # red_straight_left_occluded
#    dst: 1 # red_straight_right_occluded
#    dst: 3 # green_right_occluded
#    dst: 3 # green_left_occluded
#    dst: 3 # green_straight_occluded
#    dst: 3 # green_straight_left_occluded
#  }
#}

layer {
	name: "train_label_to_test_label"
	type: "LabelRemap"
	bottom: "label_bosch"
	top: "label"

	label_remap_param {
		src: 7 # goForward
		dst: 1 # go
	}
}

###########################################################
# resnet-101
layer {
	bottom: "data"
	top: "conv1"
	name: "conv1"
	type: "Convolution"
	convolution_param {
		num_output: 64
		kernel_size: 7
		pad: 3
		stride: 2
		bias_term: false
	}
}

layer {
	bottom: "conv1"
	top: "conv1"
	name: "bn_conv1"
	type: "BatchNorm"

}

layer {
	bottom: "conv1"
	top: "conv1"
	name: "scale_conv1"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

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

layer {
	bottom: "conv1"
	top: "pool1"
	name: "pool1"
	type: "Pooling"
	pooling_param {
		kernel_size: 3
		stride: 2
		pool: MAX
	}
}

layer {
	bottom: "pool1"
	top: "res2a_branch1"
	name: "res2a_branch1"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res2a_branch1"
	top: "res2a_branch1"
	name: "bn2a_branch1"
	type: "BatchNorm"

}

layer {
	bottom: "res2a_branch1"
	top: "res2a_branch1"
	name: "scale2a_branch1"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "pool1"
	top: "res2a_branch2a"
	name: "res2a_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 64
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res2a_branch2a"
	top: "res2a_branch2a"
	name: "bn2a_branch2a"
	type: "BatchNorm"

}

layer {
	bottom: "res2a_branch2a"
	top: "res2a_branch2a"
	name: "scale2a_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

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

layer {
	bottom: "res2a_branch2a"
	top: "res2a_branch2b"
	name: "res2a_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 64
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res2a_branch2b"
	top: "res2a_branch2b"
	name: "bn2a_branch2b"
	type: "BatchNorm"

}

layer {
	bottom: "res2a_branch2b"
	top: "res2a_branch2b"
	name: "scale2a_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res2a_branch2b"
	bottom: "res2a_branch2b"
	name: "res2a_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res2a_branch2b"
	top: "res2a_branch2c"
	name: "res2a_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res2a_branch2c"
	top: "res2a_branch2c"
	name: "bn2a_branch2c"
	type: "BatchNorm"

}

layer {
	bottom: "res2a_branch2c"
	top: "res2a_branch2c"
	name: "scale2a_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res2a_branch1"
	bottom: "res2a_branch2c"
	top: "res2a"
	name: "res2a"
	type: "Eltwise"
}

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

layer {
	bottom: "res2a"
	top: "res2b_branch2a"
	name: "res2b_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 64
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res2b_branch2a"
	top: "res2b_branch2a"
	name: "bn2b_branch2a"
	type: "BatchNorm"

}

layer {
	bottom: "res2b_branch2a"
	top: "res2b_branch2a"
	name: "scale2b_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

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

layer {
	bottom: "res2b_branch2a"
	top: "res2b_branch2b"
	name: "res2b_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 64
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res2b_branch2b"
	top: "res2b_branch2b"
	name: "bn2b_branch2b"
	type: "BatchNorm"

}

layer {
	bottom: "res2b_branch2b"
	top: "res2b_branch2b"
	name: "scale2b_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res2b_branch2b"
	bottom: "res2b_branch2b"
	name: "res2b_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res2b_branch2b"
	top: "res2b_branch2c"
	name: "res2b_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res2b_branch2c"
	top: "res2b_branch2c"
	name: "bn2b_branch2c"
	type: "BatchNorm"

}

layer {
	bottom: "res2b_branch2c"
	top: "res2b_branch2c"
	name: "scale2b_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res2a"
	bottom: "res2b_branch2c"
	top: "res2b"
	name: "res2b"
	type: "Eltwise"
}

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

layer {
	bottom: "res2b"
	top: "res2c_branch2a"
	name: "res2c_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 64
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res2c_branch2a"
	top: "res2c_branch2a"
	name: "bn2c_branch2a"
	type: "BatchNorm"

}

layer {
	bottom: "res2c_branch2a"
	top: "res2c_branch2a"
	name: "scale2c_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res2c_branch2a"
	bottom: "res2c_branch2a"
	name: "res2c_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res2c_branch2a"
	top: "res2c_branch2b"
	name: "res2c_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 64
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res2c_branch2b"
	top: "res2c_branch2b"
	name: "bn2c_branch2b"
	type: "BatchNorm"

}

layer {
	bottom: "res2c_branch2b"
	top: "res2c_branch2b"
	name: "scale2c_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res2c_branch2b"
	bottom: "res2c_branch2b"
	name: "res2c_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res2c_branch2b"
	top: "res2c_branch2c"
	name: "res2c_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res2c_branch2c"
	top: "res2c_branch2c"
	name: "bn2c_branch2c"
	type: "BatchNorm"

}

layer {
	bottom: "res2c_branch2c"
	top: "res2c_branch2c"
	name: "scale2c_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res2b"
	bottom: "res2c_branch2c"
	top: "res2c"
	name: "res2c"
	type: "Eltwise"
}

layer {
	bottom: "res2c"
	top: "res2c"
	name: "res2c_relu"
	type: "ReLU"
}

layer {
	bottom: "res2c"
	top: "res3a_branch1"
	name: "res3a_branch1"
	type: "Convolution"
	convolution_param {
		num_output: 512
		kernel_size: 1
		pad: 0
		stride: 2
		bias_term: false
	}
}

layer {
	bottom: "res3a_branch1"
	top: "res3a_branch1"
	name: "bn3a_branch1"
	type: "BatchNorm"

}

layer {
	bottom: "res3a_branch1"
	top: "res3a_branch1"
	name: "scale3a_branch1"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res2c"
	top: "res3a_branch2a"
	name: "res3a_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 128
		kernel_size: 1
		pad: 0
		stride: 2
		bias_term: false
	}
}

layer {
	bottom: "res3a_branch2a"
	top: "res3a_branch2a"
	name: "bn3a_branch2a"
	type: "BatchNorm"

}

layer {
	bottom: "res3a_branch2a"
	top: "res3a_branch2a"
	name: "scale3a_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

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

layer {
	bottom: "res3a_branch2a"
	top: "res3a_branch2b"
	name: "res3a_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 128
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res3a_branch2b"
	top: "res3a_branch2b"
	name: "bn3a_branch2b"
	type: "BatchNorm"

}

layer {
	bottom: "res3a_branch2b"
	top: "res3a_branch2b"
	name: "scale3a_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res3a_branch2b"
	bottom: "res3a_branch2b"
	name: "res3a_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res3a_branch2b"
	top: "res3a_branch2c"
	name: "res3a_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 512
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res3a_branch2c"
	top: "res3a_branch2c"
	name: "bn3a_branch2c"
	type: "BatchNorm"

}

layer {
	bottom: "res3a_branch2c"
	top: "res3a_branch2c"
	name: "scale3a_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res3a_branch1"
	bottom: "res3a_branch2c"
	top: "res3a"
	name: "res3a"
	type: "Eltwise"
}

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

layer {
	bottom: "res3a"
	top: "res3b1_branch2a"
	name: "res3b1_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 128
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res3b1_branch2a"
	top: "res3b1_branch2a"
	name: "bn3b1_branch2a"
	type: "BatchNorm"

}

layer {
	bottom: "res3b1_branch2a"
	top: "res3b1_branch2a"
	name: "scale3b1_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res3b1_branch2a"
	bottom: "res3b1_branch2a"
	name: "res3b1_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res3b1_branch2a"
	top: "res3b1_branch2b"
	name: "res3b1_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 128
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res3b1_branch2b"
	top: "res3b1_branch2b"
	name: "bn3b1_branch2b"
	type: "BatchNorm"

}

layer {
	bottom: "res3b1_branch2b"
	top: "res3b1_branch2b"
	name: "scale3b1_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res3b1_branch2b"
	bottom: "res3b1_branch2b"
	name: "res3b1_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res3b1_branch2b"
	top: "res3b1_branch2c"
	name: "res3b1_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 512
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res3b1_branch2c"
	top: "res3b1_branch2c"
	name: "bn3b1_branch2c"
	type: "BatchNorm"

}

layer {
	bottom: "res3b1_branch2c"
	top: "res3b1_branch2c"
	name: "scale3b1_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res3a"
	bottom: "res3b1_branch2c"
	top: "res3b1"
	name: "res3b1"
	type: "Eltwise"
}

layer {
	bottom: "res3b1"
	top: "res3b1"
	name: "res3b1_relu"
	type: "ReLU"
}

layer {
	bottom: "res3b1"
	top: "res3b2_branch2a"
	name: "res3b2_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 128
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res3b2_branch2a"
	top: "res3b2_branch2a"
	name: "bn3b2_branch2a"
	type: "BatchNorm"

}

layer {
	bottom: "res3b2_branch2a"
	top: "res3b2_branch2a"
	name: "scale3b2_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res3b2_branch2a"
	bottom: "res3b2_branch2a"
	name: "res3b2_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res3b2_branch2a"
	top: "res3b2_branch2b"
	name: "res3b2_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 128
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res3b2_branch2b"
	top: "res3b2_branch2b"
	name: "bn3b2_branch2b"
	type: "BatchNorm"

}

layer {
	bottom: "res3b2_branch2b"
	top: "res3b2_branch2b"
	name: "scale3b2_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res3b2_branch2b"
	bottom: "res3b2_branch2b"
	name: "res3b2_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res3b2_branch2b"
	top: "res3b2_branch2c"
	name: "res3b2_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 512
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res3b2_branch2c"
	top: "res3b2_branch2c"
	name: "bn3b2_branch2c"
	type: "BatchNorm"

}

layer {
	bottom: "res3b2_branch2c"
	top: "res3b2_branch2c"
	name: "scale3b2_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res3b1"
	bottom: "res3b2_branch2c"
	top: "res3b2"
	name: "res3b2"
	type: "Eltwise"
}

layer {
	bottom: "res3b2"
	top: "res3b2"
	name: "res3b2_relu"
	type: "ReLU"
}

layer {
	bottom: "res3b2"
	top: "res3b3_branch2a"
	name: "res3b3_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 128
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res3b3_branch2a"
	top: "res3b3_branch2a"
	name: "bn3b3_branch2a"
	type: "BatchNorm"

}

layer {
	bottom: "res3b3_branch2a"
	top: "res3b3_branch2a"
	name: "scale3b3_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res3b3_branch2a"
	bottom: "res3b3_branch2a"
	name: "res3b3_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res3b3_branch2a"
	top: "res3b3_branch2b"
	name: "res3b3_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 128
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res3b3_branch2b"
	top: "res3b3_branch2b"
	name: "bn3b3_branch2b"
	type: "BatchNorm"

}

layer {
	bottom: "res3b3_branch2b"
	top: "res3b3_branch2b"
	name: "scale3b3_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res3b3_branch2b"
	bottom: "res3b3_branch2b"
	name: "res3b3_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res3b3_branch2b"
	top: "res3b3_branch2c"
	name: "res3b3_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 512
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res3b3_branch2c"
	top: "res3b3_branch2c"
	name: "bn3b3_branch2c"
	type: "BatchNorm"

}

layer {
	bottom: "res3b3_branch2c"
	top: "res3b3_branch2c"
	name: "scale3b3_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res3b2"
	bottom: "res3b3_branch2c"
	top: "res3b3"
	name: "res3b3"
	type: "Eltwise"
}

layer {
	bottom: "res3b3"
	top: "res3b3"
	name: "res3b3_relu"
	type: "ReLU"
}

layer {
	bottom: "res3b3"
	top: "res4a_branch1"
	name: "res4a_branch1"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 2
		bias_term: false
	}
}

layer {
	bottom: "res4a_branch1"
	top: "res4a_branch1"
	name: "bn4a_branch1"
	type: "BatchNorm"

}

layer {
	bottom: "res4a_branch1"
	top: "res4a_branch1"
	name: "scale4a_branch1"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res3b3"
	top: "res4a_branch2a"
	name: "res4a_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 2
		bias_term: false
	}
}

layer {
	bottom: "res4a_branch2a"
	top: "res4a_branch2a"
	name: "bn4a_branch2a"
	type: "BatchNorm"

}

layer {
	bottom: "res4a_branch2a"
	top: "res4a_branch2a"
	name: "scale4a_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4a_branch2a"
	bottom: "res4a_branch2a"
	name: "res4a_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4a_branch2a"
	top: "res4a_branch2b"
	name: "res4a_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4a_branch2b"
	top: "res4a_branch2b"
	name: "bn4a_branch2b"
	type: "BatchNorm"

}

layer {
	bottom: "res4a_branch2b"
	top: "res4a_branch2b"
	name: "scale4a_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4a_branch2b"
	bottom: "res4a_branch2b"
	name: "res4a_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4a_branch2b"
	top: "res4a_branch2c"
	name: "res4a_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4a_branch2c"
	top: "res4a_branch2c"
	name: "bn4a_branch2c"
	type: "BatchNorm"

}

layer {
	bottom: "res4a_branch2c"
	top: "res4a_branch2c"
	name: "scale4a_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4a_branch1"
	bottom: "res4a_branch2c"
	top: "res4a"
	name: "res4a"
	type: "Eltwise"
}

layer {
	bottom: "res4a"
	top: "res4a"
	name: "res4a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4a"
	top: "res4b1_branch2a"
	name: "res4b1_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b1_branch2a"
	top: "res4b1_branch2a"
	name: "bn4b1_branch2a"
	type: "BatchNorm"

}

layer {
	bottom: "res4b1_branch2a"
	top: "res4b1_branch2a"
	name: "scale4b1_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b1_branch2a"
	bottom: "res4b1_branch2a"
	name: "res4b1_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b1_branch2a"
	top: "res4b1_branch2b"
	name: "res4b1_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b1_branch2b"
	top: "res4b1_branch2b"
	name: "bn4b1_branch2b"
	type: "BatchNorm"

}

layer {
	bottom: "res4b1_branch2b"
	top: "res4b1_branch2b"
	name: "scale4b1_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b1_branch2b"
	bottom: "res4b1_branch2b"
	name: "res4b1_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b1_branch2b"
	top: "res4b1_branch2c"
	name: "res4b1_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b1_branch2c"
	top: "res4b1_branch2c"
	name: "bn4b1_branch2c"
	type: "BatchNorm"

}

layer {
	bottom: "res4b1_branch2c"
	top: "res4b1_branch2c"
	name: "scale4b1_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4a"
	bottom: "res4b1_branch2c"
	top: "res4b1"
	name: "res4b1"
	type: "Eltwise"
}

layer {
	bottom: "res4b1"
	top: "res4b1"
	name: "res4b1_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b1"
	top: "res4b2_branch2a"
	name: "res4b2_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b2_branch2a"
	top: "res4b2_branch2a"
	name: "bn4b2_branch2a"
	type: "BatchNorm"

}

layer {
	bottom: "res4b2_branch2a"
	top: "res4b2_branch2a"
	name: "scale4b2_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b2_branch2a"
	bottom: "res4b2_branch2a"
	name: "res4b2_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b2_branch2a"
	top: "res4b2_branch2b"
	name: "res4b2_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b2_branch2b"
	top: "res4b2_branch2b"
	name: "bn4b2_branch2b"
	type: "BatchNorm"

}

layer {
	bottom: "res4b2_branch2b"
	top: "res4b2_branch2b"
	name: "scale4b2_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b2_branch2b"
	bottom: "res4b2_branch2b"
	name: "res4b2_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b2_branch2b"
	top: "res4b2_branch2c"
	name: "res4b2_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b2_branch2c"
	top: "res4b2_branch2c"
	name: "bn4b2_branch2c"
	type: "BatchNorm"

}

layer {
	bottom: "res4b2_branch2c"
	top: "res4b2_branch2c"
	name: "scale4b2_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b1"
	bottom: "res4b2_branch2c"
	top: "res4b2"
	name: "res4b2"
	type: "Eltwise"
}

layer {
	bottom: "res4b2"
	top: "res4b2"
	name: "res4b2_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b2"
	top: "res4b3_branch2a"
	name: "res4b3_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b3_branch2a"
	top: "res4b3_branch2a"
	name: "bn4b3_branch2a"
	type: "BatchNorm"

}

layer {
	bottom: "res4b3_branch2a"
	top: "res4b3_branch2a"
	name: "scale4b3_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b3_branch2a"
	bottom: "res4b3_branch2a"
	name: "res4b3_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b3_branch2a"
	top: "res4b3_branch2b"
	name: "res4b3_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b3_branch2b"
	top: "res4b3_branch2b"
	name: "bn4b3_branch2b"
	type: "BatchNorm"

}

layer {
	bottom: "res4b3_branch2b"
	top: "res4b3_branch2b"
	name: "scale4b3_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b3_branch2b"
	bottom: "res4b3_branch2b"
	name: "res4b3_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b3_branch2b"
	top: "res4b3_branch2c"
	name: "res4b3_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b3_branch2c"
	top: "res4b3_branch2c"
	name: "bn4b3_branch2c"
	type: "BatchNorm"

}

layer {
	bottom: "res4b3_branch2c"
	top: "res4b3_branch2c"
	name: "scale4b3_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b2"
	bottom: "res4b3_branch2c"
	top: "res4b3"
	name: "res4b3"
	type: "Eltwise"
}

layer {
	bottom: "res4b3"
	top: "res4b3"
	name: "res4b3_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b3"
	top: "res4b4_branch2a"
	name: "res4b4_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b4_branch2a"
	top: "res4b4_branch2a"
	name: "bn4b4_branch2a"
	type: "BatchNorm"

}

layer {
	bottom: "res4b4_branch2a"
	top: "res4b4_branch2a"
	name: "scale4b4_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b4_branch2a"
	bottom: "res4b4_branch2a"
	name: "res4b4_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b4_branch2a"
	top: "res4b4_branch2b"
	name: "res4b4_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b4_branch2b"
	top: "res4b4_branch2b"
	name: "bn4b4_branch2b"
	type: "BatchNorm"

}

layer {
	bottom: "res4b4_branch2b"
	top: "res4b4_branch2b"
	name: "scale4b4_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b4_branch2b"
	bottom: "res4b4_branch2b"
	name: "res4b4_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b4_branch2b"
	top: "res4b4_branch2c"
	name: "res4b4_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b4_branch2c"
	top: "res4b4_branch2c"
	name: "bn4b4_branch2c"
	type: "BatchNorm"

}

layer {
	bottom: "res4b4_branch2c"
	top: "res4b4_branch2c"
	name: "scale4b4_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b3"
	bottom: "res4b4_branch2c"
	top: "res4b4"
	name: "res4b4"
	type: "Eltwise"
}

layer {
	bottom: "res4b4"
	top: "res4b4"
	name: "res4b4_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b4"
	top: "res4b5_branch2a"
	name: "res4b5_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b5_branch2a"
	top: "res4b5_branch2a"
	name: "bn4b5_branch2a"
	type: "BatchNorm"

}

layer {
	bottom: "res4b5_branch2a"
	top: "res4b5_branch2a"
	name: "scale4b5_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b5_branch2a"
	bottom: "res4b5_branch2a"
	name: "res4b5_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b5_branch2a"
	top: "res4b5_branch2b"
	name: "res4b5_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b5_branch2b"
	top: "res4b5_branch2b"
	name: "bn4b5_branch2b"
	type: "BatchNorm"

}

layer {
	bottom: "res4b5_branch2b"
	top: "res4b5_branch2b"
	name: "scale4b5_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b5_branch2b"
	bottom: "res4b5_branch2b"
	name: "res4b5_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b5_branch2b"
	top: "res4b5_branch2c"
	name: "res4b5_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b5_branch2c"
	top: "res4b5_branch2c"
	name: "bn4b5_branch2c"
	type: "BatchNorm"

}

layer {
	bottom: "res4b5_branch2c"
	top: "res4b5_branch2c"
	name: "scale4b5_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b4"
	bottom: "res4b5_branch2c"
	top: "res4b5"
	name: "res4b5"
	type: "Eltwise"
}

layer {
	bottom: "res4b5"
	top: "res4b5"
	name: "res4b5_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b5"
	top: "res4b6_branch2a"
	name: "res4b6_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b6_branch2a"
	top: "res4b6_branch2a"
	name: "bn4b6_branch2a"
	type: "BatchNorm"

}

layer {
	bottom: "res4b6_branch2a"
	top: "res4b6_branch2a"
	name: "scale4b6_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b6_branch2a"
	bottom: "res4b6_branch2a"
	name: "res4b6_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b6_branch2a"
	top: "res4b6_branch2b"
	name: "res4b6_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b6_branch2b"
	top: "res4b6_branch2b"
	name: "bn4b6_branch2b"
	type: "BatchNorm"

}

layer {
	bottom: "res4b6_branch2b"
	top: "res4b6_branch2b"
	name: "scale4b6_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b6_branch2b"
	bottom: "res4b6_branch2b"
	name: "res4b6_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b6_branch2b"
	top: "res4b6_branch2c"
	name: "res4b6_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b6_branch2c"
	top: "res4b6_branch2c"
	name: "bn4b6_branch2c"
	type: "BatchNorm"

}

layer {
	bottom: "res4b6_branch2c"
	top: "res4b6_branch2c"
	name: "scale4b6_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b5"
	bottom: "res4b6_branch2c"
	top: "res4b6"
	name: "res4b6"
	type: "Eltwise"
}

layer {
	bottom: "res4b6"
	top: "res4b6"
	name: "res4b6_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b6"
	top: "res4b7_branch2a"
	name: "res4b7_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b7_branch2a"
	top: "res4b7_branch2a"
	name: "bn4b7_branch2a"
	type: "BatchNorm"

}

layer {
	bottom: "res4b7_branch2a"
	top: "res4b7_branch2a"
	name: "scale4b7_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b7_branch2a"
	bottom: "res4b7_branch2a"
	name: "res4b7_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b7_branch2a"
	top: "res4b7_branch2b"
	name: "res4b7_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b7_branch2b"
	top: "res4b7_branch2b"
	name: "bn4b7_branch2b"
	type: "BatchNorm"

}

layer {
	bottom: "res4b7_branch2b"
	top: "res4b7_branch2b"
	name: "scale4b7_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b7_branch2b"
	bottom: "res4b7_branch2b"
	name: "res4b7_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b7_branch2b"
	top: "res4b7_branch2c"
	name: "res4b7_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b7_branch2c"
	top: "res4b7_branch2c"
	name: "bn4b7_branch2c"
	type: "BatchNorm"

}

layer {
	bottom: "res4b7_branch2c"
	top: "res4b7_branch2c"
	name: "scale4b7_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b6"
	bottom: "res4b7_branch2c"
	top: "res4b7"
	name: "res4b7"
	type: "Eltwise"
}

layer {
	bottom: "res4b7"
	top: "res4b7"
	name: "res4b7_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b7"
	top: "res4b8_branch2a"
	name: "res4b8_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b8_branch2a"
	top: "res4b8_branch2a"
	name: "bn4b8_branch2a"
	type: "BatchNorm"

}

layer {
	bottom: "res4b8_branch2a"
	top: "res4b8_branch2a"
	name: "scale4b8_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b8_branch2a"
	bottom: "res4b8_branch2a"
	name: "res4b8_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b8_branch2a"
	top: "res4b8_branch2b"
	name: "res4b8_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b8_branch2b"
	top: "res4b8_branch2b"
	name: "bn4b8_branch2b"
	type: "BatchNorm"

}

layer {
	bottom: "res4b8_branch2b"
	top: "res4b8_branch2b"
	name: "scale4b8_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b8_branch2b"
	bottom: "res4b8_branch2b"
	name: "res4b8_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b8_branch2b"
	top: "res4b8_branch2c"
	name: "res4b8_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b8_branch2c"
	top: "res4b8_branch2c"
	name: "bn4b8_branch2c"
	type: "BatchNorm"

}

layer {
	bottom: "res4b8_branch2c"
	top: "res4b8_branch2c"
	name: "scale4b8_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b7"
	bottom: "res4b8_branch2c"
	top: "res4b8"
	name: "res4b8"
	type: "Eltwise"
}

layer {
	bottom: "res4b8"
	top: "res4b8"
	name: "res4b8_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b8"
	top: "res4b9_branch2a"
	name: "res4b9_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b9_branch2a"
	top: "res4b9_branch2a"
	name: "bn4b9_branch2a"
	type: "BatchNorm"

}

layer {
	bottom: "res4b9_branch2a"
	top: "res4b9_branch2a"
	name: "scale4b9_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b9_branch2a"
	bottom: "res4b9_branch2a"
	name: "res4b9_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b9_branch2a"
	top: "res4b9_branch2b"
	name: "res4b9_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b9_branch2b"
	top: "res4b9_branch2b"
	name: "bn4b9_branch2b"
	type: "BatchNorm"

}

layer {
	bottom: "res4b9_branch2b"
	top: "res4b9_branch2b"
	name: "scale4b9_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b9_branch2b"
	bottom: "res4b9_branch2b"
	name: "res4b9_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b9_branch2b"
	top: "res4b9_branch2c"
	name: "res4b9_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b9_branch2c"
	top: "res4b9_branch2c"
	name: "bn4b9_branch2c"
	type: "BatchNorm"

}

layer {
	bottom: "res4b9_branch2c"
	top: "res4b9_branch2c"
	name: "scale4b9_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b8"
	bottom: "res4b9_branch2c"
	top: "res4b9"
	name: "res4b9"
	type: "Eltwise"
}

layer {
	bottom: "res4b9"
	top: "res4b9"
	name: "res4b9_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b9"
	top: "res4b10_branch2a"
	name: "res4b10_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b10_branch2a"
	top: "res4b10_branch2a"
	name: "bn4b10_branch2a"
	type: "BatchNorm"

}

layer {
	bottom: "res4b10_branch2a"
	top: "res4b10_branch2a"
	name: "scale4b10_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b10_branch2a"
	bottom: "res4b10_branch2a"
	name: "res4b10_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b10_branch2a"
	top: "res4b10_branch2b"
	name: "res4b10_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b10_branch2b"
	top: "res4b10_branch2b"
	name: "bn4b10_branch2b"
	type: "BatchNorm"

}

layer {
	bottom: "res4b10_branch2b"
	top: "res4b10_branch2b"
	name: "scale4b10_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b10_branch2b"
	bottom: "res4b10_branch2b"
	name: "res4b10_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b10_branch2b"
	top: "res4b10_branch2c"
	name: "res4b10_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b10_branch2c"
	top: "res4b10_branch2c"
	name: "bn4b10_branch2c"
	type: "BatchNorm"

}

layer {
	bottom: "res4b10_branch2c"
	top: "res4b10_branch2c"
	name: "scale4b10_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b9"
	bottom: "res4b10_branch2c"
	top: "res4b10"
	name: "res4b10"
	type: "Eltwise"
}

layer {
	bottom: "res4b10"
	top: "res4b10"
	name: "res4b10_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b10"
	top: "res4b11_branch2a"
	name: "res4b11_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b11_branch2a"
	top: "res4b11_branch2a"
	name: "bn4b11_branch2a"
	type: "BatchNorm"

}

layer {
	bottom: "res4b11_branch2a"
	top: "res4b11_branch2a"
	name: "scale4b11_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b11_branch2a"
	bottom: "res4b11_branch2a"
	name: "res4b11_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b11_branch2a"
	top: "res4b11_branch2b"
	name: "res4b11_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b11_branch2b"
	top: "res4b11_branch2b"
	name: "bn4b11_branch2b"
	type: "BatchNorm"

}

layer {
	bottom: "res4b11_branch2b"
	top: "res4b11_branch2b"
	name: "scale4b11_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b11_branch2b"
	bottom: "res4b11_branch2b"
	name: "res4b11_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b11_branch2b"
	top: "res4b11_branch2c"
	name: "res4b11_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b11_branch2c"
	top: "res4b11_branch2c"
	name: "bn4b11_branch2c"
	type: "BatchNorm"

}

layer {
	bottom: "res4b11_branch2c"
	top: "res4b11_branch2c"
	name: "scale4b11_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b10"
	bottom: "res4b11_branch2c"
	top: "res4b11"
	name: "res4b11"
	type: "Eltwise"
}

layer {
	bottom: "res4b11"
	top: "res4b11"
	name: "res4b11_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b11"
	top: "res4b12_branch2a"
	name: "res4b12_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b12_branch2a"
	top: "res4b12_branch2a"
	name: "bn4b12_branch2a"
	type: "BatchNorm"

}

layer {
	bottom: "res4b12_branch2a"
	top: "res4b12_branch2a"
	name: "scale4b12_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b12_branch2a"
	bottom: "res4b12_branch2a"
	name: "res4b12_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b12_branch2a"
	top: "res4b12_branch2b"
	name: "res4b12_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b12_branch2b"
	top: "res4b12_branch2b"
	name: "bn4b12_branch2b"
	type: "BatchNorm"

}

layer {
	bottom: "res4b12_branch2b"
	top: "res4b12_branch2b"
	name: "scale4b12_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b12_branch2b"
	bottom: "res4b12_branch2b"
	name: "res4b12_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b12_branch2b"
	top: "res4b12_branch2c"
	name: "res4b12_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b12_branch2c"
	top: "res4b12_branch2c"
	name: "bn4b12_branch2c"
	type: "BatchNorm"

}

layer {
	bottom: "res4b12_branch2c"
	top: "res4b12_branch2c"
	name: "scale4b12_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b11"
	bottom: "res4b12_branch2c"
	top: "res4b12"
	name: "res4b12"
	type: "Eltwise"
}

layer {
	bottom: "res4b12"
	top: "res4b12"
	name: "res4b12_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b12"
	top: "res4b13_branch2a"
	name: "res4b13_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b13_branch2a"
	top: "res4b13_branch2a"
	name: "bn4b13_branch2a"
	type: "BatchNorm"

}

layer {
	bottom: "res4b13_branch2a"
	top: "res4b13_branch2a"
	name: "scale4b13_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b13_branch2a"
	bottom: "res4b13_branch2a"
	name: "res4b13_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b13_branch2a"
	top: "res4b13_branch2b"
	name: "res4b13_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b13_branch2b"
	top: "res4b13_branch2b"
	name: "bn4b13_branch2b"
	type: "BatchNorm"

}

layer {
	bottom: "res4b13_branch2b"
	top: "res4b13_branch2b"
	name: "scale4b13_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b13_branch2b"
	bottom: "res4b13_branch2b"
	name: "res4b13_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b13_branch2b"
	top: "res4b13_branch2c"
	name: "res4b13_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b13_branch2c"
	top: "res4b13_branch2c"
	name: "bn4b13_branch2c"
	type: "BatchNorm"

}

layer {
	bottom: "res4b13_branch2c"
	top: "res4b13_branch2c"
	name: "scale4b13_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b12"
	bottom: "res4b13_branch2c"
	top: "res4b13"
	name: "res4b13"
	type: "Eltwise"
}

layer {
	bottom: "res4b13"
	top: "res4b13"
	name: "res4b13_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b13"
	top: "res4b14_branch2a"
	name: "res4b14_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b14_branch2a"
	top: "res4b14_branch2a"
	name: "bn4b14_branch2a"
	type: "BatchNorm"

}

layer {
	bottom: "res4b14_branch2a"
	top: "res4b14_branch2a"
	name: "scale4b14_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b14_branch2a"
	bottom: "res4b14_branch2a"
	name: "res4b14_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b14_branch2a"
	top: "res4b14_branch2b"
	name: "res4b14_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b14_branch2b"
	top: "res4b14_branch2b"
	name: "bn4b14_branch2b"
	type: "BatchNorm"

}

layer {
	bottom: "res4b14_branch2b"
	top: "res4b14_branch2b"
	name: "scale4b14_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b14_branch2b"
	bottom: "res4b14_branch2b"
	name: "res4b14_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b14_branch2b"
	top: "res4b14_branch2c"
	name: "res4b14_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b14_branch2c"
	top: "res4b14_branch2c"
	name: "bn4b14_branch2c"
	type: "BatchNorm"

}

layer {
	bottom: "res4b14_branch2c"
	top: "res4b14_branch2c"
	name: "scale4b14_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b13"
	bottom: "res4b14_branch2c"
	top: "res4b14"
	name: "res4b14"
	type: "Eltwise"
}

layer {
	bottom: "res4b14"
	top: "res4b14"
	name: "res4b14_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b14"
	top: "res4b15_branch2a"
	name: "res4b15_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b15_branch2a"
	top: "res4b15_branch2a"
	name: "bn4b15_branch2a"
	type: "BatchNorm"

}

layer {
	bottom: "res4b15_branch2a"
	top: "res4b15_branch2a"
	name: "scale4b15_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b15_branch2a"
	bottom: "res4b15_branch2a"
	name: "res4b15_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b15_branch2a"
	top: "res4b15_branch2b"
	name: "res4b15_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b15_branch2b"
	top: "res4b15_branch2b"
	name: "bn4b15_branch2b"
	type: "BatchNorm"

}

layer {
	bottom: "res4b15_branch2b"
	top: "res4b15_branch2b"
	name: "scale4b15_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b15_branch2b"
	bottom: "res4b15_branch2b"
	name: "res4b15_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b15_branch2b"
	top: "res4b15_branch2c"
	name: "res4b15_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b15_branch2c"
	top: "res4b15_branch2c"
	name: "bn4b15_branch2c"
	type: "BatchNorm"

}

layer {
	bottom: "res4b15_branch2c"
	top: "res4b15_branch2c"
	name: "scale4b15_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b14"
	bottom: "res4b15_branch2c"
	top: "res4b15"
	name: "res4b15"
	type: "Eltwise"
}

layer {
	bottom: "res4b15"
	top: "res4b15"
	name: "res4b15_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b15"
	top: "res4b16_branch2a"
	name: "res4b16_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b16_branch2a"
	top: "res4b16_branch2a"
	name: "bn4b16_branch2a"
	type: "BatchNorm"

}

layer {
	bottom: "res4b16_branch2a"
	top: "res4b16_branch2a"
	name: "scale4b16_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b16_branch2a"
	bottom: "res4b16_branch2a"
	name: "res4b16_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b16_branch2a"
	top: "res4b16_branch2b"
	name: "res4b16_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b16_branch2b"
	top: "res4b16_branch2b"
	name: "bn4b16_branch2b"
	type: "BatchNorm"

}

layer {
	bottom: "res4b16_branch2b"
	top: "res4b16_branch2b"
	name: "scale4b16_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b16_branch2b"
	bottom: "res4b16_branch2b"
	name: "res4b16_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b16_branch2b"
	top: "res4b16_branch2c"
	name: "res4b16_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b16_branch2c"
	top: "res4b16_branch2c"
	name: "bn4b16_branch2c"
	type: "BatchNorm"

}

layer {
	bottom: "res4b16_branch2c"
	top: "res4b16_branch2c"
	name: "scale4b16_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b15"
	bottom: "res4b16_branch2c"
	top: "res4b16"
	name: "res4b16"
	type: "Eltwise"
}

layer {
	bottom: "res4b16"
	top: "res4b16"
	name: "res4b16_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b16"
	top: "res4b17_branch2a"
	name: "res4b17_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b17_branch2a"
	top: "res4b17_branch2a"
	name: "bn4b17_branch2a"
	type: "BatchNorm"

}

layer {
	bottom: "res4b17_branch2a"
	top: "res4b17_branch2a"
	name: "scale4b17_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b17_branch2a"
	bottom: "res4b17_branch2a"
	name: "res4b17_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b17_branch2a"
	top: "res4b17_branch2b"
	name: "res4b17_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b17_branch2b"
	top: "res4b17_branch2b"
	name: "bn4b17_branch2b"
	type: "BatchNorm"

}

layer {
	bottom: "res4b17_branch2b"
	top: "res4b17_branch2b"
	name: "scale4b17_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b17_branch2b"
	bottom: "res4b17_branch2b"
	name: "res4b17_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b17_branch2b"
	top: "res4b17_branch2c"
	name: "res4b17_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b17_branch2c"
	top: "res4b17_branch2c"
	name: "bn4b17_branch2c"
	type: "BatchNorm"

}

layer {
	bottom: "res4b17_branch2c"
	top: "res4b17_branch2c"
	name: "scale4b17_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b16"
	bottom: "res4b17_branch2c"
	top: "res4b17"
	name: "res4b17"
	type: "Eltwise"
}

layer {
	bottom: "res4b17"
	top: "res4b17"
	name: "res4b17_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b17"
	top: "res4b18_branch2a"
	name: "res4b18_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b18_branch2a"
	top: "res4b18_branch2a"
	name: "bn4b18_branch2a"
	type: "BatchNorm"

}

layer {
	bottom: "res4b18_branch2a"
	top: "res4b18_branch2a"
	name: "scale4b18_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b18_branch2a"
	bottom: "res4b18_branch2a"
	name: "res4b18_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b18_branch2a"
	top: "res4b18_branch2b"
	name: "res4b18_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b18_branch2b"
	top: "res4b18_branch2b"
	name: "bn4b18_branch2b"
	type: "BatchNorm"

}

layer {
	bottom: "res4b18_branch2b"
	top: "res4b18_branch2b"
	name: "scale4b18_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b18_branch2b"
	bottom: "res4b18_branch2b"
	name: "res4b18_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b18_branch2b"
	top: "res4b18_branch2c"
	name: "res4b18_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b18_branch2c"
	top: "res4b18_branch2c"
	name: "bn4b18_branch2c"
	type: "BatchNorm"

}

layer {
	bottom: "res4b18_branch2c"
	top: "res4b18_branch2c"
	name: "scale4b18_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b17"
	bottom: "res4b18_branch2c"
	top: "res4b18"
	name: "res4b18"
	type: "Eltwise"
}

layer {
	bottom: "res4b18"
	top: "res4b18"
	name: "res4b18_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b18"
	top: "res4b19_branch2a"
	name: "res4b19_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b19_branch2a"
	top: "res4b19_branch2a"
	name: "bn4b19_branch2a"
	type: "BatchNorm"

}

layer {
	bottom: "res4b19_branch2a"
	top: "res4b19_branch2a"
	name: "scale4b19_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b19_branch2a"
	bottom: "res4b19_branch2a"
	name: "res4b19_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b19_branch2a"
	top: "res4b19_branch2b"
	name: "res4b19_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b19_branch2b"
	top: "res4b19_branch2b"
	name: "bn4b19_branch2b"
	type: "BatchNorm"

}

layer {
	bottom: "res4b19_branch2b"
	top: "res4b19_branch2b"
	name: "scale4b19_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b19_branch2b"
	bottom: "res4b19_branch2b"
	name: "res4b19_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b19_branch2b"
	top: "res4b19_branch2c"
	name: "res4b19_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b19_branch2c"
	top: "res4b19_branch2c"
	name: "bn4b19_branch2c"
	type: "BatchNorm"

}

layer {
	bottom: "res4b19_branch2c"
	top: "res4b19_branch2c"
	name: "scale4b19_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b18"
	bottom: "res4b19_branch2c"
	top: "res4b19"
	name: "res4b19"
	type: "Eltwise"
}

layer {
	bottom: "res4b19"
	top: "res4b19"
	name: "res4b19_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b19"
	top: "res4b20_branch2a"
	name: "res4b20_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b20_branch2a"
	top: "res4b20_branch2a"
	name: "bn4b20_branch2a"
	type: "BatchNorm"

}

layer {
	bottom: "res4b20_branch2a"
	top: "res4b20_branch2a"
	name: "scale4b20_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b20_branch2a"
	bottom: "res4b20_branch2a"
	name: "res4b20_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b20_branch2a"
	top: "res4b20_branch2b"
	name: "res4b20_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b20_branch2b"
	top: "res4b20_branch2b"
	name: "bn4b20_branch2b"
	type: "BatchNorm"

}

layer {
	bottom: "res4b20_branch2b"
	top: "res4b20_branch2b"
	name: "scale4b20_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b20_branch2b"
	bottom: "res4b20_branch2b"
	name: "res4b20_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b20_branch2b"
	top: "res4b20_branch2c"
	name: "res4b20_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b20_branch2c"
	top: "res4b20_branch2c"
	name: "bn4b20_branch2c"
	type: "BatchNorm"

}

layer {
	bottom: "res4b20_branch2c"
	top: "res4b20_branch2c"
	name: "scale4b20_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b19"
	bottom: "res4b20_branch2c"
	top: "res4b20"
	name: "res4b20"
	type: "Eltwise"
}

layer {
	bottom: "res4b20"
	top: "res4b20"
	name: "res4b20_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b20"
	top: "res4b21_branch2a"
	name: "res4b21_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b21_branch2a"
	top: "res4b21_branch2a"
	name: "bn4b21_branch2a"
	type: "BatchNorm"

}

layer {
	bottom: "res4b21_branch2a"
	top: "res4b21_branch2a"
	name: "scale4b21_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b21_branch2a"
	bottom: "res4b21_branch2a"
	name: "res4b21_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b21_branch2a"
	top: "res4b21_branch2b"
	name: "res4b21_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b21_branch2b"
	top: "res4b21_branch2b"
	name: "bn4b21_branch2b"
	type: "BatchNorm"

}

layer {
	bottom: "res4b21_branch2b"
	top: "res4b21_branch2b"
	name: "scale4b21_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b21_branch2b"
	bottom: "res4b21_branch2b"
	name: "res4b21_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b21_branch2b"
	top: "res4b21_branch2c"
	name: "res4b21_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b21_branch2c"
	top: "res4b21_branch2c"
	name: "bn4b21_branch2c"
	type: "BatchNorm"

}

layer {
	bottom: "res4b21_branch2c"
	top: "res4b21_branch2c"
	name: "scale4b21_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b20"
	bottom: "res4b21_branch2c"
	top: "res4b21"
	name: "res4b21"
	type: "Eltwise"
}

layer {
	bottom: "res4b21"
	top: "res4b21"
	name: "res4b21_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b21"
	top: "res4b22_branch2a"
	name: "res4b22_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b22_branch2a"
	top: "res4b22_branch2a"
	name: "bn4b22_branch2a"
	type: "BatchNorm"

}

layer {
	bottom: "res4b22_branch2a"
	top: "res4b22_branch2a"
	name: "scale4b22_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b22_branch2a"
	bottom: "res4b22_branch2a"
	name: "res4b22_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b22_branch2a"
	top: "res4b22_branch2b"
	name: "res4b22_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 256
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b22_branch2b"
	top: "res4b22_branch2b"
	name: "bn4b22_branch2b"
	type: "BatchNorm"

}

layer {
	bottom: "res4b22_branch2b"
	top: "res4b22_branch2b"
	name: "scale4b22_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res4b22_branch2b"
	bottom: "res4b22_branch2b"
	name: "res4b22_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b22_branch2b"
	top: "res4b22_branch2c"
	name: "res4b22_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res4b22_branch2c"
	top: "res4b22_branch2c"
	name: "bn4b22_branch2c"
	type: "BatchNorm"

}

layer {
	bottom: "res4b22_branch2c"
	top: "res4b22_branch2c"
	name: "scale4b22_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b21"
	bottom: "res4b22_branch2c"
	top: "res4b22"
	name: "res4b22"
	type: "Eltwise"
}

layer {
	bottom: "res4b22"
	top: "res4b22"
	name: "res4b22_relu"
	type: "ReLU"
}

layer {
	bottom: "res4b22"
	top: "res5a_branch1"
	name: "res5a_branch1"
	type: "Convolution"
	convolution_param {
		num_output: 2048
		kernel_size: 1
		pad: 0
		stride: 2
		bias_term: false
	}
}

layer {
	bottom: "res5a_branch1"
	top: "res5a_branch1"
	name: "bn5a_branch1"
	type: "BatchNorm"

}

layer {
	bottom: "res5a_branch1"
	top: "res5a_branch1"
	name: "scale5a_branch1"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res4b22"
	top: "res5a_branch2a"
	name: "res5a_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 512
		kernel_size: 1
		pad: 0
		stride: 2
		bias_term: false
	}
}

layer {
	bottom: "res5a_branch2a"
	top: "res5a_branch2a"
	name: "bn5a_branch2a"
	type: "BatchNorm"

}

layer {
	bottom: "res5a_branch2a"
	top: "res5a_branch2a"
	name: "scale5a_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res5a_branch2a"
	bottom: "res5a_branch2a"
	name: "res5a_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res5a_branch2a"
	top: "res5a_branch2b"
	name: "res5a_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 512
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res5a_branch2b"
	top: "res5a_branch2b"
	name: "bn5a_branch2b"
	type: "BatchNorm"

}

layer {
	bottom: "res5a_branch2b"
	top: "res5a_branch2b"
	name: "scale5a_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res5a_branch2b"
	bottom: "res5a_branch2b"
	name: "res5a_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res5a_branch2b"
	top: "res5a_branch2c"
	name: "res5a_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 2048
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res5a_branch2c"
	top: "res5a_branch2c"
	name: "bn5a_branch2c"
	type: "BatchNorm"

}

layer {
	bottom: "res5a_branch2c"
	top: "res5a_branch2c"
	name: "scale5a_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res5a_branch1"
	bottom: "res5a_branch2c"
	top: "res5a"
	name: "res5a"
	type: "Eltwise"
}

layer {
	bottom: "res5a"
	top: "res5a"
	name: "res5a_relu"
	type: "ReLU"
}

layer {
	bottom: "res5a"
	top: "res5b_branch2a"
	name: "res5b_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 512
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res5b_branch2a"
	top: "res5b_branch2a"
	name: "bn5b_branch2a"
	type: "BatchNorm"

}

layer {
	bottom: "res5b_branch2a"
	top: "res5b_branch2a"
	name: "scale5b_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res5b_branch2a"
	bottom: "res5b_branch2a"
	name: "res5b_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res5b_branch2a"
	top: "res5b_branch2b"
	name: "res5b_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 512
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res5b_branch2b"
	top: "res5b_branch2b"
	name: "bn5b_branch2b"
	type: "BatchNorm"

}

layer {
	bottom: "res5b_branch2b"
	top: "res5b_branch2b"
	name: "scale5b_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res5b_branch2b"
	bottom: "res5b_branch2b"
	name: "res5b_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res5b_branch2b"
	top: "res5b_branch2c"
	name: "res5b_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 2048
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res5b_branch2c"
	top: "res5b_branch2c"
	name: "bn5b_branch2c"
	type: "BatchNorm"

}

layer {
	bottom: "res5b_branch2c"
	top: "res5b_branch2c"
	name: "scale5b_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res5a"
	bottom: "res5b_branch2c"
	top: "res5b"
	name: "res5b"
	type: "Eltwise"
}

layer {
	bottom: "res5b"
	top: "res5b"
	name: "res5b_relu"
	type: "ReLU"
}

layer {
	bottom: "res5b"
	top: "res5c_branch2a"
	name: "res5c_branch2a"
	type: "Convolution"
	convolution_param {
		num_output: 512
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res5c_branch2a"
	top: "res5c_branch2a"
	name: "bn5c_branch2a"
	type: "BatchNorm"

}

layer {
	bottom: "res5c_branch2a"
	top: "res5c_branch2a"
	name: "scale5c_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res5c_branch2a"
	bottom: "res5c_branch2a"
	name: "res5c_branch2a_relu"
	type: "ReLU"
}

layer {
	bottom: "res5c_branch2a"
	top: "res5c_branch2b"
	name: "res5c_branch2b"
	type: "Convolution"
	convolution_param {
		num_output: 512
		kernel_size: 3
		pad: 1
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res5c_branch2b"
	top: "res5c_branch2b"
	name: "bn5c_branch2b"
	type: "BatchNorm"

}

layer {
	bottom: "res5c_branch2b"
	top: "res5c_branch2b"
	name: "scale5c_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	top: "res5c_branch2b"
	bottom: "res5c_branch2b"
	name: "res5c_branch2b_relu"
	type: "ReLU"
}

layer {
	bottom: "res5c_branch2b"
	top: "res5c_branch2c"
	name: "res5c_branch2c"
	type: "Convolution"
	convolution_param {
		num_output: 2048
		kernel_size: 1
		pad: 0
		stride: 1
		bias_term: false
	}
}

layer {
	bottom: "res5c_branch2c"
	top: "res5c_branch2c"
	name: "bn5c_branch2c"
	type: "BatchNorm"

}

layer {
	bottom: "res5c_branch2c"
	top: "res5c_branch2c"
	name: "scale5c_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}

layer {
	bottom: "res5b"
	bottom: "res5c_branch2c"
	top: "res5c"
	name: "res5c"
	type: "Eltwise"
}

layer {
	bottom: "res5c"
	top: "res5c"
	name: "res5c_relu"
	type: "ReLU"
}

# resnet-101 end

########################################################
# result layer 1

layer{
  name: "res5c_predict_conv0"
  type: "Convolution"
  bottom: "res5c"
  top: "res5c_predict_conv0"

  convolution_param {
		num_output: 512
		kernel_size: 1
		pad: 0
		stride: 1
    bias_term: false

    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
	}

  #propagate_down : false
}

layer {
  name: "res5c_predict_conv0_bn"
  type: "BatchNorm"
  bottom: "res5c_predict_conv0"
  top: "res5c_predict_conv0"
}

layer {
	name: "res5c_predict_conv0_scale"
	type: "Scale"

	bottom: "res5c_predict_conv0"
	top: "res5c_predict_conv0"
	
	scale_param {
		bias_term: true
	}
}

layer{
  name: "res5c_predict_conv0_relu"
  type: "ReLU"
  bottom: "res5c_predict_conv0"
  top: "res5c_predict_conv0"
}



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

########################################################
# result layer 2

layer{
  name: "res4b22_predict_conv0"
  type: "Convolution"
  bottom: "res4b22"
  top: "res4b22_predict_conv0"

  convolution_param {
		num_output: 512
		kernel_size: 3
		pad: 1
		stride: 1
    bias_term: false

    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
	}

  #propagate_down : false
}

layer {
  name: "res4b22_predict_conv0_bn"
  type: "BatchNorm"
  bottom: "res4b22_predict_conv0"
  top: "res4b22_predict_conv0"


}

layer {
	name: "res4b22_predict_conv0_scale"
	type: "Scale"

	bottom: "res4b22_predict_conv0"
	top: "res4b22_predict_conv0"
	
	scale_param {
		bias_term: true
	}
}

layer{
  name: "res4b22_predict_conv0_relu"
  type: "ReLU"
  bottom: "res4b22_predict_conv0"
  top: "res4b22_predict_conv0"
}

layer{
  name: "res4b22_predict_conv1"
  type: "Convolution"
  bottom: "res4b22_predict_conv0"
  top: "res4b22_predict_conv1"

  convolution_param {
		num_output: 512
		kernel_size: 3
		pad: 1
		stride: 1
    bias_term: false

    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
	}
}

layer {
  name: "res4b22_predict_conv1_bn"
  type: "BatchNorm"
  bottom: "res4b22_predict_conv1"
  top: "res4b22_predict_conv1"


}

layer {
	name: "res4b22_predict_conv1_scale"
	type: "Scale"

	bottom: "res4b22_predict_conv1"
	top: "res4b22_predict_conv1"
	
	scale_param {
		bias_term: true
	}
}


layer{
  name: "res5c_deconv_deconv1"
  type: "Deconvolution"
  bottom: "res5c_predict_conv0"
  top: "res5c_deconv_deconv1"

  convolution_param {
    num_output: 512
    kernel_size: 2
    pad: 0
    stride: 2

    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}

layer{
  name: "res5c_deconv_conv1"
  type: "Convolution"
  bottom: "res5c_deconv_deconv1"
  top: "res5c_deconv_conv1"

  convolution_param {
    num_output: 512
    kernel_size: 3
    pad: 1
    stride: 1

    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}

layer {
  name: "res5c_deconv_conv1_bn"
  type: "BatchNorm"
  bottom: "res5c_deconv_conv1"
  top: "res5c_deconv_conv1"


}

layer {
	name: "res5c_deconv_conv1_scale"
	type: "Scale"

	bottom: "res5c_deconv_conv1"
	top: "res5c_deconv_conv1"
	
	scale_param {
		bias_term: true
	}
}


layer {
  name: "res5c_deconv_eltwise"
  type: "Eltwise"
	bottom: "res4b22_predict_conv1"
	bottom: "res5c_deconv_conv1"
	top: "res5c_deconv_eltwise"
}

layer{
  name: "res5c_deconv_eltwise_relu"
  type: "ReLU"
  bottom: "res5c_deconv_eltwise"
  top: "res5c_deconv_eltwise"
}

layer{
  name: "res4b22_predict_conv3_0"
  type: "Convolution"
  bottom: "res5c_deconv_eltwise"
  top: "res4b22_predict_conv3_0"

  convolution_param {
		num_output: 512
		kernel_size: 3
		pad: 1
		stride: 1
    bias_term: false

    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
	}
}

layer {
  name: "res4b22_predict_conv3_0_bn"
  type: "BatchNorm"
  bottom: "res4b22_predict_conv3_0"
  top: "res4b22_predict_conv3_0"


}

layer {
	name: "res4b22_predict_conv3_0_scale"
	type: "Scale"

	bottom: "res4b22_predict_conv3_0"
	top: "res4b22_predict_conv3_0"
	
	scale_param {
		bias_term: true
	}
}

layer{
  name: "res4b22_predict_conv3_0_relu"
  type: "ReLU"
  bottom: "res4b22_predict_conv3_0"
  top: "res4b22_predict_conv3_0"
}


#######################################################
# deconv 3

layer{
  name: "res3b3_predict_conv0"
  type: "Convolution"
  bottom: "res3b3"
  top: "res3b3_predict_conv0"

  convolution_param {
		num_output: 512
		kernel_size: 3
		pad: 1
		stride: 1
    bias_term: false

    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
	}

  #propagate_down : false
}

layer {
  name: "res3b3_predict_conv0_bn"
  type: "BatchNorm"
  bottom: "res3b3_predict_conv0"
  top: "res3b3_predict_conv0"
}

layer {
	name: "res3b3_predict_conv0_scale"
	type: "Scale"

	bottom: "res3b3_predict_conv0"
	top: "res3b3_predict_conv0"
	
	scale_param {
		bias_term: true
	}
}

layer{
  name: "res3b3_predict_conv0_relu"
  type: "ReLU"
  bottom: "res3b3_predict_conv0"
  top: "res3b3_predict_conv0"
}

layer{
  name: "res3b3_predict_conv1"
  type: "Convolution"
  bottom: "res3b3_predict_conv0"
  top: "res3b3_predict_conv1"

  convolution_param {
		num_output: 512
		kernel_size: 3
		pad: 1
		stride: 1
    bias_term: false

    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
	}

  #propagate_down : false
}

layer {
  name: "res3b3_predict_conv1_bn"
  type: "BatchNorm"
  bottom: "res3b3_predict_conv1"
  top: "res3b3_predict_conv1"

}

layer {
	name: "res3b3_predict_conv1_scale"
	type: "Scale"

	bottom: "res3b3_predict_conv1"
	top: "res3b3_predict_conv1"
	
	scale_param {
		bias_term: true
	}
}


layer{
  name: "res4b22_deconv_deconv1"
  type: "Deconvolution"
  bottom: "res4b22_predict_conv3_0"
  top: "res4b22_deconv_deconv1"

  convolution_param {
    num_output: 512
    kernel_size: 2
    pad: 0
    stride: 2

    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}

layer{
  name: "res4b22_deconv_conv1"
  type: "Convolution"
  bottom: "res4b22_deconv_deconv1"
  top: "res4b22_deconv_conv1"

  convolution_param {
    num_output: 512
    kernel_size: 3
    pad: 1
    stride: 1

    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}

layer {
  name: "res4b22_deconv_conv1_bn"
  type: "BatchNorm"
  bottom: "res4b22_deconv_conv1"
  top: "res4b22_deconv_conv1"
}

layer {
	name: "res4b22_deconv_conv1_scale"
	type: "Scale"

	bottom: "res4b22_deconv_conv1"
	top: "res4b22_deconv_conv1"
	
	scale_param {
		bias_term: true
	}
}

layer {
  name: "res4b22_deconv_eltwise"
  type: "Eltwise"
	bottom: "res3b3_predict_conv1"
	bottom: "res4b22_deconv_conv1"
	top: "res4b22_deconv_eltwise"
}

layer{
  name: "res4b22_deconv_eltwise_relu"
  type: "ReLU"
  bottom: "res4b22_deconv_eltwise"
  top: "res4b22_deconv_eltwise"
}

layer{
  name: "res3b3_predict_conv2"
  type: "Convolution"
  bottom: "res4b22_deconv_eltwise"
  top: "res3b3_predict_conv2"

  convolution_param {
		num_output: 512
		kernel_size: 3
		pad: 1
		stride: 1
    bias_term: false

    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
	}
}

layer {
  name: "res3b3_predict_conv2_bn"
  type: "BatchNorm"
  bottom: "res3b3_predict_conv2"
  top: "res3b3_predict_conv2"


}

layer {
	name: "res3b3_predict_conv2_scale"
	type: "Scale"

	bottom: "res3b3_predict_conv2"
	top: "res3b3_predict_conv2"
	
	scale_param {
		bias_term: true
	}
}

layer{
  name: "res3b3_predict_conv2_relu"
  type: "ReLU"
  bottom: "res3b3_predict_conv2"
  top: "res3b3_predict_conv2"
}

layer{
  name: "res3b3_deconv_deconv1"
  type: "Deconvolution"
  bottom: "res3b3_predict_conv2"
  top: "res3b3_deconv_deconv1"

  convolution_param {
    num_output: 512
    kernel_size: 2
    pad: 0
    stride: 2

    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}

layer{
  name: "res3b3_deconv_conv1"
  type: "Convolution"
  bottom: "res3b3_deconv_deconv1"
  top: "res3b3_deconv_conv1"

  convolution_param {
    num_output: 512
    kernel_size: 3
    pad: 1
    stride: 1

    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}

layer {
  name: "res3b3_deconv_conv1_bn"
  type: "BatchNorm"
  bottom: "res3b3_deconv_conv1"
  top: "res3b3_deconv_conv1"
}

layer {
	name: "res3b3_deconv_conv1_scale"
	type: "Scale"

	bottom: "res3b3_deconv_conv1"
	top: "res3b3_deconv_conv1"
	
	scale_param {
		bias_term: true
	}
}

layer{
  name: "res2c_predict_conv0"
  type: "Convolution"
  bottom: "res2c"
  top: "res2c_predict_conv0"

  convolution_param {
		num_output: 512
		kernel_size: 3
		pad: 1
		stride: 1
    bias_term: false

    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
	}

  #propagate_down : false
}

layer {
  name: "res2c_predict_conv0_bn"
  type: "BatchNorm"
  bottom: "res2c_predict_conv0"
  top: "res2c_predict_conv0"
}

layer {
	name: "res2c_predict_conv0_scale"
	type: "Scale"

	bottom: "res2c_predict_conv0"
	top: "res2c_predict_conv0"
	
	scale_param {
		bias_term: true
	}
}

layer{
  name: "res2c_predict_conv0_relu"
  type: "ReLU"
  bottom: "res2c_predict_conv0"
  top: "res2c_predict_conv0"
}

layer{
  name: "res2c_predict_conv1"
  type: "Convolution"
  bottom: "res2c_predict_conv0"
  top: "res2c_predict_conv1"

  convolution_param {
		num_output: 512
		kernel_size: 3
		pad: 1
		stride: 1
    bias_term: false

    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
	}

  #propagate_down : false
}

layer {
  name: "res2c_predict_conv1_bn"
  type: "BatchNorm"
  bottom: "res2c_predict_conv1"
  top: "res2c_predict_conv1"

}

layer {
	name: "res2c_predict_conv1_scale"
	type: "Scale"

	bottom: "res2c_predict_conv1"
	top: "res2c_predict_conv1"
	
	scale_param {
		bias_term: true
	}
}

layer {
  name: "res3b3_deconv_eltwise"
  type: "Eltwise"
	bottom: "res3b3_deconv_conv1"
	bottom: "res2c_predict_conv1"
	top: "res3b3_deconv_eltwise"
}

layer{
  name: "res3b3_deconv_eltwise_relu"
  type: "ReLU"
  bottom: "res3b3_deconv_eltwise"
  top: "res3b3_deconv_eltwise"
}

layer{
  name: "res2c_predict_conv2"
  type: "Convolution"
  bottom: "res3b3_deconv_eltwise"
  top: "res2c_predict_conv2"

  convolution_param {
		num_output: 512
		kernel_size: 3
		pad: 1
		stride: 1
    bias_term: false

    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
	}
}

layer {
  name: "res2c_predict_conv2_bn"
  type: "BatchNorm"
  bottom: "res2c_predict_conv2"
  top: "res2c_predict_conv2"


}

layer {
	name: "res2c_predict_conv2_scale"
	type: "Scale"

	bottom: "res2c_predict_conv2"
	top: "res2c_predict_conv2"
	
	scale_param {
		bias_term: true
	}
}

layer{
  name: "res2c_predict_conv2_relu"
  type: "ReLU"
  bottom: "res2c_predict_conv2"
  top: "res2c_predict_conv2"
}


layer{
  name: "res2c_predict_conv3"
  type: "Convolution"
  bottom: "res2c_predict_conv2"
  top: "res2c_predict_conv3"

  convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
    bias_term: false

    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
	}
}

layer {
  name: "res2c_predict_conv3_bn"
  type: "BatchNorm"
  bottom: "res2c_predict_conv3"
  top: "res2c_predict_conv3"


}

layer {
	name: "res2c_predict_conv3_scale"
	type: "Scale"

	bottom: "res2c_predict_conv3"
	top: "res2c_predict_conv3"
	
	scale_param {
		bias_term: true
	}
}

layer{
  name: "res2c_predict_conv3_relu"
  type: "ReLU"
  bottom: "res2c_predict_conv3"
  top: "res2c_predict_conv3"
}

layer{
  name: "res2c_predict_conv4"
  type: "Convolution"
  bottom: "res2c_predict_conv2"
  top: "res2c_predict_conv4"

  convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
    bias_term: false

    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
	}
}

layer {
  name: "res2c_predict_conv4_bn"
  type: "BatchNorm"
  bottom: "res2c_predict_conv4"
  top: "res2c_predict_conv4"


}

layer {
	name: "res2c_predict_conv4_scale"
	type: "Scale"

	bottom: "res2c_predict_conv4"
	top: "res2c_predict_conv4"
	
	scale_param {
		bias_term: true
	}
}

layer{
  name: "res2c_predict_conv4_relu"
  type: "ReLU"
  bottom: "res2c_predict_conv4"
  top: "res2c_predict_conv4"
}

layer{
  name: "res2c_predict_conv5"
  type: "Convolution"
  bottom: "res2c_predict_conv4"
  top: "res2c_predict_conv5"

  convolution_param {
		num_output: 256
		kernel_size: 1
		pad: 0
		stride: 1
    bias_term: false

    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
	}
}

layer {
  name: "res2c_predict_conv5_bn"
  type: "BatchNorm"
  bottom: "res2c_predict_conv5"
  top: "res2c_predict_conv5"


}

layer {
	name: "res2c_predict_conv5_scale"
	type: "Scale"

	bottom: "res2c_predict_conv5"
	top: "res2c_predict_conv5"
	
	scale_param {
		bias_term: true
	}
}

layer{
  name: "res2c_predict_conv5_relu"
  type: "ReLU"
  bottom: "res2c_predict_conv5"
  top: "res2c_predict_conv5"
}

layer{
  name: "res2c_predict_conv6"
  type: "Convolution"
  bottom: "res2c_predict_conv5"
  top: "res2c_predict_conv6"

  convolution_param {
		num_output: 1024
		kernel_size: 1
		pad: 0
		stride: 1
    bias_term: false

    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
	}
}

layer {
  name: "res2c_predict_conv6_bn"
  type: "BatchNorm"
  bottom: "res2c_predict_conv6"
  top: "res2c_predict_conv6"


}

layer {
	name: "res2c_predict_conv6_scale"
	type: "Scale"

	bottom: "res2c_predict_conv6"
	top: "res2c_predict_conv6"
	
	scale_param {
		bias_term: true
	}
}


layer {
  name: "res2c_predict_eltwise"
  type: "Eltwise"
	bottom: "res2c_predict_conv3"
	bottom: "res2c_predict_conv6"
	top: "res2c_predict_eltwise"
}

layer{
  name: "res2c_predict_eltwise_relu"
  type: "ReLU"
  bottom: "res2c_predict_eltwise"
  top: "res2c_predict_eltwise"
}

layer{
  name: "res2c_predict_conv7"
  type: "Convolution"
  bottom: "res2c_predict_eltwise"
  top: "res2c_predict_conv7"

  convolution_param {
		num_output: 36
		kernel_size: 3
		pad: 1
		stride: 1
    bias_term: false

    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
	}
}

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

layer {
	name: "yolo_v2_loss_4"
	type: "YOLOV2FocalLossV4"
	bottom: "res2c_predict_conv7"
	bottom: "label"
	bottom: "bbox"
	top: "y8_loss"
	top: "y8_loss_noobj"
	top: "y8_loss_obj"
	top: "y8_loss_class"
	top: "y8_loss_coord"
	top: "y8_loss_area"
	top: "y8_avg_noobj"
	top: "y8_avg_obj"
	top: "y8_avg_neg_cls"
	top: "y8_avg_pos_cls"
	top: "y8_avg_iou"

	focal_loss_param {
		alpha: 1
		gamma: 2
	}

	yolo_v2_loss_param {
		anchor {
			top_left {
				x: 0
				y: -2
			}
			size {
				width: 4
				height: 8
			}
		}

		anchor {
			top_left {
				x: -2
				y: -6
			}
			size {
				width: 8
				height: 16
			}
		}
		anchor {
			top_left {
				x: -6
				y: -14
			}
			size {
				width: 16
				height: 32
			}
		}
		anchor {
			top_left {
				x: -10
				y: -22
			}
			size {
				width: 24
				height: 48
			}
		}

		num_class: 4
		img_size {
			width: 224
			height: 224
		}
		yolo_map_size {
			width: 56
			height: 56
		}

		overlap_threshold: 0.245
		noobj_scale: 1
		obj_scale: 10
		cls_scale: 1
		coord_scale: 1
	}

	loss_weight: [10, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
}