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@@ -33,3 +33,8 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+face/pose_iter_116000.caffemodel filter=lfs diff=lfs merge=lfs -text
+hand/pose_iter_102000.caffemodel filter=lfs diff=lfs merge=lfs -text
+pose/body_25/pose_iter_584000.caffemodel filter=lfs diff=lfs merge=lfs -text
+pose/coco/pose_iter_440000.caffemodel filter=lfs diff=lfs merge=lfs -text
+pose/mpi/pose_iter_160000.caffemodel filter=lfs diff=lfs merge=lfs -text

cameraParameters/flir/17012332.xml.example

@@ -0,0 +1,28 @@
+<?xml version="1.0"?>
+<!-- Note: Camera matrix translation units are meters. -->
+<opencv_storage>
+<CameraMatrix type_id="opencv-matrix">
+  <rows>3</rows>
+  <cols>4</cols>
+  <dt>d</dt>
+  <data>
+    1. 0. 0. 0.
+    0. 1. 0. 0.
+    0. 0. 1. 0.</data></CameraMatrix>
+<Intrinsics type_id="opencv-matrix">
+  <rows>3</rows>
+  <cols>3</cols>
+  <dt>d</dt>
+  <data>
+    8.1793481631740565e+02 0. 6.0070689997785121e+02 0.
+    8.1651774059837908e+02 5.1784529566329593e+02 0. 0. 1.</data></Intrinsics>
+<Distortion type_id="opencv-matrix">
+  <rows>8</rows>
+  <cols>1</cols>
+  <dt>d</dt>
+  <data>
+    -1.8102158829399091e+00 9.1966147162623262e+00
+    -4.4293900343777355e-04 1.3638377686816653e-03
+    1.3303863414979364e+00 -1.4189051636354870e+00
+    8.4725535468475819e+00 4.7911023525901033e+00</data></Distortion>
+</opencv_storage>

face/pose_deploy.prototxt

@@ -0,0 +1,1728 @@
+input: "image"
+input_dim: 1
+input_dim: 3
+input_dim: 1 # Original: 368
+input_dim: 1 # Original: 368
+# input: "weights"
+# input_dim: 1
+# input_dim: 71
+# input_dim: 184
+# input_dim: 184
+# input: "labels"
+# input_dim: 1
+# input_dim: 71
+# input_dim: 184
+# input_dim: 184
+
+layer {
+  name: "conv1_1"
+  type: "Convolution"
+  bottom: "image"
+  top: "conv1_1"
+  param {
+    lr_mult: 1
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2
+    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: "conv1_1_re"
+  type: "ReLU"
+  bottom: "conv1_1"
+  top: "conv1_1"
+}
+layer {
+  name: "conv1_2"
+  type: "Convolution"
+  bottom: "conv1_1"
+  top: "conv1_2"
+  param {
+    lr_mult: 1
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2
+    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: "conv1_2_re"
+  type: "ReLU"
+  bottom: "conv1_2"
+  top: "conv1_2"
+}
+layer {
+  name: "pool1"
+  type: "Pooling"
+  bottom: "conv1_2"
+  top: "pool1"
+  pooling_param {
+    pool: MAX
+    kernel_size: 2
+    stride: 2
+  }
+}
+layer {
+  name: "conv2_1"
+  type: "Convolution"
+  bottom: "pool1"
+  top: "conv2_1"
+  param {
+    lr_mult: 1
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "conv2_1_re"
+  type: "ReLU"
+  bottom: "conv2_1"
+  top: "conv2_1"
+}
+layer {
+  name: "conv2_2"
+  type: "Convolution"
+  bottom: "conv2_1"
+  top: "conv2_2"
+  param {
+    lr_mult: 1
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "conv2_2_re"
+  type: "ReLU"
+  bottom: "conv2_2"
+  top: "conv2_2"
+}
+layer {
+  name: "pool2"
+  type: "Pooling"
+  bottom: "conv2_2"
+  top: "pool2"
+  pooling_param {
+    pool: MAX
+    kernel_size: 2
+    stride: 2
+  }
+}
+layer {
+  name: "conv3_1"
+  type: "Convolution"
+  bottom: "pool2"
+  top: "conv3_1"
+  param {
+    lr_mult: 1
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2
+    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: "conv3_1_re"
+  type: "ReLU"
+  bottom: "conv3_1"
+  top: "conv3_1"
+}
+layer {
+  name: "conv3_2"
+  type: "Convolution"
+  bottom: "conv3_1"
+  top: "conv3_2"
+  param {
+    lr_mult: 1
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2
+    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: "conv3_2_re"
+  type: "ReLU"
+  bottom: "conv3_2"
+  top: "conv3_2"
+}
+layer {
+  name: "conv3_3"
+  type: "Convolution"
+  bottom: "conv3_2"
+  top: "conv3_3"
+  param {
+    lr_mult: 1
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2
+    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: "conv3_3_re"
+  type: "ReLU"
+  bottom: "conv3_3"
+  top: "conv3_3"
+}
+layer {
+  name: "conv3_4"
+  type: "Convolution"
+  bottom: "conv3_3"
+  top: "conv3_4"
+  param {
+    lr_mult: 1
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2
+    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: "conv3_4_re"
+  type: "ReLU"
+  bottom: "conv3_4"
+  top: "conv3_4"
+}
+layer {
+  name: "pool3"
+  type: "Pooling"
+  bottom: "conv3_4"
+  top: "pool3"
+  pooling_param {
+    pool: MAX
+    kernel_size: 2
+    stride: 2
+  }
+}
+layer {
+  name: "conv4_1"
+  type: "Convolution"
+  bottom: "pool3"
+  top: "conv4_1"
+  param {
+    lr_mult: 1
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 512
+    pad: 1
+    kernel_size: 3
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "conv4_1_re"
+  type: "ReLU"
+  bottom: "conv4_1"
+  top: "conv4_1"
+}
+layer {
+  name: "conv4_2"
+  type: "Convolution"
+  bottom: "conv4_1"
+  top: "conv4_2"
+  param {
+    lr_mult: 1
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 512
+    pad: 1
+    kernel_size: 3
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "conv4_2_re"
+  type: "ReLU"
+  bottom: "conv4_2"
+  top: "conv4_2"
+}
+layer {
+  name: "conv4_3"
+  type: "Convolution"
+  bottom: "conv4_2"
+  top: "conv4_3"
+  param {
+    lr_mult: 1
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 512
+    pad: 1
+    kernel_size: 3
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "conv4_3_re"
+  type: "ReLU"
+  bottom: "conv4_3"
+  top: "conv4_3"
+}
+layer {
+  name: "conv4_4"
+  type: "Convolution"
+  bottom: "conv4_3"
+  top: "conv4_4"
+  param {
+    lr_mult: 1
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 512
+    pad: 1
+    kernel_size: 3
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "conv4_4_re"
+  type: "ReLU"
+  bottom: "conv4_4"
+  top: "conv4_4"
+}
+layer {
+  name: "conv5_1"
+  type: "Convolution"
+  bottom: "conv4_4"
+  top: "conv5_1"
+  param {
+    lr_mult: 1
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 512
+    pad: 1
+    kernel_size: 3
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "conv5_1_re"
+  type: "ReLU"
+  bottom: "conv5_1"
+  top: "conv5_1"
+}
+layer {
+  name: "conv5_2"
+  type: "Convolution"
+  bottom: "conv5_1"
+  top: "conv5_2"
+  param {
+    lr_mult: 1
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 512
+    pad: 1
+    kernel_size: 3
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "conv5_2_re"
+  type: "ReLU"
+  bottom: "conv5_2"
+  top: "conv5_2"
+}
+layer {
+  name: "conv5_3_CPM"
+  type: "Convolution"
+  bottom: "conv5_2"
+  top: "conv5_3_CPM"
+  param {
+    lr_mult: 1
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "conv5_3_CPM_re"
+  type: "ReLU"
+  bottom: "conv5_3_CPM"
+  top: "conv5_3_CPM"
+}
+layer {
+  name: "conv6_1_CPM"
+  type: "Convolution"
+  bottom: "conv5_3_CPM"
+  top: "conv6_1_CPM"
+  param {
+    lr_mult: 1
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2
+    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: "conv6_1_CPM_re"
+  type: "ReLU"
+  bottom: "conv6_1_CPM"
+  top: "conv6_1_CPM"
+}
+layer {
+  name: "conv6_2_CPM"
+  type: "Convolution"
+  bottom: "conv6_1_CPM"
+  top: "conv6_2_CPM"
+  param {
+    lr_mult: 1
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 71
+    pad: 0
+    kernel_size: 1
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "features_in_stage_2"
+  type: "Concat"
+  bottom: "conv6_2_CPM"
+  bottom: "conv5_3_CPM"
+  top: "features_in_stage_2"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "Mconv1_stage2"
+  type: "Convolution"
+  bottom: "features_in_stage_2"
+  top: "Mconv1_stage2"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mconv1_stage2_re"
+  type: "ReLU"
+  bottom: "Mconv1_stage2"
+  top: "Mconv1_stage2"
+}
+layer {
+  name: "Mconv2_stage2"
+  type: "Convolution"
+  bottom: "Mconv1_stage2"
+  top: "Mconv2_stage2"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mconv2_stage2_re"
+  type: "ReLU"
+  bottom: "Mconv2_stage2"
+  top: "Mconv2_stage2"
+}
+layer {
+  name: "Mconv3_stage2"
+  type: "Convolution"
+  bottom: "Mconv2_stage2"
+  top: "Mconv3_stage2"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mconv3_stage2_re"
+  type: "ReLU"
+  bottom: "Mconv3_stage2"
+  top: "Mconv3_stage2"
+}
+layer {
+  name: "Mconv4_stage2"
+  type: "Convolution"
+  bottom: "Mconv3_stage2"
+  top: "Mconv4_stage2"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mconv4_stage2_re"
+  type: "ReLU"
+  bottom: "Mconv4_stage2"
+  top: "Mconv4_stage2"
+}
+layer {
+  name: "Mconv5_stage2"
+  type: "Convolution"
+  bottom: "Mconv4_stage2"
+  top: "Mconv5_stage2"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mconv5_stage2_re"
+  type: "ReLU"
+  bottom: "Mconv5_stage2"
+  top: "Mconv5_stage2"
+}
+layer {
+  name: "Mconv6_stage2"
+  type: "Convolution"
+  bottom: "Mconv5_stage2"
+  top: "Mconv6_stage2"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 0
+    kernel_size: 1
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mconv6_stage2_re"
+  type: "ReLU"
+  bottom: "Mconv6_stage2"
+  top: "Mconv6_stage2"
+}
+layer {
+  name: "Mconv7_stage2"
+  type: "Convolution"
+  bottom: "Mconv6_stage2"
+  top: "Mconv7_stage2"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 71
+    pad: 0
+    kernel_size: 1
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "features_in_stage_3"
+  type: "Concat"
+  bottom: "Mconv7_stage2"
+  bottom: "conv5_3_CPM"
+  top: "features_in_stage_3"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "Mconv1_stage3"
+  type: "Convolution"
+  bottom: "features_in_stage_3"
+  top: "Mconv1_stage3"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mconv1_stage3_re"
+  type: "ReLU"
+  bottom: "Mconv1_stage3"
+  top: "Mconv1_stage3"
+}
+layer {
+  name: "Mconv2_stage3"
+  type: "Convolution"
+  bottom: "Mconv1_stage3"
+  top: "Mconv2_stage3"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mconv2_stage3_re"
+  type: "ReLU"
+  bottom: "Mconv2_stage3"
+  top: "Mconv2_stage3"
+}
+layer {
+  name: "Mconv3_stage3"
+  type: "Convolution"
+  bottom: "Mconv2_stage3"
+  top: "Mconv3_stage3"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mconv3_stage3_re"
+  type: "ReLU"
+  bottom: "Mconv3_stage3"
+  top: "Mconv3_stage3"
+}
+layer {
+  name: "Mconv4_stage3"
+  type: "Convolution"
+  bottom: "Mconv3_stage3"
+  top: "Mconv4_stage3"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mconv4_stage3_re"
+  type: "ReLU"
+  bottom: "Mconv4_stage3"
+  top: "Mconv4_stage3"
+}
+layer {
+  name: "Mconv5_stage3"
+  type: "Convolution"
+  bottom: "Mconv4_stage3"
+  top: "Mconv5_stage3"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mconv5_stage3_re"
+  type: "ReLU"
+  bottom: "Mconv5_stage3"
+  top: "Mconv5_stage3"
+}
+layer {
+  name: "Mconv6_stage3"
+  type: "Convolution"
+  bottom: "Mconv5_stage3"
+  top: "Mconv6_stage3"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 0
+    kernel_size: 1
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mconv6_stage3_re"
+  type: "ReLU"
+  bottom: "Mconv6_stage3"
+  top: "Mconv6_stage3"
+}
+layer {
+  name: "Mconv7_stage3"
+  type: "Convolution"
+  bottom: "Mconv6_stage3"
+  top: "Mconv7_stage3"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 71
+    pad: 0
+    kernel_size: 1
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "features_in_stage_4"
+  type: "Concat"
+  bottom: "Mconv7_stage3"
+  bottom: "conv5_3_CPM"
+  top: "features_in_stage_4"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "Mconv1_stage4"
+  type: "Convolution"
+  bottom: "features_in_stage_4"
+  top: "Mconv1_stage4"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mconv1_stage4_re"
+  type: "ReLU"
+  bottom: "Mconv1_stage4"
+  top: "Mconv1_stage4"
+}
+layer {
+  name: "Mconv2_stage4"
+  type: "Convolution"
+  bottom: "Mconv1_stage4"
+  top: "Mconv2_stage4"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mconv2_stage4_re"
+  type: "ReLU"
+  bottom: "Mconv2_stage4"
+  top: "Mconv2_stage4"
+}
+layer {
+  name: "Mconv3_stage4"
+  type: "Convolution"
+  bottom: "Mconv2_stage4"
+  top: "Mconv3_stage4"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mconv3_stage4_re"
+  type: "ReLU"
+  bottom: "Mconv3_stage4"
+  top: "Mconv3_stage4"
+}
+layer {
+  name: "Mconv4_stage4"
+  type: "Convolution"
+  bottom: "Mconv3_stage4"
+  top: "Mconv4_stage4"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mconv4_stage4_re"
+  type: "ReLU"
+  bottom: "Mconv4_stage4"
+  top: "Mconv4_stage4"
+}
+layer {
+  name: "Mconv5_stage4"
+  type: "Convolution"
+  bottom: "Mconv4_stage4"
+  top: "Mconv5_stage4"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mconv5_stage4_re"
+  type: "ReLU"
+  bottom: "Mconv5_stage4"
+  top: "Mconv5_stage4"
+}
+layer {
+  name: "Mconv6_stage4"
+  type: "Convolution"
+  bottom: "Mconv5_stage4"
+  top: "Mconv6_stage4"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 0
+    kernel_size: 1
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mconv6_stage4_re"
+  type: "ReLU"
+  bottom: "Mconv6_stage4"
+  top: "Mconv6_stage4"
+}
+layer {
+  name: "Mconv7_stage4"
+  type: "Convolution"
+  bottom: "Mconv6_stage4"
+  top: "Mconv7_stage4"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 71
+    pad: 0
+    kernel_size: 1
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "features_in_stage_5"
+  type: "Concat"
+  bottom: "Mconv7_stage4"
+  bottom: "conv5_3_CPM"
+  top: "features_in_stage_5"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "Mconv1_stage5"
+  type: "Convolution"
+  bottom: "features_in_stage_5"
+  top: "Mconv1_stage5"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mconv1_stage5_re"
+  type: "ReLU"
+  bottom: "Mconv1_stage5"
+  top: "Mconv1_stage5"
+}
+layer {
+  name: "Mconv2_stage5"
+  type: "Convolution"
+  bottom: "Mconv1_stage5"
+  top: "Mconv2_stage5"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mconv2_stage5_re"
+  type: "ReLU"
+  bottom: "Mconv2_stage5"
+  top: "Mconv2_stage5"
+}
+layer {
+  name: "Mconv3_stage5"
+  type: "Convolution"
+  bottom: "Mconv2_stage5"
+  top: "Mconv3_stage5"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mconv3_stage5_re"
+  type: "ReLU"
+  bottom: "Mconv3_stage5"
+  top: "Mconv3_stage5"
+}
+layer {
+  name: "Mconv4_stage5"
+  type: "Convolution"
+  bottom: "Mconv3_stage5"
+  top: "Mconv4_stage5"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mconv4_stage5_re"
+  type: "ReLU"
+  bottom: "Mconv4_stage5"
+  top: "Mconv4_stage5"
+}
+layer {
+  name: "Mconv5_stage5"
+  type: "Convolution"
+  bottom: "Mconv4_stage5"
+  top: "Mconv5_stage5"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mconv5_stage5_re"
+  type: "ReLU"
+  bottom: "Mconv5_stage5"
+  top: "Mconv5_stage5"
+}
+layer {
+  name: "Mconv6_stage5"
+  type: "Convolution"
+  bottom: "Mconv5_stage5"
+  top: "Mconv6_stage5"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 0
+    kernel_size: 1
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mconv6_stage5_re"
+  type: "ReLU"
+  bottom: "Mconv6_stage5"
+  top: "Mconv6_stage5"
+}
+layer {
+  name: "Mconv7_stage5"
+  type: "Convolution"
+  bottom: "Mconv6_stage5"
+  top: "Mconv7_stage5"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 71
+    pad: 0
+    kernel_size: 1
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "features_in_stage_6"
+  type: "Concat"
+  bottom: "Mconv7_stage5"
+  bottom: "conv5_3_CPM"
+  top: "features_in_stage_6"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "Mconv1_stage6"
+  type: "Convolution"
+  bottom: "features_in_stage_6"
+  top: "Mconv1_stage6"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mconv1_stage6_re"
+  type: "ReLU"
+  bottom: "Mconv1_stage6"
+  top: "Mconv1_stage6"
+}
+layer {
+  name: "Mconv2_stage6"
+  type: "Convolution"
+  bottom: "Mconv1_stage6"
+  top: "Mconv2_stage6"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mconv2_stage6_re"
+  type: "ReLU"
+  bottom: "Mconv2_stage6"
+  top: "Mconv2_stage6"
+}
+layer {
+  name: "Mconv3_stage6"
+  type: "Convolution"
+  bottom: "Mconv2_stage6"
+  top: "Mconv3_stage6"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mconv3_stage6_re"
+  type: "ReLU"
+  bottom: "Mconv3_stage6"
+  top: "Mconv3_stage6"
+}
+layer {
+  name: "Mconv4_stage6"
+  type: "Convolution"
+  bottom: "Mconv3_stage6"
+  top: "Mconv4_stage6"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mconv4_stage6_re"
+  type: "ReLU"
+  bottom: "Mconv4_stage6"
+  top: "Mconv4_stage6"
+}
+layer {
+  name: "Mconv5_stage6"
+  type: "Convolution"
+  bottom: "Mconv4_stage6"
+  top: "Mconv5_stage6"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mconv5_stage6_re"
+  type: "ReLU"
+  bottom: "Mconv5_stage6"
+  top: "Mconv5_stage6"
+}
+layer {
+  name: "Mconv6_stage6"
+  type: "Convolution"
+  bottom: "Mconv5_stage6"
+  top: "Mconv6_stage6"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 0
+    kernel_size: 1
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mconv6_stage6_re"
+  type: "ReLU"
+  bottom: "Mconv6_stage6"
+  top: "Mconv6_stage6"
+}
+layer {
+  name: "Mconv7_stage6"
+  type: "Convolution"
+  bottom: "Mconv6_stage6"
+#   top: "Mconv7_stage6"
+  top: "net_output"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 71
+    pad: 0
+    kernel_size: 1
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}

face/pose_iter_116000.caffemodel

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a60d12d5216fae25fbe605db317a75e6f9dc797a2eed0d23577b21cda8aa3510
+size 153717332

getModels.bat

@@ -0,0 +1,43 @@
+:: Avoid printing all the comments in the Windows cmd
+@echo off
+
+echo ------------------------- BODY, FOOT, FACE, AND HAND MODELS -------------------------
+echo ----- Downloading body pose (COCO and MPI), face and hand models -----
+SET WGET_EXE=..\3rdparty\windows\wget\wget.exe
+SET OPENPOSE_URL=http://vcl.snu.ac.kr/OpenPose/models/
+SET POSE_FOLDER=pose/
+SET FACE_FOLDER=face/
+SET HAND_FOLDER=hand/
+
+echo:
+echo ------------------------- POSE (BODY+FOOT) MODELS -------------------------
+echo Body (BODY_25)
+set BODY_25_FOLDER=%POSE_FOLDER%body_25/
+set BODY_25_MODEL=%BODY_25_FOLDER%pose_iter_584000.caffemodel
+%WGET_EXE% -c %OPENPOSE_URL%%BODY_25_MODEL% -P %BODY_25_FOLDER%
+
+echo Body (COCO)
+SET COCO_FOLDER=%POSE_FOLDER%coco/
+SET COCO_MODEL=%COCO_FOLDER%pose_iter_440000.caffemodel
+%WGET_EXE% -c %OPENPOSE_URL%%COCO_MODEL% -P %COCO_FOLDER%
+
+echo:
+echo Body (MPI)
+SET MPI_FOLDER=%POSE_FOLDER%mpi/
+SET MPI_MODEL=%MPI_FOLDER%pose_iter_160000.caffemodel
+%WGET_EXE% -c %OPENPOSE_URL%%MPI_MODEL% -P %MPI_FOLDER%
+echo ----------------------- POSE DOWNLOADED -----------------------
+
+echo:
+echo ------------------------- FACE MODELS -------------------------
+echo Face
+SET FACE_MODEL=%FACE_FOLDER%pose_iter_116000.caffemodel
+%WGET_EXE% -c %OPENPOSE_URL%%FACE_MODEL% -P %FACE_FOLDER%
+echo ----------------------- FACE DOWNLOADED -----------------------
+
+echo:
+echo ------------------------- HAND MODELS -------------------------
+echo Hand
+SET HAND_MODEL=%HAND_FOLDER%pose_iter_102000.caffemodel
+%WGET_EXE% -c %OPENPOSE_URL%%HAND_MODEL% -P %HAND_FOLDER%
+echo ----------------------- HAND DOWNLOADED -----------------------

getModels.sh

@@ -0,0 +1,36 @@
+# ------------------------- BODY, FOOT, FACE, AND HAND MODELS -------------------------
+# Downloading body pose (COCO and MPI), face and hand models
+OPENPOSE_URL="http://vcl.snu.ac.kr/OpenPose/models/"
+POSE_FOLDER="pose/"
+FACE_FOLDER="face/"
+HAND_FOLDER="hand/"
+
+# ------------------------- POSE (BODY+FOOT) MODELS -------------------------
+# Body (BODY_25)
+BODY_25_FOLDER=${POSE_FOLDER}"body_25/"
+BODY_25_MODEL=${BODY_25_FOLDER}"pose_iter_584000.caffemodel"
+wget -c ${OPENPOSE_URL}${BODY_25_MODEL} -P ${BODY_25_FOLDER}
+
+# Body (COCO)
+COCO_FOLDER=${POSE_FOLDER}"coco/"
+COCO_MODEL=${COCO_FOLDER}"pose_iter_440000.caffemodel"
+wget -c ${OPENPOSE_URL}${COCO_MODEL} -P ${COCO_FOLDER}
+# Alternative: it will not check whether file was fully downloaded
+# if [ ! -f $COCO_MODEL ]; then
+#     wget ${OPENPOSE_URL}$COCO_MODEL -P $COCO_FOLDER
+# fi
+
+# Body (MPI)
+MPI_FOLDER=${POSE_FOLDER}"mpi/"
+MPI_MODEL=${MPI_FOLDER}"pose_iter_160000.caffemodel"
+wget -c ${OPENPOSE_URL}${MPI_MODEL} -P ${MPI_FOLDER}
+
+# "------------------------- FACE MODELS -------------------------"
+# Face
+FACE_MODEL=${FACE_FOLDER}"pose_iter_116000.caffemodel"
+wget -c ${OPENPOSE_URL}${FACE_MODEL} -P ${FACE_FOLDER}
+
+# "------------------------- HAND MODELS -------------------------"
+# Hand
+HAND_MODEL=$HAND_FOLDER"pose_iter_102000.caffemodel"
+wget -c ${OPENPOSE_URL}${HAND_MODEL} -P ${HAND_FOLDER}

hand/pose_deploy.prototxt

@@ -0,0 +1,1756 @@
+input: "image"
+input_dim: 1 # Original: 2
+input_dim: 3 # It crashes if not left to 3
+input_dim: 1 # Original: 368
+input_dim: 1 # Original: 368
+layer {
+  name: "conv1_1"
+  type: "Convolution"
+  bottom: "image"
+  top: "conv1_1"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 64
+    pad: 1
+    kernel_size: 3
+    weight_filler {
+      type: "xavier"
+    }
+    bias_filler {
+      type: "constant"
+    }
+    dilation: 1
+  }
+}
+layer {
+  name: "relu1_1"
+  type: "ReLU"
+  bottom: "conv1_1"
+  top: "conv1_1"
+}
+layer {
+  name: "conv1_2"
+  type: "Convolution"
+  bottom: "conv1_1"
+  top: "conv1_2"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 64
+    pad: 1
+    kernel_size: 3
+    weight_filler {
+      type: "xavier"
+    }
+    bias_filler {
+      type: "constant"
+    }
+    dilation: 1
+  }
+}
+layer {
+  name: "relu1_2"
+  type: "ReLU"
+  bottom: "conv1_2"
+  top: "conv1_2"
+}
+layer {
+  name: "pool1_stage1"
+  type: "Pooling"
+  bottom: "conv1_2"
+  top: "pool1_stage1"
+  pooling_param {
+    pool: MAX
+    kernel_size: 2
+    stride: 2
+  }
+}
+layer {
+  name: "conv2_1"
+  type: "Convolution"
+  bottom: "pool1_stage1"
+  top: "conv2_1"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+    weight_filler {
+      type: "xavier"
+    }
+    bias_filler {
+      type: "constant"
+    }
+    dilation: 1
+  }
+}
+layer {
+  name: "relu2_1"
+  type: "ReLU"
+  bottom: "conv2_1"
+  top: "conv2_1"
+}
+layer {
+  name: "conv2_2"
+  type: "Convolution"
+  bottom: "conv2_1"
+  top: "conv2_2"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+    weight_filler {
+      type: "xavier"
+    }
+    bias_filler {
+      type: "constant"
+    }
+    dilation: 1
+  }
+}
+layer {
+  name: "relu2_2"
+  type: "ReLU"
+  bottom: "conv2_2"
+  top: "conv2_2"
+}
+layer {
+  name: "pool2_stage1"
+  type: "Pooling"
+  bottom: "conv2_2"
+  top: "pool2_stage1"
+  pooling_param {
+    pool: MAX
+    kernel_size: 2
+    stride: 2
+  }
+}
+layer {
+  name: "conv3_1"
+  type: "Convolution"
+  bottom: "pool2_stage1"
+  top: "conv3_1"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 256
+    pad: 1
+    kernel_size: 3
+    weight_filler {
+      type: "xavier"
+    }
+    bias_filler {
+      type: "constant"
+    }
+    dilation: 1
+  }
+}
+layer {
+  name: "relu3_1"
+  type: "ReLU"
+  bottom: "conv3_1"
+  top: "conv3_1"
+}
+layer {
+  name: "conv3_2"
+  type: "Convolution"
+  bottom: "conv3_1"
+  top: "conv3_2"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 256
+    pad: 1
+    kernel_size: 3
+    weight_filler {
+      type: "xavier"
+    }
+    bias_filler {
+      type: "constant"
+    }
+    dilation: 1
+  }
+}
+layer {
+  name: "relu3_2"
+  type: "ReLU"
+  bottom: "conv3_2"
+  top: "conv3_2"
+}
+layer {
+  name: "conv3_3"
+  type: "Convolution"
+  bottom: "conv3_2"
+  top: "conv3_3"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 256
+    pad: 1
+    kernel_size: 3
+    weight_filler {
+      type: "xavier"
+    }
+    bias_filler {
+      type: "constant"
+    }
+    dilation: 1
+  }
+}
+layer {
+  name: "relu3_3"
+  type: "ReLU"
+  bottom: "conv3_3"
+  top: "conv3_3"
+}
+layer {
+  name: "conv3_4"
+  type: "Convolution"
+  bottom: "conv3_3"
+  top: "conv3_4"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 256
+    pad: 1
+    kernel_size: 3
+    weight_filler {
+      type: "xavier"
+    }
+    bias_filler {
+      type: "constant"
+    }
+    dilation: 1
+  }
+}
+layer {
+  name: "relu3_4"
+  type: "ReLU"
+  bottom: "conv3_4"
+  top: "conv3_4"
+}
+layer {
+  name: "pool3_stage1"
+  type: "Pooling"
+  bottom: "conv3_4"
+  top: "pool3_stage1"
+  pooling_param {
+    pool: MAX
+    kernel_size: 2
+    stride: 2
+  }
+}
+layer {
+  name: "conv4_1"
+  type: "Convolution"
+  bottom: "pool3_stage1"
+  top: "conv4_1"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 512
+    pad: 1
+    kernel_size: 3
+    weight_filler {
+      type: "xavier"
+    }
+    bias_filler {
+      type: "constant"
+    }
+    dilation: 1
+  }
+}
+layer {
+  name: "relu4_1"
+  type: "ReLU"
+  bottom: "conv4_1"
+  top: "conv4_1"
+}
+layer {
+  name: "conv4_2"
+  type: "Convolution"
+  bottom: "conv4_1"
+  top: "conv4_2"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 512
+    pad: 1
+    kernel_size: 3
+    weight_filler {
+      type: "xavier"
+    }
+    bias_filler {
+      type: "constant"
+    }
+    dilation: 1
+  }
+}
+layer {
+  name: "relu4_2"
+  type: "ReLU"
+  bottom: "conv4_2"
+  top: "conv4_2"
+}
+layer {
+  name: "conv4_3"
+  type: "Convolution"
+  bottom: "conv4_2"
+  top: "conv4_3"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 512
+    pad: 1
+    kernel_size: 3
+    weight_filler {
+      type: "xavier"
+    }
+    bias_filler {
+      type: "constant"
+    }
+    dilation: 1
+  }
+}
+layer {
+  name: "relu4_3"
+  type: "ReLU"
+  bottom: "conv4_3"
+  top: "conv4_3"
+}
+layer {
+  name: "conv4_4"
+  type: "Convolution"
+  bottom: "conv4_3"
+  top: "conv4_4"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 512
+    pad: 1
+    kernel_size: 3
+    weight_filler {
+      type: "xavier"
+    }
+    bias_filler {
+      type: "constant"
+    }
+    dilation: 1
+  }
+}
+layer {
+  name: "relu4_4"
+  type: "ReLU"
+  bottom: "conv4_4"
+  top: "conv4_4"
+}
+layer {
+  name: "conv5_1"
+  type: "Convolution"
+  bottom: "conv4_4"
+  top: "conv5_1"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 512
+    pad: 1
+    kernel_size: 3
+    weight_filler {
+      type: "xavier"
+    }
+    bias_filler {
+      type: "constant"
+    }
+    dilation: 1
+  }
+}
+layer {
+  name: "relu5_1"
+  type: "ReLU"
+  bottom: "conv5_1"
+  top: "conv5_1"
+}
+layer {
+  name: "conv5_2"
+  type: "Convolution"
+  bottom: "conv5_1"
+  top: "conv5_2"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 512
+    pad: 1
+    kernel_size: 3
+    weight_filler {
+      type: "xavier"
+    }
+    bias_filler {
+      type: "constant"
+    }
+    dilation: 1
+  }
+}
+layer {
+  name: "relu5_2"
+  type: "ReLU"
+  bottom: "conv5_2"
+  top: "conv5_2"
+}
+layer {
+  name: "conv5_3_CPM"
+  type: "Convolution"
+  bottom: "conv5_2"
+  top: "conv5_3_CPM"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+    dilation: 1
+  }
+}
+layer {
+  name: "relu5_4_stage1_3"
+  type: "ReLU"
+  bottom: "conv5_3_CPM"
+  top: "conv5_3_CPM"
+}
+layer {
+  name: "conv6_1_CPM"
+  type: "Convolution"
+  bottom: "conv5_3_CPM"
+  top: "conv6_1_CPM"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 512
+    pad: 0
+    kernel_size: 1
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+    dilation: 1
+  }
+}
+layer {
+  name: "relu6_4_stage1_1"
+  type: "ReLU"
+  bottom: "conv6_1_CPM"
+  top: "conv6_1_CPM"
+}
+layer {
+  name: "conv6_2_CPM"
+  type: "Convolution"
+  bottom: "conv6_1_CPM"
+  top: "conv6_2_CPM"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 22
+    pad: 0
+    kernel_size: 1
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+    dilation: 1
+  }
+}
+layer {
+  name: "concat_stage2"
+  type: "Concat"
+  bottom: "conv6_2_CPM"
+  bottom: "conv5_3_CPM"
+  top: "concat_stage2"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "Mconv1_stage2"
+  type: "Convolution"
+  bottom: "concat_stage2"
+  top: "Mconv1_stage2"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+    dilation: 1
+  }
+}
+layer {
+  name: "Mrelu1_2_stage2_1"
+  type: "ReLU"
+  bottom: "Mconv1_stage2"
+  top: "Mconv1_stage2"
+}
+layer {
+  name: "Mconv2_stage2"
+  type: "Convolution"
+  bottom: "Mconv1_stage2"
+  top: "Mconv2_stage2"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+    dilation: 1
+  }
+}
+layer {
+  name: "Mrelu1_3_stage2_2"
+  type: "ReLU"
+  bottom: "Mconv2_stage2"
+  top: "Mconv2_stage2"
+}
+layer {
+  name: "Mconv3_stage2"
+  type: "Convolution"
+  bottom: "Mconv2_stage2"
+  top: "Mconv3_stage2"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+    dilation: 1
+  }
+}
+layer {
+  name: "Mrelu1_4_stage2_3"
+  type: "ReLU"
+  bottom: "Mconv3_stage2"
+  top: "Mconv3_stage2"
+}
+layer {
+  name: "Mconv4_stage2"
+  type: "Convolution"
+  bottom: "Mconv3_stage2"
+  top: "Mconv4_stage2"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+    dilation: 1
+  }
+}
+layer {
+  name: "Mrelu1_5_stage2_4"
+  type: "ReLU"
+  bottom: "Mconv4_stage2"
+  top: "Mconv4_stage2"
+}
+layer {
+  name: "Mconv5_stage2"
+  type: "Convolution"
+  bottom: "Mconv4_stage2"
+  top: "Mconv5_stage2"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+    dilation: 1
+  }
+}
+layer {
+  name: "Mrelu1_6_stage2_5"
+  type: "ReLU"
+  bottom: "Mconv5_stage2"
+  top: "Mconv5_stage2"
+}
+layer {
+  name: "Mconv6_stage2"
+  type: "Convolution"
+  bottom: "Mconv5_stage2"
+  top: "Mconv6_stage2"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 0
+    kernel_size: 1
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+    dilation: 1
+  }
+}
+layer {
+  name: "Mrelu1_7_stage2_6"
+  type: "ReLU"
+  bottom: "Mconv6_stage2"
+  top: "Mconv6_stage2"
+}
+layer {
+  name: "Mconv7_stage2"
+  type: "Convolution"
+  bottom: "Mconv6_stage2"
+  top: "Mconv7_stage2"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 22
+    pad: 0
+    kernel_size: 1
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+    dilation: 1
+  }
+}
+layer {
+  name: "concat_stage3"
+  type: "Concat"
+  bottom: "Mconv7_stage2"
+  bottom: "conv5_3_CPM"
+  top: "concat_stage3"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "Mconv1_stage3"
+  type: "Convolution"
+  bottom: "concat_stage3"
+  top: "Mconv1_stage3"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+    dilation: 1
+  }
+}
+layer {
+  name: "Mrelu1_2_stage3_1"
+  type: "ReLU"
+  bottom: "Mconv1_stage3"
+  top: "Mconv1_stage3"
+}
+layer {
+  name: "Mconv2_stage3"
+  type: "Convolution"
+  bottom: "Mconv1_stage3"
+  top: "Mconv2_stage3"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+    dilation: 1
+  }
+}
+layer {
+  name: "Mrelu1_3_stage3_2"
+  type: "ReLU"
+  bottom: "Mconv2_stage3"
+  top: "Mconv2_stage3"
+}
+layer {
+  name: "Mconv3_stage3"
+  type: "Convolution"
+  bottom: "Mconv2_stage3"
+  top: "Mconv3_stage3"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+    dilation: 1
+  }
+}
+layer {
+  name: "Mrelu1_4_stage3_3"
+  type: "ReLU"
+  bottom: "Mconv3_stage3"
+  top: "Mconv3_stage3"
+}
+layer {
+  name: "Mconv4_stage3"
+  type: "Convolution"
+  bottom: "Mconv3_stage3"
+  top: "Mconv4_stage3"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+    dilation: 1
+  }
+}
+layer {
+  name: "Mrelu1_5_stage3_4"
+  type: "ReLU"
+  bottom: "Mconv4_stage3"
+  top: "Mconv4_stage3"
+}
+layer {
+  name: "Mconv5_stage3"
+  type: "Convolution"
+  bottom: "Mconv4_stage3"
+  top: "Mconv5_stage3"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+    dilation: 1
+  }
+}
+layer {
+  name: "Mrelu1_6_stage3_5"
+  type: "ReLU"
+  bottom: "Mconv5_stage3"
+  top: "Mconv5_stage3"
+}
+layer {
+  name: "Mconv6_stage3"
+  type: "Convolution"
+  bottom: "Mconv5_stage3"
+  top: "Mconv6_stage3"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 0
+    kernel_size: 1
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+    dilation: 1
+  }
+}
+layer {
+  name: "Mrelu1_7_stage3_6"
+  type: "ReLU"
+  bottom: "Mconv6_stage3"
+  top: "Mconv6_stage3"
+}
+layer {
+  name: "Mconv7_stage3"
+  type: "Convolution"
+  bottom: "Mconv6_stage3"
+  top: "Mconv7_stage3"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 22
+    pad: 0
+    kernel_size: 1
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+    dilation: 1
+  }
+}
+layer {
+  name: "concat_stage4"
+  type: "Concat"
+  bottom: "Mconv7_stage3"
+  bottom: "conv5_3_CPM"
+  top: "concat_stage4"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "Mconv1_stage4"
+  type: "Convolution"
+  bottom: "concat_stage4"
+  top: "Mconv1_stage4"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+    dilation: 1
+  }
+}
+layer {
+  name: "Mrelu1_2_stage4_1"
+  type: "ReLU"
+  bottom: "Mconv1_stage4"
+  top: "Mconv1_stage4"
+}
+layer {
+  name: "Mconv2_stage4"
+  type: "Convolution"
+  bottom: "Mconv1_stage4"
+  top: "Mconv2_stage4"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+    dilation: 1
+  }
+}
+layer {
+  name: "Mrelu1_3_stage4_2"
+  type: "ReLU"
+  bottom: "Mconv2_stage4"
+  top: "Mconv2_stage4"
+}
+layer {
+  name: "Mconv3_stage4"
+  type: "Convolution"
+  bottom: "Mconv2_stage4"
+  top: "Mconv3_stage4"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+    dilation: 1
+  }
+}
+layer {
+  name: "Mrelu1_4_stage4_3"
+  type: "ReLU"
+  bottom: "Mconv3_stage4"
+  top: "Mconv3_stage4"
+}
+layer {
+  name: "Mconv4_stage4"
+  type: "Convolution"
+  bottom: "Mconv3_stage4"
+  top: "Mconv4_stage4"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+    dilation: 1
+  }
+}
+layer {
+  name: "Mrelu1_5_stage4_4"
+  type: "ReLU"
+  bottom: "Mconv4_stage4"
+  top: "Mconv4_stage4"
+}
+layer {
+  name: "Mconv5_stage4"
+  type: "Convolution"
+  bottom: "Mconv4_stage4"
+  top: "Mconv5_stage4"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+    dilation: 1
+  }
+}
+layer {
+  name: "Mrelu1_6_stage4_5"
+  type: "ReLU"
+  bottom: "Mconv5_stage4"
+  top: "Mconv5_stage4"
+}
+layer {
+  name: "Mconv6_stage4"
+  type: "Convolution"
+  bottom: "Mconv5_stage4"
+  top: "Mconv6_stage4"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 0
+    kernel_size: 1
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+    dilation: 1
+  }
+}
+layer {
+  name: "Mrelu1_7_stage4_6"
+  type: "ReLU"
+  bottom: "Mconv6_stage4"
+  top: "Mconv6_stage4"
+}
+layer {
+  name: "Mconv7_stage4"
+  type: "Convolution"
+  bottom: "Mconv6_stage4"
+  top: "Mconv7_stage4"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 22
+    pad: 0
+    kernel_size: 1
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+    dilation: 1
+  }
+}
+layer {
+  name: "concat_stage5"
+  type: "Concat"
+  bottom: "Mconv7_stage4"
+  bottom: "conv5_3_CPM"
+  top: "concat_stage5"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "Mconv1_stage5"
+  type: "Convolution"
+  bottom: "concat_stage5"
+  top: "Mconv1_stage5"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+    dilation: 1
+  }
+}
+layer {
+  name: "Mrelu1_2_stage5_1"
+  type: "ReLU"
+  bottom: "Mconv1_stage5"
+  top: "Mconv1_stage5"
+}
+layer {
+  name: "Mconv2_stage5"
+  type: "Convolution"
+  bottom: "Mconv1_stage5"
+  top: "Mconv2_stage5"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+    dilation: 1
+  }
+}
+layer {
+  name: "Mrelu1_3_stage5_2"
+  type: "ReLU"
+  bottom: "Mconv2_stage5"
+  top: "Mconv2_stage5"
+}
+layer {
+  name: "Mconv3_stage5"
+  type: "Convolution"
+  bottom: "Mconv2_stage5"
+  top: "Mconv3_stage5"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+    dilation: 1
+  }
+}
+layer {
+  name: "Mrelu1_4_stage5_3"
+  type: "ReLU"
+  bottom: "Mconv3_stage5"
+  top: "Mconv3_stage5"
+}
+layer {
+  name: "Mconv4_stage5"
+  type: "Convolution"
+  bottom: "Mconv3_stage5"
+  top: "Mconv4_stage5"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+    dilation: 1
+  }
+}
+layer {
+  name: "Mrelu1_5_stage5_4"
+  type: "ReLU"
+  bottom: "Mconv4_stage5"
+  top: "Mconv4_stage5"
+}
+layer {
+  name: "Mconv5_stage5"
+  type: "Convolution"
+  bottom: "Mconv4_stage5"
+  top: "Mconv5_stage5"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+    dilation: 1
+  }
+}
+layer {
+  name: "Mrelu1_6_stage5_5"
+  type: "ReLU"
+  bottom: "Mconv5_stage5"
+  top: "Mconv5_stage5"
+}
+layer {
+  name: "Mconv6_stage5"
+  type: "Convolution"
+  bottom: "Mconv5_stage5"
+  top: "Mconv6_stage5"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 0
+    kernel_size: 1
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+    dilation: 1
+  }
+}
+layer {
+  name: "Mrelu1_7_stage5_6"
+  type: "ReLU"
+  bottom: "Mconv6_stage5"
+  top: "Mconv6_stage5"
+}
+layer {
+  name: "Mconv7_stage5"
+  type: "Convolution"
+  bottom: "Mconv6_stage5"
+  top: "Mconv7_stage5"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 22
+    pad: 0
+    kernel_size: 1
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+    dilation: 1
+  }
+}
+layer {
+  name: "concat_stage6"
+  type: "Concat"
+  bottom: "Mconv7_stage5"
+  bottom: "conv5_3_CPM"
+  top: "concat_stage6"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "Mconv1_stage6"
+  type: "Convolution"
+  bottom: "concat_stage6"
+  top: "Mconv1_stage6"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+    dilation: 1
+  }
+}
+layer {
+  name: "Mrelu1_2_stage6_1"
+  type: "ReLU"
+  bottom: "Mconv1_stage6"
+  top: "Mconv1_stage6"
+}
+layer {
+  name: "Mconv2_stage6"
+  type: "Convolution"
+  bottom: "Mconv1_stage6"
+  top: "Mconv2_stage6"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+    dilation: 1
+  }
+}
+layer {
+  name: "Mrelu1_3_stage6_2"
+  type: "ReLU"
+  bottom: "Mconv2_stage6"
+  top: "Mconv2_stage6"
+}
+layer {
+  name: "Mconv3_stage6"
+  type: "Convolution"
+  bottom: "Mconv2_stage6"
+  top: "Mconv3_stage6"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+    dilation: 1
+  }
+}
+layer {
+  name: "Mrelu1_4_stage6_3"
+  type: "ReLU"
+  bottom: "Mconv3_stage6"
+  top: "Mconv3_stage6"
+}
+layer {
+  name: "Mconv4_stage6"
+  type: "Convolution"
+  bottom: "Mconv3_stage6"
+  top: "Mconv4_stage6"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+    dilation: 1
+  }
+}
+layer {
+  name: "Mrelu1_5_stage6_4"
+  type: "ReLU"
+  bottom: "Mconv4_stage6"
+  top: "Mconv4_stage6"
+}
+layer {
+  name: "Mconv5_stage6"
+  type: "Convolution"
+  bottom: "Mconv4_stage6"
+  top: "Mconv5_stage6"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+    dilation: 1
+  }
+}
+layer {
+  name: "Mrelu1_6_stage6_5"
+  type: "ReLU"
+  bottom: "Mconv5_stage6"
+  top: "Mconv5_stage6"
+}
+layer {
+  name: "Mconv6_stage6"
+  type: "Convolution"
+  bottom: "Mconv5_stage6"
+  top: "Mconv6_stage6"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 0
+    kernel_size: 1
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+    dilation: 1
+  }
+}
+layer {
+  name: "Mrelu1_7_stage6_6"
+  type: "ReLU"
+  bottom: "Mconv6_stage6"
+  top: "Mconv6_stage6"
+}
+layer {
+  name: "Mconv7_stage6"
+  type: "Convolution"
+  bottom: "Mconv6_stage6"
+#   top: "Mconv7_stage6"
+  top: "net_output"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 22
+    pad: 0
+    kernel_size: 1
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+    dilation: 1
+  }
+}
+

hand/pose_iter_102000.caffemodel

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f313aa5ef031ac91606e1a0383daa14be241a6e1a91c1155283dd28503c79c2d
+size 147344024

pose/body_25/pose_deploy.prototxt

@@ -0,0 +1,2332 @@
+name: "OpenPose - BODY_25"
+input: "image"
+input_dim: 1 # This value will be defined at runtime
+input_dim: 3
+input_dim: 16 # This value will be defined at runtime
+input_dim: 16 # This value will be defined at runtime
+layer {
+  name: "conv1_1"
+  type: "Convolution"
+  bottom: "image"
+  top: "conv1_1"
+  convolution_param {
+    num_output: 64
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "relu1_1"
+  type: "ReLU"
+  bottom: "conv1_1"
+  top: "conv1_1"
+}
+layer {
+  name: "conv1_2"
+  type: "Convolution"
+  bottom: "conv1_1"
+  top: "conv1_2"
+  convolution_param {
+    num_output: 64
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "relu1_2"
+  type: "ReLU"
+  bottom: "conv1_2"
+  top: "conv1_2"
+}
+layer {
+  name: "pool1_stage1"
+  type: "Pooling"
+  bottom: "conv1_2"
+  top: "pool1_stage1"
+  pooling_param {
+    pool: MAX
+    kernel_size: 2
+    stride: 2
+  }
+}
+layer {
+  name: "conv2_1"
+  type: "Convolution"
+  bottom: "pool1_stage1"
+  top: "conv2_1"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "relu2_1"
+  type: "ReLU"
+  bottom: "conv2_1"
+  top: "conv2_1"
+}
+layer {
+  name: "conv2_2"
+  type: "Convolution"
+  bottom: "conv2_1"
+  top: "conv2_2"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "relu2_2"
+  type: "ReLU"
+  bottom: "conv2_2"
+  top: "conv2_2"
+}
+layer {
+  name: "pool2_stage1"
+  type: "Pooling"
+  bottom: "conv2_2"
+  top: "pool2_stage1"
+  pooling_param {
+    pool: MAX
+    kernel_size: 2
+    stride: 2
+  }
+}
+layer {
+  name: "conv3_1"
+  type: "Convolution"
+  bottom: "pool2_stage1"
+  top: "conv3_1"
+  convolution_param {
+    num_output: 256
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "relu3_1"
+  type: "ReLU"
+  bottom: "conv3_1"
+  top: "conv3_1"
+}
+layer {
+  name: "conv3_2"
+  type: "Convolution"
+  bottom: "conv3_1"
+  top: "conv3_2"
+  convolution_param {
+    num_output: 256
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "relu3_2"
+  type: "ReLU"
+  bottom: "conv3_2"
+  top: "conv3_2"
+}
+layer {
+  name: "conv3_3"
+  type: "Convolution"
+  bottom: "conv3_2"
+  top: "conv3_3"
+  convolution_param {
+    num_output: 256
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "relu3_3"
+  type: "ReLU"
+  bottom: "conv3_3"
+  top: "conv3_3"
+}
+layer {
+  name: "conv3_4"
+  type: "Convolution"
+  bottom: "conv3_3"
+  top: "conv3_4"
+  convolution_param {
+    num_output: 256
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "relu3_4"
+  type: "ReLU"
+  bottom: "conv3_4"
+  top: "conv3_4"
+}
+layer {
+  name: "pool3_stage1"
+  type: "Pooling"
+  bottom: "conv3_4"
+  top: "pool3_stage1"
+  pooling_param {
+    pool: MAX
+    kernel_size: 2
+    stride: 2
+  }
+}
+layer {
+  name: "conv4_1"
+  type: "Convolution"
+  bottom: "pool3_stage1"
+  top: "conv4_1"
+  convolution_param {
+    num_output: 512
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "relu4_1"
+  type: "ReLU"
+  bottom: "conv4_1"
+  top: "conv4_1"
+}
+layer {
+  name: "conv4_2"
+  type: "Convolution"
+  bottom: "conv4_1"
+  top: "conv4_2"
+  convolution_param {
+    num_output: 512
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "prelu4_2"
+  type: "PReLU"
+  bottom: "conv4_2"
+  top: "conv4_2"
+}
+layer {
+  name: "conv4_3_CPM"
+  type: "Convolution"
+  bottom: "conv4_2"
+  top: "conv4_3_CPM"
+  convolution_param {
+    num_output: 256
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "prelu4_3_CPM"
+  type: "PReLU"
+  bottom: "conv4_3_CPM"
+  top: "conv4_3_CPM"
+}
+layer {
+  name: "conv4_4_CPM"
+  type: "Convolution"
+  bottom: "conv4_3_CPM"
+  top: "conv4_4_CPM"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "prelu4_4_CPM"
+  type: "PReLU"
+  bottom: "conv4_4_CPM"
+  top: "conv4_4_CPM"
+}
+layer {
+  name: "Mconv1_stage0_L2_0"
+  type: "Convolution"
+  bottom: "conv4_4_CPM"
+  top: "Mconv1_stage0_L2_0"
+  convolution_param {
+    num_output: 96
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu1_stage0_L2_0"
+  type: "PReLU"
+  bottom: "Mconv1_stage0_L2_0"
+  top: "Mconv1_stage0_L2_0"
+}
+layer {
+  name: "Mconv1_stage0_L2_1"
+  type: "Convolution"
+  bottom: "Mconv1_stage0_L2_0"
+  top: "Mconv1_stage0_L2_1"
+  convolution_param {
+    num_output: 96
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu1_stage0_L2_1"
+  type: "PReLU"
+  bottom: "Mconv1_stage0_L2_1"
+  top: "Mconv1_stage0_L2_1"
+}
+layer {
+  name: "Mconv1_stage0_L2_2"
+  type: "Convolution"
+  bottom: "Mconv1_stage0_L2_1"
+  top: "Mconv1_stage0_L2_2"
+  convolution_param {
+    num_output: 96
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu1_stage0_L2_2"
+  type: "PReLU"
+  bottom: "Mconv1_stage0_L2_2"
+  top: "Mconv1_stage0_L2_2"
+}
+layer {
+  name: "Mconv1_stage0_L2_concat"
+  type: "Concat"
+  bottom: "Mconv1_stage0_L2_0"
+  bottom: "Mconv1_stage0_L2_1"
+  bottom: "Mconv1_stage0_L2_2"
+  top: "Mconv1_stage0_L2_concat"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "Mconv2_stage0_L2_0"
+  type: "Convolution"
+  bottom: "Mconv1_stage0_L2_concat"
+  top: "Mconv2_stage0_L2_0"
+  convolution_param {
+    num_output: 96
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu2_stage0_L2_0"
+  type: "PReLU"
+  bottom: "Mconv2_stage0_L2_0"
+  top: "Mconv2_stage0_L2_0"
+}
+layer {
+  name: "Mconv2_stage0_L2_1"
+  type: "Convolution"
+  bottom: "Mconv2_stage0_L2_0"
+  top: "Mconv2_stage0_L2_1"
+  convolution_param {
+    num_output: 96
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu2_stage0_L2_1"
+  type: "PReLU"
+  bottom: "Mconv2_stage0_L2_1"
+  top: "Mconv2_stage0_L2_1"
+}
+layer {
+  name: "Mconv2_stage0_L2_2"
+  type: "Convolution"
+  bottom: "Mconv2_stage0_L2_1"
+  top: "Mconv2_stage0_L2_2"
+  convolution_param {
+    num_output: 96
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu2_stage0_L2_2"
+  type: "PReLU"
+  bottom: "Mconv2_stage0_L2_2"
+  top: "Mconv2_stage0_L2_2"
+}
+layer {
+  name: "Mconv2_stage0_L2_concat"
+  type: "Concat"
+  bottom: "Mconv2_stage0_L2_0"
+  bottom: "Mconv2_stage0_L2_1"
+  bottom: "Mconv2_stage0_L2_2"
+  top: "Mconv2_stage0_L2_concat"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "Mconv3_stage0_L2_0"
+  type: "Convolution"
+  bottom: "Mconv2_stage0_L2_concat"
+  top: "Mconv3_stage0_L2_0"
+  convolution_param {
+    num_output: 96
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu3_stage0_L2_0"
+  type: "PReLU"
+  bottom: "Mconv3_stage0_L2_0"
+  top: "Mconv3_stage0_L2_0"
+}
+layer {
+  name: "Mconv3_stage0_L2_1"
+  type: "Convolution"
+  bottom: "Mconv3_stage0_L2_0"
+  top: "Mconv3_stage0_L2_1"
+  convolution_param {
+    num_output: 96
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu3_stage0_L2_1"
+  type: "PReLU"
+  bottom: "Mconv3_stage0_L2_1"
+  top: "Mconv3_stage0_L2_1"
+}
+layer {
+  name: "Mconv3_stage0_L2_2"
+  type: "Convolution"
+  bottom: "Mconv3_stage0_L2_1"
+  top: "Mconv3_stage0_L2_2"
+  convolution_param {
+    num_output: 96
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu3_stage0_L2_2"
+  type: "PReLU"
+  bottom: "Mconv3_stage0_L2_2"
+  top: "Mconv3_stage0_L2_2"
+}
+layer {
+  name: "Mconv3_stage0_L2_concat"
+  type: "Concat"
+  bottom: "Mconv3_stage0_L2_0"
+  bottom: "Mconv3_stage0_L2_1"
+  bottom: "Mconv3_stage0_L2_2"
+  top: "Mconv3_stage0_L2_concat"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "Mconv4_stage0_L2_0"
+  type: "Convolution"
+  bottom: "Mconv3_stage0_L2_concat"
+  top: "Mconv4_stage0_L2_0"
+  convolution_param {
+    num_output: 96
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu4_stage0_L2_0"
+  type: "PReLU"
+  bottom: "Mconv4_stage0_L2_0"
+  top: "Mconv4_stage0_L2_0"
+}
+layer {
+  name: "Mconv4_stage0_L2_1"
+  type: "Convolution"
+  bottom: "Mconv4_stage0_L2_0"
+  top: "Mconv4_stage0_L2_1"
+  convolution_param {
+    num_output: 96
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu4_stage0_L2_1"
+  type: "PReLU"
+  bottom: "Mconv4_stage0_L2_1"
+  top: "Mconv4_stage0_L2_1"
+}
+layer {
+  name: "Mconv4_stage0_L2_2"
+  type: "Convolution"
+  bottom: "Mconv4_stage0_L2_1"
+  top: "Mconv4_stage0_L2_2"
+  convolution_param {
+    num_output: 96
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu4_stage0_L2_2"
+  type: "PReLU"
+  bottom: "Mconv4_stage0_L2_2"
+  top: "Mconv4_stage0_L2_2"
+}
+layer {
+  name: "Mconv4_stage0_L2_concat"
+  type: "Concat"
+  bottom: "Mconv4_stage0_L2_0"
+  bottom: "Mconv4_stage0_L2_1"
+  bottom: "Mconv4_stage0_L2_2"
+  top: "Mconv4_stage0_L2_concat"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "Mconv5_stage0_L2_0"
+  type: "Convolution"
+  bottom: "Mconv4_stage0_L2_concat"
+  top: "Mconv5_stage0_L2_0"
+  convolution_param {
+    num_output: 96
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu5_stage0_L2_0"
+  type: "PReLU"
+  bottom: "Mconv5_stage0_L2_0"
+  top: "Mconv5_stage0_L2_0"
+}
+layer {
+  name: "Mconv5_stage0_L2_1"
+  type: "Convolution"
+  bottom: "Mconv5_stage0_L2_0"
+  top: "Mconv5_stage0_L2_1"
+  convolution_param {
+    num_output: 96
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu5_stage0_L2_1"
+  type: "PReLU"
+  bottom: "Mconv5_stage0_L2_1"
+  top: "Mconv5_stage0_L2_1"
+}
+layer {
+  name: "Mconv5_stage0_L2_2"
+  type: "Convolution"
+  bottom: "Mconv5_stage0_L2_1"
+  top: "Mconv5_stage0_L2_2"
+  convolution_param {
+    num_output: 96
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu5_stage0_L2_2"
+  type: "PReLU"
+  bottom: "Mconv5_stage0_L2_2"
+  top: "Mconv5_stage0_L2_2"
+}
+layer {
+  name: "Mconv5_stage0_L2_concat"
+  type: "Concat"
+  bottom: "Mconv5_stage0_L2_0"
+  bottom: "Mconv5_stage0_L2_1"
+  bottom: "Mconv5_stage0_L2_2"
+  top: "Mconv5_stage0_L2_concat"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "Mconv6_stage0_L2"
+  type: "Convolution"
+  bottom: "Mconv5_stage0_L2_concat"
+  top: "Mconv6_stage0_L2"
+  convolution_param {
+    num_output: 256
+    pad: 0
+    kernel_size: 1
+  }
+}
+layer {
+  name: "Mprelu6_stage0_L2"
+  type: "PReLU"
+  bottom: "Mconv6_stage0_L2"
+  top: "Mconv6_stage0_L2"
+}
+layer {
+  name: "Mconv7_stage0_L2"
+  type: "Convolution"
+  bottom: "Mconv6_stage0_L2"
+  top: "Mconv7_stage0_L2"
+  convolution_param {
+    num_output: 52
+    pad: 0
+    kernel_size: 1
+  }
+}
+layer {
+  name: "concat_stage1_L2"
+  type: "Concat"
+  bottom: "conv4_4_CPM"
+  bottom: "Mconv7_stage0_L2"
+  top: "concat_stage1_L2"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "Mconv1_stage1_L2_0"
+  type: "Convolution"
+  bottom: "concat_stage1_L2"
+  top: "Mconv1_stage1_L2_0"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu1_stage1_L2_0"
+  type: "PReLU"
+  bottom: "Mconv1_stage1_L2_0"
+  top: "Mconv1_stage1_L2_0"
+}
+layer {
+  name: "Mconv1_stage1_L2_1"
+  type: "Convolution"
+  bottom: "Mconv1_stage1_L2_0"
+  top: "Mconv1_stage1_L2_1"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu1_stage1_L2_1"
+  type: "PReLU"
+  bottom: "Mconv1_stage1_L2_1"
+  top: "Mconv1_stage1_L2_1"
+}
+layer {
+  name: "Mconv1_stage1_L2_2"
+  type: "Convolution"
+  bottom: "Mconv1_stage1_L2_1"
+  top: "Mconv1_stage1_L2_2"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu1_stage1_L2_2"
+  type: "PReLU"
+  bottom: "Mconv1_stage1_L2_2"
+  top: "Mconv1_stage1_L2_2"
+}
+layer {
+  name: "Mconv1_stage1_L2_concat"
+  type: "Concat"
+  bottom: "Mconv1_stage1_L2_0"
+  bottom: "Mconv1_stage1_L2_1"
+  bottom: "Mconv1_stage1_L2_2"
+  top: "Mconv1_stage1_L2_concat"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "Mconv2_stage1_L2_0"
+  type: "Convolution"
+  bottom: "Mconv1_stage1_L2_concat"
+  top: "Mconv2_stage1_L2_0"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu2_stage1_L2_0"
+  type: "PReLU"
+  bottom: "Mconv2_stage1_L2_0"
+  top: "Mconv2_stage1_L2_0"
+}
+layer {
+  name: "Mconv2_stage1_L2_1"
+  type: "Convolution"
+  bottom: "Mconv2_stage1_L2_0"
+  top: "Mconv2_stage1_L2_1"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu2_stage1_L2_1"
+  type: "PReLU"
+  bottom: "Mconv2_stage1_L2_1"
+  top: "Mconv2_stage1_L2_1"
+}
+layer {
+  name: "Mconv2_stage1_L2_2"
+  type: "Convolution"
+  bottom: "Mconv2_stage1_L2_1"
+  top: "Mconv2_stage1_L2_2"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu2_stage1_L2_2"
+  type: "PReLU"
+  bottom: "Mconv2_stage1_L2_2"
+  top: "Mconv2_stage1_L2_2"
+}
+layer {
+  name: "Mconv2_stage1_L2_concat"
+  type: "Concat"
+  bottom: "Mconv2_stage1_L2_0"
+  bottom: "Mconv2_stage1_L2_1"
+  bottom: "Mconv2_stage1_L2_2"
+  top: "Mconv2_stage1_L2_concat"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "Mconv3_stage1_L2_0"
+  type: "Convolution"
+  bottom: "Mconv2_stage1_L2_concat"
+  top: "Mconv3_stage1_L2_0"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu3_stage1_L2_0"
+  type: "PReLU"
+  bottom: "Mconv3_stage1_L2_0"
+  top: "Mconv3_stage1_L2_0"
+}
+layer {
+  name: "Mconv3_stage1_L2_1"
+  type: "Convolution"
+  bottom: "Mconv3_stage1_L2_0"
+  top: "Mconv3_stage1_L2_1"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu3_stage1_L2_1"
+  type: "PReLU"
+  bottom: "Mconv3_stage1_L2_1"
+  top: "Mconv3_stage1_L2_1"
+}
+layer {
+  name: "Mconv3_stage1_L2_2"
+  type: "Convolution"
+  bottom: "Mconv3_stage1_L2_1"
+  top: "Mconv3_stage1_L2_2"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu3_stage1_L2_2"
+  type: "PReLU"
+  bottom: "Mconv3_stage1_L2_2"
+  top: "Mconv3_stage1_L2_2"
+}
+layer {
+  name: "Mconv3_stage1_L2_concat"
+  type: "Concat"
+  bottom: "Mconv3_stage1_L2_0"
+  bottom: "Mconv3_stage1_L2_1"
+  bottom: "Mconv3_stage1_L2_2"
+  top: "Mconv3_stage1_L2_concat"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "Mconv4_stage1_L2_0"
+  type: "Convolution"
+  bottom: "Mconv3_stage1_L2_concat"
+  top: "Mconv4_stage1_L2_0"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu4_stage1_L2_0"
+  type: "PReLU"
+  bottom: "Mconv4_stage1_L2_0"
+  top: "Mconv4_stage1_L2_0"
+}
+layer {
+  name: "Mconv4_stage1_L2_1"
+  type: "Convolution"
+  bottom: "Mconv4_stage1_L2_0"
+  top: "Mconv4_stage1_L2_1"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu4_stage1_L2_1"
+  type: "PReLU"
+  bottom: "Mconv4_stage1_L2_1"
+  top: "Mconv4_stage1_L2_1"
+}
+layer {
+  name: "Mconv4_stage1_L2_2"
+  type: "Convolution"
+  bottom: "Mconv4_stage1_L2_1"
+  top: "Mconv4_stage1_L2_2"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu4_stage1_L2_2"
+  type: "PReLU"
+  bottom: "Mconv4_stage1_L2_2"
+  top: "Mconv4_stage1_L2_2"
+}
+layer {
+  name: "Mconv4_stage1_L2_concat"
+  type: "Concat"
+  bottom: "Mconv4_stage1_L2_0"
+  bottom: "Mconv4_stage1_L2_1"
+  bottom: "Mconv4_stage1_L2_2"
+  top: "Mconv4_stage1_L2_concat"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "Mconv5_stage1_L2_0"
+  type: "Convolution"
+  bottom: "Mconv4_stage1_L2_concat"
+  top: "Mconv5_stage1_L2_0"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu5_stage1_L2_0"
+  type: "PReLU"
+  bottom: "Mconv5_stage1_L2_0"
+  top: "Mconv5_stage1_L2_0"
+}
+layer {
+  name: "Mconv5_stage1_L2_1"
+  type: "Convolution"
+  bottom: "Mconv5_stage1_L2_0"
+  top: "Mconv5_stage1_L2_1"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu5_stage1_L2_1"
+  type: "PReLU"
+  bottom: "Mconv5_stage1_L2_1"
+  top: "Mconv5_stage1_L2_1"
+}
+layer {
+  name: "Mconv5_stage1_L2_2"
+  type: "Convolution"
+  bottom: "Mconv5_stage1_L2_1"
+  top: "Mconv5_stage1_L2_2"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu5_stage1_L2_2"
+  type: "PReLU"
+  bottom: "Mconv5_stage1_L2_2"
+  top: "Mconv5_stage1_L2_2"
+}
+layer {
+  name: "Mconv5_stage1_L2_concat"
+  type: "Concat"
+  bottom: "Mconv5_stage1_L2_0"
+  bottom: "Mconv5_stage1_L2_1"
+  bottom: "Mconv5_stage1_L2_2"
+  top: "Mconv5_stage1_L2_concat"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "Mconv6_stage1_L2"
+  type: "Convolution"
+  bottom: "Mconv5_stage1_L2_concat"
+  top: "Mconv6_stage1_L2"
+  convolution_param {
+    num_output: 512
+    pad: 0
+    kernel_size: 1
+  }
+}
+layer {
+  name: "Mprelu6_stage1_L2"
+  type: "PReLU"
+  bottom: "Mconv6_stage1_L2"
+  top: "Mconv6_stage1_L2"
+}
+layer {
+  name: "Mconv7_stage1_L2"
+  type: "Convolution"
+  bottom: "Mconv6_stage1_L2"
+  top: "Mconv7_stage1_L2"
+  convolution_param {
+    num_output: 52
+    pad: 0
+    kernel_size: 1
+  }
+}
+layer {
+  name: "concat_stage2_L2"
+  type: "Concat"
+  bottom: "conv4_4_CPM"
+  bottom: "Mconv7_stage1_L2"
+  top: "concat_stage2_L2"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "Mconv1_stage2_L2_0"
+  type: "Convolution"
+  bottom: "concat_stage2_L2"
+  top: "Mconv1_stage2_L2_0"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu1_stage2_L2_0"
+  type: "PReLU"
+  bottom: "Mconv1_stage2_L2_0"
+  top: "Mconv1_stage2_L2_0"
+}
+layer {
+  name: "Mconv1_stage2_L2_1"
+  type: "Convolution"
+  bottom: "Mconv1_stage2_L2_0"
+  top: "Mconv1_stage2_L2_1"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu1_stage2_L2_1"
+  type: "PReLU"
+  bottom: "Mconv1_stage2_L2_1"
+  top: "Mconv1_stage2_L2_1"
+}
+layer {
+  name: "Mconv1_stage2_L2_2"
+  type: "Convolution"
+  bottom: "Mconv1_stage2_L2_1"
+  top: "Mconv1_stage2_L2_2"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu1_stage2_L2_2"
+  type: "PReLU"
+  bottom: "Mconv1_stage2_L2_2"
+  top: "Mconv1_stage2_L2_2"
+}
+layer {
+  name: "Mconv1_stage2_L2_concat"
+  type: "Concat"
+  bottom: "Mconv1_stage2_L2_0"
+  bottom: "Mconv1_stage2_L2_1"
+  bottom: "Mconv1_stage2_L2_2"
+  top: "Mconv1_stage2_L2_concat"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "Mconv2_stage2_L2_0"
+  type: "Convolution"
+  bottom: "Mconv1_stage2_L2_concat"
+  top: "Mconv2_stage2_L2_0"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu2_stage2_L2_0"
+  type: "PReLU"
+  bottom: "Mconv2_stage2_L2_0"
+  top: "Mconv2_stage2_L2_0"
+}
+layer {
+  name: "Mconv2_stage2_L2_1"
+  type: "Convolution"
+  bottom: "Mconv2_stage2_L2_0"
+  top: "Mconv2_stage2_L2_1"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu2_stage2_L2_1"
+  type: "PReLU"
+  bottom: "Mconv2_stage2_L2_1"
+  top: "Mconv2_stage2_L2_1"
+}
+layer {
+  name: "Mconv2_stage2_L2_2"
+  type: "Convolution"
+  bottom: "Mconv2_stage2_L2_1"
+  top: "Mconv2_stage2_L2_2"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu2_stage2_L2_2"
+  type: "PReLU"
+  bottom: "Mconv2_stage2_L2_2"
+  top: "Mconv2_stage2_L2_2"
+}
+layer {
+  name: "Mconv2_stage2_L2_concat"
+  type: "Concat"
+  bottom: "Mconv2_stage2_L2_0"
+  bottom: "Mconv2_stage2_L2_1"
+  bottom: "Mconv2_stage2_L2_2"
+  top: "Mconv2_stage2_L2_concat"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "Mconv3_stage2_L2_0"
+  type: "Convolution"
+  bottom: "Mconv2_stage2_L2_concat"
+  top: "Mconv3_stage2_L2_0"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu3_stage2_L2_0"
+  type: "PReLU"
+  bottom: "Mconv3_stage2_L2_0"
+  top: "Mconv3_stage2_L2_0"
+}
+layer {
+  name: "Mconv3_stage2_L2_1"
+  type: "Convolution"
+  bottom: "Mconv3_stage2_L2_0"
+  top: "Mconv3_stage2_L2_1"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu3_stage2_L2_1"
+  type: "PReLU"
+  bottom: "Mconv3_stage2_L2_1"
+  top: "Mconv3_stage2_L2_1"
+}
+layer {
+  name: "Mconv3_stage2_L2_2"
+  type: "Convolution"
+  bottom: "Mconv3_stage2_L2_1"
+  top: "Mconv3_stage2_L2_2"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu3_stage2_L2_2"
+  type: "PReLU"
+  bottom: "Mconv3_stage2_L2_2"
+  top: "Mconv3_stage2_L2_2"
+}
+layer {
+  name: "Mconv3_stage2_L2_concat"
+  type: "Concat"
+  bottom: "Mconv3_stage2_L2_0"
+  bottom: "Mconv3_stage2_L2_1"
+  bottom: "Mconv3_stage2_L2_2"
+  top: "Mconv3_stage2_L2_concat"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "Mconv4_stage2_L2_0"
+  type: "Convolution"
+  bottom: "Mconv3_stage2_L2_concat"
+  top: "Mconv4_stage2_L2_0"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu4_stage2_L2_0"
+  type: "PReLU"
+  bottom: "Mconv4_stage2_L2_0"
+  top: "Mconv4_stage2_L2_0"
+}
+layer {
+  name: "Mconv4_stage2_L2_1"
+  type: "Convolution"
+  bottom: "Mconv4_stage2_L2_0"
+  top: "Mconv4_stage2_L2_1"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu4_stage2_L2_1"
+  type: "PReLU"
+  bottom: "Mconv4_stage2_L2_1"
+  top: "Mconv4_stage2_L2_1"
+}
+layer {
+  name: "Mconv4_stage2_L2_2"
+  type: "Convolution"
+  bottom: "Mconv4_stage2_L2_1"
+  top: "Mconv4_stage2_L2_2"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu4_stage2_L2_2"
+  type: "PReLU"
+  bottom: "Mconv4_stage2_L2_2"
+  top: "Mconv4_stage2_L2_2"
+}
+layer {
+  name: "Mconv4_stage2_L2_concat"
+  type: "Concat"
+  bottom: "Mconv4_stage2_L2_0"
+  bottom: "Mconv4_stage2_L2_1"
+  bottom: "Mconv4_stage2_L2_2"
+  top: "Mconv4_stage2_L2_concat"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "Mconv5_stage2_L2_0"
+  type: "Convolution"
+  bottom: "Mconv4_stage2_L2_concat"
+  top: "Mconv5_stage2_L2_0"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu5_stage2_L2_0"
+  type: "PReLU"
+  bottom: "Mconv5_stage2_L2_0"
+  top: "Mconv5_stage2_L2_0"
+}
+layer {
+  name: "Mconv5_stage2_L2_1"
+  type: "Convolution"
+  bottom: "Mconv5_stage2_L2_0"
+  top: "Mconv5_stage2_L2_1"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu5_stage2_L2_1"
+  type: "PReLU"
+  bottom: "Mconv5_stage2_L2_1"
+  top: "Mconv5_stage2_L2_1"
+}
+layer {
+  name: "Mconv5_stage2_L2_2"
+  type: "Convolution"
+  bottom: "Mconv5_stage2_L2_1"
+  top: "Mconv5_stage2_L2_2"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu5_stage2_L2_2"
+  type: "PReLU"
+  bottom: "Mconv5_stage2_L2_2"
+  top: "Mconv5_stage2_L2_2"
+}
+layer {
+  name: "Mconv5_stage2_L2_concat"
+  type: "Concat"
+  bottom: "Mconv5_stage2_L2_0"
+  bottom: "Mconv5_stage2_L2_1"
+  bottom: "Mconv5_stage2_L2_2"
+  top: "Mconv5_stage2_L2_concat"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "Mconv6_stage2_L2"
+  type: "Convolution"
+  bottom: "Mconv5_stage2_L2_concat"
+  top: "Mconv6_stage2_L2"
+  convolution_param {
+    num_output: 512
+    pad: 0
+    kernel_size: 1
+  }
+}
+layer {
+  name: "Mprelu6_stage2_L2"
+  type: "PReLU"
+  bottom: "Mconv6_stage2_L2"
+  top: "Mconv6_stage2_L2"
+}
+layer {
+  name: "Mconv7_stage2_L2"
+  type: "Convolution"
+  bottom: "Mconv6_stage2_L2"
+  top: "Mconv7_stage2_L2"
+  convolution_param {
+    num_output: 52
+    pad: 0
+    kernel_size: 1
+  }
+}
+layer {
+  name: "concat_stage3_L2"
+  type: "Concat"
+  bottom: "conv4_4_CPM"
+  bottom: "Mconv7_stage2_L2"
+  top: "concat_stage3_L2"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "Mconv1_stage3_L2_0"
+  type: "Convolution"
+  bottom: "concat_stage3_L2"
+  top: "Mconv1_stage3_L2_0"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu1_stage3_L2_0"
+  type: "PReLU"
+  bottom: "Mconv1_stage3_L2_0"
+  top: "Mconv1_stage3_L2_0"
+}
+layer {
+  name: "Mconv1_stage3_L2_1"
+  type: "Convolution"
+  bottom: "Mconv1_stage3_L2_0"
+  top: "Mconv1_stage3_L2_1"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu1_stage3_L2_1"
+  type: "PReLU"
+  bottom: "Mconv1_stage3_L2_1"
+  top: "Mconv1_stage3_L2_1"
+}
+layer {
+  name: "Mconv1_stage3_L2_2"
+  type: "Convolution"
+  bottom: "Mconv1_stage3_L2_1"
+  top: "Mconv1_stage3_L2_2"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu1_stage3_L2_2"
+  type: "PReLU"
+  bottom: "Mconv1_stage3_L2_2"
+  top: "Mconv1_stage3_L2_2"
+}
+layer {
+  name: "Mconv1_stage3_L2_concat"
+  type: "Concat"
+  bottom: "Mconv1_stage3_L2_0"
+  bottom: "Mconv1_stage3_L2_1"
+  bottom: "Mconv1_stage3_L2_2"
+  top: "Mconv1_stage3_L2_concat"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "Mconv2_stage3_L2_0"
+  type: "Convolution"
+  bottom: "Mconv1_stage3_L2_concat"
+  top: "Mconv2_stage3_L2_0"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu2_stage3_L2_0"
+  type: "PReLU"
+  bottom: "Mconv2_stage3_L2_0"
+  top: "Mconv2_stage3_L2_0"
+}
+layer {
+  name: "Mconv2_stage3_L2_1"
+  type: "Convolution"
+  bottom: "Mconv2_stage3_L2_0"
+  top: "Mconv2_stage3_L2_1"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu2_stage3_L2_1"
+  type: "PReLU"
+  bottom: "Mconv2_stage3_L2_1"
+  top: "Mconv2_stage3_L2_1"
+}
+layer {
+  name: "Mconv2_stage3_L2_2"
+  type: "Convolution"
+  bottom: "Mconv2_stage3_L2_1"
+  top: "Mconv2_stage3_L2_2"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu2_stage3_L2_2"
+  type: "PReLU"
+  bottom: "Mconv2_stage3_L2_2"
+  top: "Mconv2_stage3_L2_2"
+}
+layer {
+  name: "Mconv2_stage3_L2_concat"
+  type: "Concat"
+  bottom: "Mconv2_stage3_L2_0"
+  bottom: "Mconv2_stage3_L2_1"
+  bottom: "Mconv2_stage3_L2_2"
+  top: "Mconv2_stage3_L2_concat"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "Mconv3_stage3_L2_0"
+  type: "Convolution"
+  bottom: "Mconv2_stage3_L2_concat"
+  top: "Mconv3_stage3_L2_0"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu3_stage3_L2_0"
+  type: "PReLU"
+  bottom: "Mconv3_stage3_L2_0"
+  top: "Mconv3_stage3_L2_0"
+}
+layer {
+  name: "Mconv3_stage3_L2_1"
+  type: "Convolution"
+  bottom: "Mconv3_stage3_L2_0"
+  top: "Mconv3_stage3_L2_1"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu3_stage3_L2_1"
+  type: "PReLU"
+  bottom: "Mconv3_stage3_L2_1"
+  top: "Mconv3_stage3_L2_1"
+}
+layer {
+  name: "Mconv3_stage3_L2_2"
+  type: "Convolution"
+  bottom: "Mconv3_stage3_L2_1"
+  top: "Mconv3_stage3_L2_2"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu3_stage3_L2_2"
+  type: "PReLU"
+  bottom: "Mconv3_stage3_L2_2"
+  top: "Mconv3_stage3_L2_2"
+}
+layer {
+  name: "Mconv3_stage3_L2_concat"
+  type: "Concat"
+  bottom: "Mconv3_stage3_L2_0"
+  bottom: "Mconv3_stage3_L2_1"
+  bottom: "Mconv3_stage3_L2_2"
+  top: "Mconv3_stage3_L2_concat"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "Mconv4_stage3_L2_0"
+  type: "Convolution"
+  bottom: "Mconv3_stage3_L2_concat"
+  top: "Mconv4_stage3_L2_0"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu4_stage3_L2_0"
+  type: "PReLU"
+  bottom: "Mconv4_stage3_L2_0"
+  top: "Mconv4_stage3_L2_0"
+}
+layer {
+  name: "Mconv4_stage3_L2_1"
+  type: "Convolution"
+  bottom: "Mconv4_stage3_L2_0"
+  top: "Mconv4_stage3_L2_1"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu4_stage3_L2_1"
+  type: "PReLU"
+  bottom: "Mconv4_stage3_L2_1"
+  top: "Mconv4_stage3_L2_1"
+}
+layer {
+  name: "Mconv4_stage3_L2_2"
+  type: "Convolution"
+  bottom: "Mconv4_stage3_L2_1"
+  top: "Mconv4_stage3_L2_2"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu4_stage3_L2_2"
+  type: "PReLU"
+  bottom: "Mconv4_stage3_L2_2"
+  top: "Mconv4_stage3_L2_2"
+}
+layer {
+  name: "Mconv4_stage3_L2_concat"
+  type: "Concat"
+  bottom: "Mconv4_stage3_L2_0"
+  bottom: "Mconv4_stage3_L2_1"
+  bottom: "Mconv4_stage3_L2_2"
+  top: "Mconv4_stage3_L2_concat"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "Mconv5_stage3_L2_0"
+  type: "Convolution"
+  bottom: "Mconv4_stage3_L2_concat"
+  top: "Mconv5_stage3_L2_0"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu5_stage3_L2_0"
+  type: "PReLU"
+  bottom: "Mconv5_stage3_L2_0"
+  top: "Mconv5_stage3_L2_0"
+}
+layer {
+  name: "Mconv5_stage3_L2_1"
+  type: "Convolution"
+  bottom: "Mconv5_stage3_L2_0"
+  top: "Mconv5_stage3_L2_1"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu5_stage3_L2_1"
+  type: "PReLU"
+  bottom: "Mconv5_stage3_L2_1"
+  top: "Mconv5_stage3_L2_1"
+}
+layer {
+  name: "Mconv5_stage3_L2_2"
+  type: "Convolution"
+  bottom: "Mconv5_stage3_L2_1"
+  top: "Mconv5_stage3_L2_2"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu5_stage3_L2_2"
+  type: "PReLU"
+  bottom: "Mconv5_stage3_L2_2"
+  top: "Mconv5_stage3_L2_2"
+}
+layer {
+  name: "Mconv5_stage3_L2_concat"
+  type: "Concat"
+  bottom: "Mconv5_stage3_L2_0"
+  bottom: "Mconv5_stage3_L2_1"
+  bottom: "Mconv5_stage3_L2_2"
+  top: "Mconv5_stage3_L2_concat"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "Mconv6_stage3_L2"
+  type: "Convolution"
+  bottom: "Mconv5_stage3_L2_concat"
+  top: "Mconv6_stage3_L2"
+  convolution_param {
+    num_output: 512
+    pad: 0
+    kernel_size: 1
+  }
+}
+layer {
+  name: "Mprelu6_stage3_L2"
+  type: "PReLU"
+  bottom: "Mconv6_stage3_L2"
+  top: "Mconv6_stage3_L2"
+}
+layer {
+  name: "Mconv7_stage3_L2"
+  type: "Convolution"
+  bottom: "Mconv6_stage3_L2"
+  top: "Mconv7_stage3_L2"
+  convolution_param {
+    num_output: 52
+    pad: 0
+    kernel_size: 1
+  }
+}
+layer {
+  name: "concat_stage0_L1"
+  type: "Concat"
+  bottom: "conv4_4_CPM"
+  bottom: "Mconv7_stage3_L2"
+  top: "concat_stage0_L1"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "Mconv1_stage0_L1_0"
+  type: "Convolution"
+  bottom: "concat_stage0_L1"
+  top: "Mconv1_stage0_L1_0"
+  convolution_param {
+    num_output: 96
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu1_stage0_L1_0"
+  type: "PReLU"
+  bottom: "Mconv1_stage0_L1_0"
+  top: "Mconv1_stage0_L1_0"
+}
+layer {
+  name: "Mconv1_stage0_L1_1"
+  type: "Convolution"
+  bottom: "Mconv1_stage0_L1_0"
+  top: "Mconv1_stage0_L1_1"
+  convolution_param {
+    num_output: 96
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu1_stage0_L1_1"
+  type: "PReLU"
+  bottom: "Mconv1_stage0_L1_1"
+  top: "Mconv1_stage0_L1_1"
+}
+layer {
+  name: "Mconv1_stage0_L1_2"
+  type: "Convolution"
+  bottom: "Mconv1_stage0_L1_1"
+  top: "Mconv1_stage0_L1_2"
+  convolution_param {
+    num_output: 96
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu1_stage0_L1_2"
+  type: "PReLU"
+  bottom: "Mconv1_stage0_L1_2"
+  top: "Mconv1_stage0_L1_2"
+}
+layer {
+  name: "Mconv1_stage0_L1_concat"
+  type: "Concat"
+  bottom: "Mconv1_stage0_L1_0"
+  bottom: "Mconv1_stage0_L1_1"
+  bottom: "Mconv1_stage0_L1_2"
+  top: "Mconv1_stage0_L1_concat"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "Mconv2_stage0_L1_0"
+  type: "Convolution"
+  bottom: "Mconv1_stage0_L1_concat"
+  top: "Mconv2_stage0_L1_0"
+  convolution_param {
+    num_output: 96
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu2_stage0_L1_0"
+  type: "PReLU"
+  bottom: "Mconv2_stage0_L1_0"
+  top: "Mconv2_stage0_L1_0"
+}
+layer {
+  name: "Mconv2_stage0_L1_1"
+  type: "Convolution"
+  bottom: "Mconv2_stage0_L1_0"
+  top: "Mconv2_stage0_L1_1"
+  convolution_param {
+    num_output: 96
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu2_stage0_L1_1"
+  type: "PReLU"
+  bottom: "Mconv2_stage0_L1_1"
+  top: "Mconv2_stage0_L1_1"
+}
+layer {
+  name: "Mconv2_stage0_L1_2"
+  type: "Convolution"
+  bottom: "Mconv2_stage0_L1_1"
+  top: "Mconv2_stage0_L1_2"
+  convolution_param {
+    num_output: 96
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu2_stage0_L1_2"
+  type: "PReLU"
+  bottom: "Mconv2_stage0_L1_2"
+  top: "Mconv2_stage0_L1_2"
+}
+layer {
+  name: "Mconv2_stage0_L1_concat"
+  type: "Concat"
+  bottom: "Mconv2_stage0_L1_0"
+  bottom: "Mconv2_stage0_L1_1"
+  bottom: "Mconv2_stage0_L1_2"
+  top: "Mconv2_stage0_L1_concat"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "Mconv3_stage0_L1_0"
+  type: "Convolution"
+  bottom: "Mconv2_stage0_L1_concat"
+  top: "Mconv3_stage0_L1_0"
+  convolution_param {
+    num_output: 96
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu3_stage0_L1_0"
+  type: "PReLU"
+  bottom: "Mconv3_stage0_L1_0"
+  top: "Mconv3_stage0_L1_0"
+}
+layer {
+  name: "Mconv3_stage0_L1_1"
+  type: "Convolution"
+  bottom: "Mconv3_stage0_L1_0"
+  top: "Mconv3_stage0_L1_1"
+  convolution_param {
+    num_output: 96
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu3_stage0_L1_1"
+  type: "PReLU"
+  bottom: "Mconv3_stage0_L1_1"
+  top: "Mconv3_stage0_L1_1"
+}
+layer {
+  name: "Mconv3_stage0_L1_2"
+  type: "Convolution"
+  bottom: "Mconv3_stage0_L1_1"
+  top: "Mconv3_stage0_L1_2"
+  convolution_param {
+    num_output: 96
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu3_stage0_L1_2"
+  type: "PReLU"
+  bottom: "Mconv3_stage0_L1_2"
+  top: "Mconv3_stage0_L1_2"
+}
+layer {
+  name: "Mconv3_stage0_L1_concat"
+  type: "Concat"
+  bottom: "Mconv3_stage0_L1_0"
+  bottom: "Mconv3_stage0_L1_1"
+  bottom: "Mconv3_stage0_L1_2"
+  top: "Mconv3_stage0_L1_concat"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "Mconv4_stage0_L1_0"
+  type: "Convolution"
+  bottom: "Mconv3_stage0_L1_concat"
+  top: "Mconv4_stage0_L1_0"
+  convolution_param {
+    num_output: 96
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu4_stage0_L1_0"
+  type: "PReLU"
+  bottom: "Mconv4_stage0_L1_0"
+  top: "Mconv4_stage0_L1_0"
+}
+layer {
+  name: "Mconv4_stage0_L1_1"
+  type: "Convolution"
+  bottom: "Mconv4_stage0_L1_0"
+  top: "Mconv4_stage0_L1_1"
+  convolution_param {
+    num_output: 96
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu4_stage0_L1_1"
+  type: "PReLU"
+  bottom: "Mconv4_stage0_L1_1"
+  top: "Mconv4_stage0_L1_1"
+}
+layer {
+  name: "Mconv4_stage0_L1_2"
+  type: "Convolution"
+  bottom: "Mconv4_stage0_L1_1"
+  top: "Mconv4_stage0_L1_2"
+  convolution_param {
+    num_output: 96
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu4_stage0_L1_2"
+  type: "PReLU"
+  bottom: "Mconv4_stage0_L1_2"
+  top: "Mconv4_stage0_L1_2"
+}
+layer {
+  name: "Mconv4_stage0_L1_concat"
+  type: "Concat"
+  bottom: "Mconv4_stage0_L1_0"
+  bottom: "Mconv4_stage0_L1_1"
+  bottom: "Mconv4_stage0_L1_2"
+  top: "Mconv4_stage0_L1_concat"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "Mconv5_stage0_L1_0"
+  type: "Convolution"
+  bottom: "Mconv4_stage0_L1_concat"
+  top: "Mconv5_stage0_L1_0"
+  convolution_param {
+    num_output: 96
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu5_stage0_L1_0"
+  type: "PReLU"
+  bottom: "Mconv5_stage0_L1_0"
+  top: "Mconv5_stage0_L1_0"
+}
+layer {
+  name: "Mconv5_stage0_L1_1"
+  type: "Convolution"
+  bottom: "Mconv5_stage0_L1_0"
+  top: "Mconv5_stage0_L1_1"
+  convolution_param {
+    num_output: 96
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu5_stage0_L1_1"
+  type: "PReLU"
+  bottom: "Mconv5_stage0_L1_1"
+  top: "Mconv5_stage0_L1_1"
+}
+layer {
+  name: "Mconv5_stage0_L1_2"
+  type: "Convolution"
+  bottom: "Mconv5_stage0_L1_1"
+  top: "Mconv5_stage0_L1_2"
+  convolution_param {
+    num_output: 96
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu5_stage0_L1_2"
+  type: "PReLU"
+  bottom: "Mconv5_stage0_L1_2"
+  top: "Mconv5_stage0_L1_2"
+}
+layer {
+  name: "Mconv5_stage0_L1_concat"
+  type: "Concat"
+  bottom: "Mconv5_stage0_L1_0"
+  bottom: "Mconv5_stage0_L1_1"
+  bottom: "Mconv5_stage0_L1_2"
+  top: "Mconv5_stage0_L1_concat"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "Mconv6_stage0_L1"
+  type: "Convolution"
+  bottom: "Mconv5_stage0_L1_concat"
+  top: "Mconv6_stage0_L1"
+  convolution_param {
+    num_output: 256
+    pad: 0
+    kernel_size: 1
+  }
+}
+layer {
+  name: "Mprelu6_stage0_L1"
+  type: "PReLU"
+  bottom: "Mconv6_stage0_L1"
+  top: "Mconv6_stage0_L1"
+}
+layer {
+  name: "Mconv7_stage0_L1"
+  type: "Convolution"
+  bottom: "Mconv6_stage0_L1"
+  top: "Mconv7_stage0_L1"
+  convolution_param {
+    num_output: 26
+    pad: 0
+    kernel_size: 1
+  }
+}
+layer {
+  name: "concat_stage1_L1"
+  type: "Concat"
+  bottom: "conv4_4_CPM"
+  bottom: "Mconv7_stage0_L1"
+  bottom: "Mconv7_stage3_L2"
+  top: "concat_stage1_L1"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "Mconv1_stage1_L1_0"
+  type: "Convolution"
+  bottom: "concat_stage1_L1"
+  top: "Mconv1_stage1_L1_0"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu1_stage1_L1_0"
+  type: "PReLU"
+  bottom: "Mconv1_stage1_L1_0"
+  top: "Mconv1_stage1_L1_0"
+}
+layer {
+  name: "Mconv1_stage1_L1_1"
+  type: "Convolution"
+  bottom: "Mconv1_stage1_L1_0"
+  top: "Mconv1_stage1_L1_1"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu1_stage1_L1_1"
+  type: "PReLU"
+  bottom: "Mconv1_stage1_L1_1"
+  top: "Mconv1_stage1_L1_1"
+}
+layer {
+  name: "Mconv1_stage1_L1_2"
+  type: "Convolution"
+  bottom: "Mconv1_stage1_L1_1"
+  top: "Mconv1_stage1_L1_2"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu1_stage1_L1_2"
+  type: "PReLU"
+  bottom: "Mconv1_stage1_L1_2"
+  top: "Mconv1_stage1_L1_2"
+}
+layer {
+  name: "Mconv1_stage1_L1_concat"
+  type: "Concat"
+  bottom: "Mconv1_stage1_L1_0"
+  bottom: "Mconv1_stage1_L1_1"
+  bottom: "Mconv1_stage1_L1_2"
+  top: "Mconv1_stage1_L1_concat"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "Mconv2_stage1_L1_0"
+  type: "Convolution"
+  bottom: "Mconv1_stage1_L1_concat"
+  top: "Mconv2_stage1_L1_0"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu2_stage1_L1_0"
+  type: "PReLU"
+  bottom: "Mconv2_stage1_L1_0"
+  top: "Mconv2_stage1_L1_0"
+}
+layer {
+  name: "Mconv2_stage1_L1_1"
+  type: "Convolution"
+  bottom: "Mconv2_stage1_L1_0"
+  top: "Mconv2_stage1_L1_1"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu2_stage1_L1_1"
+  type: "PReLU"
+  bottom: "Mconv2_stage1_L1_1"
+  top: "Mconv2_stage1_L1_1"
+}
+layer {
+  name: "Mconv2_stage1_L1_2"
+  type: "Convolution"
+  bottom: "Mconv2_stage1_L1_1"
+  top: "Mconv2_stage1_L1_2"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu2_stage1_L1_2"
+  type: "PReLU"
+  bottom: "Mconv2_stage1_L1_2"
+  top: "Mconv2_stage1_L1_2"
+}
+layer {
+  name: "Mconv2_stage1_L1_concat"
+  type: "Concat"
+  bottom: "Mconv2_stage1_L1_0"
+  bottom: "Mconv2_stage1_L1_1"
+  bottom: "Mconv2_stage1_L1_2"
+  top: "Mconv2_stage1_L1_concat"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "Mconv3_stage1_L1_0"
+  type: "Convolution"
+  bottom: "Mconv2_stage1_L1_concat"
+  top: "Mconv3_stage1_L1_0"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu3_stage1_L1_0"
+  type: "PReLU"
+  bottom: "Mconv3_stage1_L1_0"
+  top: "Mconv3_stage1_L1_0"
+}
+layer {
+  name: "Mconv3_stage1_L1_1"
+  type: "Convolution"
+  bottom: "Mconv3_stage1_L1_0"
+  top: "Mconv3_stage1_L1_1"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu3_stage1_L1_1"
+  type: "PReLU"
+  bottom: "Mconv3_stage1_L1_1"
+  top: "Mconv3_stage1_L1_1"
+}
+layer {
+  name: "Mconv3_stage1_L1_2"
+  type: "Convolution"
+  bottom: "Mconv3_stage1_L1_1"
+  top: "Mconv3_stage1_L1_2"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu3_stage1_L1_2"
+  type: "PReLU"
+  bottom: "Mconv3_stage1_L1_2"
+  top: "Mconv3_stage1_L1_2"
+}
+layer {
+  name: "Mconv3_stage1_L1_concat"
+  type: "Concat"
+  bottom: "Mconv3_stage1_L1_0"
+  bottom: "Mconv3_stage1_L1_1"
+  bottom: "Mconv3_stage1_L1_2"
+  top: "Mconv3_stage1_L1_concat"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "Mconv4_stage1_L1_0"
+  type: "Convolution"
+  bottom: "Mconv3_stage1_L1_concat"
+  top: "Mconv4_stage1_L1_0"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu4_stage1_L1_0"
+  type: "PReLU"
+  bottom: "Mconv4_stage1_L1_0"
+  top: "Mconv4_stage1_L1_0"
+}
+layer {
+  name: "Mconv4_stage1_L1_1"
+  type: "Convolution"
+  bottom: "Mconv4_stage1_L1_0"
+  top: "Mconv4_stage1_L1_1"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu4_stage1_L1_1"
+  type: "PReLU"
+  bottom: "Mconv4_stage1_L1_1"
+  top: "Mconv4_stage1_L1_1"
+}
+layer {
+  name: "Mconv4_stage1_L1_2"
+  type: "Convolution"
+  bottom: "Mconv4_stage1_L1_1"
+  top: "Mconv4_stage1_L1_2"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu4_stage1_L1_2"
+  type: "PReLU"
+  bottom: "Mconv4_stage1_L1_2"
+  top: "Mconv4_stage1_L1_2"
+}
+layer {
+  name: "Mconv4_stage1_L1_concat"
+  type: "Concat"
+  bottom: "Mconv4_stage1_L1_0"
+  bottom: "Mconv4_stage1_L1_1"
+  bottom: "Mconv4_stage1_L1_2"
+  top: "Mconv4_stage1_L1_concat"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "Mconv5_stage1_L1_0"
+  type: "Convolution"
+  bottom: "Mconv4_stage1_L1_concat"
+  top: "Mconv5_stage1_L1_0"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu5_stage1_L1_0"
+  type: "PReLU"
+  bottom: "Mconv5_stage1_L1_0"
+  top: "Mconv5_stage1_L1_0"
+}
+layer {
+  name: "Mconv5_stage1_L1_1"
+  type: "Convolution"
+  bottom: "Mconv5_stage1_L1_0"
+  top: "Mconv5_stage1_L1_1"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu5_stage1_L1_1"
+  type: "PReLU"
+  bottom: "Mconv5_stage1_L1_1"
+  top: "Mconv5_stage1_L1_1"
+}
+layer {
+  name: "Mconv5_stage1_L1_2"
+  type: "Convolution"
+  bottom: "Mconv5_stage1_L1_1"
+  top: "Mconv5_stage1_L1_2"
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "Mprelu5_stage1_L1_2"
+  type: "PReLU"
+  bottom: "Mconv5_stage1_L1_2"
+  top: "Mconv5_stage1_L1_2"
+}
+layer {
+  name: "Mconv5_stage1_L1_concat"
+  type: "Concat"
+  bottom: "Mconv5_stage1_L1_0"
+  bottom: "Mconv5_stage1_L1_1"
+  bottom: "Mconv5_stage1_L1_2"
+  top: "Mconv5_stage1_L1_concat"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "Mconv6_stage1_L1"
+  type: "Convolution"
+  bottom: "Mconv5_stage1_L1_concat"
+  top: "Mconv6_stage1_L1"
+  convolution_param {
+    num_output: 512
+    pad: 0
+    kernel_size: 1
+  }
+}
+layer {
+  name: "Mprelu6_stage1_L1"
+  type: "PReLU"
+  bottom: "Mconv6_stage1_L1"
+  top: "Mconv6_stage1_L1"
+}
+layer {
+  name: "Mconv7_stage1_L1"
+  type: "Convolution"
+  bottom: "Mconv6_stage1_L1"
+  top: "Mconv7_stage1_L1"
+  convolution_param {
+    num_output: 26
+    pad: 0
+    kernel_size: 1
+  }
+}
+layer {
+  name: "net_output"
+  type: "Concat"
+  bottom: "Mconv7_stage1_L1"
+  bottom: "Mconv7_stage3_L2"
+  top: "net_output"
+  concat_param {
+    axis: 1
+  }
+}

pose/body_25/pose_iter_584000.caffemodel

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:44e3d7ebd8c8b62d4366d67127f1b562611a9e8fd0f4f3cdeeb4bb4a6ed12be6
+size 104715850

pose/coco/pose_deploy_linevec.prototxt

@@ -0,0 +1,2976 @@
+input: "image"
+input_dim: 1
+input_dim: 3
+input_dim: 1 # This value will be defined at runtime
+input_dim: 1 # This value will be defined at runtime
+layer {
+  name: "conv1_1"
+  type: "Convolution"
+  bottom: "image"
+  top: "conv1_1"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    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: "relu1_1"
+  type: "ReLU"
+  bottom: "conv1_1"
+  top: "conv1_1"
+}
+layer {
+  name: "conv1_2"
+  type: "Convolution"
+  bottom: "conv1_1"
+  top: "conv1_2"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    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: "relu1_2"
+  type: "ReLU"
+  bottom: "conv1_2"
+  top: "conv1_2"
+}
+layer {
+  name: "pool1_stage1"
+  type: "Pooling"
+  bottom: "conv1_2"
+  top: "pool1_stage1"
+  pooling_param {
+    pool: MAX
+    kernel_size: 2
+    stride: 2
+  }
+}
+layer {
+  name: "conv2_1"
+  type: "Convolution"
+  bottom: "pool1_stage1"
+  top: "conv2_1"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "relu2_1"
+  type: "ReLU"
+  bottom: "conv2_1"
+  top: "conv2_1"
+}
+layer {
+  name: "conv2_2"
+  type: "Convolution"
+  bottom: "conv2_1"
+  top: "conv2_2"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "relu2_2"
+  type: "ReLU"
+  bottom: "conv2_2"
+  top: "conv2_2"
+}
+layer {
+  name: "pool2_stage1"
+  type: "Pooling"
+  bottom: "conv2_2"
+  top: "pool2_stage1"
+  pooling_param {
+    pool: MAX
+    kernel_size: 2
+    stride: 2
+  }
+}
+layer {
+  name: "conv3_1"
+  type: "Convolution"
+  bottom: "pool2_stage1"
+  top: "conv3_1"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    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: "relu3_1"
+  type: "ReLU"
+  bottom: "conv3_1"
+  top: "conv3_1"
+}
+layer {
+  name: "conv3_2"
+  type: "Convolution"
+  bottom: "conv3_1"
+  top: "conv3_2"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    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: "relu3_2"
+  type: "ReLU"
+  bottom: "conv3_2"
+  top: "conv3_2"
+}
+layer {
+  name: "conv3_3"
+  type: "Convolution"
+  bottom: "conv3_2"
+  top: "conv3_3"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    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: "relu3_3"
+  type: "ReLU"
+  bottom: "conv3_3"
+  top: "conv3_3"
+}
+layer {
+  name: "conv3_4"
+  type: "Convolution"
+  bottom: "conv3_3"
+  top: "conv3_4"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    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: "relu3_4"
+  type: "ReLU"
+  bottom: "conv3_4"
+  top: "conv3_4"
+}
+layer {
+  name: "pool3_stage1"
+  type: "Pooling"
+  bottom: "conv3_4"
+  top: "pool3_stage1"
+  pooling_param {
+    pool: MAX
+    kernel_size: 2
+    stride: 2
+  }
+}
+layer {
+  name: "conv4_1"
+  type: "Convolution"
+  bottom: "pool3_stage1"
+  top: "conv4_1"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 512
+    pad: 1
+    kernel_size: 3
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "relu4_1"
+  type: "ReLU"
+  bottom: "conv4_1"
+  top: "conv4_1"
+}
+layer {
+  name: "conv4_2"
+  type: "Convolution"
+  bottom: "conv4_1"
+  top: "conv4_2"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 512
+    pad: 1
+    kernel_size: 3
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "relu4_2"
+  type: "ReLU"
+  bottom: "conv4_2"
+  top: "conv4_2"
+}
+layer {
+  name: "conv4_3_CPM"
+  type: "Convolution"
+  bottom: "conv4_2"
+  top: "conv4_3_CPM"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    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: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    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: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    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: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    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: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    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: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    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: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    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: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    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: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    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: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    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: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 38
+    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: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 19
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 38
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 19
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 38
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 19
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 38
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 19
+    pad: 0
+    kernel_size: 1
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "concat_stage5"
+  type: "Concat"
+  bottom: "Mconv7_stage4_L1"
+  bottom: "Mconv7_stage4_L2"
+  bottom: "conv4_4_CPM"
+  top: "concat_stage5"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "Mconv1_stage5_L1"
+  type: "Convolution"
+  bottom: "concat_stage5"
+  top: "Mconv1_stage5_L1"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mrelu1_stage5_L1"
+  type: "ReLU"
+  bottom: "Mconv1_stage5_L1"
+  top: "Mconv1_stage5_L1"
+}
+layer {
+  name: "Mconv1_stage5_L2"
+  type: "Convolution"
+  bottom: "concat_stage5"
+  top: "Mconv1_stage5_L2"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mrelu1_stage5_L2"
+  type: "ReLU"
+  bottom: "Mconv1_stage5_L2"
+  top: "Mconv1_stage5_L2"
+}
+layer {
+  name: "Mconv2_stage5_L1"
+  type: "Convolution"
+  bottom: "Mconv1_stage5_L1"
+  top: "Mconv2_stage5_L1"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mrelu2_stage5_L1"
+  type: "ReLU"
+  bottom: "Mconv2_stage5_L1"
+  top: "Mconv2_stage5_L1"
+}
+layer {
+  name: "Mconv2_stage5_L2"
+  type: "Convolution"
+  bottom: "Mconv1_stage5_L2"
+  top: "Mconv2_stage5_L2"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mrelu2_stage5_L2"
+  type: "ReLU"
+  bottom: "Mconv2_stage5_L2"
+  top: "Mconv2_stage5_L2"
+}
+layer {
+  name: "Mconv3_stage5_L1"
+  type: "Convolution"
+  bottom: "Mconv2_stage5_L1"
+  top: "Mconv3_stage5_L1"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mrelu3_stage5_L1"
+  type: "ReLU"
+  bottom: "Mconv3_stage5_L1"
+  top: "Mconv3_stage5_L1"
+}
+layer {
+  name: "Mconv3_stage5_L2"
+  type: "Convolution"
+  bottom: "Mconv2_stage5_L2"
+  top: "Mconv3_stage5_L2"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mrelu3_stage5_L2"
+  type: "ReLU"
+  bottom: "Mconv3_stage5_L2"
+  top: "Mconv3_stage5_L2"
+}
+layer {
+  name: "Mconv4_stage5_L1"
+  type: "Convolution"
+  bottom: "Mconv3_stage5_L1"
+  top: "Mconv4_stage5_L1"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mrelu4_stage5_L1"
+  type: "ReLU"
+  bottom: "Mconv4_stage5_L1"
+  top: "Mconv4_stage5_L1"
+}
+layer {
+  name: "Mconv4_stage5_L2"
+  type: "Convolution"
+  bottom: "Mconv3_stage5_L2"
+  top: "Mconv4_stage5_L2"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mrelu4_stage5_L2"
+  type: "ReLU"
+  bottom: "Mconv4_stage5_L2"
+  top: "Mconv4_stage5_L2"
+}
+layer {
+  name: "Mconv5_stage5_L1"
+  type: "Convolution"
+  bottom: "Mconv4_stage5_L1"
+  top: "Mconv5_stage5_L1"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mrelu5_stage5_L1"
+  type: "ReLU"
+  bottom: "Mconv5_stage5_L1"
+  top: "Mconv5_stage5_L1"
+}
+layer {
+  name: "Mconv5_stage5_L2"
+  type: "Convolution"
+  bottom: "Mconv4_stage5_L2"
+  top: "Mconv5_stage5_L2"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mrelu5_stage5_L2"
+  type: "ReLU"
+  bottom: "Mconv5_stage5_L2"
+  top: "Mconv5_stage5_L2"
+}
+layer {
+  name: "Mconv6_stage5_L1"
+  type: "Convolution"
+  bottom: "Mconv5_stage5_L1"
+  top: "Mconv6_stage5_L1"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 0
+    kernel_size: 1
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mrelu6_stage5_L1"
+  type: "ReLU"
+  bottom: "Mconv6_stage5_L1"
+  top: "Mconv6_stage5_L1"
+}
+layer {
+  name: "Mconv6_stage5_L2"
+  type: "Convolution"
+  bottom: "Mconv5_stage5_L2"
+  top: "Mconv6_stage5_L2"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 0
+    kernel_size: 1
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mrelu6_stage5_L2"
+  type: "ReLU"
+  bottom: "Mconv6_stage5_L2"
+  top: "Mconv6_stage5_L2"
+}
+layer {
+  name: "Mconv7_stage5_L1"
+  type: "Convolution"
+  bottom: "Mconv6_stage5_L1"
+  top: "Mconv7_stage5_L1"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 38
+    pad: 0
+    kernel_size: 1
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mconv7_stage5_L2"
+  type: "Convolution"
+  bottom: "Mconv6_stage5_L2"
+  top: "Mconv7_stage5_L2"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 19
+    pad: 0
+    kernel_size: 1
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "concat_stage6"
+  type: "Concat"
+  bottom: "Mconv7_stage5_L1"
+  bottom: "Mconv7_stage5_L2"
+  bottom: "conv4_4_CPM"
+  top: "concat_stage6"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "Mconv1_stage6_L1"
+  type: "Convolution"
+  bottom: "concat_stage6"
+  top: "Mconv1_stage6_L1"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mrelu1_stage6_L1"
+  type: "ReLU"
+  bottom: "Mconv1_stage6_L1"
+  top: "Mconv1_stage6_L1"
+}
+layer {
+  name: "Mconv1_stage6_L2"
+  type: "Convolution"
+  bottom: "concat_stage6"
+  top: "Mconv1_stage6_L2"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mrelu1_stage6_L2"
+  type: "ReLU"
+  bottom: "Mconv1_stage6_L2"
+  top: "Mconv1_stage6_L2"
+}
+layer {
+  name: "Mconv2_stage6_L1"
+  type: "Convolution"
+  bottom: "Mconv1_stage6_L1"
+  top: "Mconv2_stage6_L1"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mrelu2_stage6_L1"
+  type: "ReLU"
+  bottom: "Mconv2_stage6_L1"
+  top: "Mconv2_stage6_L1"
+}
+layer {
+  name: "Mconv2_stage6_L2"
+  type: "Convolution"
+  bottom: "Mconv1_stage6_L2"
+  top: "Mconv2_stage6_L2"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mrelu2_stage6_L2"
+  type: "ReLU"
+  bottom: "Mconv2_stage6_L2"
+  top: "Mconv2_stage6_L2"
+}
+layer {
+  name: "Mconv3_stage6_L1"
+  type: "Convolution"
+  bottom: "Mconv2_stage6_L1"
+  top: "Mconv3_stage6_L1"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mrelu3_stage6_L1"
+  type: "ReLU"
+  bottom: "Mconv3_stage6_L1"
+  top: "Mconv3_stage6_L1"
+}
+layer {
+  name: "Mconv3_stage6_L2"
+  type: "Convolution"
+  bottom: "Mconv2_stage6_L2"
+  top: "Mconv3_stage6_L2"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mrelu3_stage6_L2"
+  type: "ReLU"
+  bottom: "Mconv3_stage6_L2"
+  top: "Mconv3_stage6_L2"
+}
+layer {
+  name: "Mconv4_stage6_L1"
+  type: "Convolution"
+  bottom: "Mconv3_stage6_L1"
+  top: "Mconv4_stage6_L1"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mrelu4_stage6_L1"
+  type: "ReLU"
+  bottom: "Mconv4_stage6_L1"
+  top: "Mconv4_stage6_L1"
+}
+layer {
+  name: "Mconv4_stage6_L2"
+  type: "Convolution"
+  bottom: "Mconv3_stage6_L2"
+  top: "Mconv4_stage6_L2"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mrelu4_stage6_L2"
+  type: "ReLU"
+  bottom: "Mconv4_stage6_L2"
+  top: "Mconv4_stage6_L2"
+}
+layer {
+  name: "Mconv5_stage6_L1"
+  type: "Convolution"
+  bottom: "Mconv4_stage6_L1"
+  top: "Mconv5_stage6_L1"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mrelu5_stage6_L1"
+  type: "ReLU"
+  bottom: "Mconv5_stage6_L1"
+  top: "Mconv5_stage6_L1"
+}
+layer {
+  name: "Mconv5_stage6_L2"
+  type: "Convolution"
+  bottom: "Mconv4_stage6_L2"
+  top: "Mconv5_stage6_L2"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mrelu5_stage6_L2"
+  type: "ReLU"
+  bottom: "Mconv5_stage6_L2"
+  top: "Mconv5_stage6_L2"
+}
+layer {
+  name: "Mconv6_stage6_L1"
+  type: "Convolution"
+  bottom: "Mconv5_stage6_L1"
+  top: "Mconv6_stage6_L1"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 0
+    kernel_size: 1
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mrelu6_stage6_L1"
+  type: "ReLU"
+  bottom: "Mconv6_stage6_L1"
+  top: "Mconv6_stage6_L1"
+}
+layer {
+  name: "Mconv6_stage6_L2"
+  type: "Convolution"
+  bottom: "Mconv5_stage6_L2"
+  top: "Mconv6_stage6_L2"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 0
+    kernel_size: 1
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mrelu6_stage6_L2"
+  type: "ReLU"
+  bottom: "Mconv6_stage6_L2"
+  top: "Mconv6_stage6_L2"
+}
+layer {
+  name: "Mconv7_stage6_L1"
+  type: "Convolution"
+  bottom: "Mconv6_stage6_L1"
+  top: "Mconv7_stage6_L1"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 38
+    pad: 0
+    kernel_size: 1
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mconv7_stage6_L2"
+  type: "Convolution"
+  bottom: "Mconv6_stage6_L2"
+  top: "Mconv7_stage6_L2"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 19
+    pad: 0
+    kernel_size: 1
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "concat_stage7"
+  type: "Concat"
+  bottom: "Mconv7_stage6_L2"
+  bottom: "Mconv7_stage6_L1"
+  # top: "concat_stage7"
+  top: "net_output"
+  concat_param {
+    axis: 1
+  }
+}

pose/coco/pose_iter_440000.caffemodel

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b4cf475576abd7b15d5316f1ee65eb492b5c9f5865e70a2e7882ed31fb682549
+size 209274056

pose/mpi/pose_deploy_linevec.prototxt

@@ -0,0 +1,2975 @@
+input: "image"
+input_dim: 1
+input_dim: 3
+input_dim: 1 # This value will be defined at runtime
+input_dim: 1 # This value will be defined at runtime
+layer {
+  name: "conv1_1"
+  type: "Convolution"
+  bottom: "image"
+  top: "conv1_1"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    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: "relu1_1"
+  type: "ReLU"
+  bottom: "conv1_1"
+  top: "conv1_1"
+}
+layer {
+  name: "conv1_2"
+  type: "Convolution"
+  bottom: "conv1_1"
+  top: "conv1_2"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    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: "relu1_2"
+  type: "ReLU"
+  bottom: "conv1_2"
+  top: "conv1_2"
+}
+layer {
+  name: "pool1_stage1"
+  type: "Pooling"
+  bottom: "conv1_2"
+  top: "pool1_stage1"
+  pooling_param {
+    pool: MAX
+    kernel_size: 2
+    stride: 2
+  }
+}
+layer {
+  name: "conv2_1"
+  type: "Convolution"
+  bottom: "pool1_stage1"
+  top: "conv2_1"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "relu2_1"
+  type: "ReLU"
+  bottom: "conv2_1"
+  top: "conv2_1"
+}
+layer {
+  name: "conv2_2"
+  type: "Convolution"
+  bottom: "conv2_1"
+  top: "conv2_2"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "relu2_2"
+  type: "ReLU"
+  bottom: "conv2_2"
+  top: "conv2_2"
+}
+layer {
+  name: "pool2_stage1"
+  type: "Pooling"
+  bottom: "conv2_2"
+  top: "pool2_stage1"
+  pooling_param {
+    pool: MAX
+    kernel_size: 2
+    stride: 2
+  }
+}
+layer {
+  name: "conv3_1"
+  type: "Convolution"
+  bottom: "pool2_stage1"
+  top: "conv3_1"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    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: "relu3_1"
+  type: "ReLU"
+  bottom: "conv3_1"
+  top: "conv3_1"
+}
+layer {
+  name: "conv3_2"
+  type: "Convolution"
+  bottom: "conv3_1"
+  top: "conv3_2"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    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: "relu3_2"
+  type: "ReLU"
+  bottom: "conv3_2"
+  top: "conv3_2"
+}
+layer {
+  name: "conv3_3"
+  type: "Convolution"
+  bottom: "conv3_2"
+  top: "conv3_3"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    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: "relu3_3"
+  type: "ReLU"
+  bottom: "conv3_3"
+  top: "conv3_3"
+}
+layer {
+  name: "conv3_4"
+  type: "Convolution"
+  bottom: "conv3_3"
+  top: "conv3_4"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    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: "relu3_4"
+  type: "ReLU"
+  bottom: "conv3_4"
+  top: "conv3_4"
+}
+layer {
+  name: "pool3_stage1"
+  type: "Pooling"
+  bottom: "conv3_4"
+  top: "pool3_stage1"
+  pooling_param {
+    pool: MAX
+    kernel_size: 2
+    stride: 2
+  }
+}
+layer {
+  name: "conv4_1"
+  type: "Convolution"
+  bottom: "pool3_stage1"
+  top: "conv4_1"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 512
+    pad: 1
+    kernel_size: 3
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "relu4_1"
+  type: "ReLU"
+  bottom: "conv4_1"
+  top: "conv4_1"
+}
+layer {
+  name: "conv4_2"
+  type: "Convolution"
+  bottom: "conv4_1"
+  top: "conv4_2"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 512
+    pad: 1
+    kernel_size: 3
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "relu4_2"
+  type: "ReLU"
+  bottom: "conv4_2"
+  top: "conv4_2"
+}
+layer {
+  name: "conv4_3_CPM"
+  type: "Convolution"
+  bottom: "conv4_2"
+  top: "conv4_3_CPM"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    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: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    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: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    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: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    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: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    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: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    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: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    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: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    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: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    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: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    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: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 28
+    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: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 28
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 28
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 28
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    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_stage5"
+  type: "Concat"
+  bottom: "Mconv7_stage4_L1"
+  bottom: "Mconv7_stage4_L2"
+  bottom: "conv4_4_CPM"
+  top: "concat_stage5"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "Mconv1_stage5_L1"
+  type: "Convolution"
+  bottom: "concat_stage5"
+  top: "Mconv1_stage5_L1"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mrelu1_stage5_L1"
+  type: "ReLU"
+  bottom: "Mconv1_stage5_L1"
+  top: "Mconv1_stage5_L1"
+}
+layer {
+  name: "Mconv1_stage5_L2"
+  type: "Convolution"
+  bottom: "concat_stage5"
+  top: "Mconv1_stage5_L2"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mrelu1_stage5_L2"
+  type: "ReLU"
+  bottom: "Mconv1_stage5_L2"
+  top: "Mconv1_stage5_L2"
+}
+layer {
+  name: "Mconv2_stage5_L1"
+  type: "Convolution"
+  bottom: "Mconv1_stage5_L1"
+  top: "Mconv2_stage5_L1"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mrelu2_stage5_L1"
+  type: "ReLU"
+  bottom: "Mconv2_stage5_L1"
+  top: "Mconv2_stage5_L1"
+}
+layer {
+  name: "Mconv2_stage5_L2"
+  type: "Convolution"
+  bottom: "Mconv1_stage5_L2"
+  top: "Mconv2_stage5_L2"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mrelu2_stage5_L2"
+  type: "ReLU"
+  bottom: "Mconv2_stage5_L2"
+  top: "Mconv2_stage5_L2"
+}
+layer {
+  name: "Mconv3_stage5_L1"
+  type: "Convolution"
+  bottom: "Mconv2_stage5_L1"
+  top: "Mconv3_stage5_L1"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mrelu3_stage5_L1"
+  type: "ReLU"
+  bottom: "Mconv3_stage5_L1"
+  top: "Mconv3_stage5_L1"
+}
+layer {
+  name: "Mconv3_stage5_L2"
+  type: "Convolution"
+  bottom: "Mconv2_stage5_L2"
+  top: "Mconv3_stage5_L2"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mrelu3_stage5_L2"
+  type: "ReLU"
+  bottom: "Mconv3_stage5_L2"
+  top: "Mconv3_stage5_L2"
+}
+layer {
+  name: "Mconv4_stage5_L1"
+  type: "Convolution"
+  bottom: "Mconv3_stage5_L1"
+  top: "Mconv4_stage5_L1"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mrelu4_stage5_L1"
+  type: "ReLU"
+  bottom: "Mconv4_stage5_L1"
+  top: "Mconv4_stage5_L1"
+}
+layer {
+  name: "Mconv4_stage5_L2"
+  type: "Convolution"
+  bottom: "Mconv3_stage5_L2"
+  top: "Mconv4_stage5_L2"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mrelu4_stage5_L2"
+  type: "ReLU"
+  bottom: "Mconv4_stage5_L2"
+  top: "Mconv4_stage5_L2"
+}
+layer {
+  name: "Mconv5_stage5_L1"
+  type: "Convolution"
+  bottom: "Mconv4_stage5_L1"
+  top: "Mconv5_stage5_L1"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mrelu5_stage5_L1"
+  type: "ReLU"
+  bottom: "Mconv5_stage5_L1"
+  top: "Mconv5_stage5_L1"
+}
+layer {
+  name: "Mconv5_stage5_L2"
+  type: "Convolution"
+  bottom: "Mconv4_stage5_L2"
+  top: "Mconv5_stage5_L2"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mrelu5_stage5_L2"
+  type: "ReLU"
+  bottom: "Mconv5_stage5_L2"
+  top: "Mconv5_stage5_L2"
+}
+layer {
+  name: "Mconv6_stage5_L1"
+  type: "Convolution"
+  bottom: "Mconv5_stage5_L1"
+  top: "Mconv6_stage5_L1"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 0
+    kernel_size: 1
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mrelu6_stage5_L1"
+  type: "ReLU"
+  bottom: "Mconv6_stage5_L1"
+  top: "Mconv6_stage5_L1"
+}
+layer {
+  name: "Mconv6_stage5_L2"
+  type: "Convolution"
+  bottom: "Mconv5_stage5_L2"
+  top: "Mconv6_stage5_L2"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 0
+    kernel_size: 1
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mrelu6_stage5_L2"
+  type: "ReLU"
+  bottom: "Mconv6_stage5_L2"
+  top: "Mconv6_stage5_L2"
+}
+layer {
+  name: "Mconv7_stage5_L1"
+  type: "Convolution"
+  bottom: "Mconv6_stage5_L1"
+  top: "Mconv7_stage5_L1"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 28
+    pad: 0
+    kernel_size: 1
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mconv7_stage5_L2"
+  type: "Convolution"
+  bottom: "Mconv6_stage5_L2"
+  top: "Mconv7_stage5_L2"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    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_stage6"
+  type: "Concat"
+  bottom: "Mconv7_stage5_L1"
+  bottom: "Mconv7_stage5_L2"
+  bottom: "conv4_4_CPM"
+  top: "concat_stage6"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "Mconv1_stage6_L1"
+  type: "Convolution"
+  bottom: "concat_stage6"
+  top: "Mconv1_stage6_L1"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mrelu1_stage6_L1"
+  type: "ReLU"
+  bottom: "Mconv1_stage6_L1"
+  top: "Mconv1_stage6_L1"
+}
+layer {
+  name: "Mconv1_stage6_L2"
+  type: "Convolution"
+  bottom: "concat_stage6"
+  top: "Mconv1_stage6_L2"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mrelu1_stage6_L2"
+  type: "ReLU"
+  bottom: "Mconv1_stage6_L2"
+  top: "Mconv1_stage6_L2"
+}
+layer {
+  name: "Mconv2_stage6_L1"
+  type: "Convolution"
+  bottom: "Mconv1_stage6_L1"
+  top: "Mconv2_stage6_L1"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mrelu2_stage6_L1"
+  type: "ReLU"
+  bottom: "Mconv2_stage6_L1"
+  top: "Mconv2_stage6_L1"
+}
+layer {
+  name: "Mconv2_stage6_L2"
+  type: "Convolution"
+  bottom: "Mconv1_stage6_L2"
+  top: "Mconv2_stage6_L2"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mrelu2_stage6_L2"
+  type: "ReLU"
+  bottom: "Mconv2_stage6_L2"
+  top: "Mconv2_stage6_L2"
+}
+layer {
+  name: "Mconv3_stage6_L1"
+  type: "Convolution"
+  bottom: "Mconv2_stage6_L1"
+  top: "Mconv3_stage6_L1"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mrelu3_stage6_L1"
+  type: "ReLU"
+  bottom: "Mconv3_stage6_L1"
+  top: "Mconv3_stage6_L1"
+}
+layer {
+  name: "Mconv3_stage6_L2"
+  type: "Convolution"
+  bottom: "Mconv2_stage6_L2"
+  top: "Mconv3_stage6_L2"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mrelu3_stage6_L2"
+  type: "ReLU"
+  bottom: "Mconv3_stage6_L2"
+  top: "Mconv3_stage6_L2"
+}
+layer {
+  name: "Mconv4_stage6_L1"
+  type: "Convolution"
+  bottom: "Mconv3_stage6_L1"
+  top: "Mconv4_stage6_L1"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mrelu4_stage6_L1"
+  type: "ReLU"
+  bottom: "Mconv4_stage6_L1"
+  top: "Mconv4_stage6_L1"
+}
+layer {
+  name: "Mconv4_stage6_L2"
+  type: "Convolution"
+  bottom: "Mconv3_stage6_L2"
+  top: "Mconv4_stage6_L2"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mrelu4_stage6_L2"
+  type: "ReLU"
+  bottom: "Mconv4_stage6_L2"
+  top: "Mconv4_stage6_L2"
+}
+layer {
+  name: "Mconv5_stage6_L1"
+  type: "Convolution"
+  bottom: "Mconv4_stage6_L1"
+  top: "Mconv5_stage6_L1"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mrelu5_stage6_L1"
+  type: "ReLU"
+  bottom: "Mconv5_stage6_L1"
+  top: "Mconv5_stage6_L1"
+}
+layer {
+  name: "Mconv5_stage6_L2"
+  type: "Convolution"
+  bottom: "Mconv4_stage6_L2"
+  top: "Mconv5_stage6_L2"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mrelu5_stage6_L2"
+  type: "ReLU"
+  bottom: "Mconv5_stage6_L2"
+  top: "Mconv5_stage6_L2"
+}
+layer {
+  name: "Mconv6_stage6_L1"
+  type: "Convolution"
+  bottom: "Mconv5_stage6_L1"
+  top: "Mconv6_stage6_L1"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 0
+    kernel_size: 1
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mrelu6_stage6_L1"
+  type: "ReLU"
+  bottom: "Mconv6_stage6_L1"
+  top: "Mconv6_stage6_L1"
+}
+layer {
+  name: "Mconv6_stage6_L2"
+  type: "Convolution"
+  bottom: "Mconv5_stage6_L2"
+  top: "Mconv6_stage6_L2"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 0
+    kernel_size: 1
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mrelu6_stage6_L2"
+  type: "ReLU"
+  bottom: "Mconv6_stage6_L2"
+  top: "Mconv6_stage6_L2"
+}
+layer {
+  name: "Mconv7_stage6_L1"
+  type: "Convolution"
+  bottom: "Mconv6_stage6_L1"
+  top: "Mconv7_stage6_L1"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 28
+    pad: 0
+    kernel_size: 1
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "Mconv7_stage6_L2"
+  type: "Convolution"
+  bottom: "Mconv6_stage6_L2"
+  top: "Mconv7_stage6_L2"
+  param {
+    lr_mult: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    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_stage7"
+  type: "Concat"
+  bottom: "Mconv7_stage6_L2"
+  bottom: "Mconv7_stage6_L1"
+  top: "net_output"
+  concat_param {
+    axis: 1
+  }
+}

pose/mpi/pose_deploy_linevec_faster_4_stages.prototxt

@@ -0,0 +1,2081 @@
+input: "image"
+input_dim: 1
+input_dim: 3
+input_dim: 1 # This value will be defined at runtime
+input_dim: 1 # This value will be defined at runtime
+layer {
+  name: "conv1_1"
+  type: "Convolution"
+  bottom: "image"
+  top: "conv1_1"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    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: "relu1_1"
+  type: "ReLU"
+  bottom: "conv1_1"
+  top: "conv1_1"
+}
+layer {
+  name: "conv1_2"
+  type: "Convolution"
+  bottom: "conv1_1"
+  top: "conv1_2"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    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: "relu1_2"
+  type: "ReLU"
+  bottom: "conv1_2"
+  top: "conv1_2"
+}
+layer {
+  name: "pool1_stage1"
+  type: "Pooling"
+  bottom: "conv1_2"
+  top: "pool1_stage1"
+  pooling_param {
+    pool: MAX
+    kernel_size: 2
+    stride: 2
+  }
+}
+layer {
+  name: "conv2_1"
+  type: "Convolution"
+  bottom: "pool1_stage1"
+  top: "conv2_1"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "relu2_1"
+  type: "ReLU"
+  bottom: "conv2_1"
+  top: "conv2_1"
+}
+layer {
+  name: "conv2_2"
+  type: "Convolution"
+  bottom: "conv2_1"
+  top: "conv2_2"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "relu2_2"
+  type: "ReLU"
+  bottom: "conv2_2"
+  top: "conv2_2"
+}
+layer {
+  name: "pool2_stage1"
+  type: "Pooling"
+  bottom: "conv2_2"
+  top: "pool2_stage1"
+  pooling_param {
+    pool: MAX
+    kernel_size: 2
+    stride: 2
+  }
+}
+layer {
+  name: "conv3_1"
+  type: "Convolution"
+  bottom: "pool2_stage1"
+  top: "conv3_1"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    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: "relu3_1"
+  type: "ReLU"
+  bottom: "conv3_1"
+  top: "conv3_1"
+}
+layer {
+  name: "conv3_2"
+  type: "Convolution"
+  bottom: "conv3_1"
+  top: "conv3_2"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    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: "relu3_2"
+  type: "ReLU"
+  bottom: "conv3_2"
+  top: "conv3_2"
+}
+layer {
+  name: "conv3_3"
+  type: "Convolution"
+  bottom: "conv3_2"
+  top: "conv3_3"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    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: "relu3_3"
+  type: "ReLU"
+  bottom: "conv3_3"
+  top: "conv3_3"
+}
+layer {
+  name: "conv3_4"
+  type: "Convolution"
+  bottom: "conv3_3"
+  top: "conv3_4"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    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: "relu3_4"
+  type: "ReLU"
+  bottom: "conv3_4"
+  top: "conv3_4"
+}
+layer {
+  name: "pool3_stage1"
+  type: "Pooling"
+  bottom: "conv3_4"
+  top: "pool3_stage1"
+  pooling_param {
+    pool: MAX
+    kernel_size: 2
+    stride: 2
+  }
+}
+layer {
+  name: "conv4_1"
+  type: "Convolution"
+  bottom: "pool3_stage1"
+  top: "conv4_1"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 512
+    pad: 1
+    kernel_size: 3
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "relu4_1"
+  type: "ReLU"
+  bottom: "conv4_1"
+  top: "conv4_1"
+}
+layer {
+  name: "conv4_2"
+  type: "Convolution"
+  bottom: "conv4_1"
+  top: "conv4_2"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 512
+    pad: 1
+    kernel_size: 3
+    weight_filler {
+      type: "gaussian"
+      std: 0.01
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layer {
+  name: "relu4_2"
+  type: "ReLU"
+  bottom: "conv4_2"
+  top: "conv4_2"
+}
+layer {
+  name: "conv4_3_CPM"
+  type: "Convolution"
+  bottom: "conv4_2"
+  top: "conv4_3_CPM"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    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: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    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: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    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: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    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: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    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: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    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: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    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: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    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: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    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: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    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: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 28
+    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: 1.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2.0
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 28
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 28
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 3
+    kernel_size: 7
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 128
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    decay_mult: 0
+  }
+  convolution_param {
+    num_output: 28
+    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: 4.0
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 8.0
+    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_stage7"
+  type: "Concat"
+  bottom: "Mconv7_stage4_L2"
+  bottom: "Mconv7_stage4_L1"
+  top: "net_output"
+  concat_param {
+    axis: 1
+  }
+}

pose/mpi/pose_iter_160000.caffemodel

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2ea61d8549a3386972ba9a310468f961e7157d94c5ee2529a51b3901bb82ee21
+size 205950363