optimize code in Example app

Signed-off-by: khemendra kumar <khemendra.kumar@huawei.com>
Change-Id: Ib05d4159d1b9e9fe8dd42ce4c665aa5968b7496d

diff --git a/example-apps/ROBO/aPaaS/Obj_Detection_service/MobileNetSSD_deploy.prototxt b/example-apps/ROBO/aPaaS/Obj_Detection_service/MobileNetSSD_deploy.prototxt
new file mode 100755 (executable)
index 0000000..fdc8126
--- /dev/null
+++ b/example-apps/ROBO/aPaaS/Obj_Detection_service/MobileNetSSD_deploy.prototxt
@@ -0,0 +1,1912 @@
+name: "MobileNet-SSD"
+input: "data"
+input_shape {
+  dim: 1
+  dim: 3
+  dim: 300
+  dim: 300
+}
+layer {
+  name: "conv0"
+  type: "Convolution"
+  bottom: "data"
+  top: "conv0"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 32
+    pad: 1
+    kernel_size: 3
+    stride: 2
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "conv0/relu"
+  type: "ReLU"
+  bottom: "conv0"
+  top: "conv0"
+}
+layer {
+  name: "conv1/dw"
+  type: "Convolution"
+  bottom: "conv0"
+  top: "conv1/dw"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 32
+    pad: 1
+    kernel_size: 3
+    group: 32
+    engine: CAFFE
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "conv1/dw/relu"
+  type: "ReLU"
+  bottom: "conv1/dw"
+  top: "conv1/dw"
+}
+layer {
+  name: "conv1"
+  type: "Convolution"
+  bottom: "conv1/dw"
+  top: "conv1"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 64
+    kernel_size: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "conv1/relu"
+  type: "ReLU"
+  bottom: "conv1"
+  top: "conv1"
+}
+layer {
+  name: "conv2/dw"
+  type: "Convolution"
+  bottom: "conv1"
+  top: "conv2/dw"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 64
+    pad: 1
+    kernel_size: 3
+    stride: 2
+    group: 64
+    engine: CAFFE
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "conv2/dw/relu"
+  type: "ReLU"
+  bottom: "conv2/dw"
+  top: "conv2/dw"
+}
+layer {
+  name: "conv2"
+  type: "Convolution"
+  bottom: "conv2/dw"
+  top: "conv2"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 128
+    kernel_size: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "conv2/relu"
+  type: "ReLU"
+  bottom: "conv2"
+  top: "conv2"
+}
+layer {
+  name: "conv3/dw"
+  type: "Convolution"
+  bottom: "conv2"
+  top: "conv3/dw"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+    group: 128
+    engine: CAFFE
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "conv3/dw/relu"
+  type: "ReLU"
+  bottom: "conv3/dw"
+  top: "conv3/dw"
+}
+layer {
+  name: "conv3"
+  type: "Convolution"
+  bottom: "conv3/dw"
+  top: "conv3"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 128
+    kernel_size: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "conv3/relu"
+  type: "ReLU"
+  bottom: "conv3"
+  top: "conv3"
+}
+layer {
+  name: "conv4/dw"
+  type: "Convolution"
+  bottom: "conv3"
+  top: "conv4/dw"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+    stride: 2
+    group: 128
+    engine: CAFFE
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "conv4/dw/relu"
+  type: "ReLU"
+  bottom: "conv4/dw"
+  top: "conv4/dw"
+}
+layer {
+  name: "conv4"
+  type: "Convolution"
+  bottom: "conv4/dw"
+  top: "conv4"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 256
+    kernel_size: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "conv4/relu"
+  type: "ReLU"
+  bottom: "conv4"
+  top: "conv4"
+}
+layer {
+  name: "conv5/dw"
+  type: "Convolution"
+  bottom: "conv4"
+  top: "conv5/dw"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 256
+    pad: 1
+    kernel_size: 3
+    group: 256
+    engine: CAFFE
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "conv5/dw/relu"
+  type: "ReLU"
+  bottom: "conv5/dw"
+  top: "conv5/dw"
+}
+layer {
+  name: "conv5"
+  type: "Convolution"
+  bottom: "conv5/dw"
+  top: "conv5"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 256
+    kernel_size: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "conv5/relu"
+  type: "ReLU"
+  bottom: "conv5"
+  top: "conv5"
+}
+layer {
+  name: "conv6/dw"
+  type: "Convolution"
+  bottom: "conv5"
+  top: "conv6/dw"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 256
+    pad: 1
+    kernel_size: 3
+    stride: 2
+    group: 256
+    engine: CAFFE
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "conv6/dw/relu"
+  type: "ReLU"
+  bottom: "conv6/dw"
+  top: "conv6/dw"
+}
+layer {
+  name: "conv6"
+  type: "Convolution"
+  bottom: "conv6/dw"
+  top: "conv6"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 512
+    kernel_size: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "conv6/relu"
+  type: "ReLU"
+  bottom: "conv6"
+  top: "conv6"
+}
+layer {
+  name: "conv7/dw"
+  type: "Convolution"
+  bottom: "conv6"
+  top: "conv7/dw"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 512
+    pad: 1
+    kernel_size: 3
+    group: 512
+    engine: CAFFE
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "conv7/dw/relu"
+  type: "ReLU"
+  bottom: "conv7/dw"
+  top: "conv7/dw"
+}
+layer {
+  name: "conv7"
+  type: "Convolution"
+  bottom: "conv7/dw"
+  top: "conv7"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 512
+    kernel_size: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "conv7/relu"
+  type: "ReLU"
+  bottom: "conv7"
+  top: "conv7"
+}
+layer {
+  name: "conv8/dw"
+  type: "Convolution"
+  bottom: "conv7"
+  top: "conv8/dw"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 512
+    pad: 1
+    kernel_size: 3
+    group: 512
+    engine: CAFFE
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "conv8/dw/relu"
+  type: "ReLU"
+  bottom: "conv8/dw"
+  top: "conv8/dw"
+}
+layer {
+  name: "conv8"
+  type: "Convolution"
+  bottom: "conv8/dw"
+  top: "conv8"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 512
+    kernel_size: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "conv8/relu"
+  type: "ReLU"
+  bottom: "conv8"
+  top: "conv8"
+}
+layer {
+  name: "conv9/dw"
+  type: "Convolution"
+  bottom: "conv8"
+  top: "conv9/dw"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 512
+    pad: 1
+    kernel_size: 3
+    group: 512
+    engine: CAFFE
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "conv9/dw/relu"
+  type: "ReLU"
+  bottom: "conv9/dw"
+  top: "conv9/dw"
+}
+layer {
+  name: "conv9"
+  type: "Convolution"
+  bottom: "conv9/dw"
+  top: "conv9"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 512
+    kernel_size: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "conv9/relu"
+  type: "ReLU"
+  bottom: "conv9"
+  top: "conv9"
+}
+layer {
+  name: "conv10/dw"
+  type: "Convolution"
+  bottom: "conv9"
+  top: "conv10/dw"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 512
+    pad: 1
+    kernel_size: 3
+    group: 512
+    engine: CAFFE
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "conv10/dw/relu"
+  type: "ReLU"
+  bottom: "conv10/dw"
+  top: "conv10/dw"
+}
+layer {
+  name: "conv10"
+  type: "Convolution"
+  bottom: "conv10/dw"
+  top: "conv10"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 512
+    kernel_size: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "conv10/relu"
+  type: "ReLU"
+  bottom: "conv10"
+  top: "conv10"
+}
+layer {
+  name: "conv11/dw"
+  type: "Convolution"
+  bottom: "conv10"
+  top: "conv11/dw"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 512
+    pad: 1
+    kernel_size: 3
+    group: 512
+    engine: CAFFE
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "conv11/dw/relu"
+  type: "ReLU"
+  bottom: "conv11/dw"
+  top: "conv11/dw"
+}
+layer {
+  name: "conv11"
+  type: "Convolution"
+  bottom: "conv11/dw"
+  top: "conv11"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 512
+    kernel_size: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "conv11/relu"
+  type: "ReLU"
+  bottom: "conv11"
+  top: "conv11"
+}
+layer {
+  name: "conv12/dw"
+  type: "Convolution"
+  bottom: "conv11"
+  top: "conv12/dw"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 512
+    pad: 1
+    kernel_size: 3
+    stride: 2
+    group: 512
+    engine: CAFFE
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "conv12/dw/relu"
+  type: "ReLU"
+  bottom: "conv12/dw"
+  top: "conv12/dw"
+}
+layer {
+  name: "conv12"
+  type: "Convolution"
+  bottom: "conv12/dw"
+  top: "conv12"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 1024
+    kernel_size: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "conv12/relu"
+  type: "ReLU"
+  bottom: "conv12"
+  top: "conv12"
+}
+layer {
+  name: "conv13/dw"
+  type: "Convolution"
+  bottom: "conv12"
+  top: "conv13/dw"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 1024
+    pad: 1
+    kernel_size: 3
+    group: 1024
+    engine: CAFFE
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "conv13/dw/relu"
+  type: "ReLU"
+  bottom: "conv13/dw"
+  top: "conv13/dw"
+}
+layer {
+  name: "conv13"
+  type: "Convolution"
+  bottom: "conv13/dw"
+  top: "conv13"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 1024
+    kernel_size: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "conv13/relu"
+  type: "ReLU"
+  bottom: "conv13"
+  top: "conv13"
+}
+layer {
+  name: "conv14_1"
+  type: "Convolution"
+  bottom: "conv13"
+  top: "conv14_1"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 256
+    kernel_size: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "conv14_1/relu"
+  type: "ReLU"
+  bottom: "conv14_1"
+  top: "conv14_1"
+}
+layer {
+  name: "conv14_2"
+  type: "Convolution"
+  bottom: "conv14_1"
+  top: "conv14_2"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 512
+    pad: 1
+    kernel_size: 3
+    stride: 2
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "conv14_2/relu"
+  type: "ReLU"
+  bottom: "conv14_2"
+  top: "conv14_2"
+}
+layer {
+  name: "conv15_1"
+  type: "Convolution"
+  bottom: "conv14_2"
+  top: "conv15_1"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 128
+    kernel_size: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "conv15_1/relu"
+  type: "ReLU"
+  bottom: "conv15_1"
+  top: "conv15_1"
+}
+layer {
+  name: "conv15_2"
+  type: "Convolution"
+  bottom: "conv15_1"
+  top: "conv15_2"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 256
+    pad: 1
+    kernel_size: 3
+    stride: 2
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "conv15_2/relu"
+  type: "ReLU"
+  bottom: "conv15_2"
+  top: "conv15_2"
+}
+layer {
+  name: "conv16_1"
+  type: "Convolution"
+  bottom: "conv15_2"
+  top: "conv16_1"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 128
+    kernel_size: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "conv16_1/relu"
+  type: "ReLU"
+  bottom: "conv16_1"
+  top: "conv16_1"
+}
+layer {
+  name: "conv16_2"
+  type: "Convolution"
+  bottom: "conv16_1"
+  top: "conv16_2"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 256
+    pad: 1
+    kernel_size: 3
+    stride: 2
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "conv16_2/relu"
+  type: "ReLU"
+  bottom: "conv16_2"
+  top: "conv16_2"
+}
+layer {
+  name: "conv17_1"
+  type: "Convolution"
+  bottom: "conv16_2"
+  top: "conv17_1"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 64
+    kernel_size: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "conv17_1/relu"
+  type: "ReLU"
+  bottom: "conv17_1"
+  top: "conv17_1"
+}
+layer {
+  name: "conv17_2"
+  type: "Convolution"
+  bottom: "conv17_1"
+  top: "conv17_2"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+    stride: 2
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "conv17_2/relu"
+  type: "ReLU"
+  bottom: "conv17_2"
+  top: "conv17_2"
+}
+layer {
+  name: "conv11_mbox_loc"
+  type: "Convolution"
+  bottom: "conv11"
+  top: "conv11_mbox_loc"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 12
+    kernel_size: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "conv11_mbox_loc_perm"
+  type: "Permute"
+  bottom: "conv11_mbox_loc"
+  top: "conv11_mbox_loc_perm"
+  permute_param {
+    order: 0
+    order: 2
+    order: 3
+    order: 1
+  }
+}
+layer {
+  name: "conv11_mbox_loc_flat"
+  type: "Flatten"
+  bottom: "conv11_mbox_loc_perm"
+  top: "conv11_mbox_loc_flat"
+  flatten_param {
+    axis: 1
+  }
+}
+layer {
+  name: "conv11_mbox_conf"
+  type: "Convolution"
+  bottom: "conv11"
+  top: "conv11_mbox_conf"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 63
+    kernel_size: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "conv11_mbox_conf_perm"
+  type: "Permute"
+  bottom: "conv11_mbox_conf"
+  top: "conv11_mbox_conf_perm"
+  permute_param {
+    order: 0
+    order: 2
+    order: 3
+    order: 1
+  }
+}
+layer {
+  name: "conv11_mbox_conf_flat"
+  type: "Flatten"
+  bottom: "conv11_mbox_conf_perm"
+  top: "conv11_mbox_conf_flat"
+  flatten_param {
+    axis: 1
+  }
+}
+layer {
+  name: "conv11_mbox_priorbox"
+  type: "PriorBox"
+  bottom: "conv11"
+  bottom: "data"
+  top: "conv11_mbox_priorbox"
+  prior_box_param {
+    min_size: 60.0
+    aspect_ratio: 2.0
+    flip: true
+    clip: false
+    variance: 0.1
+    variance: 0.1
+    variance: 0.2
+    variance: 0.2
+    offset: 0.5
+  }
+}
+layer {
+  name: "conv13_mbox_loc"
+  type: "Convolution"
+  bottom: "conv13"
+  top: "conv13_mbox_loc"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 24
+    kernel_size: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "conv13_mbox_loc_perm"
+  type: "Permute"
+  bottom: "conv13_mbox_loc"
+  top: "conv13_mbox_loc_perm"
+  permute_param {
+    order: 0
+    order: 2
+    order: 3
+    order: 1
+  }
+}
+layer {
+  name: "conv13_mbox_loc_flat"
+  type: "Flatten"
+  bottom: "conv13_mbox_loc_perm"
+  top: "conv13_mbox_loc_flat"
+  flatten_param {
+    axis: 1
+  }
+}
+layer {
+  name: "conv13_mbox_conf"
+  type: "Convolution"
+  bottom: "conv13"
+  top: "conv13_mbox_conf"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 126
+    kernel_size: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "conv13_mbox_conf_perm"
+  type: "Permute"
+  bottom: "conv13_mbox_conf"
+  top: "conv13_mbox_conf_perm"
+  permute_param {
+    order: 0
+    order: 2
+    order: 3
+    order: 1
+  }
+}
+layer {
+  name: "conv13_mbox_conf_flat"
+  type: "Flatten"
+  bottom: "conv13_mbox_conf_perm"
+  top: "conv13_mbox_conf_flat"
+  flatten_param {
+    axis: 1
+  }
+}
+layer {
+  name: "conv13_mbox_priorbox"
+  type: "PriorBox"
+  bottom: "conv13"
+  bottom: "data"
+  top: "conv13_mbox_priorbox"
+  prior_box_param {
+    min_size: 105.0
+    max_size: 150.0
+    aspect_ratio: 2.0
+    aspect_ratio: 3.0
+    flip: true
+    clip: false
+    variance: 0.1
+    variance: 0.1
+    variance: 0.2
+    variance: 0.2
+    offset: 0.5
+  }
+}
+layer {
+  name: "conv14_2_mbox_loc"
+  type: "Convolution"
+  bottom: "conv14_2"
+  top: "conv14_2_mbox_loc"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 24
+    kernel_size: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "conv14_2_mbox_loc_perm"
+  type: "Permute"
+  bottom: "conv14_2_mbox_loc"
+  top: "conv14_2_mbox_loc_perm"
+  permute_param {
+    order: 0
+    order: 2
+    order: 3
+    order: 1
+  }
+}
+layer {
+  name: "conv14_2_mbox_loc_flat"
+  type: "Flatten"
+  bottom: "conv14_2_mbox_loc_perm"
+  top: "conv14_2_mbox_loc_flat"
+  flatten_param {
+    axis: 1
+  }
+}
+layer {
+  name: "conv14_2_mbox_conf"
+  type: "Convolution"
+  bottom: "conv14_2"
+  top: "conv14_2_mbox_conf"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 126
+    kernel_size: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "conv14_2_mbox_conf_perm"
+  type: "Permute"
+  bottom: "conv14_2_mbox_conf"
+  top: "conv14_2_mbox_conf_perm"
+  permute_param {
+    order: 0
+    order: 2
+    order: 3
+    order: 1
+  }
+}
+layer {
+  name: "conv14_2_mbox_conf_flat"
+  type: "Flatten"
+  bottom: "conv14_2_mbox_conf_perm"
+  top: "conv14_2_mbox_conf_flat"
+  flatten_param {
+    axis: 1
+  }
+}
+layer {
+  name: "conv14_2_mbox_priorbox"
+  type: "PriorBox"
+  bottom: "conv14_2"
+  bottom: "data"
+  top: "conv14_2_mbox_priorbox"
+  prior_box_param {
+    min_size: 150.0
+    max_size: 195.0
+    aspect_ratio: 2.0
+    aspect_ratio: 3.0
+    flip: true
+    clip: false
+    variance: 0.1
+    variance: 0.1
+    variance: 0.2
+    variance: 0.2
+    offset: 0.5
+  }
+}
+layer {
+  name: "conv15_2_mbox_loc"
+  type: "Convolution"
+  bottom: "conv15_2"
+  top: "conv15_2_mbox_loc"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 24
+    kernel_size: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "conv15_2_mbox_loc_perm"
+  type: "Permute"
+  bottom: "conv15_2_mbox_loc"
+  top: "conv15_2_mbox_loc_perm"
+  permute_param {
+    order: 0
+    order: 2
+    order: 3
+    order: 1
+  }
+}
+layer {
+  name: "conv15_2_mbox_loc_flat"
+  type: "Flatten"
+  bottom: "conv15_2_mbox_loc_perm"
+  top: "conv15_2_mbox_loc_flat"
+  flatten_param {
+    axis: 1
+  }
+}
+layer {
+  name: "conv15_2_mbox_conf"
+  type: "Convolution"
+  bottom: "conv15_2"
+  top: "conv15_2_mbox_conf"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 126
+    kernel_size: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "conv15_2_mbox_conf_perm"
+  type: "Permute"
+  bottom: "conv15_2_mbox_conf"
+  top: "conv15_2_mbox_conf_perm"
+  permute_param {
+    order: 0
+    order: 2
+    order: 3
+    order: 1
+  }
+}
+layer {
+  name: "conv15_2_mbox_conf_flat"
+  type: "Flatten"
+  bottom: "conv15_2_mbox_conf_perm"
+  top: "conv15_2_mbox_conf_flat"
+  flatten_param {
+    axis: 1
+  }
+}
+layer {
+  name: "conv15_2_mbox_priorbox"
+  type: "PriorBox"
+  bottom: "conv15_2"
+  bottom: "data"
+  top: "conv15_2_mbox_priorbox"
+  prior_box_param {
+    min_size: 195.0
+    max_size: 240.0
+    aspect_ratio: 2.0
+    aspect_ratio: 3.0
+    flip: true
+    clip: false
+    variance: 0.1
+    variance: 0.1
+    variance: 0.2
+    variance: 0.2
+    offset: 0.5
+  }
+}
+layer {
+  name: "conv16_2_mbox_loc"
+  type: "Convolution"
+  bottom: "conv16_2"
+  top: "conv16_2_mbox_loc"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 24
+    kernel_size: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "conv16_2_mbox_loc_perm"
+  type: "Permute"
+  bottom: "conv16_2_mbox_loc"
+  top: "conv16_2_mbox_loc_perm"
+  permute_param {
+    order: 0
+    order: 2
+    order: 3
+    order: 1
+  }
+}
+layer {
+  name: "conv16_2_mbox_loc_flat"
+  type: "Flatten"
+  bottom: "conv16_2_mbox_loc_perm"
+  top: "conv16_2_mbox_loc_flat"
+  flatten_param {
+    axis: 1
+  }
+}
+layer {
+  name: "conv16_2_mbox_conf"
+  type: "Convolution"
+  bottom: "conv16_2"
+  top: "conv16_2_mbox_conf"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 126
+    kernel_size: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "conv16_2_mbox_conf_perm"
+  type: "Permute"
+  bottom: "conv16_2_mbox_conf"
+  top: "conv16_2_mbox_conf_perm"
+  permute_param {
+    order: 0
+    order: 2
+    order: 3
+    order: 1
+  }
+}
+layer {
+  name: "conv16_2_mbox_conf_flat"
+  type: "Flatten"
+  bottom: "conv16_2_mbox_conf_perm"
+  top: "conv16_2_mbox_conf_flat"
+  flatten_param {
+    axis: 1
+  }
+}
+layer {
+  name: "conv16_2_mbox_priorbox"
+  type: "PriorBox"
+  bottom: "conv16_2"
+  bottom: "data"
+  top: "conv16_2_mbox_priorbox"
+  prior_box_param {
+    min_size: 240.0
+    max_size: 285.0
+    aspect_ratio: 2.0
+    aspect_ratio: 3.0
+    flip: true
+    clip: false
+    variance: 0.1
+    variance: 0.1
+    variance: 0.2
+    variance: 0.2
+    offset: 0.5
+  }
+}
+layer {
+  name: "conv17_2_mbox_loc"
+  type: "Convolution"
+  bottom: "conv17_2"
+  top: "conv17_2_mbox_loc"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 24
+    kernel_size: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "conv17_2_mbox_loc_perm"
+  type: "Permute"
+  bottom: "conv17_2_mbox_loc"
+  top: "conv17_2_mbox_loc_perm"
+  permute_param {
+    order: 0
+    order: 2
+    order: 3
+    order: 1
+  }
+}
+layer {
+  name: "conv17_2_mbox_loc_flat"
+  type: "Flatten"
+  bottom: "conv17_2_mbox_loc_perm"
+  top: "conv17_2_mbox_loc_flat"
+  flatten_param {
+    axis: 1
+  }
+}
+layer {
+  name: "conv17_2_mbox_conf"
+  type: "Convolution"
+  bottom: "conv17_2"
+  top: "conv17_2_mbox_conf"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 2.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 126
+    kernel_size: 1
+    weight_filler {
+      type: "msra"
+    }
+    bias_filler {
+      type: "constant"
+      value: 0.0
+    }
+  }
+}
+layer {
+  name: "conv17_2_mbox_conf_perm"
+  type: "Permute"
+  bottom: "conv17_2_mbox_conf"
+  top: "conv17_2_mbox_conf_perm"
+  permute_param {
+    order: 0
+    order: 2
+    order: 3
+    order: 1
+  }
+}
+layer {
+  name: "conv17_2_mbox_conf_flat"
+  type: "Flatten"
+  bottom: "conv17_2_mbox_conf_perm"
+  top: "conv17_2_mbox_conf_flat"
+  flatten_param {
+    axis: 1
+  }
+}
+layer {
+  name: "conv17_2_mbox_priorbox"
+  type: "PriorBox"
+  bottom: "conv17_2"
+  bottom: "data"
+  top: "conv17_2_mbox_priorbox"
+  prior_box_param {
+    min_size: 285.0
+    max_size: 300.0
+    aspect_ratio: 2.0
+    aspect_ratio: 3.0
+    flip: true
+    clip: false
+    variance: 0.1
+    variance: 0.1
+    variance: 0.2
+    variance: 0.2
+    offset: 0.5
+  }
+}
+layer {
+  name: "mbox_loc"
+  type: "Concat"
+  bottom: "conv11_mbox_loc_flat"
+  bottom: "conv13_mbox_loc_flat"
+  bottom: "conv14_2_mbox_loc_flat"
+  bottom: "conv15_2_mbox_loc_flat"
+  bottom: "conv16_2_mbox_loc_flat"
+  bottom: "conv17_2_mbox_loc_flat"
+  top: "mbox_loc"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "mbox_conf"
+  type: "Concat"
+  bottom: "conv11_mbox_conf_flat"
+  bottom: "conv13_mbox_conf_flat"
+  bottom: "conv14_2_mbox_conf_flat"
+  bottom: "conv15_2_mbox_conf_flat"
+  bottom: "conv16_2_mbox_conf_flat"
+  bottom: "conv17_2_mbox_conf_flat"
+  top: "mbox_conf"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "mbox_priorbox"
+  type: "Concat"
+  bottom: "conv11_mbox_priorbox"
+  bottom: "conv13_mbox_priorbox"
+  bottom: "conv14_2_mbox_priorbox"
+  bottom: "conv15_2_mbox_priorbox"
+  bottom: "conv16_2_mbox_priorbox"
+  bottom: "conv17_2_mbox_priorbox"
+  top: "mbox_priorbox"
+  concat_param {
+    axis: 2
+  }
+}
+layer {
+  name: "mbox_conf_reshape"
+  type: "Reshape"
+  bottom: "mbox_conf"
+  top: "mbox_conf_reshape"
+  reshape_param {
+    shape {
+      dim: 0
+      dim: -1
+      dim: 21
+    }
+  }
+}
+layer {
+  name: "mbox_conf_softmax"
+  type: "Softmax"
+  bottom: "mbox_conf_reshape"
+  top: "mbox_conf_softmax"
+  softmax_param {
+    axis: 2
+  }
+}
+layer {
+  name: "mbox_conf_flatten"
+  type: "Flatten"
+  bottom: "mbox_conf_softmax"
+  top: "mbox_conf_flatten"
+  flatten_param {
+    axis: 1
+  }
+}
+layer {
+  name: "detection_out"
+  type: "DetectionOutput"
+  bottom: "mbox_loc"
+  bottom: "mbox_conf_flatten"
+  bottom: "mbox_priorbox"
+  top: "detection_out"
+  include {
+    phase: TEST
+  }
+  detection_output_param {
+    num_classes: 21
+    share_location: true
+    background_label_id: 0
+    nms_param {
+      nms_threshold: 0.45
+      top_k: 100
+    }
+    code_type: CENTER_SIZE
+    keep_top_k: 100
+    confidence_threshold: 0.25
+  }
+}

diff --git a/example-apps/ROBO/aPaaS/Obj_Detection_service/detection/obj_detection_service.py b/example-apps/ROBO/aPaaS/Obj_Detection_service/detection/obj_detection_service.py
index 055f864..52a6bab 100644 (file)
--- a/example-apps/ROBO/aPaaS/Obj_Detection_service/detection/obj_detection_service.py
+++ b/example-apps/ROBO/aPaaS/Obj_Detection_service/detection/obj_detection_service.py
@@ -203,7 +203,8 @@ def Detection(img):
     cv2.destroyAllWindows()
     # Detect_result = {'ImposedImage': 'frame', 'ObjCount': count,
     # 'ObjType': type, 'Time': time}
-    Detect_result = {'ImposedImage': "frame", 'ObjCount': count}
+    Detect_result = {'ImposedImage': "frame", 'ObjCount': count,
+                     'labels': label}
     return Detect_result
 
 
@@ -264,7 +265,6 @@ def Obj_Detection():
     else:
         app.logger.info('Allowed file types are txt, pdf, png, jpg, jpeg, gif')
         return Response("failure")
-    # return jsonify({'Face number': num, 'Result': 'upload success'})
     return jsonify(Detect_result)
 
 

diff --git a/example-apps/ROBO/aPaaS/Obj_Detection_service/images/img.jpeg b/example-apps/ROBO/aPaaS/Obj_Detection_service/images/img.jpeg
index 483e586..df1ebc1 100644 (file)
Binary files a/example-apps/ROBO/aPaaS/Obj_Detection_service/images/img.jpeg and b/example-apps/ROBO/aPaaS/Obj_Detection_service/images/img.jpeg differ