diff --git a/hyperlpr_pip_pkg/hyperlpr/models/dnn/.DS_Store b/hyperlpr_pip_pkg/hyperlpr/models/dnn/.DS_Store
new file mode 100644
index 0000000..7e1cf91
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diff --git a/hyperlpr_pip_pkg/hyperlpr/models/dnn/HorizonalFinemapping.caffemodel b/hyperlpr_pip_pkg/hyperlpr/models/dnn/HorizonalFinemapping.caffemodel
new file mode 100644
index 0000000..94866be
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diff --git a/hyperlpr_pip_pkg/hyperlpr/models/dnn/HorizonalFinemapping.prototxt b/hyperlpr_pip_pkg/hyperlpr/models/dnn/HorizonalFinemapping.prototxt
new file mode 100644
index 0000000..21726dd
--- /dev/null
+++ b/hyperlpr_pip_pkg/hyperlpr/models/dnn/HorizonalFinemapping.prototxt
@@ -0,0 +1,95 @@
+input: "data"
+input_dim: 1
+input_dim: 3
+input_dim: 16
+input_dim: 66
+layer {
+  name: "conv1"
+  type: "Convolution"
+  bottom: "data"
+  top: "conv1"
+  convolution_param {
+    num_output: 10
+    bias_term: true
+    pad: 0
+    kernel_size: 3
+    stride: 1
+  }
+}
+layer {
+  name: "relu1"
+  type: "ReLU"
+  bottom: "conv1"
+  top: "conv1"
+}
+layer {
+  name: "max_pooling2d_3"
+  type: "Pooling"
+  bottom: "conv1"
+  top: "max_pooling2d_3"
+  pooling_param {
+    pool: MAX
+    kernel_size: 2
+    stride: 2
+    pad: 0
+  }
+}
+layer {
+  name: "conv2"
+  type: "Convolution"
+  bottom: "max_pooling2d_3"
+  top: "conv2"
+  convolution_param {
+    num_output: 16
+    bias_term: true
+    pad: 0
+    kernel_size: 3
+    stride: 1
+  }
+}
+layer {
+  name: "relu2"
+  type: "ReLU"
+  bottom: "conv2"
+  top: "conv2"
+}
+layer {
+  name: "conv3"
+  type: "Convolution"
+  bottom: "conv2"
+  top: "conv3"
+  convolution_param {
+    num_output: 32
+    bias_term: true
+    pad: 0
+    kernel_size: 3
+    stride: 1
+  }
+}
+layer {
+  name: "relu3"
+  type: "ReLU"
+  bottom: "conv3"
+  top: "conv3"
+}
+layer {
+  name: "flatten_2"
+  type: "Flatten"
+  bottom: "conv3"
+  top: "flatten_2"
+}
+layer {
+  name: "dense"
+  type: "InnerProduct"
+  bottom: "flatten_2"
+  top: "dense"
+  inner_product_param {
+    num_output: 2
+  }
+}
+layer {
+  name: "relu4"
+  type: "ReLU"
+  bottom: "dense"
+  top: "dense"
+}
diff --git a/hyperlpr_pip_pkg/hyperlpr/models/dnn/SegmenationFree-Inception.caffemodel b/hyperlpr_pip_pkg/hyperlpr/models/dnn/SegmenationFree-Inception.caffemodel
new file mode 100644
index 0000000..65a9954
Binary files /dev/null and b/hyperlpr_pip_pkg/hyperlpr/models/dnn/SegmenationFree-Inception.caffemodel differ
diff --git a/hyperlpr_pip_pkg/hyperlpr/models/dnn/SegmenationFree-Inception.prototxt b/hyperlpr_pip_pkg/hyperlpr/models/dnn/SegmenationFree-Inception.prototxt
new file mode 100644
index 0000000..8419763
--- /dev/null
+++ b/hyperlpr_pip_pkg/hyperlpr/models/dnn/SegmenationFree-Inception.prototxt
@@ -0,0 +1,454 @@
+input: "data"
+input_dim: 1
+input_dim: 3
+input_dim: 160
+input_dim: 40
+layer {
+  name: "conv0"
+  type: "Convolution"
+  bottom: "data"
+  top: "conv0"
+  convolution_param {
+    num_output: 32
+    bias_term: true
+    pad_h: 1
+    pad_w: 1
+    kernel_h: 3
+    kernel_w: 3
+    stride_h: 1
+    stride_w: 1
+  }
+}
+layer {
+  name: "bn0"
+  type: "BatchNorm"
+  bottom: "conv0"
+  top: "bn0"
+  batch_norm_param {
+    moving_average_fraction: 0.99
+    eps: 0.001
+  }
+}
+layer {
+  name: "bn0_scale"
+  type: "Scale"
+  bottom: "bn0"
+  top: "bn0"
+  scale_param {
+    bias_term: true
+  }
+}
+layer {
+  name: "relu0"
+  type: "ReLU"
+  bottom: "bn0"
+  top: "bn0"
+}
+layer {
+  name: "pool0"
+  type: "Pooling"
+  bottom: "bn0"
+  top: "pool0"
+  pooling_param {
+    pool: MAX
+    kernel_h: 2
+    kernel_w: 2
+    stride_h: 2
+    stride_w: 2
+    pad_h: 0
+    pad_w: 0
+  }
+}
+layer {
+  name: "conv1"
+  type: "Convolution"
+  bottom: "pool0"
+  top: "conv1"
+  convolution_param {
+    num_output: 64
+    bias_term: true
+    pad_h: 1
+    pad_w: 1
+    kernel_h: 3
+    kernel_w: 3
+    stride_h: 1
+    stride_w: 1
+  }
+}
+layer {
+  name: "bn1"
+  type: "BatchNorm"
+  bottom: "conv1"
+  top: "bn1"
+  batch_norm_param {
+    moving_average_fraction: 0.99
+    eps: 0.001
+  }
+}
+layer {
+  name: "bn1_scale"
+  type: "Scale"
+  bottom: "bn1"
+  top: "bn1"
+  scale_param {
+    bias_term: true
+  }
+}
+layer {
+  name: "relu1"
+  type: "ReLU"
+  bottom: "bn1"
+  top: "bn1"
+}
+layer {
+  name: "pool1"
+  type: "Pooling"
+  bottom: "bn1"
+  top: "pool1"
+  pooling_param {
+    pool: MAX
+    kernel_h: 2
+    kernel_w: 2
+    stride_h: 2
+    stride_w: 2
+    pad_h: 0
+    pad_w: 0
+  }
+}
+layer {
+  name: "conv2"
+  type: "Convolution"
+  bottom: "pool1"
+  top: "conv2"
+  convolution_param {
+    num_output: 128
+    bias_term: true
+    pad_h: 1
+    pad_w: 1
+    kernel_h: 3
+    kernel_w: 3
+    stride_h: 1
+    stride_w: 1
+  }
+}
+layer {
+  name: "bn2"
+  type: "BatchNorm"
+  bottom: "conv2"
+  top: "bn2"
+  batch_norm_param {
+    moving_average_fraction: 0.99
+    eps: 0.001
+  }
+}
+layer {
+  name: "bn2_scale"
+  type: "Scale"
+  bottom: "bn2"
+  top: "bn2"
+  scale_param {
+    bias_term: true
+  }
+}
+layer {
+  name: "relu2"
+  type: "ReLU"
+  bottom: "bn2"
+  top: "bn2"
+}
+layer {
+  name: "pool2"
+  type: "Pooling"
+  bottom: "bn2"
+  top: "pool2"
+  pooling_param {
+    pool: MAX
+    kernel_h: 2
+    kernel_w: 2
+    stride_h: 2
+    stride_w: 2
+    pad_h: 0
+    pad_w: 0
+  }
+}
+layer {
+  name: "conv2d_1"
+  type: "Convolution"
+  bottom: "pool2"
+  top: "conv2d_1"
+  convolution_param {
+    num_output: 256
+    bias_term: true
+    pad_h: 0
+    pad_w: 0
+    kernel_h: 1
+    kernel_w: 5
+    stride_h: 1
+    stride_w: 1
+  }
+}
+layer {
+  name: "batch_normalization_1"
+  type: "BatchNorm"
+  bottom: "conv2d_1"
+  top: "batch_normalization_1"
+  batch_norm_param {
+    moving_average_fraction: 0.99
+    eps: 0.001
+  }
+}
+layer {
+  name: "batch_normalization_1_scale"
+  type: "Scale"
+  bottom: "batch_normalization_1"
+  top: "batch_normalization_1"
+  scale_param {
+    bias_term: true
+  }
+}
+layer {
+  name: "activation_1"
+  type: "ReLU"
+  bottom: "batch_normalization_1"
+  top: "batch_normalization_1"
+}
+layer {
+  name: "conv2d_2"
+  type: "Convolution"
+  bottom: "batch_normalization_1"
+  top: "conv2d_2"
+  convolution_param {
+    num_output: 256
+    bias_term: true
+    pad_h: 3
+    pad_w: 0
+    kernel_h: 7
+    kernel_w: 1
+    stride_h: 1
+    stride_w: 1
+  }
+}
+layer {
+  name: "conv2d_3"
+  type: "Convolution"
+  bottom: "batch_normalization_1"
+  top: "conv2d_3"
+  convolution_param {
+    num_output: 256
+    bias_term: true
+    pad_h: 2
+    pad_w: 0
+    kernel_h: 5
+    kernel_w: 1
+    stride_h: 1
+    stride_w: 1
+  }
+}
+layer {
+  name: "conv2d_4"
+  type: "Convolution"
+  bottom: "batch_normalization_1"
+  top: "conv2d_4"
+  convolution_param {
+    num_output: 256
+    bias_term: true
+    pad_h: 1
+    pad_w: 0
+    kernel_h: 3
+    kernel_w: 1
+    stride_h: 1
+    stride_w: 1
+  }
+}
+layer {
+  name: "conv2d_5"
+  type: "Convolution"
+  bottom: "batch_normalization_1"
+  top: "conv2d_5"
+  convolution_param {
+    num_output: 256
+    bias_term: true
+    pad_h: 0
+    pad_w: 0
+    kernel_h: 1
+    kernel_w: 1
+    stride_h: 1
+    stride_w: 1
+  }
+}
+layer {
+  name: "batch_normalization_2"
+  type: "BatchNorm"
+  bottom: "conv2d_2"
+  top: "batch_normalization_2"
+  batch_norm_param {
+    moving_average_fraction: 0.99
+    eps: 0.001
+  }
+}
+layer {
+  name: "batch_normalization_2_scale"
+  type: "Scale"
+  bottom: "batch_normalization_2"
+  top: "batch_normalization_2"
+  scale_param {
+    bias_term: true
+  }
+}
+layer {
+  name: "batch_normalization_3"
+  type: "BatchNorm"
+  bottom: "conv2d_3"
+  top: "batch_normalization_3"
+  batch_norm_param {
+    moving_average_fraction: 0.99
+    eps: 0.001
+  }
+}
+layer {
+  name: "batch_normalization_3_scale"
+  type: "Scale"
+  bottom: "batch_normalization_3"
+  top: "batch_normalization_3"
+  scale_param {
+    bias_term: true
+  }
+}
+layer {
+  name: "batch_normalization_4"
+  type: "BatchNorm"
+  bottom: "conv2d_4"
+  top: "batch_normalization_4"
+  batch_norm_param {
+    moving_average_fraction: 0.99
+    eps: 0.001
+  }
+}
+layer {
+  name: "batch_normalization_4_scale"
+  type: "Scale"
+  bottom: "batch_normalization_4"
+  top: "batch_normalization_4"
+  scale_param {
+    bias_term: true
+  }
+}
+layer {
+  name: "batch_normalization_5"
+  type: "BatchNorm"
+  bottom: "conv2d_5"
+  top: "batch_normalization_5"
+  batch_norm_param {
+    moving_average_fraction: 0.99
+    eps: 0.001
+  }
+}
+layer {
+  name: "batch_normalization_5_scale"
+  type: "Scale"
+  bottom: "batch_normalization_5"
+  top: "batch_normalization_5"
+  scale_param {
+    bias_term: true
+  }
+}
+layer {
+  name: "activation_2"
+  type: "ReLU"
+  bottom: "batch_normalization_2"
+  top: "batch_normalization_2"
+}
+layer {
+  name: "activation_3"
+  type: "ReLU"
+  bottom: "batch_normalization_3"
+  top: "batch_normalization_3"
+}
+layer {
+  name: "activation_4"
+  type: "ReLU"
+  bottom: "batch_normalization_4"
+  top: "batch_normalization_4"
+}
+layer {
+  name: "activation_5"
+  type: "ReLU"
+  bottom: "batch_normalization_5"
+  top: "batch_normalization_5"
+}
+layer {
+  name: "concatenate_1"
+  type: "Concat"
+  bottom: "batch_normalization_2"
+  bottom: "batch_normalization_3"
+  bottom: "batch_normalization_4"
+  bottom: "batch_normalization_5"
+  top: "concatenate_1"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "conv_1024_11"
+  type: "Convolution"
+  bottom: "concatenate_1"
+  top: "conv_1024_11"
+  convolution_param {
+    num_output: 1024
+    bias_term: true
+    pad_h: 0
+    pad_w: 0
+    kernel_h: 1
+    kernel_w: 1
+    stride_h: 1
+    stride_w: 1
+  }
+}
+layer {
+  name: "batch_normalization_6"
+  type: "BatchNorm"
+  bottom: "conv_1024_11"
+  top: "batch_normalization_6"
+  batch_norm_param {
+    moving_average_fraction: 0.99
+    eps: 0.001
+  }
+}
+layer {
+  name: "batch_normalization_6_scale"
+  type: "Scale"
+  bottom: "batch_normalization_6"
+  top: "batch_normalization_6"
+  scale_param {
+    bias_term: true
+  }
+}
+layer {
+  name: "activation_6"
+  type: "ReLU"
+  bottom: "batch_normalization_6"
+  top: "batch_normalization_6"
+}
+layer {
+  name: "conv_class_11"
+  type: "Convolution"
+  bottom: "batch_normalization_6"
+  top: "conv_class_11"
+  convolution_param {
+    num_output: 84
+    bias_term: true
+    pad_h: 0
+    pad_w: 0
+    kernel_h: 1
+    kernel_w: 1
+    stride_h: 1
+    stride_w: 1
+  }
+}
+layer {
+  name: "prob"
+  type: "Softmax"
+  bottom: "conv_class_11"
+  top: "prob"
+}
+
diff --git a/hyperlpr_pip_pkg/hyperlpr/models/dnn/mininet_ssd_v1.caffemodel b/hyperlpr_pip_pkg/hyperlpr/models/dnn/mininet_ssd_v1.caffemodel
new file mode 100644
index 0000000..6bbc358
Binary files /dev/null and b/hyperlpr_pip_pkg/hyperlpr/models/dnn/mininet_ssd_v1.caffemodel differ
diff --git a/hyperlpr_pip_pkg/hyperlpr/models/dnn/mininet_ssd_v1.prototxt b/hyperlpr_pip_pkg/hyperlpr/models/dnn/mininet_ssd_v1.prototxt
new file mode 100644
index 0000000..3e5c355
--- /dev/null
+++ b/hyperlpr_pip_pkg/hyperlpr/models/dnn/mininet_ssd_v1.prototxt
@@ -0,0 +1,1462 @@
+layer {
+  name: "data"
+  type: "Input"
+  top: "data"
+  input_param {
+    shape {
+      dim: 1
+      dim: 3
+      dim: 512
+      dim: 512
+    }
+  }
+}
+layer {
+  name: "ssd0_mobilenet0_conv0"
+  type: "Convolution"
+  bottom: "data"
+  top: "ssd0_mobilenet0_conv0"
+  convolution_param {
+    num_output: 8
+    bias_term: true
+    pad: 1
+    kernel_size: 3
+    group: 1
+    stride: 2
+    dilation: 1
+  }
+}
+layer {
+  name: "ssd0_mobilenet0_batchnorm0/relu"
+  type: "ReLU"
+  bottom: "ssd0_mobilenet0_conv0"
+  top: "ssd0_mobilenet0_conv0"
+  relu_param {
+    negative_slope: 0.0
+  }
+}
+layer {
+  name: "ssd0_mobilenet0_conv1"
+  type: "Convolution"
+  bottom: "ssd0_mobilenet0_conv0"
+  top: "ssd0_mobilenet0_conv1"
+  convolution_param {
+    num_output: 8
+    bias_term: true
+    pad: 1
+    kernel_size: 3
+    group: 8
+    stride: 1
+    dilation: 1
+  }
+}
+layer {
+  name: "ssd0_mobilenet0_batchnorm1/relu"
+  type: "ReLU"
+  bottom: "ssd0_mobilenet0_conv1"
+  top: "ssd0_mobilenet0_conv1"
+  relu_param {
+    negative_slope: 0.0
+  }
+}
+layer {
+  name: "ssd0_mobilenet0_conv2"
+  type: "Convolution"
+  bottom: "ssd0_mobilenet0_conv1"
+  top: "ssd0_mobilenet0_conv2"
+  convolution_param {
+    num_output: 16
+    bias_term: true
+    pad: 0
+    kernel_size: 1
+    group: 1
+    stride: 1
+    dilation: 1
+  }
+}
+layer {
+  name: "ssd0_mobilenet0_batchnorm2/relu"
+  type: "ReLU"
+  bottom: "ssd0_mobilenet0_conv2"
+  top: "ssd0_mobilenet0_conv2"
+  relu_param {
+    negative_slope: 0.0
+  }
+}
+layer {
+  name: "ssd0_mobilenet0_conv3"
+  type: "Convolution"
+  bottom: "ssd0_mobilenet0_conv2"
+  top: "ssd0_mobilenet0_conv3"
+  convolution_param {
+    num_output: 16
+    bias_term: true
+    pad: 1
+    kernel_size: 3
+    group: 16
+    stride: 2
+    dilation: 1
+  }
+}
+layer {
+  name: "ssd0_mobilenet0_batchnorm3/relu"
+  type: "ReLU"
+  bottom: "ssd0_mobilenet0_conv3"
+  top: "ssd0_mobilenet0_conv3"
+  relu_param {
+    negative_slope: 0.0
+  }
+}
+layer {
+  name: "ssd0_mobilenet0_conv4"
+  type: "Convolution"
+  bottom: "ssd0_mobilenet0_conv3"
+  top: "ssd0_mobilenet0_conv4"
+  convolution_param {
+    num_output: 32
+    bias_term: true
+    pad: 0
+    kernel_size: 1
+    group: 1
+    stride: 1
+    dilation: 1
+  }
+}
+layer {
+  name: "ssd0_mobilenet0_batchnorm4/relu"
+  type: "ReLU"
+  bottom: "ssd0_mobilenet0_conv4"
+  top: "ssd0_mobilenet0_conv4"
+  relu_param {
+    negative_slope: 0.0
+  }
+}
+layer {
+  name: "ssd0_mobilenet0_conv5"
+  type: "Convolution"
+  bottom: "ssd0_mobilenet0_conv4"
+  top: "ssd0_mobilenet0_conv5"
+  convolution_param {
+    num_output: 32
+    bias_term: true
+    pad: 1
+    kernel_size: 3
+    group: 32
+    stride: 1
+    dilation: 1
+  }
+}
+layer {
+  name: "ssd0_mobilenet0_batchnorm5/relu"
+  type: "ReLU"
+  bottom: "ssd0_mobilenet0_conv5"
+  top: "ssd0_mobilenet0_conv5"
+  relu_param {
+    negative_slope: 0.0
+  }
+}
+layer {
+  name: "ssd0_mobilenet0_conv6"
+  type: "Convolution"
+  bottom: "ssd0_mobilenet0_conv5"
+  top: "ssd0_mobilenet0_conv6"
+  convolution_param {
+    num_output: 32
+    bias_term: true
+    pad: 0
+    kernel_size: 1
+    group: 1
+    stride: 1
+    dilation: 1
+  }
+}
+layer {
+  name: "ssd0_mobilenet0_batchnorm6/relu"
+  type: "ReLU"
+  bottom: "ssd0_mobilenet0_conv6"
+  top: "ssd0_mobilenet0_conv6"
+  relu_param {
+    negative_slope: 0.0
+  }
+}
+layer {
+  name: "ssd0_mobilenet0_conv7"
+  type: "Convolution"
+  bottom: "ssd0_mobilenet0_conv6"
+  top: "ssd0_mobilenet0_conv7"
+  convolution_param {
+    num_output: 32
+    bias_term: true
+    pad: 1
+    kernel_size: 3
+    group: 32
+    stride: 2
+    dilation: 1
+  }
+}
+layer {
+  name: "ssd0_mobilenet0_batchnorm7/relu"
+  type: "ReLU"
+  bottom: "ssd0_mobilenet0_conv7"
+  top: "ssd0_mobilenet0_conv7"
+  relu_param {
+    negative_slope: 0.0
+  }
+}
+layer {
+  name: "ssd0_mobilenet0_conv8"
+  type: "Convolution"
+  bottom: "ssd0_mobilenet0_conv7"
+  top: "ssd0_mobilenet0_conv8"
+  convolution_param {
+    num_output: 64
+    bias_term: true
+    pad: 0
+    kernel_size: 1
+    group: 1
+    stride: 1
+    dilation: 1
+  }
+}
+layer {
+  name: "ssd0_mobilenet0_batchnorm8/relu"
+  type: "ReLU"
+  bottom: "ssd0_mobilenet0_conv8"
+  top: "ssd0_mobilenet0_conv8"
+  relu_param {
+    negative_slope: 0.0
+  }
+}
+layer {
+  name: "ssd0_mobilenet0_conv9"
+  type: "Convolution"
+  bottom: "ssd0_mobilenet0_conv8"
+  top: "ssd0_mobilenet0_conv9"
+  convolution_param {
+    num_output: 64
+    bias_term: true
+    pad: 1
+    kernel_size: 3
+    group: 64
+    stride: 1
+    dilation: 1
+  }
+}
+layer {
+  name: "ssd0_mobilenet0_batchnorm9/relu"
+  type: "ReLU"
+  bottom: "ssd0_mobilenet0_conv9"
+  top: "ssd0_mobilenet0_conv9"
+  relu_param {
+    negative_slope: 0.0
+  }
+}
+layer {
+  name: "ssd0_mobilenet0_conv10"
+  type: "Convolution"
+  bottom: "ssd0_mobilenet0_conv9"
+  top: "ssd0_mobilenet0_conv10"
+  convolution_param {
+    num_output: 64
+    bias_term: true
+    pad: 0
+    kernel_size: 1
+    group: 1
+    stride: 1
+    dilation: 1
+  }
+}
+layer {
+  name: "ssd0_mobilenet0_batchnorm10/relu"
+  type: "ReLU"
+  bottom: "ssd0_mobilenet0_conv10"
+  top: "ssd0_mobilenet0_conv10"
+  relu_param {
+    negative_slope: 0.0
+  }
+}
+layer {
+  name: "ssd0_mobilenet0_conv11"
+  type: "Convolution"
+  bottom: "ssd0_mobilenet0_conv10"
+  top: "ssd0_mobilenet0_conv11"
+  convolution_param {
+    num_output: 64
+    bias_term: true
+    pad: 1
+    kernel_size: 3
+    group: 64
+    stride: 2
+    dilation: 1
+  }
+}
+layer {
+  name: "ssd0_mobilenet0_batchnorm11/relu"
+  type: "ReLU"
+  bottom: "ssd0_mobilenet0_conv11"
+  top: "ssd0_mobilenet0_conv11"
+  relu_param {
+    negative_slope: 0.0
+  }
+}
+layer {
+  name: "ssd0_mobilenet0_conv12"
+  type: "Convolution"
+  bottom: "ssd0_mobilenet0_conv11"
+  top: "ssd0_mobilenet0_conv12"
+  convolution_param {
+    num_output: 128
+    bias_term: true
+    pad: 0
+    kernel_size: 1
+    group: 1
+    stride: 1
+    dilation: 1
+  }
+}
+layer {
+  name: "ssd0_mobilenet0_batchnorm12/relu"
+  type: "ReLU"
+  bottom: "ssd0_mobilenet0_conv12"
+  top: "ssd0_mobilenet0_conv12"
+  relu_param {
+    negative_slope: 0.0
+  }
+}
+layer {
+  name: "ssd0_mobilenet0_conv13"
+  type: "Convolution"
+  bottom: "ssd0_mobilenet0_conv12"
+  top: "ssd0_mobilenet0_conv13"
+  convolution_param {
+    num_output: 128
+    bias_term: true
+    pad: 1
+    kernel_size: 3
+    group: 128
+    stride: 1
+    dilation: 1
+  }
+}
+layer {
+  name: "ssd0_mobilenet0_batchnorm13/relu"
+  type: "ReLU"
+  bottom: "ssd0_mobilenet0_conv13"
+  top: "ssd0_mobilenet0_conv13"
+  relu_param {
+    negative_slope: 0.0
+  }
+}
+layer {
+  name: "ssd0_mobilenet0_conv14"
+  type: "Convolution"
+  bottom: "ssd0_mobilenet0_conv13"
+  top: "ssd0_mobilenet0_conv14"
+  convolution_param {
+    num_output: 128
+    bias_term: true
+    pad: 0
+    kernel_size: 1
+    group: 1
+    stride: 1
+    dilation: 1
+  }
+}
+layer {
+  name: "ssd0_mobilenet0_batchnorm14/relu"
+  type: "ReLU"
+  bottom: "ssd0_mobilenet0_conv14"
+  top: "ssd0_mobilenet0_conv14"
+  relu_param {
+    negative_slope: 0.0
+  }
+}
+layer {
+  name: "ssd0_mobilenet0_conv15"
+  type: "Convolution"
+  bottom: "ssd0_mobilenet0_conv14"
+  top: "ssd0_mobilenet0_conv15"
+  convolution_param {
+    num_output: 128
+    bias_term: true
+    pad: 1
+    kernel_size: 3
+    group: 128
+    stride: 1
+    dilation: 1
+  }
+}
+layer {
+  name: "ssd0_mobilenet0_batchnorm15/relu"
+  type: "ReLU"
+  bottom: "ssd0_mobilenet0_conv15"
+  top: "ssd0_mobilenet0_conv15"
+  relu_param {
+    negative_slope: 0.0
+  }
+}
+layer {
+  name: "ssd0_mobilenet0_conv16"
+  type: "Convolution"
+  bottom: "ssd0_mobilenet0_conv15"
+  top: "ssd0_mobilenet0_conv16"
+  convolution_param {
+    num_output: 128
+    bias_term: true
+    pad: 0
+    kernel_size: 1
+    group: 1
+    stride: 1
+    dilation: 1
+  }
+}
+layer {
+  name: "ssd0_mobilenet0_batchnorm16/relu"
+  type: "ReLU"
+  bottom: "ssd0_mobilenet0_conv16"
+  top: "ssd0_mobilenet0_conv16"
+  relu_param {
+    negative_slope: 0.0
+  }
+}
+layer {
+  name: "ssd0_mobilenet0_conv17"
+  type: "Convolution"
+  bottom: "ssd0_mobilenet0_conv16"
+  top: "ssd0_mobilenet0_conv17"
+  convolution_param {
+    num_output: 128
+    bias_term: true
+    pad: 1
+    kernel_size: 3
+    group: 128
+    stride: 1
+    dilation: 1
+  }
+}
+layer {
+  name: "ssd0_mobilenet0_batchnorm17/relu"
+  type: "ReLU"
+  bottom: "ssd0_mobilenet0_conv17"
+  top: "ssd0_mobilenet0_conv17"
+  relu_param {
+    negative_slope: 0.0
+  }
+}
+layer {
+  name: "ssd0_mobilenet0_conv18"
+  type: "Convolution"
+  bottom: "ssd0_mobilenet0_conv17"
+  top: "ssd0_mobilenet0_conv18"
+  convolution_param {
+    num_output: 128
+    bias_term: true
+    pad: 0
+    kernel_size: 1
+    group: 1
+    stride: 1
+    dilation: 1
+  }
+}
+layer {
+  name: "ssd0_mobilenet0_batchnorm18/relu"
+  type: "ReLU"
+  bottom: "ssd0_mobilenet0_conv18"
+  top: "ssd0_mobilenet0_conv18"
+  relu_param {
+    negative_slope: 0.0
+  }
+}
+layer {
+  name: "ssd0_mobilenet0_conv19"
+  type: "Convolution"
+  bottom: "ssd0_mobilenet0_conv18"
+  top: "ssd0_mobilenet0_conv19"
+  convolution_param {
+    num_output: 128
+    bias_term: true
+    pad: 1
+    kernel_size: 3
+    group: 128
+    stride: 1
+    dilation: 1
+  }
+}
+layer {
+  name: "ssd0_mobilenet0_batchnorm19/relu"
+  type: "ReLU"
+  bottom: "ssd0_mobilenet0_conv19"
+  top: "ssd0_mobilenet0_conv19"
+  relu_param {
+    negative_slope: 0.0
+  }
+}
+layer {
+  name: "ssd0_mobilenet0_conv20"
+  type: "Convolution"
+  bottom: "ssd0_mobilenet0_conv19"
+  top: "ssd0_mobilenet0_conv20"
+  convolution_param {
+    num_output: 128
+    bias_term: true
+    pad: 0
+    kernel_size: 1
+    group: 1
+    stride: 1
+    dilation: 1
+  }
+}
+layer {
+  name: "ssd0_mobilenet0_batchnorm20/relu"
+  type: "ReLU"
+  bottom: "ssd0_mobilenet0_conv20"
+  top: "ssd0_mobilenet0_conv20"
+  relu_param {
+    negative_slope: 0.0
+  }
+}
+layer {
+  name: "ssd0_mobilenet0_conv21"
+  type: "Convolution"
+  bottom: "ssd0_mobilenet0_conv20"
+  top: "ssd0_mobilenet0_conv21"
+  convolution_param {
+    num_output: 128
+    bias_term: true
+    pad: 1
+    kernel_size: 3
+    group: 128
+    stride: 1
+    dilation: 1
+  }
+}
+layer {
+  name: "ssd0_mobilenet0_batchnorm21/relu"
+  type: "ReLU"
+  bottom: "ssd0_mobilenet0_conv21"
+  top: "ssd0_mobilenet0_conv21"
+  relu_param {
+    negative_slope: 0.0
+  }
+}
+layer {
+  name: "ssd0_mobilenet0_conv22"
+  type: "Convolution"
+  bottom: "ssd0_mobilenet0_conv21"
+  top: "ssd0_mobilenet0_conv22"
+  convolution_param {
+    num_output: 128
+    bias_term: true
+    pad: 0
+    kernel_size: 1
+    group: 1
+    stride: 1
+    dilation: 1
+  }
+}
+layer {
+  name: "ssd0_mobilenet0_batchnorm22/relu"
+  type: "ReLU"
+  bottom: "ssd0_mobilenet0_conv22"
+  top: "ssd0_mobilenet0_conv22"
+  relu_param {
+    negative_slope: 0.0
+  }
+}
+layer {
+  name: "ssd0_convpredictor1_conv0"
+  type: "Convolution"
+  bottom: "ssd0_mobilenet0_conv22"
+  top: "ssd0_convpredictor1_conv0"
+  convolution_param {
+    num_output: 12
+    bias_term: true
+    pad: 1
+    kernel_size: 3
+    group: 1
+    stride: 1
+    dilation: 1
+  }
+}
+layer {
+  name: "ssd0_transpose6"
+  type: "Permute"
+  bottom: "ssd0_convpredictor1_conv0"
+  top: "ssd0_transpose6"
+  permute_param {
+    order: 0
+    order: 2
+    order: 3
+    order: 1
+  }
+}
+layer {
+  name: "ssd0_flatten6"
+  type: "Flatten"
+  bottom: "ssd0_transpose6"
+  top: "ssd0_flatten6"
+}
+layer {
+  name: "ssd0_mobilenet0_conv23"
+  type: "Convolution"
+  bottom: "ssd0_mobilenet0_conv22"
+  top: "ssd0_mobilenet0_conv23"
+  convolution_param {
+    num_output: 128
+    bias_term: true
+    pad: 1
+    kernel_size: 3
+    group: 128
+    stride: 2
+    dilation: 1
+  }
+}
+layer {
+  name: "ssd0_mobilenet0_batchnorm23/relu"
+  type: "ReLU"
+  bottom: "ssd0_mobilenet0_conv23"
+  top: "ssd0_mobilenet0_conv23"
+  relu_param {
+    negative_slope: 0.0
+  }
+}
+layer {
+  name: "ssd0_mobilenet0_conv24"
+  type: "Convolution"
+  bottom: "ssd0_mobilenet0_conv23"
+  top: "ssd0_mobilenet0_conv24"
+  convolution_param {
+    num_output: 256
+    bias_term: true
+    pad: 0
+    kernel_size: 1
+    group: 1
+    stride: 1
+    dilation: 1
+  }
+}
+layer {
+  name: "ssd0_mobilenet0_batchnorm24/relu"
+  type: "ReLU"
+  bottom: "ssd0_mobilenet0_conv24"
+  top: "ssd0_mobilenet0_conv24"
+  relu_param {
+    negative_slope: 0.0
+  }
+}
+layer {
+  name: "ssd0_mobilenet0_conv25"
+  type: "Convolution"
+  bottom: "ssd0_mobilenet0_conv24"
+  top: "ssd0_mobilenet0_conv25"
+  convolution_param {
+    num_output: 256
+    bias_term: true
+    pad: 1
+    kernel_size: 3
+    group: 256
+    stride: 1
+    dilation: 1
+  }
+}
+layer {
+  name: "ssd0_mobilenet0_batchnorm25/relu"
+  type: "ReLU"
+  bottom: "ssd0_mobilenet0_conv25"
+  top: "ssd0_mobilenet0_conv25"
+  relu_param {
+    negative_slope: 0.0
+  }
+}
+layer {
+  name: "ssd0_mobilenet0_conv26"
+  type: "Convolution"
+  bottom: "ssd0_mobilenet0_conv25"
+  top: "ssd0_mobilenet0_conv26"
+  convolution_param {
+    num_output: 256
+    bias_term: true
+    pad: 0
+    kernel_size: 1
+    group: 1
+    stride: 1
+    dilation: 1
+  }
+}
+layer {
+  name: "ssd0_mobilenet0_batchnorm26/relu"
+  type: "ReLU"
+  bottom: "ssd0_mobilenet0_conv26"
+  top: "ssd0_mobilenet0_conv26"
+  relu_param {
+    negative_slope: 0.0
+  }
+}
+layer {
+  name: "ssd0_convpredictor3_conv0"
+  type: "Convolution"
+  bottom: "ssd0_mobilenet0_conv26"
+  top: "ssd0_convpredictor3_conv0"
+  convolution_param {
+    num_output: 16
+    bias_term: true
+    pad: 1
+    kernel_size: 3
+    group: 1
+    stride: 1
+    dilation: 1
+  }
+}
+layer {
+  name: "ssd0_transpose7"
+  type: "Permute"
+  bottom: "ssd0_convpredictor3_conv0"
+  top: "ssd0_transpose7"
+  permute_param {
+    order: 0
+    order: 2
+    order: 3
+    order: 1
+  }
+}
+layer {
+  name: "ssd0_flatten7"
+  type: "Flatten"
+  bottom: "ssd0_transpose7"
+  top: "ssd0_flatten7"
+}
+layer {
+  name: "ssd0_expand_trans_conv0"
+  type: "Convolution"
+  bottom: "ssd0_mobilenet0_conv26"
+  top: "ssd0_expand_trans_conv0"
+  convolution_param {
+    num_output: 128
+    bias_term: true
+    pad: 1
+    kernel_size: 1
+    group: 1
+    stride: 1
+    dilation: 1
+  }
+}
+layer {
+  name: "ssd0_expand_trans_bn0/relu"
+  type: "ReLU"
+  bottom: "ssd0_expand_trans_conv0"
+  top: "ssd0_expand_trans_conv0"
+  relu_param {
+    negative_slope: 0.0
+  }
+}
+layer {
+  name: "ssd0_expand_conv0"
+  type: "Convolution"
+  bottom: "ssd0_expand_trans_conv0"
+  top: "ssd0_expand_conv0"
+  convolution_param {
+    num_output: 128
+    bias_term: true
+    pad: 1
+    kernel_size: 3
+    group: 1
+    stride: 2
+    dilation: 1
+  }
+}
+layer {
+  name: "ssd0_expand_bn0/relu"
+  type: "ReLU"
+  bottom: "ssd0_expand_conv0"
+  top: "ssd0_expand_conv0"
+  relu_param {
+    negative_slope: 0.0
+  }
+}
+layer {
+  name: "ssd0_convpredictor5_conv0"
+  type: "Convolution"
+  bottom: "ssd0_expand_conv0"
+  top: "ssd0_convpredictor5_conv0"
+  convolution_param {
+    num_output: 16
+    bias_term: true
+    pad: 1
+    kernel_size: 3
+    group: 1
+    stride: 1
+    dilation: 1
+  }
+}
+layer {
+  name: "ssd0_transpose8"
+  type: "Permute"
+  bottom: "ssd0_convpredictor5_conv0"
+  top: "ssd0_transpose8"
+  permute_param {
+    order: 0
+    order: 2
+    order: 3
+    order: 1
+  }
+}
+layer {
+  name: "ssd0_flatten8"
+  type: "Flatten"
+  bottom: "ssd0_transpose8"
+  top: "ssd0_flatten8"
+}
+layer {
+  name: "ssd0_expand_trans_conv1"
+  type: "Convolution"
+  bottom: "ssd0_expand_conv0"
+  top: "ssd0_expand_trans_conv1"
+  convolution_param {
+    num_output: 128
+    bias_term: true
+    pad: 1
+    kernel_size: 1
+    group: 1
+    stride: 1
+    dilation: 1
+  }
+}
+layer {
+  name: "ssd0_expand_trans_bn1/relu"
+  type: "ReLU"
+  bottom: "ssd0_expand_trans_conv1"
+  top: "ssd0_expand_trans_conv1"
+  relu_param {
+    negative_slope: 0.0
+  }
+}
+layer {
+  name: "ssd0_expand_conv1"
+  type: "Convolution"
+  bottom: "ssd0_expand_trans_conv1"
+  top: "ssd0_expand_conv1"
+  convolution_param {
+    num_output: 128
+    bias_term: true
+    pad: 1
+    kernel_size: 3
+    group: 1
+    stride: 2
+    dilation: 1
+  }
+}
+layer {
+  name: "ssd0_expand_bn1/relu"
+  type: "ReLU"
+  bottom: "ssd0_expand_conv1"
+  top: "ssd0_expand_conv1"
+  relu_param {
+    negative_slope: 0.0
+  }
+}
+layer {
+  name: "ssd0_convpredictor7_conv0"
+  type: "Convolution"
+  bottom: "ssd0_expand_conv1"
+  top: "ssd0_convpredictor7_conv0"
+  convolution_param {
+    num_output: 16
+    bias_term: true
+    pad: 1
+    kernel_size: 3
+    group: 1
+    stride: 1
+    dilation: 1
+  }
+}
+layer {
+  name: "ssd0_transpose9"
+  type: "Permute"
+  bottom: "ssd0_convpredictor7_conv0"
+  top: "ssd0_transpose9"
+  permute_param {
+    order: 0
+    order: 2
+    order: 3
+    order: 1
+  }
+}
+layer {
+  name: "ssd0_flatten9"
+  type: "Flatten"
+  bottom: "ssd0_transpose9"
+  top: "ssd0_flatten9"
+}
+layer {
+  name: "ssd0_expand_trans_conv2"
+  type: "Convolution"
+  bottom: "ssd0_expand_conv1"
+  top: "ssd0_expand_trans_conv2"
+  convolution_param {
+    num_output: 128
+    bias_term: true
+    pad: 1
+    kernel_size: 1
+    group: 1
+    stride: 1
+    dilation: 1
+  }
+}
+layer {
+  name: "ssd0_expand_trans_bn2/relu"
+  type: "ReLU"
+  bottom: "ssd0_expand_trans_conv2"
+  top: "ssd0_expand_trans_conv2"
+  relu_param {
+    negative_slope: 0.0
+  }
+}
+layer {
+  name: "ssd0_expand_conv2"
+  type: "Convolution"
+  bottom: "ssd0_expand_trans_conv2"
+  top: "ssd0_expand_conv2"
+  convolution_param {
+    num_output: 64
+    bias_term: true
+    pad: 1
+    kernel_size: 3
+    group: 1
+    stride: 2
+    dilation: 1
+  }
+}
+layer {
+  name: "ssd0_expand_bn2/relu"
+  type: "ReLU"
+  bottom: "ssd0_expand_conv2"
+  top: "ssd0_expand_conv2"
+  relu_param {
+    negative_slope: 0.0
+  }
+}
+layer {
+  name: "ssd0_convpredictor9_conv0"
+  type: "Convolution"
+  bottom: "ssd0_expand_conv2"
+  top: "ssd0_convpredictor9_conv0"
+  convolution_param {
+    num_output: 12
+    bias_term: true
+    pad: 1
+    kernel_size: 3
+    group: 1
+    stride: 1
+    dilation: 1
+  }
+}
+layer {
+  name: "ssd0_transpose10"
+  type: "Permute"
+  bottom: "ssd0_convpredictor9_conv0"
+  top: "ssd0_transpose10"
+  permute_param {
+    order: 0
+    order: 2
+    order: 3
+    order: 1
+  }
+}
+layer {
+  name: "ssd0_flatten10"
+  type: "Flatten"
+  bottom: "ssd0_transpose10"
+  top: "ssd0_flatten10"
+}
+layer {
+  name: "ssd0_expand_trans_conv3"
+  type: "Convolution"
+  bottom: "ssd0_expand_conv2"
+  top: "ssd0_expand_trans_conv3"
+  convolution_param {
+    num_output: 128
+    bias_term: true
+    pad: 1
+    kernel_size: 1
+    group: 1
+    stride: 1
+    dilation: 1
+  }
+}
+layer {
+  name: "ssd0_expand_trans_bn3/relu"
+  type: "ReLU"
+  bottom: "ssd0_expand_trans_conv3"
+  top: "ssd0_expand_trans_conv3"
+  relu_param {
+    negative_slope: 0.0
+  }
+}
+layer {
+  name: "ssd0_expand_conv3"
+  type: "Convolution"
+  bottom: "ssd0_expand_trans_conv3"
+  top: "ssd0_expand_conv3"
+  convolution_param {
+    num_output: 64
+    bias_term: true
+    pad: 1
+    kernel_size: 3
+    group: 1
+    stride: 2
+    dilation: 1
+  }
+}
+layer {
+  name: "ssd0_expand_bn3/relu"
+  type: "ReLU"
+  bottom: "ssd0_expand_conv3"
+  top: "ssd0_expand_conv3"
+  relu_param {
+    negative_slope: 0.0
+  }
+}
+layer {
+  name: "ssd0_convpredictor11_conv0"
+  type: "Convolution"
+  bottom: "ssd0_expand_conv3"
+  top: "ssd0_convpredictor11_conv0"
+  convolution_param {
+    num_output: 12
+    bias_term: true
+    pad: 1
+    kernel_size: 3
+    group: 1
+    stride: 1
+    dilation: 1
+  }
+}
+layer {
+  name: "ssd0_transpose11"
+  type: "Permute"
+  bottom: "ssd0_convpredictor11_conv0"
+  top: "ssd0_transpose11"
+  permute_param {
+    order: 0
+    order: 2
+    order: 3
+    order: 1
+  }
+}
+layer {
+  name: "ssd0_flatten11"
+  type: "Flatten"
+  bottom: "ssd0_transpose11"
+  top: "ssd0_flatten11"
+}
+layer {
+  name: "ssd0_concat1"
+  type: "Concat"
+  bottom: "ssd0_flatten6"
+  bottom: "ssd0_flatten7"
+  bottom: "ssd0_flatten8"
+  bottom: "ssd0_flatten9"
+  bottom: "ssd0_flatten10"
+  bottom: "ssd0_flatten11"
+  top: "ssd0_concat1"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "ssd0_convpredictor0_conv0"
+  type: "Convolution"
+  bottom: "ssd0_mobilenet0_conv22"
+  top: "ssd0_convpredictor0_conv0"
+  convolution_param {
+    num_output: 6
+    bias_term: true
+    pad: 1
+    kernel_size: 3
+    group: 1
+    stride: 1
+    dilation: 1
+  }
+}
+layer {
+  name: "ssd0_transpose0"
+  type: "Permute"
+  bottom: "ssd0_convpredictor0_conv0"
+  top: "ssd0_transpose0"
+  permute_param {
+    order: 0
+    order: 2
+    order: 3
+    order: 1
+  }
+}
+layer {
+  name: "ssd0_flatten0"
+  type: "Flatten"
+  bottom: "ssd0_transpose0"
+  top: "ssd0_flatten0"
+}
+layer {
+  name: "ssd0_convpredictor2_conv0"
+  type: "Convolution"
+  bottom: "ssd0_mobilenet0_conv26"
+  top: "ssd0_convpredictor2_conv0"
+  convolution_param {
+    num_output: 8
+    bias_term: true
+    pad: 1
+    kernel_size: 3
+    group: 1
+    stride: 1
+    dilation: 1
+  }
+}
+layer {
+  name: "ssd0_transpose1"
+  type: "Permute"
+  bottom: "ssd0_convpredictor2_conv0"
+  top: "ssd0_transpose1"
+  permute_param {
+    order: 0
+    order: 2
+    order: 3
+    order: 1
+  }
+}
+layer {
+  name: "ssd0_flatten1"
+  type: "Flatten"
+  bottom: "ssd0_transpose1"
+  top: "ssd0_flatten1"
+}
+layer {
+  name: "ssd0_convpredictor4_conv0"
+  type: "Convolution"
+  bottom: "ssd0_expand_conv0"
+  top: "ssd0_convpredictor4_conv0"
+  convolution_param {
+    num_output: 8
+    bias_term: true
+    pad: 1
+    kernel_size: 3
+    group: 1
+    stride: 1
+    dilation: 1
+  }
+}
+layer {
+  name: "ssd0_transpose2"
+  type: "Permute"
+  bottom: "ssd0_convpredictor4_conv0"
+  top: "ssd0_transpose2"
+  permute_param {
+    order: 0
+    order: 2
+    order: 3
+    order: 1
+  }
+}
+layer {
+  name: "ssd0_flatten2"
+  type: "Flatten"
+  bottom: "ssd0_transpose2"
+  top: "ssd0_flatten2"
+}
+layer {
+  name: "ssd0_convpredictor6_conv0"
+  type: "Convolution"
+  bottom: "ssd0_expand_conv1"
+  top: "ssd0_convpredictor6_conv0"
+  convolution_param {
+    num_output: 8
+    bias_term: true
+    pad: 1
+    kernel_size: 3
+    group: 1
+    stride: 1
+    dilation: 1
+  }
+}
+layer {
+  name: "ssd0_transpose3"
+  type: "Permute"
+  bottom: "ssd0_convpredictor6_conv0"
+  top: "ssd0_transpose3"
+  permute_param {
+    order: 0
+    order: 2
+    order: 3
+    order: 1
+  }
+}
+layer {
+  name: "ssd0_flatten3"
+  type: "Flatten"
+  bottom: "ssd0_transpose3"
+  top: "ssd0_flatten3"
+}
+layer {
+  name: "ssd0_convpredictor8_conv0"
+  type: "Convolution"
+  bottom: "ssd0_expand_conv2"
+  top: "ssd0_convpredictor8_conv0"
+  convolution_param {
+    num_output: 6
+    bias_term: true
+    pad: 1
+    kernel_size: 3
+    group: 1
+    stride: 1
+    dilation: 1
+  }
+}
+layer {
+  name: "ssd0_transpose4"
+  type: "Permute"
+  bottom: "ssd0_convpredictor8_conv0"
+  top: "ssd0_transpose4"
+  permute_param {
+    order: 0
+    order: 2
+    order: 3
+    order: 1
+  }
+}
+layer {
+  name: "ssd0_flatten4"
+  type: "Flatten"
+  bottom: "ssd0_transpose4"
+  top: "ssd0_flatten4"
+}
+layer {
+  name: "ssd0_convpredictor10_conv0"
+  type: "Convolution"
+  bottom: "ssd0_expand_conv3"
+  top: "ssd0_convpredictor10_conv0"
+  convolution_param {
+    num_output: 6
+    bias_term: true
+    pad: 1
+    kernel_size: 3
+    group: 1
+    stride: 1
+    dilation: 1
+  }
+}
+layer {
+  name: "ssd0_transpose5"
+  type: "Permute"
+  bottom: "ssd0_convpredictor10_conv0"
+  top: "ssd0_transpose5"
+  permute_param {
+    order: 0
+    order: 2
+    order: 3
+    order: 1
+  }
+}
+layer {
+  name: "ssd0_flatten5"
+  type: "Flatten"
+  bottom: "ssd0_transpose5"
+  top: "ssd0_flatten5"
+}
+layer {
+  name: "ssd0_concat0"
+  type: "Concat"
+  bottom: "ssd0_flatten0"
+  bottom: "ssd0_flatten1"
+  bottom: "ssd0_flatten2"
+  bottom: "ssd0_flatten3"
+  bottom: "ssd0_flatten4"
+  bottom: "ssd0_flatten5"
+  top: "ssd0_concat0"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "ssd0_reshape6"
+  type: "Reshape"
+  bottom: "ssd0_concat0"
+  top: "ssd0_reshape6"
+  reshape_param {
+    shape {
+      dim: 0
+      dim: -1
+      dim: 2
+    }
+  }
+}
+layer {
+  name: "softmax0"
+  type: "Softmax"
+  bottom: "ssd0_reshape6"
+  top: "softmax0"
+  softmax_param {
+    axis: 2
+  }
+}
+layer {
+  name: "flatten0"
+  type: "Flatten"
+  bottom: "softmax0"
+  top: "flatten0"
+}
+layer {
+  name: "ssd0_mobilenet0_relu22_fwd_priorbox"
+  type: "PriorBox"
+  bottom: "ssd0_mobilenet0_conv22"
+  bottom: "data"
+  top: "ssd0_mobilenet0_relu22_fwd_priorbox"
+  prior_box_param {
+    min_size: 51.20000076293945
+    max_size: 102.4000015258789
+    aspect_ratio: 1.0
+    aspect_ratio: 2.0
+    flip: false
+    clip: false
+    variance: 0.10000000149011612
+    variance: 0.10000000149011612
+    variance: 0.20000000298023224
+    variance: 0.20000000298023224
+    offset: 0.5
+  }
+}
+layer {
+  name: "ssd0_mobilenet0_relu26_fwd_priorbox"
+  type: "PriorBox"
+  bottom: "ssd0_mobilenet0_conv26"
+  bottom: "data"
+  top: "ssd0_mobilenet0_relu26_fwd_priorbox"
+  prior_box_param {
+    min_size: 102.4000015258789
+    max_size: 189.39999389648438
+    aspect_ratio: 1.0
+    aspect_ratio: 2.0
+    aspect_ratio: 3.0
+    flip: false
+    clip: false
+    variance: 0.10000000149011612
+    variance: 0.10000000149011612
+    variance: 0.20000000298023224
+    variance: 0.20000000298023224
+    offset: 0.5
+  }
+}
+layer {
+  name: "ssd0_expand_reu0_priorbox"
+  type: "PriorBox"
+  bottom: "ssd0_expand_conv0"
+  bottom: "data"
+  top: "ssd0_expand_reu0_priorbox"
+  prior_box_param {
+    min_size: 189.39999389648438
+    max_size: 276.3999938964844
+    aspect_ratio: 1.0
+    aspect_ratio: 2.0
+    aspect_ratio: 3.0
+    flip: false
+    clip: false
+    variance: 0.10000000149011612
+    variance: 0.10000000149011612
+    variance: 0.20000000298023224
+    variance: 0.20000000298023224
+    offset: 0.5
+  }
+}
+layer {
+  name: "ssd0_expand_reu1_priorbox"
+  type: "PriorBox"
+  bottom: "ssd0_expand_conv1"
+  bottom: "data"
+  top: "ssd0_expand_reu1_priorbox"
+  prior_box_param {
+    min_size: 276.3999938964844
+    max_size: 363.5199890136719
+    aspect_ratio: 1.0
+    aspect_ratio: 2.0
+    aspect_ratio: 3.0
+    flip: false
+    clip: false
+    variance: 0.10000000149011612
+    variance: 0.10000000149011612
+    variance: 0.20000000298023224
+    variance: 0.20000000298023224
+    offset: 0.5
+  }
+}
+layer {
+  name: "ssd0_expand_reu2_priorbox"
+  type: "PriorBox"
+  bottom: "ssd0_expand_conv2"
+  bottom: "data"
+  top: "ssd0_expand_reu2_priorbox"
+  prior_box_param {
+    min_size: 363.5199890136719
+    max_size: 450.6000061035156
+    aspect_ratio: 1.0
+    aspect_ratio: 2.0
+    flip: false
+    clip: false
+    variance: 0.10000000149011612
+    variance: 0.10000000149011612
+    variance: 0.20000000298023224
+    variance: 0.20000000298023224
+    offset: 0.5
+  }
+}
+layer {
+  name: "ssd0_expand_reu3_priorbox"
+  type: "PriorBox"
+  bottom: "ssd0_expand_conv3"
+  bottom: "data"
+  top: "ssd0_expand_reu3_priorbox"
+  prior_box_param {
+    min_size: 450.6000061035156
+    max_size: 492.0
+    aspect_ratio: 1.0
+    aspect_ratio: 2.0
+    flip: false
+    clip: false
+    variance: 0.10000000149011612
+    variance: 0.10000000149011612
+    variance: 0.20000000298023224
+    variance: 0.20000000298023224
+    offset: 0.5
+  }
+}
+layer {
+  name: "concat0"
+  type: "Concat"
+  bottom: "ssd0_mobilenet0_relu22_fwd_priorbox"
+  bottom: "ssd0_mobilenet0_relu26_fwd_priorbox"
+  bottom: "ssd0_expand_reu0_priorbox"
+  bottom: "ssd0_expand_reu1_priorbox"
+  bottom: "ssd0_expand_reu2_priorbox"
+  bottom: "ssd0_expand_reu3_priorbox"
+  top: "concat0"
+  concat_param {
+    axis: 2
+  }
+}
+layer {
+  name: "detection_out"
+  type: "DetectionOutput"
+  bottom: "ssd0_concat1"
+  bottom: "flatten0"
+  bottom: "concat0"
+  top: "detection_out"
+  detection_output_param {
+    num_classes: 2
+    share_location: true
+    background_label_id: 0
+    nms_param {
+      nms_threshold: 0.44999998807907104
+      top_k: 400
+    }
+    code_type: CENTER_SIZE
+    keep_top_k: 100
+    confidence_threshold: 0.009999999776482582
+  }
+}
diff --git a/hyperlpr_pip_pkg/hyperlpr/models/dnn/refinenet.caffemodel b/hyperlpr_pip_pkg/hyperlpr/models/dnn/refinenet.caffemodel
new file mode 100755
index 0000000..d02bcab
Binary files /dev/null and b/hyperlpr_pip_pkg/hyperlpr/models/dnn/refinenet.caffemodel differ
diff --git a/hyperlpr_pip_pkg/hyperlpr/models/dnn/refinenet.prototxt b/hyperlpr_pip_pkg/hyperlpr/models/dnn/refinenet.prototxt
new file mode 100755
index 0000000..5ef8e75
--- /dev/null
+++ b/hyperlpr_pip_pkg/hyperlpr/models/dnn/refinenet.prototxt
@@ -0,0 +1,300 @@
+name: "ONet"
+input: "data"
+input_dim: 1
+input_dim: 3
+input_dim: 48
+input_dim: 120
+
+##################################
+layer {
+  name: "conv1"
+  type: "Convolution"
+  bottom: "data"
+  top: "conv1"
+  param {
+    lr_mult: 1
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2
+    decay_mult: 1
+  }
+  convolution_param {
+    num_output: 32
+    kernel_size: 3
+    stride: 1
+     weight_filler {
+      type: "xavier"
+	}
+    bias_filler {
+      type: "constant"
+      value: 0
+    }
+  }
+}
+layer {
+  name: "prelu1"
+  type: "PReLU"
+  bottom: "conv1"
+  top: "conv1"
+}
+layer {
+  name: "pool1"
+  type: "Pooling"
+  bottom: "conv1"
+  top: "pool1"
+  pooling_param {
+    pool: MAX
+    kernel_size: 3
+    stride: 2
+  }
+}
+layer {
+  name: "conv2"
+  type: "Convolution"
+  bottom: "pool1"
+  top: "conv2"
+  param {
+    lr_mult: 1
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2
+    decay_mult: 1
+  }
+  convolution_param {
+    num_output: 64
+    kernel_size: 3
+    stride: 1
+     weight_filler {
+      type: "xavier"
+	}
+    bias_filler {
+      type: "constant"
+      value: 0
+    }
+  }
+}
+
+layer {
+  name: "prelu2"
+  type: "PReLU"
+  bottom: "conv2"
+  top: "conv2"
+}
+layer {
+  name: "pool2"
+  type: "Pooling"
+  bottom: "conv2"
+  top: "pool2"
+  pooling_param {
+    pool: MAX
+    kernel_size: 3
+    stride: 2
+  }
+}
+
+layer {
+  name: "conv3"
+  type: "Convolution"
+  bottom: "pool2"
+  top: "conv3"
+  param {
+    lr_mult: 1
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2
+    decay_mult: 1
+  }
+  convolution_param {
+	num_output: 64
+	kernel_size: 3
+    weight_filler {
+      type: "xavier"
+	}
+    bias_filler {
+      type: "constant"
+      value: 0
+    }
+  }
+}
+layer {
+  name: "prelu3"
+  type: "PReLU"
+  bottom: "conv3"
+  top: "conv3"
+}
+layer {
+  name: "pool3"
+  type: "Pooling"
+  bottom: "conv3"
+  top: "pool3"
+  pooling_param {
+    pool: MAX
+    kernel_size: 2
+    stride: 2
+  }
+}
+layer {
+  name: "conv4"
+  type: "Convolution"
+  bottom: "pool3"
+  top: "conv4"
+  param {
+    lr_mult: 1
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2
+    decay_mult: 1
+  }
+  convolution_param {
+	num_output: 128
+	kernel_size: 2
+    weight_filler {
+      type: "xavier"
+	}
+    bias_filler {
+      type: "constant"
+      value: 0
+    }
+  }
+}
+layer {
+  name: "prelu4"
+  type: "PReLU"
+  bottom: "conv4"
+  top: "conv4"
+}
+
+
+layer {
+  name: "conv5i"
+  type: "InnerProduct"
+  bottom: "conv4"
+  top: "conv5"
+  param {
+    lr_mult: 1
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2
+    decay_mult: 1
+  }
+  inner_product_param {
+	#kernel_size: 3
+	num_output: 256
+    weight_filler {
+      type: "xavier"
+	}
+    bias_filler {
+      type: "constant"
+      value: 0
+    }
+  }
+}
+
+layer {
+  name: "drop5i"
+  type: "Dropout"
+  bottom: "conv5"
+  top: "conv5"
+  dropout_param {
+    dropout_ratio: 0.25
+  }
+}
+layer {
+  name: "prelu5"
+  type: "PReLU"
+  bottom: "conv5"
+  top: "conv5"
+}
+
+
+layer {
+  name: "conv6i-1"
+  type: "InnerProduct"
+  bottom: "conv5"
+  top: "conv6-1"
+  param {
+    lr_mult: 1
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2
+    decay_mult: 1
+  }
+  inner_product_param {
+    #kernel_size: 1
+	num_output: 2
+    weight_filler {
+      type: "xavier"
+	}
+    bias_filler {
+      type: "constant"
+      value: 0
+    }
+  }
+}
+
+
+layer {
+  name: "conv6i-2"
+  type: "InnerProduct"
+  bottom: "conv5"
+  top: "conv6-2"
+  param {
+    lr_mult: 1
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2
+    decay_mult: 1
+  }
+  inner_product_param {
+  	#kernel_size: 1
+	num_output: 4
+    weight_filler {
+      type: "xavier"
+	}
+    bias_filler {
+      type: "constant"
+      value: 0
+    }
+  }
+}
+
+layer {
+  name: "conv6-3"
+  type: "InnerProduct"
+  bottom: "conv5"
+  top: "conv6-3"
+  param {
+    lr_mult: 1
+    decay_mult: 1
+  }
+  param {
+    lr_mult: 2
+    decay_mult: 1
+  }
+  inner_product_param {
+  	#kernel_size: 1
+	num_output: 8
+    weight_filler {
+      type: "xavier"
+	}
+    bias_filler {
+      type: "constant"
+      value: 0
+    }
+  }
+}
+
+
+layer {
+  name: "prob1"
+  type: "Softmax"
+  bottom: "conv6-1"
+  top: "prob1"
+}
\ No newline at end of file