modularization_models/detection/license_plate_recognition/lpr/model/CharacterRecognization.prototxt

input: "data"
input_dim: 1
input_dim: 1
input_dim: 30
input_dim: 14
layer {
  name: "conv2d_1"
  type: "Convolution"
  bottom: "data"
  top: "conv2d_1"
  convolution_param {
    num_output: 32
    bias_term: true
    pad: 0
    kernel_size: 3
    stride: 1
  }
}
layer {
  name: "activation_1"
  type: "ReLU"
  bottom: "conv2d_1"
  top: "activation_1"
}
layer {
  name: "max_pooling2d_1"
  type: "Pooling"
  bottom: "activation_1"
  top: "max_pooling2d_1"
  pooling_param {
    pool: MAX
    kernel_size: 2
    stride: 2
    pad: 0
  }
}
layer {
  name: "conv2d_2"
  type: "Convolution"
  bottom: "max_pooling2d_1"
  top: "conv2d_2"
  convolution_param {
    num_output: 64
    bias_term: true
    pad: 0
    kernel_size: 3
    stride: 1
  }
}
layer {
  name: "activation_2"
  type: "ReLU"
  bottom: "conv2d_2"
  top: "activation_2"
}
layer {
  name: "max_pooling2d_2"
  type: "Pooling"
  bottom: "activation_2"
  top: "max_pooling2d_2"
  pooling_param {
    pool: MAX
    kernel_size: 2
    stride: 2
    pad: 0
  }
}
layer {
  name: "conv2d_3"
  type: "Convolution"
  bottom: "max_pooling2d_2"
  top: "conv2d_3"
  convolution_param {
    num_output: 128
    bias_term: true
    pad: 0
    kernel_size: 2
    stride: 1
  }
}
layer {
  name: "activation_3"
  type: "ReLU"
  bottom: "conv2d_3"
  top: "activation_3"
}
layer {
  name: "flatten_1"
  type: "Flatten"
  bottom: "activation_3"
  top: "flatten_1"
}
layer {
  name: "dense_1"
  type: "InnerProduct"
  bottom: "flatten_1"
  top: "dense_1"
  inner_product_param {
    num_output: 256
  }
}
layer {
  name: "relu2"
  type: "ReLU"
  bottom: "dense_1"
  top: "relu2"
}
layer {
  name: "dense2"
  type: "InnerProduct"
  bottom: "relu2"
  top: "dense2"
  inner_product_param {
    num_output: 65
  }
}

layer {
  name: "prob"
  type: "Softmax"
  bottom: "dense2"
  top: "prob"
}