saiv/face/fr/Proto.prototxt

   1 name: "DL_FR"
   2 input: "data"
   3 input_dim:1
   4 input_dim:3
   5 input_dim:61
   6 input_dim:61
   7 #################  laye-1
   8 layers {
   9   bottom: "data"
  10   top: "conv1/3x3_s2_1"
  11   name: "conv1/3x3_s2_1"
  12   type: CONVOLUTION
  13   convolution_param {
  14     num_output: 64
  15     kernel_size: 3
  16     stride: 2
  17   }
  18 }
  19 layers {
  20   bottom: "conv1/3x3_s2_1"
  21   top: "conv1/3x3_s2_1"
  22   name: "conv1/relu_3x3"
  23   type: PRELU
  24   prelu_param {
  25     channel_shared: false
  26   }
  27 }
  28
  29 layers {
  30   name: "conv1/norm1"
  31   type: LRN
  32   bottom: "conv1/3x3_s2_1"
  33   top: "conv1/norm1"
  34   lrn_param {
  35     local_size: 3
  36     alpha: 0.0001
  37     beta: 0.75
  38   }
  39 }
  40
  41 #####################layer-2
  42
  43 layers {
  44   bottom: "conv1/norm1"
  45   top: "conv2/3x3_s2_1"
  46   name: "conv2/3x3_s2_1"
  47   type: CONVOLUTION
  48   convolution_param {
  49     num_output: 128
  50     kernel_size: 3
  51     stride: 2
  52   }
  53 }
  54 layers {
  55   bottom: "conv2/3x3_s2_1"
  56   top: "conv2/3x3_s2_1"
  57   name: "conv2/relu_3x3"
  58   type: PRELU
  59   prelu_param {
  60     channel_shared: false
  61   }
  62 }
  63
  64 layers {
  65   name: "conv2/norm1"
  66   type: LRN
  67   bottom: "conv2/3x3_s2_1"
  68   top: "conv2/norm1"
  69   lrn_param {
  70     local_size: 3
  71     alpha: 0.0001
  72     beta: 0.75
  73   }
  74 }
  75
  76
  77 ##################################### layer-3
  78
  79 layers {
  80   bottom: "conv2/norm1"
  81   top: "conv3/2x2_s2_1"
  82   name: "conv3/2x2_s2_1"
  83   type: CONVOLUTION
  84   convolution_param {
  85     num_output: 256
  86     kernel_size: 2
  87     stride: 2
  88   }
  89 }
  90 layers {
  91   bottom: "conv3/2x2_s2_1"
  92   top: "conv3/2x2_s2_1"
  93   name: "conv3/relu_2x2_1"
  94   type: PRELU
  95   prelu_param {
  96     channel_shared: false
  97   }
  98 }
  99 layers {
 100   bottom: "conv3/2x2_s2_1"
 101   top: "conv3/2x2_s1_2"
 102   name: "conv3/2x2_s1_2"
 103   type: CONVOLUTION
 104   convolution_param {
 105     num_output: 384
 106     kernel_size: 2
 107     pad: 1
 108     stride: 1
 109   }
 110 }
 111 layers {
 112   bottom: "conv3/2x2_s1_2"
 113   top: "conv3/2x2_s1_2"
 114   name: "conv3/relu_2x2_2"
 115   type: PRELU
 116   prelu_param {
 117     channel_shared: false
 118   }
 119 }
 120 #####################layer-4
 121
 122 layers {
 123   bottom: "conv3/2x2_s1_2"
 124   top: "conv4/2x2_s1_1"
 125   name: "conv4/2x2_s1_1"
 126   type: CONVOLUTION
 127   convolution_param {
 128     num_output: 256
 129     kernel_size: 2
 130     stride: 1
 131   }
 132 }
 133 layers {
 134   bottom: "conv4/2x2_s1_1"
 135   top: "conv4/2x2_s1_1"
 136   name: "conv4/relu_2x2_1"
 137   type: PRELU
 138   prelu_param {
 139     channel_shared: false
 140   }
 141 }
 142
 143 layers {
 144   bottom: "conv4/2x2_s1_1"
 145   top: "conv4/2x2_s1_2"
 146   name: "conv4/2x2_s1_2"
 147   type: CONVOLUTION
 148   convolution_param {
 149     num_output: 128
 150     kernel_size: 2
 151     pad: 1
 152     stride: 1
 153   }
 154 }
 155 layers {
 156   bottom: "conv4/2x2_s1_2"
 157   top: "conv4/2x2_s1_2"
 158   name: "conv4/relu_2x2_2"
 159   type: PRELU
 160   prelu_param {
 161     channel_shared: false
 162   }
 163 }
 164 ##############4x4 bin
 165 layers {
 166   name: "pool4_1"
 167   type: POOLING
 168   bottom: "conv4/2x2_s1_2"
 169   top: "pool4_1"
 170   pooling_param {
 171     pool: MAX
 172     kernel_size: 2
 173     stride: 2
 174   }
 175 }
 176
 177 layers {
 178   name: "pool4_1_flatten"
 179   type: FLATTEN
 180   bottom: "pool4_1"
 181   top: "pool4_1_flatten"
 182 }
 183
 184
 185 ###############2*2 bin
 186
 187 layers {
 188   name: "pool4_2"
 189   type: POOLING
 190   bottom: "conv4/2x2_s1_2"
 191   top: "pool4_2"
 192   pooling_param {
 193     pool: MAX
 194     kernel_size: 4
 195     stride: 4
 196   }
 197 }
 198
 199 layers {
 200   name: "pool4_2_flatten"
 201   type: FLATTEN
 202   bottom: "pool4_2"
 203   top: "pool4_2_flatten"
 204 }
 205
 206
 207 #############1*1 bin
 208
 209 layers {
 210   name: "pool4_3"
 211   type: POOLING
 212   bottom: "conv4/2x2_s1_2"
 213   top: "pool4_3"
 214   pooling_param {
 215     pool: MAX
 216     kernel_size: 8
 217     stride: 8
 218   }
 219 }
 220
 221 layers {
 222   name: "pool4_3_flatten"
 223   type: FLATTEN
 224   bottom: "pool4_3"
 225   top: "pool4_3_flatten"
 226 }
 227
 228 layers {
 229   bottom: "pool4_1_flatten"
 230   bottom: "pool4_2_flatten"
 231   bottom: "pool4_3_flatten"
 232   top: "pool4_spp"
 233   name: "pool4_spp"
 234   type: CONCAT
 235 }
 236
 237
 238 ##########################fc-5
 239
 240 layers {
 241   name: "fc5"
 242   type: INNER_PRODUCT
 243   bottom: "pool4_spp"
 244   top: "fc5"
 245   inner_product_param {
 246     num_output: 512
 247   }
 248 }
 249 layers {
 250   name: "relu5"
 251   type: PRELU
 252   bottom: "fc5"
 253   top: "fc5"
 254   prelu_param {
 255     channel_shared: false
 256   }
 257 }
 258 #layers {
 259 #  name: "drop5"
 260 #  type: DROPOUT
 261 #  bottom: "fc5"
 262 #  top: "fc5"
 263 #  dropout_param {
 264 #    dropout_ratio: 0.2
 265 #  }
 266 #}
 267
 268 ##############fc-6
 269 layers {
 270   name: "fc6"
 271   type: INNER_PRODUCT
 272   bottom: "fc5"
 273   top: "fc6"
 274   inner_product_param {
 275     num_output: 256
 276   }
 277 }
 278 layers {
 279   name: "relu6"
 280   type: PRELU
 281   bottom: "fc6"
 282   top: "fc6"
 283   prelu_param {
 284     channel_shared: false
 285   }
 286 }
 287 #layers {
 288 #  name: "drop6"
 289 #  type: DROPOUT
 290 #  bottom: "fc6"
 291 #  top: "fc6"
 292 #  dropout_param {
 293 #    dropout_ratio: 0.1
 294 #  }
 295 #}
 296 #layers {
 297 #  name: "fc7_face64"
 298 #  type: INNER_PRODUCT
 299 #  bottom: "fc6"
 300 #  top: "fc7_face64"
 301 #  inner_product_param {
 302 #    num_output: 2193
 303 #   }
 304 #}
 305 #layers {
 306 #  name: "accuracy_top1"
 307 #  type: ACCURACY
 308 #  bottom: "fc7_face64"
 309 #  bottom: "label"
 310 #  top: "accuracy_top1"
 311 #  accuracy_param {
 312 #    top_k: 1
 313 #  }
 314 #  include: { phase: TEST }
 315 #}
 316 #layers {
 317 #  name: "loss"
 318 #  type: SOFTMAX_LOSS
 319 #  bottom: "fc7_face64"
 320 #  bottom: "label"
 321 #  top: "loss"
 322 #}