1  name: "MobileNet-SSD"
   2  input: "data"
   3  input_shape {
   4    dim: 1
   5    dim: 3
   6    dim: 300
   7    dim: 300
   8  }
   9  layer {
  10    name: "conv0"
  11    type: "Convolution"
  12    bottom: "data"
  13    top: "conv0"
  14    param {
  15      lr_mult: 1.0
  16      decay_mult: 1.0
  17    }
  18    param {
  19      lr_mult: 2.0
  20      decay_mult: 0.0
  21    }
  22    convolution_param {
  23      num_output: 32
  24      pad: 1
  25      kernel_size: 3
  26      stride: 2
  27      weight_filler {
  28        type: "msra"
  29      }
  30      bias_filler {
  31        type: "constant"
  32        value: 0.0
  33      }
  34    }
  35  }
  36  layer {
  37    name: "conv0/relu"
  38    type: "ReLU"
  39    bottom: "conv0"
  40    top: "conv0"
  41  }
  42  layer {
  43    name: "conv1/dw"
  44    type: "Convolution"
  45    bottom: "conv0"
  46    top: "conv1/dw"
  47    param {
  48      lr_mult: 1.0
  49      decay_mult: 1.0
  50    }
  51    param {
  52      lr_mult: 2.0
  53      decay_mult: 0.0
  54    }
  55    convolution_param {
  56      num_output: 32
  57      pad: 1
  58      kernel_size: 3
  59      group: 32
  60      engine: CAFFE
  61      weight_filler {
  62        type: "msra"
  63      }
  64      bias_filler {
  65        type: "constant"
  66        value: 0.0
  67      }
  68    }
  69  }
  70  layer {
  71    name: "conv1/dw/relu"
  72    type: "ReLU"
  73    bottom: "conv1/dw"
  74    top: "conv1/dw"
  75  }
  76  layer {
  77    name: "conv1"
  78    type: "Convolution"
  79    bottom: "conv1/dw"
  80    top: "conv1"
  81    param {
  82      lr_mult: 1.0
  83      decay_mult: 1.0
  84    }
  85    param {
  86      lr_mult: 2.0
  87      decay_mult: 0.0
  88    }
  89    convolution_param {
  90      num_output: 64
  91      kernel_size: 1
  92      weight_filler {
  93        type: "msra"
  94      }
  95      bias_filler {
  96        type: "constant"
  97        value: 0.0
  98      }
  99    }
 100  }
 101  layer {
 102    name: "conv1/relu"
 103    type: "ReLU"
 104    bottom: "conv1"
 105    top: "conv1"
 106  }
 107  layer {
 108    name: "conv2/dw"
 109    type: "Convolution"
 110    bottom: "conv1"
 111    top: "conv2/dw"
 112    param {
 113      lr_mult: 1.0
 114      decay_mult: 1.0
 115    }
 116    param {
 117      lr_mult: 2.0
 118      decay_mult: 0.0
 119    }
 120    convolution_param {
 121      num_output: 64
 122      pad: 1
 123      kernel_size: 3
 124      stride: 2
 125      group: 64
 126      engine: CAFFE
 127      weight_filler {
 128        type: "msra"
 129      }
 130      bias_filler {
 131        type: "constant"
 132        value: 0.0
 133      }
 134    }
 135  }
 136  layer {
 137    name: "conv2/dw/relu"
 138    type: "ReLU"
 139    bottom: "conv2/dw"
 140    top: "conv2/dw"
 141  }
 142  layer {
 143    name: "conv2"
 144    type: "Convolution"
 145    bottom: "conv2/dw"
 146    top: "conv2"
 147    param {
 148      lr_mult: 1.0
 149      decay_mult: 1.0
 150    }
 151    param {
 152      lr_mult: 2.0
 153      decay_mult: 0.0
 154    }
 155    convolution_param {
 156      num_output: 128
 157      kernel_size: 1
 158      weight_filler {
 159        type: "msra"
 160      }
 161      bias_filler {
 162        type: "constant"
 163        value: 0.0
 164      }
 165    }
 166  }
 167  layer {
 168    name: "conv2/relu"
 169    type: "ReLU"
 170    bottom: "conv2"
 171    top: "conv2"
 172  }
 173  layer {
 174    name: "conv3/dw"
 175    type: "Convolution"
 176    bottom: "conv2"
 177    top: "conv3/dw"
 178    param {
 179      lr_mult: 1.0
 180      decay_mult: 1.0
 181    }
 182    param {
 183      lr_mult: 2.0
 184      decay_mult: 0.0
 185    }
 186    convolution_param {
 187      num_output: 128
 188      pad: 1
 189      kernel_size: 3
 190      group: 128
 191      engine: CAFFE
 192      weight_filler {
 193        type: "msra"
 194      }
 195      bias_filler {
 196        type: "constant"
 197        value: 0.0
 198      }
 199    }
 200  }
 201  layer {
 202    name: "conv3/dw/relu"
 203    type: "ReLU"
 204    bottom: "conv3/dw"
 205    top: "conv3/dw"
 206  }
 207  layer {
 208    name: "conv3"
 209    type: "Convolution"
 210    bottom: "conv3/dw"
 211    top: "conv3"
 212    param {
 213      lr_mult: 1.0
 214      decay_mult: 1.0
 215    }
 216    param {
 217      lr_mult: 2.0
 218      decay_mult: 0.0
 219    }
 220    convolution_param {
 221      num_output: 128
 222      kernel_size: 1
 223      weight_filler {
 224        type: "msra"
 225      }
 226      bias_filler {
 227        type: "constant"
 228        value: 0.0
 229      }
 230    }
 231  }
 232  layer {
 233    name: "conv3/relu"
 234    type: "ReLU"
 235    bottom: "conv3"
 236    top: "conv3"
 237  }
 238  layer {
 239    name: "conv4/dw"
 240    type: "Convolution"
 241    bottom: "conv3"
 242    top: "conv4/dw"
 243    param {
 244      lr_mult: 1.0
 245      decay_mult: 1.0
 246    }
 247    param {
 248      lr_mult: 2.0
 249      decay_mult: 0.0
 250    }
 251    convolution_param {
 252      num_output: 128
 253      pad: 1
 254      kernel_size: 3
 255      stride: 2
 256      group: 128
 257      engine: CAFFE
 258      weight_filler {
 259        type: "msra"
 260      }
 261      bias_filler {
 262        type: "constant"
 263        value: 0.0
 264      }
 265    }
 266  }
 267  layer {
 268    name: "conv4/dw/relu"
 269    type: "ReLU"
 270    bottom: "conv4/dw"
 271    top: "conv4/dw"
 272  }
 273  layer {
 274    name: "conv4"
 275    type: "Convolution"
 276    bottom: "conv4/dw"
 277    top: "conv4"
 278    param {
 279      lr_mult: 1.0
 280      decay_mult: 1.0
 281    }
 282    param {
 283      lr_mult: 2.0
 284      decay_mult: 0.0
 285    }
 286    convolution_param {
 287      num_output: 256
 288      kernel_size: 1
 289      weight_filler {
 290        type: "msra"
 291      }
 292      bias_filler {
 293        type: "constant"
 294        value: 0.0
 295      }
 296    }
 297  }
 298  layer {
 299    name: "conv4/relu"
 300    type: "ReLU"
 301    bottom: "conv4"
 302    top: "conv4"
 303  }
 304  layer {
 305    name: "conv5/dw"
 306    type: "Convolution"
 307    bottom: "conv4"
 308    top: "conv5/dw"
 309    param {
 310      lr_mult: 1.0
 311      decay_mult: 1.0
 312    }
 313    param {
 314      lr_mult: 2.0
 315      decay_mult: 0.0
 316    }
 317    convolution_param {
 318      num_output: 256
 319      pad: 1
 320      kernel_size: 3
 321      group: 256
 322      engine: CAFFE
 323      weight_filler {
 324        type: "msra"
 325      }
 326      bias_filler {
 327        type: "constant"
 328        value: 0.0
 329      }
 330    }
 331  }
 332  layer {
 333    name: "conv5/dw/relu"
 334    type: "ReLU"
 335    bottom: "conv5/dw"
 336    top: "conv5/dw"
 337  }
 338  layer {
 339    name: "conv5"
 340    type: "Convolution"
 341    bottom: "conv5/dw"
 342    top: "conv5"
 343    param {
 344      lr_mult: 1.0
 345      decay_mult: 1.0
 346    }
 347    param {
 348      lr_mult: 2.0
 349      decay_mult: 0.0
 350    }
 351    convolution_param {
 352      num_output: 256
 353      kernel_size: 1
 354      weight_filler {
 355        type: "msra"
 356      }
 357      bias_filler {
 358        type: "constant"
 359        value: 0.0
 360      }
 361    }
 362  }
 363  layer {
 364    name: "conv5/relu"
 365    type: "ReLU"
 366    bottom: "conv5"
 367    top: "conv5"
 368  }
 369  layer {
 370    name: "conv6/dw"
 371    type: "Convolution"
 372    bottom: "conv5"
 373    top: "conv6/dw"
 374    param {
 375      lr_mult: 1.0
 376      decay_mult: 1.0
 377    }
 378    param {
 379      lr_mult: 2.0
 380      decay_mult: 0.0
 381    }
 382    convolution_param {
 383      num_output: 256
 384      pad: 1
 385      kernel_size: 3
 386      stride: 2
 387      group: 256
 388      engine: CAFFE
 389      weight_filler {
 390        type: "msra"
 391      }
 392      bias_filler {
 393        type: "constant"
 394        value: 0.0
 395      }
 396    }
 397  }
 398  layer {
 399    name: "conv6/dw/relu"
 400    type: "ReLU"
 401    bottom: "conv6/dw"
 402    top: "conv6/dw"
 403  }
 404  layer {
 405    name: "conv6"
 406    type: "Convolution"
 407    bottom: "conv6/dw"
 408    top: "conv6"
 409    param {
 410      lr_mult: 1.0
 411      decay_mult: 1.0
 412    }
 413    param {
 414      lr_mult: 2.0
 415      decay_mult: 0.0
 416    }
 417    convolution_param {
 418      num_output: 512
 419      kernel_size: 1
 420      weight_filler {
 421        type: "msra"
 422      }
 423      bias_filler {
 424        type: "constant"
 425        value: 0.0
 426      }
 427    }
 428  }
 429  layer {
 430    name: "conv6/relu"
 431    type: "ReLU"
 432    bottom: "conv6"
 433    top: "conv6"
 434  }
 435  layer {
 436    name: "conv7/dw"
 437    type: "Convolution"
 438    bottom: "conv6"
 439    top: "conv7/dw"
 440    param {
 441      lr_mult: 1.0
 442      decay_mult: 1.0
 443    }
 444    param {
 445      lr_mult: 2.0
 446      decay_mult: 0.0
 447    }
 448    convolution_param {
 449      num_output: 512
 450      pad: 1
 451      kernel_size: 3
 452      group: 512
 453      engine: CAFFE
 454      weight_filler {
 455        type: "msra"
 456      }
 457      bias_filler {
 458        type: "constant"
 459        value: 0.0
 460      }
 461    }
 462  }
 463  layer {
 464    name: "conv7/dw/relu"
 465    type: "ReLU"
 466    bottom: "conv7/dw"
 467    top: "conv7/dw"
 468  }
 469  layer {
 470    name: "conv7"
 471    type: "Convolution"
 472    bottom: "conv7/dw"
 473    top: "conv7"
 474    param {
 475      lr_mult: 1.0
 476      decay_mult: 1.0
 477    }
 478    param {
 479      lr_mult: 2.0
 480      decay_mult: 0.0
 481    }
 482    convolution_param {
 483      num_output: 512
 484      kernel_size: 1
 485      weight_filler {
 486        type: "msra"
 487      }
 488      bias_filler {
 489        type: "constant"
 490        value: 0.0
 491      }
 492    }
 493  }
 494  layer {
 495    name: "conv7/relu"
 496    type: "ReLU"
 497    bottom: "conv7"
 498    top: "conv7"
 499  }
 500  layer {
 501    name: "conv8/dw"
 502    type: "Convolution"
 503    bottom: "conv7"
 504    top: "conv8/dw"
 505    param {
 506      lr_mult: 1.0
 507      decay_mult: 1.0
 508    }
 509    param {
 510      lr_mult: 2.0
 511      decay_mult: 0.0
 512    }
 513    convolution_param {
 514      num_output: 512
 515      pad: 1
 516      kernel_size: 3
 517      group: 512
 518      engine: CAFFE
 519      weight_filler {
 520        type: "msra"
 521      }
 522      bias_filler {
 523        type: "constant"
 524        value: 0.0
 525      }
 526    }
 527  }
 528  layer {
 529    name: "conv8/dw/relu"
 530    type: "ReLU"
 531    bottom: "conv8/dw"
 532    top: "conv8/dw"
 533  }
 534  layer {
 535    name: "conv8"
 536    type: "Convolution"
 537    bottom: "conv8/dw"
 538    top: "conv8"
 539    param {
 540      lr_mult: 1.0
 541      decay_mult: 1.0
 542    }
 543    param {
 544      lr_mult: 2.0
 545      decay_mult: 0.0
 546    }
 547    convolution_param {
 548      num_output: 512
 549      kernel_size: 1
 550      weight_filler {
 551        type: "msra"
 552      }
 553      bias_filler {
 554        type: "constant"
 555        value: 0.0
 556      }
 557    }
 558  }
 559  layer {
 560    name: "conv8/relu"
 561    type: "ReLU"
 562    bottom: "conv8"
 563    top: "conv8"
 564  }
 565  layer {
 566    name: "conv9/dw"
 567    type: "Convolution"
 568    bottom: "conv8"
 569    top: "conv9/dw"
 570    param {
 571      lr_mult: 1.0
 572      decay_mult: 1.0
 573    }
 574    param {
 575      lr_mult: 2.0
 576      decay_mult: 0.0
 577    }
 578    convolution_param {
 579      num_output: 512
 580      pad: 1
 581      kernel_size: 3
 582      group: 512
 583      engine: CAFFE
 584      weight_filler {
 585        type: "msra"
 586      }
 587      bias_filler {
 588        type: "constant"
 589        value: 0.0
 590      }
 591    }
 592  }
 593  layer {
 594    name: "conv9/dw/relu"
 595    type: "ReLU"
 596    bottom: "conv9/dw"
 597    top: "conv9/dw"
 598  }
 599  layer {
 600    name: "conv9"
 601    type: "Convolution"
 602    bottom: "conv9/dw"
 603    top: "conv9"
 604    param {
 605      lr_mult: 1.0
 606      decay_mult: 1.0
 607    }
 608    param {
 609      lr_mult: 2.0
 610      decay_mult: 0.0
 611    }
 612    convolution_param {
 613      num_output: 512
 614      kernel_size: 1
 615      weight_filler {
 616        type: "msra"
 617      }
 618      bias_filler {
 619        type: "constant"
 620        value: 0.0
 621      }
 622    }
 623  }
 624  layer {
 625    name: "conv9/relu"
 626    type: "ReLU"
 627    bottom: "conv9"
 628    top: "conv9"
 629  }
 630  layer {
 631    name: "conv10/dw"
 632    type: "Convolution"
 633    bottom: "conv9"
 634    top: "conv10/dw"
 635    param {
 636      lr_mult: 1.0
 637      decay_mult: 1.0
 638    }
 639    param {
 640      lr_mult: 2.0
 641      decay_mult: 0.0
 642    }
 643    convolution_param {
 644      num_output: 512
 645      pad: 1
 646      kernel_size: 3
 647      group: 512
 648      engine: CAFFE
 649      weight_filler {
 650        type: "msra"
 651      }
 652      bias_filler {
 653        type: "constant"
 654        value: 0.0
 655      }
 656    }
 657  }
 658  layer {
 659    name: "conv10/dw/relu"
 660    type: "ReLU"
 661    bottom: "conv10/dw"
 662    top: "conv10/dw"
 663  }
 664  layer {
 665    name: "conv10"
 666    type: "Convolution"
 667    bottom: "conv10/dw"
 668    top: "conv10"
 669    param {
 670      lr_mult: 1.0
 671      decay_mult: 1.0
 672    }
 673    param {
 674      lr_mult: 2.0
 675      decay_mult: 0.0
 676    }
 677    convolution_param {
 678      num_output: 512
 679      kernel_size: 1
 680      weight_filler {
 681        type: "msra"
 682      }
 683      bias_filler {
 684        type: "constant"
 685        value: 0.0
 686      }
 687    }
 688  }
 689  layer {
 690    name: "conv10/relu"
 691    type: "ReLU"
 692    bottom: "conv10"
 693    top: "conv10"
 694  }
 695  layer {
 696    name: "conv11/dw"
 697    type: "Convolution"
 698    bottom: "conv10"
 699    top: "conv11/dw"
 700    param {
 701      lr_mult: 1.0
 702      decay_mult: 1.0
 703    }
 704    param {
 705      lr_mult: 2.0
 706      decay_mult: 0.0
 707    }
 708    convolution_param {
 709      num_output: 512
 710      pad: 1
 711      kernel_size: 3
 712      group: 512
 713      engine: CAFFE
 714      weight_filler {
 715        type: "msra"
 716      }
 717      bias_filler {
 718        type: "constant"
 719        value: 0.0
 720      }
 721    }
 722  }
 723  layer {
 724    name: "conv11/dw/relu"
 725    type: "ReLU"
 726    bottom: "conv11/dw"
 727    top: "conv11/dw"
 728  }
 729  layer {
 730    name: "conv11"
 731    type: "Convolution"
 732    bottom: "conv11/dw"
 733    top: "conv11"
 734    param {
 735      lr_mult: 1.0
 736      decay_mult: 1.0
 737    }
 738    param {
 739      lr_mult: 2.0
 740      decay_mult: 0.0
 741    }
 742    convolution_param {
 743      num_output: 512
 744      kernel_size: 1
 745      weight_filler {
 746        type: "msra"
 747      }
 748      bias_filler {
 749        type: "constant"
 750        value: 0.0
 751      }
 752    }
 753  }
 754  layer {
 755    name: "conv11/relu"
 756    type: "ReLU"
 757    bottom: "conv11"
 758    top: "conv11"
 759  }
 760  layer {
 761    name: "conv12/dw"
 762    type: "Convolution"
 763    bottom: "conv11"
 764    top: "conv12/dw"
 765    param {
 766      lr_mult: 1.0
 767      decay_mult: 1.0
 768    }
 769    param {
 770      lr_mult: 2.0
 771      decay_mult: 0.0
 772    }
 773    convolution_param {
 774      num_output: 512
 775      pad: 1
 776      kernel_size: 3
 777      stride: 2
 778      group: 512
 779      engine: CAFFE
 780      weight_filler {
 781        type: "msra"
 782      }
 783      bias_filler {
 784        type: "constant"
 785        value: 0.0
 786      }
 787    }
 788  }
 789  layer {
 790    name: "conv12/dw/relu"
 791    type: "ReLU"
 792    bottom: "conv12/dw"
 793    top: "conv12/dw"
 794  }
 795  layer {
 796    name: "conv12"
 797    type: "Convolution"
 798    bottom: "conv12/dw"
 799    top: "conv12"
 800    param {
 801      lr_mult: 1.0
 802      decay_mult: 1.0
 803    }
 804    param {
 805      lr_mult: 2.0
 806      decay_mult: 0.0
 807    }
 808    convolution_param {
 809      num_output: 1024
 810      kernel_size: 1
 811      weight_filler {
 812        type: "msra"
 813      }
 814      bias_filler {
 815        type: "constant"
 816        value: 0.0
 817      }
 818    }
 819  }
 820  layer {
 821    name: "conv12/relu"
 822    type: "ReLU"
 823    bottom: "conv12"
 824    top: "conv12"
 825  }
 826  layer {
 827    name: "conv13/dw"
 828    type: "Convolution"
 829    bottom: "conv12"
 830    top: "conv13/dw"
 831    param {
 832      lr_mult: 1.0
 833      decay_mult: 1.0
 834    }
 835    param {
 836      lr_mult: 2.0
 837      decay_mult: 0.0
 838    }
 839    convolution_param {
 840      num_output: 1024
 841      pad: 1
 842      kernel_size: 3
 843      group: 1024
 844      engine: CAFFE
 845      weight_filler {
 846        type: "msra"
 847      }
 848      bias_filler {
 849        type: "constant"
 850        value: 0.0
 851      }
 852    }
 853  }
 854  layer {
 855    name: "conv13/dw/relu"
 856    type: "ReLU"
 857    bottom: "conv13/dw"
 858    top: "conv13/dw"
 859  }
 860  layer {
 861    name: "conv13"
 862    type: "Convolution"
 863    bottom: "conv13/dw"
 864    top: "conv13"
 865    param {
 866      lr_mult: 1.0
 867      decay_mult: 1.0
 868    }
 869    param {
 870      lr_mult: 2.0
 871      decay_mult: 0.0
 872    }
 873    convolution_param {
 874      num_output: 1024
 875      kernel_size: 1
 876      weight_filler {
 877        type: "msra"
 878      }
 879      bias_filler {
 880        type: "constant"
 881        value: 0.0
 882      }
 883    }
 884  }
 885  layer {
 886    name: "conv13/relu"
 887    type: "ReLU"
 888    bottom: "conv13"
 889    top: "conv13"
 890  }
 891  layer {
 892    name: "conv14_1"
 893    type: "Convolution"
 894    bottom: "conv13"
 895    top: "conv14_1"
 896    param {
 897      lr_mult: 1.0
 898      decay_mult: 1.0
 899    }
 900    param {
 901      lr_mult: 2.0
 902      decay_mult: 0.0
 903    }
 904    convolution_param {
 905      num_output: 256
 906      kernel_size: 1
 907      weight_filler {
 908        type: "msra"
 909      }
 910      bias_filler {
 911        type: "constant"
 912        value: 0.0
 913      }
 914    }
 915  }
 916  layer {
 917    name: "conv14_1/relu"
 918    type: "ReLU"
 919    bottom: "conv14_1"
 920    top: "conv14_1"
 921  }
 922  layer {
 923    name: "conv14_2"
 924    type: "Convolution"
 925    bottom: "conv14_1"
 926    top: "conv14_2"
 927    param {
 928      lr_mult: 1.0
 929      decay_mult: 1.0
 930    }
 931    param {
 932      lr_mult: 2.0
 933      decay_mult: 0.0
 934    }
 935    convolution_param {
 936      num_output: 512
 937      pad: 1
 938      kernel_size: 3
 939      stride: 2
 940      weight_filler {
 941        type: "msra"
 942      }
 943      bias_filler {
 944        type: "constant"
 945        value: 0.0
 946      }
 947    }
 948  }
 949  layer {
 950    name: "conv14_2/relu"
 951    type: "ReLU"
 952    bottom: "conv14_2"
 953    top: "conv14_2"
 954  }
 955  layer {
 956    name: "conv15_1"
 957    type: "Convolution"
 958    bottom: "conv14_2"
 959    top: "conv15_1"
 960    param {
 961      lr_mult: 1.0
 962      decay_mult: 1.0
 963    }
 964    param {
 965      lr_mult: 2.0
 966      decay_mult: 0.0
 967    }
 968    convolution_param {
 969      num_output: 128
 970      kernel_size: 1
 971      weight_filler {
 972        type: "msra"
 973      }
 974      bias_filler {
 975        type: "constant"
 976        value: 0.0
 977      }
 978    }
 979  }
 980  layer {
 981    name: "conv15_1/relu"
 982    type: "ReLU"
 983    bottom: "conv15_1"
 984    top: "conv15_1"
 985  }
 986  layer {
 987    name: "conv15_2"
 988    type: "Convolution"
 989    bottom: "conv15_1"
 990    top: "conv15_2"
 991    param {
 992      lr_mult: 1.0
 993      decay_mult: 1.0
 994    }
 995    param {
 996      lr_mult: 2.0
 997      decay_mult: 0.0
 998    }
 999    convolution_param {
1000      num_output: 256
1001      pad: 1
1002      kernel_size: 3
1003      stride: 2
1004      weight_filler {
1005        type: "msra"
1006      }
1007      bias_filler {
1008        type: "constant"
1009        value: 0.0
1010      }
1011    }
1012  }
1013  layer {
1014    name: "conv15_2/relu"
1015    type: "ReLU"
1016    bottom: "conv15_2"
1017    top: "conv15_2"
1018  }
1019  layer {
1020    name: "conv16_1"
1021    type: "Convolution"
1022    bottom: "conv15_2"
1023    top: "conv16_1"
1024    param {
1025      lr_mult: 1.0
1026      decay_mult: 1.0
1027    }
1028    param {
1029      lr_mult: 2.0
1030      decay_mult: 0.0
1031    }
1032    convolution_param {
1033      num_output: 128
1034      kernel_size: 1
1035      weight_filler {
1036        type: "msra"
1037      }
1038      bias_filler {
1039        type: "constant"
1040        value: 0.0
1041      }
1042    }
1043  }
1044  layer {
1045    name: "conv16_1/relu"
1046    type: "ReLU"
1047    bottom: "conv16_1"
1048    top: "conv16_1"
1049  }
1050  layer {
1051    name: "conv16_2"
1052    type: "Convolution"
1053    bottom: "conv16_1"
1054    top: "conv16_2"
1055    param {
1056      lr_mult: 1.0
1057      decay_mult: 1.0
1058    }
1059    param {
1060      lr_mult: 2.0
1061      decay_mult: 0.0
1062    }
1063    convolution_param {
1064      num_output: 256
1065      pad: 1
1066      kernel_size: 3
1067      stride: 2
1068      weight_filler {
1069        type: "msra"
1070      }
1071      bias_filler {
1072        type: "constant"
1073        value: 0.0
1074      }
1075    }
1076  }
1077  layer {
1078    name: "conv16_2/relu"
1079    type: "ReLU"
1080    bottom: "conv16_2"
1081    top: "conv16_2"
1082  }
1083  layer {
1084    name: "conv17_1"
1085    type: "Convolution"
1086    bottom: "conv16_2"
1087    top: "conv17_1"
1088    param {
1089      lr_mult: 1.0
1090      decay_mult: 1.0
1091    }
1092    param {
1093      lr_mult: 2.0
1094      decay_mult: 0.0
1095    }
1096    convolution_param {
1097      num_output: 64
1098      kernel_size: 1
1099      weight_filler {
1100        type: "msra"
1101      }
1102      bias_filler {
1103        type: "constant"
1104        value: 0.0
1105      }
1106    }
1107  }
1108  layer {
1109    name: "conv17_1/relu"
1110    type: "ReLU"
1111    bottom: "conv17_1"
1112    top: "conv17_1"
1113  }
1114  layer {
1115    name: "conv17_2"
1116    type: "Convolution"
1117    bottom: "conv17_1"
1118    top: "conv17_2"
1119    param {
1120      lr_mult: 1.0
1121      decay_mult: 1.0
1122    }
1123    param {
1124      lr_mult: 2.0
1125      decay_mult: 0.0
1126    }
1127    convolution_param {
1128      num_output: 128
1129      pad: 1
1130      kernel_size: 3
1131      stride: 2
1132      weight_filler {
1133        type: "msra"
1134      }
1135      bias_filler {
1136        type: "constant"
1137        value: 0.0
1138      }
1139    }
1140  }
1141  layer {
1142    name: "conv17_2/relu"
1143    type: "ReLU"
1144    bottom: "conv17_2"
1145    top: "conv17_2"
1146  }
1147  layer {
1148    name: "conv11_mbox_loc"
1149    type: "Convolution"
1150    bottom: "conv11"
1151    top: "conv11_mbox_loc"
1152    param {
1153      lr_mult: 1.0
1154      decay_mult: 1.0
1155    }
1156    param {
1157      lr_mult: 2.0
1158      decay_mult: 0.0
1159    }
1160    convolution_param {
1161      num_output: 12
1162      kernel_size: 1
1163      weight_filler {
1164        type: "msra"
1165      }
1166      bias_filler {
1167        type: "constant"
1168        value: 0.0
1169      }
1170    }
1171  }
1172  layer {
1173    name: "conv11_mbox_loc_perm"
1174    type: "Permute"
1175    bottom: "conv11_mbox_loc"
1176    top: "conv11_mbox_loc_perm"
1177    permute_param {
1178      order: 0
1179      order: 2
1180      order: 3
1181      order: 1
1182    }
1183  }
1184  layer {
1185    name: "conv11_mbox_loc_flat"
1186    type: "Flatten"
1187    bottom: "conv11_mbox_loc_perm"
1188    top: "conv11_mbox_loc_flat"
1189    flatten_param {
1190      axis: 1
1191    }
1192  }
1193  layer {
1194    name: "conv11_mbox_conf"
1195    type: "Convolution"
1196    bottom: "conv11"
1197    top: "conv11_mbox_conf"
1198    param {
1199      lr_mult: 1.0
1200      decay_mult: 1.0
1201    }
1202    param {
1203      lr_mult: 2.0
1204      decay_mult: 0.0
1205    }
1206    convolution_param {
1207      num_output: 63
1208      kernel_size: 1
1209      weight_filler {
1210        type: "msra"
1211      }
1212      bias_filler {
1213        type: "constant"
1214        value: 0.0
1215      }
1216    }
1217  }
1218  layer {
1219    name: "conv11_mbox_conf_perm"
1220    type: "Permute"
1221    bottom: "conv11_mbox_conf"
1222    top: "conv11_mbox_conf_perm"
1223    permute_param {
1224      order: 0
1225      order: 2
1226      order: 3
1227      order: 1
1228    }
1229  }
1230  layer {
1231    name: "conv11_mbox_conf_flat"
1232    type: "Flatten"
1233    bottom: "conv11_mbox_conf_perm"
1234    top: "conv11_mbox_conf_flat"
1235    flatten_param {
1236      axis: 1
1237    }
1238  }
1239  layer {
1240    name: "conv11_mbox_priorbox"
1241    type: "PriorBox"
1242    bottom: "conv11"
1243    bottom: "data"
1244    top: "conv11_mbox_priorbox"
1245    prior_box_param {
1246      min_size: 60.0
1247      aspect_ratio: 2.0
1248      flip: true
1249      clip: false
1250      variance: 0.1
1251      variance: 0.1
1252      variance: 0.2
1253      variance: 0.2
1254      offset: 0.5
1255    }
1256  }
1257  layer {
1258    name: "conv13_mbox_loc"
1259    type: "Convolution"
1260    bottom: "conv13"
1261    top: "conv13_mbox_loc"
1262    param {
1263      lr_mult: 1.0
1264      decay_mult: 1.0
1265    }
1266    param {
1267      lr_mult: 2.0
1268      decay_mult: 0.0
1269    }
1270    convolution_param {
1271      num_output: 24
1272      kernel_size: 1
1273      weight_filler {
1274        type: "msra"
1275      }
1276      bias_filler {
1277        type: "constant"
1278        value: 0.0
1279      }
1280    }
1281  }
1282  layer {
1283    name: "conv13_mbox_loc_perm"
1284    type: "Permute"
1285    bottom: "conv13_mbox_loc"
1286    top: "conv13_mbox_loc_perm"
1287    permute_param {
1288      order: 0
1289      order: 2
1290      order: 3
1291      order: 1
1292    }
1293  }
1294  layer {
1295    name: "conv13_mbox_loc_flat"
1296    type: "Flatten"
1297    bottom: "conv13_mbox_loc_perm"
1298    top: "conv13_mbox_loc_flat"
1299    flatten_param {
1300      axis: 1
1301    }
1302  }
1303  layer {
1304    name: "conv13_mbox_conf"
1305    type: "Convolution"
1306    bottom: "conv13"
1307    top: "conv13_mbox_conf"
1308    param {
1309      lr_mult: 1.0
1310      decay_mult: 1.0
1311    }
1312    param {
1313      lr_mult: 2.0
1314      decay_mult: 0.0
1315    }
1316    convolution_param {
1317      num_output: 126
1318      kernel_size: 1
1319      weight_filler {
1320        type: "msra"
1321      }
1322      bias_filler {
1323        type: "constant"
1324        value: 0.0
1325      }
1326    }
1327  }
1328  layer {
1329    name: "conv13_mbox_conf_perm"
1330    type: "Permute"
1331    bottom: "conv13_mbox_conf"
1332    top: "conv13_mbox_conf_perm"
1333    permute_param {
1334      order: 0
1335      order: 2
1336      order: 3
1337      order: 1
1338    }
1339  }
1340  layer {
1341    name: "conv13_mbox_conf_flat"
1342    type: "Flatten"
1343    bottom: "conv13_mbox_conf_perm"
1344    top: "conv13_mbox_conf_flat"
1345    flatten_param {
1346      axis: 1
1347    }
1348  }
1349  layer {
1350    name: "conv13_mbox_priorbox"
1351    type: "PriorBox"
1352    bottom: "conv13"
1353    bottom: "data"
1354    top: "conv13_mbox_priorbox"
1355    prior_box_param {
1356      min_size: 105.0
1357      max_size: 150.0
1358      aspect_ratio: 2.0
1359      aspect_ratio: 3.0
1360      flip: true
1361      clip: false
1362      variance: 0.1
1363      variance: 0.1
1364      variance: 0.2
1365      variance: 0.2
1366      offset: 0.5
1367    }
1368  }
1369  layer {
1370    name: "conv14_2_mbox_loc"
1371    type: "Convolution"
1372    bottom: "conv14_2"
1373    top: "conv14_2_mbox_loc"
1374    param {
1375      lr_mult: 1.0
1376      decay_mult: 1.0
1377    }
1378    param {
1379      lr_mult: 2.0
1380      decay_mult: 0.0
1381    }
1382    convolution_param {
1383      num_output: 24
1384      kernel_size: 1
1385      weight_filler {
1386        type: "msra"
1387      }
1388      bias_filler {
1389        type: "constant"
1390        value: 0.0
1391      }
1392    }
1393  }
1394  layer {
1395    name: "conv14_2_mbox_loc_perm"
1396    type: "Permute"
1397    bottom: "conv14_2_mbox_loc"
1398    top: "conv14_2_mbox_loc_perm"
1399    permute_param {
1400      order: 0
1401      order: 2
1402      order: 3
1403      order: 1
1404    }
1405  }
1406  layer {
1407    name: "conv14_2_mbox_loc_flat"
1408    type: "Flatten"
1409    bottom: "conv14_2_mbox_loc_perm"
1410    top: "conv14_2_mbox_loc_flat"
1411    flatten_param {
1412      axis: 1
1413    }
1414  }
1415  layer {
1416    name: "conv14_2_mbox_conf"
1417    type: "Convolution"
1418    bottom: "conv14_2"
1419    top: "conv14_2_mbox_conf"
1420    param {
1421      lr_mult: 1.0
1422      decay_mult: 1.0
1423    }
1424    param {
1425      lr_mult: 2.0
1426      decay_mult: 0.0
1427    }
1428    convolution_param {
1429      num_output: 126
1430      kernel_size: 1
1431      weight_filler {
1432        type: "msra"
1433      }
1434      bias_filler {
1435        type: "constant"
1436        value: 0.0
1437      }
1438    }
1439  }
1440  layer {
1441    name: "conv14_2_mbox_conf_perm"
1442    type: "Permute"
1443    bottom: "conv14_2_mbox_conf"
1444    top: "conv14_2_mbox_conf_perm"
1445    permute_param {
1446      order: 0
1447      order: 2
1448      order: 3
1449      order: 1
1450    }
1451  }
1452  layer {
1453    name: "conv14_2_mbox_conf_flat"
1454    type: "Flatten"
1455    bottom: "conv14_2_mbox_conf_perm"
1456    top: "conv14_2_mbox_conf_flat"
1457    flatten_param {
1458      axis: 1
1459    }
1460  }
1461  layer {
1462    name: "conv14_2_mbox_priorbox"
1463    type: "PriorBox"
1464    bottom: "conv14_2"
1465    bottom: "data"
1466    top: "conv14_2_mbox_priorbox"
1467    prior_box_param {
1468      min_size: 150.0
1469      max_size: 195.0
1470      aspect_ratio: 2.0
1471      aspect_ratio: 3.0
1472      flip: true
1473      clip: false
1474      variance: 0.1
1475      variance: 0.1
1476      variance: 0.2
1477      variance: 0.2
1478      offset: 0.5
1479    }
1480  }
1481  layer {
1482    name: "conv15_2_mbox_loc"
1483    type: "Convolution"
1484    bottom: "conv15_2"
1485    top: "conv15_2_mbox_loc"
1486    param {
1487      lr_mult: 1.0
1488      decay_mult: 1.0
1489    }
1490    param {
1491      lr_mult: 2.0
1492      decay_mult: 0.0
1493    }
1494    convolution_param {
1495      num_output: 24
1496      kernel_size: 1
1497      weight_filler {
1498        type: "msra"
1499      }
1500      bias_filler {
1501        type: "constant"
1502        value: 0.0
1503      }
1504    }
1505  }
1506  layer {
1507    name: "conv15_2_mbox_loc_perm"
1508    type: "Permute"
1509    bottom: "conv15_2_mbox_loc"
1510    top: "conv15_2_mbox_loc_perm"
1511    permute_param {
1512      order: 0
1513      order: 2
1514      order: 3
1515      order: 1
1516    }
1517  }
1518  layer {
1519    name: "conv15_2_mbox_loc_flat"
1520    type: "Flatten"
1521    bottom: "conv15_2_mbox_loc_perm"
1522    top: "conv15_2_mbox_loc_flat"
1523    flatten_param {
1524      axis: 1
1525    }
1526  }
1527  layer {
1528    name: "conv15_2_mbox_conf"
1529    type: "Convolution"
1530    bottom: "conv15_2"
1531    top: "conv15_2_mbox_conf"
1532    param {
1533      lr_mult: 1.0
1534      decay_mult: 1.0
1535    }
1536    param {
1537      lr_mult: 2.0
1538      decay_mult: 0.0
1539    }
1540    convolution_param {
1541      num_output: 126
1542      kernel_size: 1
1543      weight_filler {
1544        type: "msra"
1545      }
1546      bias_filler {
1547        type: "constant"
1548        value: 0.0
1549      }
1550    }
1551  }
1552  layer {
1553    name: "conv15_2_mbox_conf_perm"
1554    type: "Permute"
1555    bottom: "conv15_2_mbox_conf"
1556    top: "conv15_2_mbox_conf_perm"
1557    permute_param {
1558      order: 0
1559      order: 2
1560      order: 3
1561      order: 1
1562    }
1563  }
1564  layer {
1565    name: "conv15_2_mbox_conf_flat"
1566    type: "Flatten"
1567    bottom: "conv15_2_mbox_conf_perm"
1568    top: "conv15_2_mbox_conf_flat"
1569    flatten_param {
1570      axis: 1
1571    }
1572  }
1573  layer {
1574    name: "conv15_2_mbox_priorbox"
1575    type: "PriorBox"
1576    bottom: "conv15_2"
1577    bottom: "data"
1578    top: "conv15_2_mbox_priorbox"
1579    prior_box_param {
1580      min_size: 195.0
1581      max_size: 240.0
1582      aspect_ratio: 2.0
1583      aspect_ratio: 3.0
1584      flip: true
1585      clip: false
1586      variance: 0.1
1587      variance: 0.1
1588      variance: 0.2
1589      variance: 0.2
1590      offset: 0.5
1591    }
1592  }
1593  layer {
1594    name: "conv16_2_mbox_loc"
1595    type: "Convolution"
1596    bottom: "conv16_2"
1597    top: "conv16_2_mbox_loc"
1598    param {
1599      lr_mult: 1.0
1600      decay_mult: 1.0
1601    }
1602    param {
1603      lr_mult: 2.0
1604      decay_mult: 0.0
1605    }
1606    convolution_param {
1607      num_output: 24
1608      kernel_size: 1
1609      weight_filler {
1610        type: "msra"
1611      }
1612      bias_filler {
1613        type: "constant"
1614        value: 0.0
1615      }
1616    }
1617  }
1618  layer {
1619    name: "conv16_2_mbox_loc_perm"
1620    type: "Permute"
1621    bottom: "conv16_2_mbox_loc"
1622    top: "conv16_2_mbox_loc_perm"
1623    permute_param {
1624      order: 0
1625      order: 2
1626      order: 3
1627      order: 1
1628    }
1629  }
1630  layer {
1631    name: "conv16_2_mbox_loc_flat"
1632    type: "Flatten"
1633    bottom: "conv16_2_mbox_loc_perm"
1634    top: "conv16_2_mbox_loc_flat"
1635    flatten_param {
1636      axis: 1
1637    }
1638  }
1639  layer {
1640    name: "conv16_2_mbox_conf"
1641    type: "Convolution"
1642    bottom: "conv16_2"
1643    top: "conv16_2_mbox_conf"
1644    param {
1645      lr_mult: 1.0
1646      decay_mult: 1.0
1647    }
1648    param {
1649      lr_mult: 2.0
1650      decay_mult: 0.0
1651    }
1652    convolution_param {
1653      num_output: 126
1654      kernel_size: 1
1655      weight_filler {
1656        type: "msra"
1657      }
1658      bias_filler {
1659        type: "constant"
1660        value: 0.0
1661      }
1662    }
1663  }
1664  layer {
1665    name: "conv16_2_mbox_conf_perm"
1666    type: "Permute"
1667    bottom: "conv16_2_mbox_conf"
1668    top: "conv16_2_mbox_conf_perm"
1669    permute_param {
1670      order: 0
1671      order: 2
1672      order: 3
1673      order: 1
1674    }
1675  }
1676  layer {
1677    name: "conv16_2_mbox_conf_flat"
1678    type: "Flatten"
1679    bottom: "conv16_2_mbox_conf_perm"
1680    top: "conv16_2_mbox_conf_flat"
1681    flatten_param {
1682      axis: 1
1683    }
1684  }
1685  layer {
1686    name: "conv16_2_mbox_priorbox"
1687    type: "PriorBox"
1688    bottom: "conv16_2"
1689    bottom: "data"
1690    top: "conv16_2_mbox_priorbox"
1691    prior_box_param {
1692      min_size: 240.0
1693      max_size: 285.0
1694      aspect_ratio: 2.0
1695      aspect_ratio: 3.0
1696      flip: true
1697      clip: false
1698      variance: 0.1
1699      variance: 0.1
1700      variance: 0.2
1701      variance: 0.2
1702      offset: 0.5
1703    }
1704  }
1705  layer {
1706    name: "conv17_2_mbox_loc"
1707    type: "Convolution"
1708    bottom: "conv17_2"
1709    top: "conv17_2_mbox_loc"
1710    param {
1711      lr_mult: 1.0
1712      decay_mult: 1.0
1713    }
1714    param {
1715      lr_mult: 2.0
1716      decay_mult: 0.0
1717    }
1718    convolution_param {
1719      num_output: 24
1720      kernel_size: 1
1721      weight_filler {
1722        type: "msra"
1723      }
1724      bias_filler {
1725        type: "constant"
1726        value: 0.0
1727      }
1728    }
1729  }
1730  layer {
1731    name: "conv17_2_mbox_loc_perm"
1732    type: "Permute"
1733    bottom: "conv17_2_mbox_loc"
1734    top: "conv17_2_mbox_loc_perm"
1735    permute_param {
1736      order: 0
1737      order: 2
1738      order: 3
1739      order: 1
1740    }
1741  }
1742  layer {
1743    name: "conv17_2_mbox_loc_flat"
1744    type: "Flatten"
1745    bottom: "conv17_2_mbox_loc_perm"
1746    top: "conv17_2_mbox_loc_flat"
1747    flatten_param {
1748      axis: 1
1749    }
1750  }
1751  layer {
1752    name: "conv17_2_mbox_conf"
1753    type: "Convolution"
1754    bottom: "conv17_2"
1755    top: "conv17_2_mbox_conf"
1756    param {
1757      lr_mult: 1.0
1758      decay_mult: 1.0
1759    }
1760    param {
1761      lr_mult: 2.0
1762      decay_mult: 0.0
1763    }
1764    convolution_param {
1765      num_output: 126
1766      kernel_size: 1
1767      weight_filler {
1768        type: "msra"
1769      }
1770      bias_filler {
1771        type: "constant"
1772        value: 0.0
1773      }
1774    }
1775  }
1776  layer {
1777    name: "conv17_2_mbox_conf_perm"
1778    type: "Permute"
1779    bottom: "conv17_2_mbox_conf"
1780    top: "conv17_2_mbox_conf_perm"
1781    permute_param {
1782      order: 0
1783      order: 2
1784      order: 3
1785      order: 1
1786    }
1787  }
1788  layer {
1789    name: "conv17_2_mbox_conf_flat"
1790    type: "Flatten"
1791    bottom: "conv17_2_mbox_conf_perm"
1792    top: "conv17_2_mbox_conf_flat"
1793    flatten_param {
1794      axis: 1
1795    }
1796  }
1797  layer {
1798    name: "conv17_2_mbox_priorbox"
1799    type: "PriorBox"
1800    bottom: "conv17_2"
1801    bottom: "data"
1802    top: "conv17_2_mbox_priorbox"
1803    prior_box_param {
1804      min_size: 285.0
1805      max_size: 300.0
1806      aspect_ratio: 2.0
1807      aspect_ratio: 3.0
1808      flip: true
1809      clip: false
1810      variance: 0.1
1811      variance: 0.1
1812      variance: 0.2
1813      variance: 0.2
1814      offset: 0.5
1815    }
1816  }
1817  layer {
1818    name: "mbox_loc"
1819    type: "Concat"
1820    bottom: "conv11_mbox_loc_flat"
1821    bottom: "conv13_mbox_loc_flat"
1822    bottom: "conv14_2_mbox_loc_flat"
1823    bottom: "conv15_2_mbox_loc_flat"
1824    bottom: "conv16_2_mbox_loc_flat"
1825    bottom: "conv17_2_mbox_loc_flat"
1826    top: "mbox_loc"
1827    concat_param {
1828      axis: 1
1829    }
1830  }
1831  layer {
1832    name: "mbox_conf"
1833    type: "Concat"
1834    bottom: "conv11_mbox_conf_flat"
1835    bottom: "conv13_mbox_conf_flat"
1836    bottom: "conv14_2_mbox_conf_flat"
1837    bottom: "conv15_2_mbox_conf_flat"
1838    bottom: "conv16_2_mbox_conf_flat"
1839    bottom: "conv17_2_mbox_conf_flat"
1840    top: "mbox_conf"
1841    concat_param {
1842      axis: 1
1843    }
1844  }
1845  layer {
1846    name: "mbox_priorbox"
1847    type: "Concat"
1848    bottom: "conv11_mbox_priorbox"
1849    bottom: "conv13_mbox_priorbox"
1850    bottom: "conv14_2_mbox_priorbox"
1851    bottom: "conv15_2_mbox_priorbox"
1852    bottom: "conv16_2_mbox_priorbox"
1853    bottom: "conv17_2_mbox_priorbox"
1854    top: "mbox_priorbox"
1855    concat_param {
1856      axis: 2
1857    }
1858  }
1859  layer {
1860    name: "mbox_conf_reshape"
1861    type: "Reshape"
1862    bottom: "mbox_conf"
1863    top: "mbox_conf_reshape"
1864    reshape_param {
1865      shape {
1866        dim: 0
1867        dim: -1
1868        dim: 21
1869      }
1870    }
1871  }
1872  layer {
1873    name: "mbox_conf_softmax"
1874    type: "Softmax"
1875    bottom: "mbox_conf_reshape"
1876    top: "mbox_conf_softmax"
1877    softmax_param {
1878      axis: 2
1879    }
1880  }
1881  layer {
1882    name: "mbox_conf_flatten"
1883    type: "Flatten"
1884    bottom: "mbox_conf_softmax"
1885    top: "mbox_conf_flatten"
1886    flatten_param {
1887      axis: 1
1888    }
1889  }
1890  layer {
1891    name: "detection_out"
1892    type: "DetectionOutput"
1893    bottom: "mbox_loc"
1894    bottom: "mbox_conf_flatten"
1895    bottom: "mbox_priorbox"
1896    top: "detection_out"
1897    include {
1898      phase: TEST
1899    }
1900    detection_output_param {
1901      num_classes: 21
1902      share_location: true
1903      background_label_id: 0
1904      nms_param {
1905        nms_threshold: 0.45
1906        top_k: 100
1907      }
1908      code_type: CENTER_SIZE
1909      keep_top_k: 100
1910      confidence_threshold: 0.25
1911    }
1912  }
1913