daily pastebin goal
59%
SHARE
TWEET

Untitled

a guest Feb 13th, 2018 65 Never
Not a member of Pastebin yet? Sign Up, it unlocks many cool features!
  1. name: "net"
  2.  
  3. # input: "data"
  4. #input_dim: 1
  5. #input_dim: 3
  6. #input_dim: 1024
  7. #input_dim: 2048
  8. #
  9.  
  10. #layer {
  11. #  name: "data"
  12. #  type: "ImageData"
  13. #  top: "data"
  14. #  include {
  15. #    phase: TEST
  16. #  }
  17. #  image_data_param {
  18. #    source: "Daimler2048x1024/images/listing.txt"
  19. #    batch_size: 1
  20. #    new_height: 1024
  21. #    new_width: 2048
  22. #  }
  23. #}
  24.  
  25. layer {
  26.   name: "data"
  27.   type: "Input"
  28.   top: "data"
  29.   input_param { shape: { dim: 1 dim: 3 dim: 512 dim: 1024 } }
  30. }
  31.  
  32. #layer {
  33. #  type: 'DummyData'
  34. #  name: 'dummy_data'
  35. #  top: 'dummy_data'
  36. #  dummy_data_param {
  37. #    num: 1
  38. #       channels: 3
  39. #       height: 1024
  40. #       width: 2048
  41. #    data_filler { type: 'gaussian' std: 0.1 }
  42. #  }
  43. #}
  44.  
  45.  
  46. layer {
  47.   name: "conv1/7x7_s2"
  48.   type: "Convolution"
  49.   bottom: "data"
  50.   top: "conv1/7x7_s2"
  51.   convolution_param {
  52.     num_output: 64
  53.     pad: 3
  54.     kernel_size: 7
  55.     stride: 2
  56.   }
  57. }
  58. layer {
  59.   name: "conv1/relu_7x7"
  60.   type: "ReLU"
  61.   bottom: "conv1/7x7_s2"
  62.   top: "conv1/7x7_s2"
  63. }
  64. layer {
  65.   name: "pool1/3x3_s2"
  66.   type: "Pooling"
  67.   bottom: "conv1/7x7_s2"
  68.   top: "pool1/3x3_s2"
  69.   pooling_param {
  70.     pool: MAX
  71.     kernel_size: 3
  72.     stride: 2
  73.   }
  74. }
  75. layer {
  76.   name: "pool1/norm1"
  77.   type: "LRN"
  78.   bottom: "pool1/3x3_s2"
  79.   top: "pool1/norm1"
  80.   lrn_param {
  81.     local_size: 5
  82.     alpha: 0.0001
  83.     beta: 0.75
  84.   }
  85. }
  86. layer {
  87.   name: "conv2/3x3_reduce"
  88.   type: "Convolution"
  89.   bottom: "pool1/norm1"
  90.   top: "conv2/3x3_reduce"
  91.   convolution_param {
  92.     num_output: 64
  93.     kernel_size: 1
  94.   }
  95. }
  96. layer {
  97.   name: "conv2/relu_3x3_reduce"
  98.   type: "ReLU"
  99.   bottom: "conv2/3x3_reduce"
  100.   top: "conv2/3x3_reduce"
  101. }
  102. layer {
  103.   name: "conv2/3x3"
  104.   type: "Convolution"
  105.   bottom: "conv2/3x3_reduce"
  106.   top: "conv2/3x3"
  107.   convolution_param {
  108.     num_output: 192
  109.     pad: 1
  110.     kernel_size: 3
  111.   }
  112. }
  113. layer {
  114.   name: "conv2/relu_3x3"
  115.   type: "ReLU"
  116.   bottom: "conv2/3x3"
  117.   top: "conv2/3x3"
  118. }
  119. layer {
  120.   name: "conv2/norm2"
  121.   type: "LRN"
  122.   bottom: "conv2/3x3"
  123.   top: "conv2/norm2"
  124.   lrn_param {
  125.     local_size: 5
  126.     alpha: 0.0001
  127.     beta: 0.75
  128.   }
  129. }
  130. layer {
  131.   name: "pool2/3x3_s2"
  132.   type: "Pooling"
  133.   bottom: "conv2/norm2"
  134.   top: "pool2/3x3_s2"
  135.   pooling_param {
  136.     pool: MAX
  137.     kernel_size: 3
  138.     stride: 2
  139.   }
  140. }
  141. layer {
  142.   name: "inception_3a/1x1"
  143.   type: "Convolution"
  144.   bottom: "pool2/3x3_s2"
  145.   top: "inception_3a/1x1"
  146.   convolution_param {
  147.     num_output: 64
  148.     kernel_size: 1
  149.   }
  150. }
  151. layer {
  152.   name: "inception_3a/relu_1x1"
  153.   type: "ReLU"
  154.   bottom: "inception_3a/1x1"
  155.   top: "inception_3a/1x1"
  156. }
  157. layer {
  158.   name: "inception_3a/3x3_reduce"
  159.   type: "Convolution"
  160.   bottom: "pool2/3x3_s2"
  161.   top: "inception_3a/3x3_reduce"
  162.   convolution_param {
  163.     num_output: 96
  164.     kernel_size: 1
  165.   }
  166. }
  167. layer {
  168.   name: "inception_3a/relu_3x3_reduce"
  169.   type: "ReLU"
  170.   bottom: "inception_3a/3x3_reduce"
  171.   top: "inception_3a/3x3_reduce"
  172. }
  173. layer {
  174.   name: "inception_3a/3x3"
  175.   type: "Convolution"
  176.   bottom: "inception_3a/3x3_reduce"
  177.   top: "inception_3a/3x3"
  178.   convolution_param {
  179.     num_output: 128
  180.     pad: 1
  181.     kernel_size: 3
  182.   }
  183. }
  184. layer {
  185.   name: "inception_3a/relu_3x3"
  186.   type: "ReLU"
  187.   bottom: "inception_3a/3x3"
  188.   top: "inception_3a/3x3"
  189. }
  190. layer {
  191.   name: "inception_3a/5x5_reduce"
  192.   type: "Convolution"
  193.   bottom: "pool2/3x3_s2"
  194.   top: "inception_3a/5x5_reduce"
  195.   convolution_param {
  196.     num_output: 16
  197.     kernel_size: 1
  198.   }
  199. }
  200. layer {
  201.   name: "inception_3a/relu_5x5_reduce"
  202.   type: "ReLU"
  203.   bottom: "inception_3a/5x5_reduce"
  204.   top: "inception_3a/5x5_reduce"
  205. }
  206. layer {
  207.   name: "inception_3a/5x5"
  208.   type: "Convolution"
  209.   bottom: "inception_3a/5x5_reduce"
  210.   top: "inception_3a/5x5"
  211.   convolution_param {
  212.     num_output: 32
  213.     pad: 2
  214.     kernel_size: 5
  215.   }
  216. }
  217. layer {
  218.   name: "inception_3a/relu_5x5"
  219.   type: "ReLU"
  220.   bottom: "inception_3a/5x5"
  221.   top: "inception_3a/5x5"
  222. }
  223. layer {
  224.   name: "inception_3a/pool"
  225.   type: "Pooling"
  226.   bottom: "pool2/3x3_s2"
  227.   top: "inception_3a/pool"
  228.   pooling_param {
  229.     pool: MAX
  230.     kernel_size: 3
  231.     stride: 1
  232.     pad: 1
  233.   }
  234. }
  235. layer {
  236.   name: "inception_3a/pool_proj"
  237.   type: "Convolution"
  238.   bottom: "inception_3a/pool"
  239.   top: "inception_3a/pool_proj"
  240.   convolution_param {
  241.     num_output: 32
  242.     kernel_size: 1
  243.   }
  244. }
  245. layer {
  246.   name: "inception_3a/relu_pool_proj"
  247.   type: "ReLU"
  248.   bottom: "inception_3a/pool_proj"
  249.   top: "inception_3a/pool_proj"
  250. }
  251. layer {
  252.   name: "inception_3a/output"
  253.   type: "Concat"
  254.   bottom: "inception_3a/1x1"
  255.   bottom: "inception_3a/3x3"
  256.   bottom: "inception_3a/5x5"
  257.   bottom: "inception_3a/pool_proj"
  258.   top: "inception_3a/output"
  259. }
  260. layer {
  261.   name: "inception_3b/1x1"
  262.   type: "Convolution"
  263.   bottom: "inception_3a/output"
  264.   top: "inception_3b/1x1"
  265.   convolution_param {
  266.     num_output: 128
  267.     kernel_size: 1
  268.   }
  269. }
  270. layer {
  271.   name: "inception_3b/relu_1x1"
  272.   type: "ReLU"
  273.   bottom: "inception_3b/1x1"
  274.   top: "inception_3b/1x1"
  275. }
  276. layer {
  277.   name: "inception_3b/3x3_reduce"
  278.   type: "Convolution"
  279.   bottom: "inception_3a/output"
  280.   top: "inception_3b/3x3_reduce"
  281.   convolution_param {
  282.     num_output: 128
  283.     kernel_size: 1
  284.   }
  285. }
  286. layer {
  287.   name: "inception_3b/relu_3x3_reduce"
  288.   type: "ReLU"
  289.   bottom: "inception_3b/3x3_reduce"
  290.   top: "inception_3b/3x3_reduce"
  291. }
  292. layer {
  293.   name: "inception_3b/3x3"
  294.   type: "Convolution"
  295.   bottom: "inception_3b/3x3_reduce"
  296.   top: "inception_3b/3x3"
  297.   convolution_param {
  298.     num_output: 192
  299.     pad: 1
  300.     kernel_size: 3
  301.   }
  302. }
  303. layer {
  304.   name: "inception_3b/relu_3x3"
  305.   type: "ReLU"
  306.   bottom: "inception_3b/3x3"
  307.   top: "inception_3b/3x3"
  308. }
  309. layer {
  310.   name: "inception_3b/5x5_reduce"
  311.   type: "Convolution"
  312.   bottom: "inception_3a/output"
  313.   top: "inception_3b/5x5_reduce"
  314.   convolution_param {
  315.     num_output: 32
  316.     kernel_size: 1
  317.   }
  318. }
  319. layer {
  320.   name: "inception_3b/relu_5x5_reduce"
  321.   type: "ReLU"
  322.   bottom: "inception_3b/5x5_reduce"
  323.   top: "inception_3b/5x5_reduce"
  324. }
  325. layer {
  326.   name: "inception_3b/5x5"
  327.   type: "Convolution"
  328.   bottom: "inception_3b/5x5_reduce"
  329.   top: "inception_3b/5x5"
  330.   convolution_param {
  331.     num_output: 96
  332.     pad: 2
  333.     kernel_size: 5
  334.   }
  335. }
  336. layer {
  337.   name: "inception_3b/relu_5x5"
  338.   type: "ReLU"
  339.   bottom: "inception_3b/5x5"
  340.   top: "inception_3b/5x5"
  341. }
  342. layer {
  343.   name: "inception_3b/pool"
  344.   type: "Pooling"
  345.   bottom: "inception_3a/output"
  346.   top: "inception_3b/pool"
  347.   pooling_param {
  348.     pool: MAX
  349.     kernel_size: 3
  350.     stride: 1
  351.     pad: 1
  352.   }
  353. }
  354. layer {
  355.   name: "inception_3b/pool_proj"
  356.   type: "Convolution"
  357.   bottom: "inception_3b/pool"
  358.   top: "inception_3b/pool_proj"
  359.   convolution_param {
  360.     num_output: 64
  361.     kernel_size: 1
  362.   }
  363. }
  364. layer {
  365.   name: "inception_3b/relu_pool_proj"
  366.   type: "ReLU"
  367.   bottom: "inception_3b/pool_proj"
  368.   top: "inception_3b/pool_proj"
  369. }
  370. layer {
  371.   name: "inception_3b/output"
  372.   type: "Concat"
  373.   bottom: "inception_3b/1x1"
  374.   bottom: "inception_3b/3x3"
  375.   bottom: "inception_3b/5x5"
  376.   bottom: "inception_3b/pool_proj"
  377.   top: "inception_3b/output"
  378. }
  379. layer {
  380.   name: "pool3/3x3_s2"
  381.   type: "Pooling"
  382.   bottom: "inception_3b/output"
  383.   top: "pool3/3x3_s2"
  384.   pooling_param {
  385.     pool: MAX
  386.     kernel_size: 3
  387.     stride: 2
  388.   }
  389. }
  390. layer {
  391.   name: "inception_4a/1x1"
  392.   type: "Convolution"
  393.   bottom: "pool3/3x3_s2"
  394.   top: "inception_4a/1x1"
  395.   convolution_param {
  396.     num_output: 192
  397.     kernel_size: 1
  398.   }
  399. }
  400. layer {
  401.   name: "inception_4a/relu_1x1"
  402.   type: "ReLU"
  403.   bottom: "inception_4a/1x1"
  404.   top: "inception_4a/1x1"
  405. }
  406. layer {
  407.   name: "inception_4a/3x3_reduce"
  408.   type: "Convolution"
  409.   bottom: "pool3/3x3_s2"
  410.   top: "inception_4a/3x3_reduce"
  411.   convolution_param {
  412.     num_output: 96
  413.     kernel_size: 1
  414.   }
  415. }
  416. layer {
  417.   name: "inception_4a/relu_3x3_reduce"
  418.   type: "ReLU"
  419.   bottom: "inception_4a/3x3_reduce"
  420.   top: "inception_4a/3x3_reduce"
  421. }
  422. layer {
  423.   name: "inception_4a/3x3"
  424.   type: "Convolution"
  425.   bottom: "inception_4a/3x3_reduce"
  426.   top: "inception_4a/3x3"
  427.   convolution_param {
  428.     num_output: 208
  429.     pad: 1
  430.     kernel_size: 3
  431.   }
  432. }
  433. layer {
  434.   name: "inception_4a/relu_3x3"
  435.   type: "ReLU"
  436.   bottom: "inception_4a/3x3"
  437.   top: "inception_4a/3x3"
  438. }
  439. layer {
  440.   name: "inception_4a/5x5_reduce"
  441.   type: "Convolution"
  442.   bottom: "pool3/3x3_s2"
  443.   top: "inception_4a/5x5_reduce"
  444.   convolution_param {
  445.     num_output: 16
  446.     kernel_size: 1
  447.   }
  448. }
  449. layer {
  450.   name: "inception_4a/relu_5x5_reduce"
  451.   type: "ReLU"
  452.   bottom: "inception_4a/5x5_reduce"
  453.   top: "inception_4a/5x5_reduce"
  454. }
  455. layer {
  456.   name: "inception_4a/5x5"
  457.   type: "Convolution"
  458.   bottom: "inception_4a/5x5_reduce"
  459.   top: "inception_4a/5x5"
  460.   convolution_param {
  461.     num_output: 48
  462.     pad: 2
  463.     kernel_size: 5
  464.   }
  465. }
  466. layer {
  467.   name: "inception_4a/relu_5x5"
  468.   type: "ReLU"
  469.   bottom: "inception_4a/5x5"
  470.   top: "inception_4a/5x5"
  471. }
  472. layer {
  473.   name: "inception_4a/pool"
  474.   type: "Pooling"
  475.   bottom: "pool3/3x3_s2"
  476.   top: "inception_4a/pool"
  477.   pooling_param {
  478.     pool: MAX
  479.     kernel_size: 3
  480.     stride: 1
  481.     pad: 1
  482.   }
  483. }
  484. layer {
  485.   name: "inception_4a/pool_proj"
  486.   type: "Convolution"
  487.   bottom: "inception_4a/pool"
  488.   top: "inception_4a/pool_proj"
  489.   convolution_param {
  490.     num_output: 64
  491.     kernel_size: 1
  492.   }
  493. }
  494. layer {
  495.   name: "inception_4a/relu_pool_proj"
  496.   type: "ReLU"
  497.   bottom: "inception_4a/pool_proj"
  498.   top: "inception_4a/pool_proj"
  499. }
  500. layer {
  501.   name: "inception_4a/output"
  502.   type: "Concat"
  503.   bottom: "inception_4a/1x1"
  504.   bottom: "inception_4a/3x3"
  505.   bottom: "inception_4a/5x5"
  506.   bottom: "inception_4a/pool_proj"
  507.   top: "inception_4a/output"
  508. }
  509. layer {
  510.   name: "inception_4b/1x1"
  511.   type: "Convolution"
  512.   bottom: "inception_4a/output"
  513.   top: "inception_4b/1x1"
  514.   convolution_param {
  515.     num_output: 160
  516.     kernel_size: 1
  517.   }
  518. }
  519. layer {
  520.   name: "inception_4b/relu_1x1"
  521.   type: "ReLU"
  522.   bottom: "inception_4b/1x1"
  523.   top: "inception_4b/1x1"
  524. }
  525. layer {
  526.   name: "inception_4b/3x3_reduce"
  527.   type: "Convolution"
  528.   bottom: "inception_4a/output"
  529.   top: "inception_4b/3x3_reduce"
  530.   convolution_param {
  531.     num_output: 112
  532.     kernel_size: 1
  533.   }
  534. }
  535. layer {
  536.   name: "inception_4b/relu_3x3_reduce"
  537.   type: "ReLU"
  538.   bottom: "inception_4b/3x3_reduce"
  539.   top: "inception_4b/3x3_reduce"
  540. }
  541. layer {
  542.   name: "inception_4b/3x3"
  543.   type: "Convolution"
  544.   bottom: "inception_4b/3x3_reduce"
  545.   top: "inception_4b/3x3"
  546.   convolution_param {
  547.     num_output: 224
  548.     pad: 1
  549.     kernel_size: 3
  550.   }
  551. }
  552. layer {
  553.   name: "inception_4b/relu_3x3"
  554.   type: "ReLU"
  555.   bottom: "inception_4b/3x3"
  556.   top: "inception_4b/3x3"
  557. }
  558. layer {
  559.   name: "inception_4b/5x5_reduce"
  560.   type: "Convolution"
  561.   bottom: "inception_4a/output"
  562.   top: "inception_4b/5x5_reduce"
  563.   convolution_param {
  564.     num_output: 24
  565.     kernel_size: 1
  566.   }
  567. }
  568. layer {
  569.   name: "inception_4b/relu_5x5_reduce"
  570.   type: "ReLU"
  571.   bottom: "inception_4b/5x5_reduce"
  572.   top: "inception_4b/5x5_reduce"
  573. }
  574. layer {
  575.   name: "inception_4b/5x5"
  576.   type: "Convolution"
  577.   bottom: "inception_4b/5x5_reduce"
  578.   top: "inception_4b/5x5"
  579.   convolution_param {
  580.     num_output: 64
  581.     pad: 2
  582.     kernel_size: 5
  583.   }
  584. }
  585. layer {
  586.   name: "inception_4b/relu_5x5"
  587.   type: "ReLU"
  588.   bottom: "inception_4b/5x5"
  589.   top: "inception_4b/5x5"
  590. }
  591. layer {
  592.   name: "inception_4b/pool"
  593.   type: "Pooling"
  594.   bottom: "inception_4a/output"
  595.   top: "inception_4b/pool"
  596.   pooling_param {
  597.     pool: MAX
  598.     kernel_size: 3
  599.     stride: 1
  600.     pad: 1
  601.   }
  602. }
  603. layer {
  604.   name: "inception_4b/pool_proj"
  605.   type: "Convolution"
  606.   bottom: "inception_4b/pool"
  607.   top: "inception_4b/pool_proj"
  608.   convolution_param {
  609.     num_output: 64
  610.     kernel_size: 1
  611.   }
  612. }
  613. layer {
  614.   name: "inception_4b/relu_pool_proj"
  615.   type: "ReLU"
  616.   bottom: "inception_4b/pool_proj"
  617.   top: "inception_4b/pool_proj"
  618. }
  619. layer {
  620.   name: "inception_4b/output"
  621.   type: "Concat"
  622.   bottom: "inception_4b/1x1"
  623.   bottom: "inception_4b/3x3"
  624.   bottom: "inception_4b/5x5"
  625.   bottom: "inception_4b/pool_proj"
  626.   top: "inception_4b/output"
  627. }
  628. layer {
  629.   name: "inception_4c/1x1"
  630.   type: "Convolution"
  631.   bottom: "inception_4b/output"
  632.   top: "inception_4c/1x1"
  633.   convolution_param {
  634.     num_output: 128
  635.     kernel_size: 1
  636.   }
  637. }
  638. layer {
  639.   name: "inception_4c/relu_1x1"
  640.   type: "ReLU"
  641.   bottom: "inception_4c/1x1"
  642.   top: "inception_4c/1x1"
  643. }
  644. layer {
  645.   name: "inception_4c/3x3_reduce"
  646.   type: "Convolution"
  647.   bottom: "inception_4b/output"
  648.   top: "inception_4c/3x3_reduce"
  649.   convolution_param {
  650.     num_output: 128
  651.     kernel_size: 1
  652.   }
  653. }
  654. layer {
  655.   name: "inception_4c/relu_3x3_reduce"
  656.   type: "ReLU"
  657.   bottom: "inception_4c/3x3_reduce"
  658.   top: "inception_4c/3x3_reduce"
  659. }
  660. layer {
  661.   name: "inception_4c/3x3"
  662.   type: "Convolution"
  663.   bottom: "inception_4c/3x3_reduce"
  664.   top: "inception_4c/3x3"
  665.   convolution_param {
  666.     num_output: 256
  667.     pad: 1
  668.     kernel_size: 3
  669.   }
  670. }
  671. layer {
  672.   name: "inception_4c/relu_3x3"
  673.   type: "ReLU"
  674.   bottom: "inception_4c/3x3"
  675.   top: "inception_4c/3x3"
  676. }
  677. layer {
  678.   name: "inception_4c/5x5_reduce"
  679.   type: "Convolution"
  680.   bottom: "inception_4b/output"
  681.   top: "inception_4c/5x5_reduce"
  682.   convolution_param {
  683.     num_output: 24
  684.     kernel_size: 1
  685.   }
  686. }
  687. layer {
  688.   name: "inception_4c/relu_5x5_reduce"
  689.   type: "ReLU"
  690.   bottom: "inception_4c/5x5_reduce"
  691.   top: "inception_4c/5x5_reduce"
  692. }
  693. layer {
  694.   name: "inception_4c/5x5"
  695.   type: "Convolution"
  696.   bottom: "inception_4c/5x5_reduce"
  697.   top: "inception_4c/5x5"
  698.   convolution_param {
  699.     num_output: 64
  700.     pad: 2
  701.     kernel_size: 5
  702.   }
  703. }
  704. layer {
  705.   name: "inception_4c/relu_5x5"
  706.   type: "ReLU"
  707.   bottom: "inception_4c/5x5"
  708.   top: "inception_4c/5x5"
  709. }
  710. layer {
  711.   name: "inception_4c/pool"
  712.   type: "Pooling"
  713.   bottom: "inception_4b/output"
  714.   top: "inception_4c/pool"
  715.   pooling_param {
  716.     pool: MAX
  717.     kernel_size: 3
  718.     stride: 1
  719.     pad: 1
  720.   }
  721. }
  722. layer {
  723.   name: "inception_4c/pool_proj"
  724.   type: "Convolution"
  725.   bottom: "inception_4c/pool"
  726.   top: "inception_4c/pool_proj"
  727.   convolution_param {
  728.     num_output: 64
  729.     kernel_size: 1
  730.   }
  731. }
  732. layer {
  733.   name: "inception_4c/relu_pool_proj"
  734.   type: "ReLU"
  735.   bottom: "inception_4c/pool_proj"
  736.   top: "inception_4c/pool_proj"
  737. }
  738. layer {
  739.   name: "inception_4c/output"
  740.   type: "Concat"
  741.   bottom: "inception_4c/1x1"
  742.   bottom: "inception_4c/3x3"
  743.   bottom: "inception_4c/5x5"
  744.   bottom: "inception_4c/pool_proj"
  745.   top: "inception_4c/output"
  746. }
  747. layer {
  748.   name: "inception_4d/1x1"
  749.   type: "Convolution"
  750.   bottom: "inception_4c/output"
  751.   top: "inception_4d/1x1"
  752.   convolution_param {
  753.     num_output: 112
  754.     kernel_size: 1
  755.   }
  756. }
  757. layer {
  758.   name: "inception_4d/relu_1x1"
  759.   type: "ReLU"
  760.   bottom: "inception_4d/1x1"
  761.   top: "inception_4d/1x1"
  762. }
  763. layer {
  764.   name: "inception_4d/3x3_reduce"
  765.   type: "Convolution"
  766.   bottom: "inception_4c/output"
  767.   top: "inception_4d/3x3_reduce"
  768.   convolution_param {
  769.     num_output: 144
  770.     kernel_size: 1
  771.   }
  772. }
  773. layer {
  774.   name: "inception_4d/relu_3x3_reduce"
  775.   type: "ReLU"
  776.   bottom: "inception_4d/3x3_reduce"
  777.   top: "inception_4d/3x3_reduce"
  778. }
  779. layer {
  780.   name: "inception_4d/3x3"
  781.   type: "Convolution"
  782.   bottom: "inception_4d/3x3_reduce"
  783.   top: "inception_4d/3x3"
  784.   convolution_param {
  785.     num_output: 288
  786.     pad: 1
  787.     kernel_size: 3
  788.   }
  789. }
  790. layer {
  791.   name: "inception_4d/relu_3x3"
  792.   type: "ReLU"
  793.   bottom: "inception_4d/3x3"
  794.   top: "inception_4d/3x3"
  795. }
  796. layer {
  797.   name: "inception_4d/5x5_reduce"
  798.   type: "Convolution"
  799.   bottom: "inception_4c/output"
  800.   top: "inception_4d/5x5_reduce"
  801.   convolution_param {
  802.     num_output: 32
  803.     kernel_size: 1
  804.   }
  805. }
  806. layer {
  807.   name: "inception_4d/relu_5x5_reduce"
  808.   type: "ReLU"
  809.   bottom: "inception_4d/5x5_reduce"
  810.   top: "inception_4d/5x5_reduce"
  811. }
  812. layer {
  813.   name: "inception_4d/5x5"
  814.   type: "Convolution"
  815.   bottom: "inception_4d/5x5_reduce"
  816.   top: "inception_4d/5x5"
  817.   convolution_param {
  818.     num_output: 64
  819.     pad: 2
  820.     kernel_size: 5
  821.   }
  822. }
  823. layer {
  824.   name: "inception_4d/relu_5x5"
  825.   type: "ReLU"
  826.   bottom: "inception_4d/5x5"
  827.   top: "inception_4d/5x5"
  828. }
  829. layer {
  830.   name: "inception_4d/pool"
  831.   type: "Pooling"
  832.   bottom: "inception_4c/output"
  833.   top: "inception_4d/pool"
  834.   pooling_param {
  835.     pool: MAX
  836.     kernel_size: 3
  837.     stride: 1
  838.     pad: 1
  839.   }
  840. }
  841. layer {
  842.   name: "inception_4d/pool_proj"
  843.   type: "Convolution"
  844.   bottom: "inception_4d/pool"
  845.   top: "inception_4d/pool_proj"
  846.   convolution_param {
  847.     num_output: 64
  848.     kernel_size: 1
  849.   }
  850. }
  851. layer {
  852.   name: "inception_4d/relu_pool_proj"
  853.   type: "ReLU"
  854.   bottom: "inception_4d/pool_proj"
  855.   top: "inception_4d/pool_proj"
  856. }
  857. layer {
  858.   name: "inception_4d/output"
  859.   type: "Concat"
  860.   bottom: "inception_4d/1x1"
  861.   bottom: "inception_4d/3x3"
  862.   bottom: "inception_4d/5x5"
  863.   bottom: "inception_4d/pool_proj"
  864.   top: "inception_4d/output"
  865. }
  866. layer {
  867.   name: "inception_4e/1x1"
  868.   type: "Convolution"
  869.   bottom: "inception_4d/output"
  870.   top: "inception_4e/1x1"
  871.   convolution_param {
  872.     num_output: 256
  873.     kernel_size: 1
  874.   }
  875. }
  876. layer {
  877.   name: "inception_4e/relu_1x1"
  878.   type: "ReLU"
  879.   bottom: "inception_4e/1x1"
  880.   top: "inception_4e/1x1"
  881. }
  882. layer {
  883.   name: "inception_4e/3x3_reduce"
  884.   type: "Convolution"
  885.   bottom: "inception_4d/output"
  886.   top: "inception_4e/3x3_reduce"
  887.   convolution_param {
  888.     num_output: 160
  889.     kernel_size: 1
  890.   }
  891. }
  892. layer {
  893.   name: "inception_4e/relu_3x3_reduce"
  894.   type: "ReLU"
  895.   bottom: "inception_4e/3x3_reduce"
  896.   top: "inception_4e/3x3_reduce"
  897. }
  898. layer {
  899.   name: "inception_4e/3x3"
  900.   type: "Convolution"
  901.   bottom: "inception_4e/3x3_reduce"
  902.   top: "inception_4e/3x3"
  903.   convolution_param {
  904.     num_output: 320
  905.     pad: 1
  906.     kernel_size: 3
  907.   }
  908. }
  909. layer {
  910.   name: "inception_4e/relu_3x3"
  911.   type: "ReLU"
  912.   bottom: "inception_4e/3x3"
  913.   top: "inception_4e/3x3"
  914. }
  915. layer {
  916.   name: "inception_4e/5x5_reduce"
  917.   type: "Convolution"
  918.   bottom: "inception_4d/output"
  919.   top: "inception_4e/5x5_reduce"
  920.   convolution_param {
  921.     num_output: 32
  922.     kernel_size: 1
  923.   }
  924. }
  925. layer {
  926.   name: "inception_4e/relu_5x5_reduce"
  927.   type: "ReLU"
  928.   bottom: "inception_4e/5x5_reduce"
  929.   top: "inception_4e/5x5_reduce"
  930. }
  931. layer {
  932.   name: "inception_4e/5x5"
  933.   type: "Convolution"
  934.   bottom: "inception_4e/5x5_reduce"
  935.   top: "inception_4e/5x5"
  936.   convolution_param {
  937.     num_output: 128
  938.     pad: 2
  939.     kernel_size: 5
  940.   }
  941. }
  942. layer {
  943.   name: "inception_4e/relu_5x5"
  944.   type: "ReLU"
  945.   bottom: "inception_4e/5x5"
  946.   top: "inception_4e/5x5"
  947. }
  948. layer {
  949.   name: "inception_4e/pool"
  950.   type: "Pooling"
  951.   bottom: "inception_4d/output"
  952.   top: "inception_4e/pool"
  953.   pooling_param {
  954.     pool: MAX
  955.     kernel_size: 3
  956.     stride: 1
  957.     pad: 1
  958.   }
  959. }
  960. layer {
  961.   name: "inception_4e/pool_proj"
  962.   type: "Convolution"
  963.   bottom: "inception_4e/pool"
  964.   top: "inception_4e/pool_proj"
  965.   convolution_param {
  966.     num_output: 128
  967.     kernel_size: 1
  968.   }
  969. }
  970. layer {
  971.   name: "inception_4e/relu_pool_proj"
  972.   type: "ReLU"
  973.   bottom: "inception_4e/pool_proj"
  974.   top: "inception_4e/pool_proj"
  975. }
  976. layer {
  977.   name: "inception_4e/output"
  978.   type: "Concat"
  979.   bottom: "inception_4e/1x1"
  980.   bottom: "inception_4e/3x3"
  981.   bottom: "inception_4e/5x5"
  982.   bottom: "inception_4e/pool_proj"
  983.   top: "inception_4e/output"
  984. }
  985. layer {
  986.   name: "inception_5a/1x1"
  987.   type: "Convolution"
  988.   bottom: "inception_4e/output"
  989.   top: "inception_5a/1x1"
  990.   convolution_param {
  991.     num_output: 256
  992.     kernel_size: 1
  993.   }
  994. }
  995. layer {
  996.   name: "inception_5a/relu_1x1"
  997.   type: "ReLU"
  998.   bottom: "inception_5a/1x1"
  999.   top: "inception_5a/1x1"
  1000. }
  1001. layer {
  1002.   name: "inception_5a/3x3_reduce"
  1003.   type: "Convolution"
  1004.   bottom: "inception_4e/output"
  1005.   top: "inception_5a/3x3_reduce"
  1006.   convolution_param {
  1007.     num_output: 160
  1008.     kernel_size: 1
  1009.   }
  1010. }
  1011. layer {
  1012.   name: "inception_5a/relu_3x3_reduce"
  1013.   type: "ReLU"
  1014.   bottom: "inception_5a/3x3_reduce"
  1015.   top: "inception_5a/3x3_reduce"
  1016. }
  1017. layer {
  1018.   name: "inception_5a/3x3"
  1019.   type: "Convolution"
  1020.   bottom: "inception_5a/3x3_reduce"
  1021.   top: "inception_5a/3x3"
  1022.   convolution_param {
  1023.     num_output: 320
  1024.     pad: 1
  1025.     kernel_size: 3
  1026.   }
  1027. }
  1028. layer {
  1029.   name: "inception_5a/relu_3x3"
  1030.   type: "ReLU"
  1031.   bottom: "inception_5a/3x3"
  1032.   top: "inception_5a/3x3"
  1033. }
  1034. layer {
  1035.   name: "inception_5a/5x5_reduce"
  1036.   type: "Convolution"
  1037.   bottom: "inception_4e/output"
  1038.   top: "inception_5a/5x5_reduce"
  1039.   convolution_param {
  1040.     num_output: 32
  1041.     kernel_size: 1
  1042.   }
  1043. }
  1044. layer {
  1045.   name: "inception_5a/relu_5x5_reduce"
  1046.   type: "ReLU"
  1047.   bottom: "inception_5a/5x5_reduce"
  1048.   top: "inception_5a/5x5_reduce"
  1049. }
  1050. layer {
  1051.   name: "inception_5a/5x5"
  1052.   type: "Convolution"
  1053.   bottom: "inception_5a/5x5_reduce"
  1054.   top: "inception_5a/5x5"
  1055.   convolution_param {
  1056.     num_output: 128
  1057.     pad: 2
  1058.     kernel_size: 5
  1059.   }
  1060. }
  1061. layer {
  1062.   name: "inception_5a/relu_5x5"
  1063.   type: "ReLU"
  1064.   bottom: "inception_5a/5x5"
  1065.   top: "inception_5a/5x5"
  1066. }
  1067. layer {
  1068.   name: "inception_5a/pool"
  1069.   type: "Pooling"
  1070.   bottom: "inception_4e/output"
  1071.   top: "inception_5a/pool"
  1072.   pooling_param {
  1073.     pool: MAX
  1074.     kernel_size: 3
  1075.     stride: 1
  1076.     pad: 1
  1077.   }
  1078. }
  1079. layer {
  1080.   name: "inception_5a/pool_proj"
  1081.   type: "Convolution"
  1082.   bottom: "inception_5a/pool"
  1083.   top: "inception_5a/pool_proj"
  1084.   convolution_param {
  1085.     num_output: 128
  1086.     kernel_size: 1
  1087.   }
  1088. }
  1089. layer {
  1090.   name: "inception_5a/relu_pool_proj"
  1091.   type: "ReLU"
  1092.   bottom: "inception_5a/pool_proj"
  1093.   top: "inception_5a/pool_proj"
  1094. }
  1095. layer {
  1096.   name: "inception_5a/output"
  1097.   type: "Concat"
  1098.   bottom: "inception_5a/1x1"
  1099.   bottom: "inception_5a/3x3"
  1100.   bottom: "inception_5a/5x5"
  1101.   bottom: "inception_5a/pool_proj"
  1102.   top: "inception_5a/output"
  1103. }
  1104. layer {
  1105.   name: "inception_5b/1x1"
  1106.   type: "Convolution"
  1107.   bottom: "inception_5a/output"
  1108.   top: "inception_5b/1x1"
  1109.   convolution_param {
  1110.     num_output: 384
  1111.     kernel_size: 1
  1112.   }
  1113. }
  1114. layer {
  1115.   name: "inception_5b/relu_1x1"
  1116.   type: "ReLU"
  1117.   bottom: "inception_5b/1x1"
  1118.   top: "inception_5b/1x1"
  1119. }
  1120. layer {
  1121.   name: "inception_5b/3x3_reduce"
  1122.   type: "Convolution"
  1123.   bottom: "inception_5a/output"
  1124.   top: "inception_5b/3x3_reduce"
  1125.   convolution_param {
  1126.     num_output: 192
  1127.     kernel_size: 1
  1128.   }
  1129. }
  1130. layer {
  1131.   name: "inception_5b/relu_3x3_reduce"
  1132.   type: "ReLU"
  1133.   bottom: "inception_5b/3x3_reduce"
  1134.   top: "inception_5b/3x3_reduce"
  1135. }
  1136. layer {
  1137.   name: "inception_5b/3x3"
  1138.   type: "Convolution"
  1139.   bottom: "inception_5b/3x3_reduce"
  1140.   top: "inception_5b/3x3"
  1141.   convolution_param {
  1142.     num_output: 384
  1143.     pad: 1
  1144.     kernel_size: 3
  1145.   }
  1146. }
  1147. layer {
  1148.   name: "inception_5b/relu_3x3"
  1149.   type: "ReLU"
  1150.   bottom: "inception_5b/3x3"
  1151.   top: "inception_5b/3x3"
  1152. }
  1153. layer {
  1154.   name: "inception_5b/5x5_reduce"
  1155.   type: "Convolution"
  1156.   bottom: "inception_5a/output"
  1157.   top: "inception_5b/5x5_reduce"
  1158.   convolution_param {
  1159.     num_output: 48
  1160.     kernel_size: 1
  1161.   }
  1162. }
  1163. layer {
  1164.   name: "inception_5b/relu_5x5_reduce"
  1165.   type: "ReLU"
  1166.   bottom: "inception_5b/5x5_reduce"
  1167.   top: "inception_5b/5x5_reduce"
  1168. }
  1169. layer {
  1170.   name: "inception_5b/5x5"
  1171.   type: "Convolution"
  1172.   bottom: "inception_5b/5x5_reduce"
  1173.   top: "inception_5b/5x5"
  1174.   convolution_param {
  1175.     num_output: 128
  1176.     pad: 2
  1177.     kernel_size: 5
  1178.   }
  1179. }
  1180. layer {
  1181.   name: "inception_5b/relu_5x5"
  1182.   type: "ReLU"
  1183.   bottom: "inception_5b/5x5"
  1184.   top: "inception_5b/5x5"
  1185. }
  1186. layer {
  1187.   name: "inception_5b/pool"
  1188.   type: "Pooling"
  1189.   bottom: "inception_5a/output"
  1190.   top: "inception_5b/pool"
  1191.   pooling_param {
  1192.     pool: MAX
  1193.     kernel_size: 3
  1194.     stride: 1
  1195.     pad: 1
  1196.   }
  1197. }
  1198. layer {
  1199.   name: "inception_5b/pool_proj"
  1200.   type: "Convolution"
  1201.   bottom: "inception_5b/pool"
  1202.   top: "inception_5b/pool_proj"
  1203.   convolution_param {
  1204.     num_output: 128
  1205.     kernel_size: 1
  1206.   }
  1207. }
  1208. layer {
  1209.   name: "inception_5b/relu_pool_proj"
  1210.   type: "ReLU"
  1211.   bottom: "inception_5b/pool_proj"
  1212.   top: "inception_5b/pool_proj"
  1213. }
  1214. layer {
  1215.   name: "inception_5b/output"
  1216.   type: "Concat"
  1217.   bottom: "inception_5b/1x1"
  1218.   bottom: "inception_5b/3x3"
  1219.   bottom: "inception_5b/5x5"
  1220.   bottom: "inception_5b/pool_proj"
  1221.   top: "inception_5b/output"
  1222. }
  1223. layer {
  1224.   name: "pool5/drop_7x7_s1"
  1225.   type: "Dropout"
  1226.   bottom: "inception_5b/output"
  1227.   top: "pool5/7x7_s1"
  1228.   dropout_param {
  1229.     dropout_ratio: 0.4
  1230.   }
  1231. }
  1232. layer {
  1233.   name: "loss3/classifier/19c"
  1234.   type: "Convolution"
  1235.   bottom: "pool5/7x7_s1"
  1236.   top: "loss3/classifier"
  1237.   convolution_param {
  1238.     num_output: 19
  1239.     kernel_size: 1
  1240.   }
  1241. }
  1242.  
  1243.  
  1244. layer {
  1245.   name: "upscore2"
  1246.   type: "Deconvolution"
  1247.   bottom: "loss3/classifier"
  1248.   top: "upscore2"
  1249.   convolution_param {
  1250.     num_output: 19
  1251.     bias_term: false
  1252.     kernel_size: 4
  1253.     stride: 2
  1254.     pad: 1
  1255.   }
  1256. }
  1257. layer {
  1258.   name: "score-pool3"
  1259.   type: "Convolution"
  1260.   bottom: "inception_3b/output"
  1261.   top: "score-pool3"
  1262.   convolution_param {
  1263.     num_output: 19
  1264.     kernel_size: 1
  1265.     engine: CAFFE
  1266.   }
  1267. }
  1268. layer {
  1269.   name: "fuse"
  1270.   type: "Eltwise"
  1271.   bottom: "upscore2"
  1272.   bottom: "score-pool3"
  1273.   top: "score-fused"
  1274.   eltwise_param {
  1275.     operation: SUM
  1276.   }
  1277. }
  1278. layer {
  1279.     type: 'Softmax'
  1280.     name: 'prob'
  1281.     bottom: 'score-fused'
  1282.     top: 'prob'
  1283.     softmax_param {
  1284.         engine: CAFFE
  1285.     }
  1286. }
RAW Paste Data
We use cookies for various purposes including analytics. By continuing to use Pastebin, you agree to our use of cookies as described in the Cookies Policy. OK, I Understand
 
Top