darknet.cfg 1.0 KB

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111
  1. [net]
  2. batch=128
  3. subdivisions=1
  4. height=224
  5. width=224
  6. channels=3
  7. momentum=0.9
  8. decay=0.0005
  9. max_crop=320
  10. learning_rate=0.1
  11. policy=poly
  12. power=4
  13. max_batches=1600000
  14. [convolutional]
  15. batch_normalize=1
  16. filters=16
  17. size=3
  18. stride=1
  19. pad=1
  20. activation=leaky
  21. [maxpool]
  22. size=2
  23. stride=2
  24. [convolutional]
  25. batch_normalize=1
  26. filters=32
  27. size=3
  28. stride=1
  29. pad=1
  30. activation=leaky
  31. [maxpool]
  32. size=2
  33. stride=2
  34. [convolutional]
  35. batch_normalize=1
  36. filters=64
  37. size=3
  38. stride=1
  39. pad=1
  40. activation=leaky
  41. [maxpool]
  42. size=2
  43. stride=2
  44. [convolutional]
  45. batch_normalize=1
  46. filters=128
  47. size=3
  48. stride=1
  49. pad=1
  50. activation=leaky
  51. [maxpool]
  52. size=2
  53. stride=2
  54. [convolutional]
  55. batch_normalize=1
  56. filters=256
  57. size=3
  58. stride=1
  59. pad=1
  60. activation=leaky
  61. [maxpool]
  62. size=2
  63. stride=2
  64. [convolutional]
  65. batch_normalize=1
  66. filters=512
  67. size=3
  68. stride=1
  69. pad=1
  70. activation=leaky
  71. [maxpool]
  72. size=2
  73. stride=2
  74. padding=1
  75. [convolutional]
  76. batch_normalize=1
  77. filters=1024
  78. size=3
  79. stride=1
  80. pad=1
  81. activation=leaky
  82. [convolutional]
  83. filters=1000
  84. size=1
  85. stride=1
  86. pad=1
  87. activation=leaky
  88. [avgpool]
  89. [softmax]
  90. groups=1
  91. [cost]
  92. type=sse