yolo9000.cfg 2.3 KB

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  1. [net]
  2. # Testing
  3. batch=1
  4. subdivisions=1
  5. # Training
  6. # batch=64
  7. # subdivisions=8
  8. batch=1
  9. subdivisions=1
  10. height=544
  11. width=544
  12. channels=3
  13. momentum=0.9
  14. decay=0.0005
  15. learning_rate=0.001
  16. burn_in=1000
  17. max_batches = 500200
  18. policy=steps
  19. steps=400000,450000
  20. scales=.1,.1
  21. hue=.1
  22. saturation=.75
  23. exposure=.75
  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. [convolutional]
  52. batch_normalize=1
  53. filters=64
  54. size=1
  55. stride=1
  56. pad=1
  57. activation=leaky
  58. [convolutional]
  59. batch_normalize=1
  60. filters=128
  61. size=3
  62. stride=1
  63. pad=1
  64. activation=leaky
  65. [maxpool]
  66. size=2
  67. stride=2
  68. [convolutional]
  69. batch_normalize=1
  70. filters=256
  71. size=3
  72. stride=1
  73. pad=1
  74. activation=leaky
  75. [convolutional]
  76. batch_normalize=1
  77. filters=128
  78. size=1
  79. stride=1
  80. pad=1
  81. activation=leaky
  82. [convolutional]
  83. batch_normalize=1
  84. filters=256
  85. size=3
  86. stride=1
  87. pad=1
  88. activation=leaky
  89. [maxpool]
  90. size=2
  91. stride=2
  92. [convolutional]
  93. batch_normalize=1
  94. filters=512
  95. size=3
  96. stride=1
  97. pad=1
  98. activation=leaky
  99. [convolutional]
  100. batch_normalize=1
  101. filters=256
  102. size=1
  103. stride=1
  104. pad=1
  105. activation=leaky
  106. [convolutional]
  107. batch_normalize=1
  108. filters=512
  109. size=3
  110. stride=1
  111. pad=1
  112. activation=leaky
  113. [convolutional]
  114. batch_normalize=1
  115. filters=256
  116. size=1
  117. stride=1
  118. pad=1
  119. activation=leaky
  120. [convolutional]
  121. batch_normalize=1
  122. filters=512
  123. size=3
  124. stride=1
  125. pad=1
  126. activation=leaky
  127. [maxpool]
  128. size=2
  129. stride=2
  130. [convolutional]
  131. batch_normalize=1
  132. filters=1024
  133. size=3
  134. stride=1
  135. pad=1
  136. activation=leaky
  137. [convolutional]
  138. batch_normalize=1
  139. filters=512
  140. size=1
  141. stride=1
  142. pad=1
  143. activation=leaky
  144. [convolutional]
  145. batch_normalize=1
  146. filters=1024
  147. size=3
  148. stride=1
  149. pad=1
  150. activation=leaky
  151. [convolutional]
  152. batch_normalize=1
  153. filters=512
  154. size=1
  155. stride=1
  156. pad=1
  157. activation=leaky
  158. [convolutional]
  159. batch_normalize=1
  160. filters=1024
  161. size=3
  162. stride=1
  163. pad=1
  164. activation=leaky
  165. [convolutional]
  166. filters=28269
  167. size=1
  168. stride=1
  169. pad=1
  170. activation=linear
  171. [region]
  172. anchors = 0.77871, 1.14074, 3.00525, 4.31277, 9.22725, 9.61974
  173. bias_match=1
  174. classes=9418
  175. coords=4
  176. num=3
  177. softmax=1
  178. jitter=.2
  179. rescore=1
  180. object_scale=5
  181. noobject_scale=1
  182. class_scale=1
  183. coord_scale=1
  184. thresh = .6
  185. absolute=1
  186. random=1
  187. tree=data/9k.tree
  188. map = data/coco9k.map