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yolov2.cfg 2.7 KB

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  1. [net]
  2. # Testing
  3. batch=1
  4. subdivisions=1
  5. # Training
  6. # batch=64
  7. # subdivisions=8
  8. width=608
  9. height=608
  10. channels=3
  11. momentum=0.9
  12. decay=0.0005
  13. angle=0
  14. saturation = 1.5
  15. exposure = 1.5
  16. hue=.1
  17. learning_rate=0.001
  18. burn_in=1000
  19. max_batches = 500200
  20. policy=steps
  21. steps=400000,450000
  22. scales=.1,.1
  23. [convolutional]
  24. batch_normalize=1
  25. filters=32
  26. size=3
  27. stride=1
  28. pad=1
  29. activation=leaky
  30. [maxpool]
  31. size=2
  32. stride=2
  33. [convolutional]
  34. batch_normalize=1
  35. filters=64
  36. size=3
  37. stride=1
  38. pad=1
  39. activation=leaky
  40. [maxpool]
  41. size=2
  42. stride=2
  43. [convolutional]
  44. batch_normalize=1
  45. filters=128
  46. size=3
  47. stride=1
  48. pad=1
  49. activation=leaky
  50. [convolutional]
  51. batch_normalize=1
  52. filters=64
  53. size=1
  54. stride=1
  55. pad=1
  56. activation=leaky
  57. [convolutional]
  58. batch_normalize=1
  59. filters=128
  60. size=3
  61. stride=1
  62. pad=1
  63. activation=leaky
  64. [maxpool]
  65. size=2
  66. stride=2
  67. [convolutional]
  68. batch_normalize=1
  69. filters=256
  70. size=3
  71. stride=1
  72. pad=1
  73. activation=leaky
  74. [convolutional]
  75. batch_normalize=1
  76. filters=128
  77. size=1
  78. stride=1
  79. pad=1
  80. activation=leaky
  81. [convolutional]
  82. batch_normalize=1
  83. filters=256
  84. size=3
  85. stride=1
  86. pad=1
  87. activation=leaky
  88. [maxpool]
  89. size=2
  90. stride=2
  91. [convolutional]
  92. batch_normalize=1
  93. filters=512
  94. size=3
  95. stride=1
  96. pad=1
  97. activation=leaky
  98. [convolutional]
  99. batch_normalize=1
  100. filters=256
  101. size=1
  102. stride=1
  103. pad=1
  104. activation=leaky
  105. [convolutional]
  106. batch_normalize=1
  107. filters=512
  108. size=3
  109. stride=1
  110. pad=1
  111. activation=leaky
  112. [convolutional]
  113. batch_normalize=1
  114. filters=256
  115. size=1
  116. stride=1
  117. pad=1
  118. activation=leaky
  119. [convolutional]
  120. batch_normalize=1
  121. filters=512
  122. size=3
  123. stride=1
  124. pad=1
  125. activation=leaky
  126. [maxpool]
  127. size=2
  128. stride=2
  129. [convolutional]
  130. batch_normalize=1
  131. filters=1024
  132. size=3
  133. stride=1
  134. pad=1
  135. activation=leaky
  136. [convolutional]
  137. batch_normalize=1
  138. filters=512
  139. size=1
  140. stride=1
  141. pad=1
  142. activation=leaky
  143. [convolutional]
  144. batch_normalize=1
  145. filters=1024
  146. size=3
  147. stride=1
  148. pad=1
  149. activation=leaky
  150. [convolutional]
  151. batch_normalize=1
  152. filters=512
  153. size=1
  154. stride=1
  155. pad=1
  156. activation=leaky
  157. [convolutional]
  158. batch_normalize=1
  159. filters=1024
  160. size=3
  161. stride=1
  162. pad=1
  163. activation=leaky
  164. #######
  165. [convolutional]
  166. batch_normalize=1
  167. size=3
  168. stride=1
  169. pad=1
  170. filters=1024
  171. activation=leaky
  172. [convolutional]
  173. batch_normalize=1
  174. size=3
  175. stride=1
  176. pad=1
  177. filters=1024
  178. activation=leaky
  179. [route]
  180. layers=-9
  181. [convolutional]
  182. batch_normalize=1
  183. size=1
  184. stride=1
  185. pad=1
  186. filters=64
  187. activation=leaky
  188. [reorg]
  189. stride=2
  190. [route]
  191. layers=-1,-4
  192. [convolutional]
  193. batch_normalize=1
  194. size=3
  195. stride=1
  196. pad=1
  197. filters=1024
  198. activation=leaky
  199. [convolutional]
  200. size=1
  201. stride=1
  202. pad=1
  203. filters=425
  204. activation=linear
  205. [region]
  206. anchors = 0.57273, 0.677385, 1.87446, 2.06253, 3.33843, 5.47434, 7.88282, 3.52778, 9.77052, 9.16828
  207. bias_match=1
  208. classes=80
  209. coords=4
  210. num=5
  211. softmax=1
  212. jitter=.3
  213. rescore=1
  214. object_scale=5
  215. noobject_scale=1
  216. class_scale=1
  217. coord_scale=1
  218. absolute=1
  219. thresh = .6
  220. random=1