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  1. [net]
  2. # Testing
  3. batch=64
  4. subdivisions=2
  5. # Training
  6. # batch=64
  7. # subdivisions=2
  8. width=416
  9. height=416
  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.  
  18. learning_rate=0.001
  19. burn_in=1000
  20. max_batches = 500200
  21. policy=steps
  22. steps=400000,450000
  23. scales=.1,.1
  24.  
  25. [convolutional]
  26. batch_normalize=1
  27. filters=16
  28. size=3
  29. stride=1
  30. pad=2
  31. activation=leaky
  32.  
  33. [maxpool]
  34. size=2
  35. stride=2
  36.  
  37. [convolutional]
  38. batch_normalize=1
  39. filters=32
  40. size=3
  41. stride=1
  42. pad=1
  43. activation=leaky
  44.  
  45. [maxpool]
  46. size=2
  47. stride=2
  48.  
  49. [convolutional]
  50. batch_normalize=1
  51. filters=64
  52. size=3
  53. stride=1
  54. pad=1
  55. activation=leaky
  56.  
  57. [maxpool]
  58. size=2
  59. stride=2
  60.  
  61. [convolutional]
  62. batch_normalize=1
  63. filters=128
  64. size=3
  65. stride=1
  66. pad=1
  67. activation=leaky
  68.  
  69. [maxpool]
  70. size=2
  71. stride=2
  72.  
  73. [convolutional]
  74. batch_normalize=1
  75. filters=256
  76. size=3
  77. stride=1
  78. pad=1
  79. activation=leaky
  80.  
  81. [maxpool]
  82. size=2
  83. stride=2
  84.  
  85. [convolutional]
  86. batch_normalize=1
  87. filters=512
  88. size=3
  89. stride=1
  90. pad=1
  91. activation=leaky
  92.  
  93. [maxpool]
  94. size=2
  95. stride=1
  96.  
  97. [convolutional]
  98. batch_normalize=1
  99. filters=1024
  100. size=3
  101. stride=1
  102. pad=1
  103. activation=leaky
  104.  
  105. ###########
  106.  
  107. [convolutional]
  108. batch_normalize=1
  109. filters=256
  110. size=1
  111. stride=1
  112. pad=1
  113. activation=leaky
  114.  
  115. [convolutional]
  116. batch_normalize=1
  117. filters=512
  118. size=3
  119. stride=1
  120. pad=1
  121. activation=leaky
  122.  
  123. [convolutional]
  124. size=1
  125. stride=1
  126. pad=1
  127. filters=18
  128. activation=linear
  129.  
  130.  
  131.  
  132. [yolo]
  133. mask = 3,4,5
  134. anchors=0.635167,1.913028, 0.886652, 1.642199,1.001117, 1.876485, 1.05377783, 1.4272505, 2.0242668, 3.98870333, 6.3863475, 7.13946675
  135. classes=1
  136. num=6
  137. jitter=.3
  138. ignore_thresh = .7
  139. truth_thresh = 1
  140. random=1
  141.  
  142. [route]
  143. layers = -4
  144.  
  145. [convolutional]
  146. batch_normalize=1
  147. filters=128
  148. size=1
  149. stride=1
  150. pad=1
  151. activation=leaky
  152.  
  153. [upsample]
  154. stride=2
  155.  
  156. [route]
  157. layers = -1, 8
  158.  
  159. [convolutional]
  160. batch_normalize=1
  161. filters=256
  162. size=3
  163. stride=1
  164. pad=1
  165. activation=leaky
  166.  
  167. [convolutional]
  168. size=1
  169. stride=1
  170. pad=1
  171. filters=18
  172. activation=linear
  173.  
  174. [yolo]
  175. mask = 0,1,2
  176. anchors = 0.635167,1.913028, 0.886652, 1.642199,1.001117, 1.876485, 1.05377783, 1.4272505, 2.0242668, 3.98870333, 6.3863475, 7.13946675
  177. classes=1
  178. num=6
  179. jitter=.3
  180. ignore_thresh = .7
  181. truth_thresh = 1
  182. random=1
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