yolov3-tiny-prn.cfg 2.0 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=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. 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=16
  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=32
  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=64
  46. size=3
  47. stride=1
  48. pad=1
  49. activation=leaky
  50. [maxpool]
  51. size=2
  52. stride=2
  53. [convolutional]
  54. batch_normalize=1
  55. filters=128
  56. size=3
  57. stride=1
  58. pad=1
  59. activation=leaky
  60. [maxpool]
  61. size=2
  62. stride=2
  63. [convolutional]
  64. batch_normalize=1
  65. filters=256
  66. size=3
  67. stride=1
  68. pad=1
  69. activation=leaky
  70. [maxpool]
  71. size=2
  72. stride=2
  73. [convolutional]
  74. batch_normalize=1
  75. filters=512
  76. size=3
  77. stride=1
  78. pad=1
  79. activation=leaky
  80. [maxpool]
  81. size=2
  82. stride=1
  83. [convolutional]
  84. batch_normalize=1
  85. filters=512
  86. size=3
  87. stride=1
  88. pad=1
  89. activation=leaky
  90. [shortcut]
  91. activation=leaky
  92. from=-3
  93. ###########
  94. [convolutional]
  95. batch_normalize=1
  96. filters=256
  97. size=1
  98. stride=1
  99. pad=1
  100. activation=leaky
  101. [convolutional]
  102. batch_normalize=1
  103. filters=256
  104. size=3
  105. stride=1
  106. pad=1
  107. activation=leaky
  108. [shortcut]
  109. activation=leaky
  110. from=-2
  111. [convolutional]
  112. size=1
  113. stride=1
  114. pad=1
  115. filters=255
  116. activation=linear
  117. [yolo]
  118. mask = 3,4,5
  119. anchors = 10,14, 23,27, 37,58, 81,82, 135,169, 344,319
  120. classes=80
  121. num=6
  122. jitter=.3
  123. ignore_thresh = .7
  124. truth_thresh = 1
  125. random=1
  126. [route]
  127. layers = -4
  128. [convolutional]
  129. batch_normalize=1
  130. filters=128
  131. size=1
  132. stride=1
  133. pad=1
  134. activation=leaky
  135. [upsample]
  136. stride=2
  137. [shortcut]
  138. activation=leaky
  139. from=8
  140. [convolutional]
  141. batch_normalize=1
  142. filters=128
  143. size=3
  144. stride=1
  145. pad=1
  146. activation=leaky
  147. [shortcut]
  148. activation=leaky
  149. from=-3
  150. [shortcut]
  151. activation=leaky
  152. from=8
  153. [convolutional]
  154. size=1
  155. stride=1
  156. pad=1
  157. filters=255
  158. activation=linear
  159. [yolo]
  160. mask = 1,2,3
  161. anchors = 10,14, 23,27, 37,58, 81,82, 135,169, 344,319
  162. classes=80
  163. num=6
  164. jitter=.3
  165. ignore_thresh = .7
  166. truth_thresh = 1
  167. random=1