yolov3-tiny_xnor.cfg 2.0 KB

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154155156157158159160161162163164165166167168169170171172173174175176177178179180181182183184185186187188189190191192193194195196197
  1. [net]
  2. # Testing
  3. #batch=1
  4. #subdivisions=1
  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. 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. xnor=1
  35. bin_output=1
  36. batch_normalize=1
  37. filters=32
  38. size=3
  39. stride=1
  40. pad=1
  41. activation=leaky
  42. [maxpool]
  43. size=2
  44. stride=2
  45. [convolutional]
  46. xnor=1
  47. bin_output=1
  48. batch_normalize=1
  49. filters=64
  50. size=3
  51. stride=1
  52. pad=1
  53. activation=leaky
  54. [maxpool]
  55. size=2
  56. stride=2
  57. [convolutional]
  58. xnor=1
  59. bin_output=1
  60. batch_normalize=1
  61. filters=128
  62. size=3
  63. stride=1
  64. pad=1
  65. activation=leaky
  66. [maxpool]
  67. size=2
  68. stride=2
  69. [convolutional]
  70. xnor=1
  71. batch_normalize=1
  72. filters=256
  73. size=3
  74. stride=1
  75. pad=1
  76. activation=leaky
  77. [maxpool]
  78. size=2
  79. stride=2
  80. [convolutional]
  81. xnor=1
  82. bin_output=1
  83. batch_normalize=1
  84. filters=512
  85. size=3
  86. stride=1
  87. pad=1
  88. activation=leaky
  89. [maxpool]
  90. size=2
  91. stride=1
  92. [convolutional]
  93. xnor=1
  94. bin_output=1
  95. batch_normalize=1
  96. filters=1024
  97. size=3
  98. stride=1
  99. pad=1
  100. activation=leaky
  101. ###########
  102. [convolutional]
  103. xnor=1
  104. batch_normalize=1
  105. filters=256
  106. size=1
  107. stride=1
  108. pad=1
  109. activation=leaky
  110. [convolutional]
  111. batch_normalize=1
  112. filters=512
  113. size=3
  114. stride=1
  115. pad=1
  116. activation=leaky
  117. [convolutional]
  118. size=1
  119. stride=1
  120. pad=1
  121. filters=255
  122. activation=linear
  123. [yolo]
  124. mask = 3,4,5
  125. anchors = 10,14, 23,27, 37,58, 81,82, 135,169, 344,319
  126. classes=80
  127. num=6
  128. jitter=.3
  129. ignore_thresh = .7
  130. truth_thresh = 1
  131. random=1
  132. [route]
  133. layers = -4
  134. [convolutional]
  135. xnor=1
  136. batch_normalize=1
  137. filters=128
  138. size=1
  139. stride=1
  140. pad=1
  141. activation=leaky
  142. [upsample]
  143. stride=2
  144. [route]
  145. layers = -1, 8
  146. [convolutional]
  147. xnor=1
  148. batch_normalize=1
  149. filters=256
  150. size=3
  151. stride=1
  152. pad=1
  153. activation=leaky
  154. [convolutional]
  155. size=1
  156. stride=1
  157. pad=1
  158. filters=255
  159. activation=linear
  160. [yolo]
  161. mask = 0,1,2
  162. anchors = 10,14, 23,27, 37,58, 81,82, 135,169, 344,319
  163. classes=80
  164. num=6
  165. jitter=.3
  166. ignore_thresh = .7
  167. truth_thresh = 1
  168. random=1