yolov3-tiny_occlusion_track.cfg 2.2 KB

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  1. [net]
  2. # Testing
  3. #batch=1
  4. #subdivisions=1
  5. # Training
  6. batch=8
  7. subdivisions=4
  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. track=1
  18. time_steps=20
  19. augment_speed=3
  20. learning_rate=0.001
  21. burn_in=1000
  22. max_batches = 10000
  23. policy=steps
  24. steps=9000,9500
  25. scales=.1,.1
  26. [convolutional]
  27. batch_normalize=1
  28. filters=16
  29. size=3
  30. stride=1
  31. pad=1
  32. activation=leaky
  33. [maxpool]
  34. size=2
  35. stride=2
  36. [convolutional]
  37. batch_normalize=1
  38. filters=32
  39. size=3
  40. stride=1
  41. pad=1
  42. activation=leaky
  43. [maxpool]
  44. size=2
  45. stride=2
  46. [convolutional]
  47. batch_normalize=1
  48. filters=64
  49. size=3
  50. stride=1
  51. pad=1
  52. activation=leaky
  53. [maxpool]
  54. size=2
  55. stride=2
  56. [convolutional]
  57. batch_normalize=1
  58. filters=128
  59. size=3
  60. stride=1
  61. pad=1
  62. activation=leaky
  63. [maxpool]
  64. size=2
  65. stride=2
  66. [convolutional]
  67. batch_normalize=1
  68. filters=256
  69. size=3
  70. stride=1
  71. pad=1
  72. activation=leaky
  73. [maxpool]
  74. size=2
  75. stride=2
  76. [convolutional]
  77. batch_normalize=1
  78. filters=512
  79. size=3
  80. stride=1
  81. pad=1
  82. activation=leaky
  83. [maxpool]
  84. size=2
  85. stride=1
  86. [convolutional]
  87. batch_normalize=1
  88. filters=1024
  89. size=3
  90. stride=1
  91. pad=1
  92. activation=leaky
  93. ###########
  94. [crnn]
  95. batch_normalize=1
  96. size=3
  97. pad=1
  98. output=512
  99. hidden=256
  100. activation=leaky
  101. #[shortcut]
  102. #from=-2
  103. #activation=linear
  104. ###########
  105. [convolutional]
  106. batch_normalize=1
  107. filters=256
  108. size=1
  109. stride=1
  110. pad=1
  111. activation=leaky
  112. [convolutional]
  113. batch_normalize=1
  114. filters=512
  115. size=3
  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. [convolutional]
  127. size=1
  128. stride=1
  129. pad=1
  130. filters=18
  131. activation=linear
  132. [yolo]
  133. mask = 3,4,5
  134. anchors = 10,14, 23,27, 37,58, 81,82, 135,169, 344,319
  135. classes=1
  136. num=6
  137. jitter=.3
  138. ignore_thresh = .7
  139. truth_thresh = 1
  140. random=0
  141. [route]
  142. layers = -4
  143. [convolutional]
  144. batch_normalize=1
  145. filters=128
  146. size=1
  147. stride=1
  148. pad=1
  149. activation=leaky
  150. [upsample]
  151. stride=2
  152. [route]
  153. layers = -1, 8
  154. [crnn]
  155. batch_normalize=1
  156. size=3
  157. pad=1
  158. output=256
  159. hidden=128
  160. activation=leaky
  161. [convolutional]
  162. batch_normalize=1
  163. filters=256
  164. size=3
  165. stride=1
  166. pad=1
  167. activation=leaky
  168. [convolutional]
  169. size=1
  170. stride=1
  171. pad=1
  172. filters=18
  173. activation=linear
  174. [yolo]
  175. mask = 0,1,2
  176. anchors = 10,14, 23,27, 37,58, 81,82, 135,169, 344,319
  177. classes=1
  178. num=6
  179. jitter=.3
  180. ignore_thresh = .7
  181. truth_thresh = 1
  182. random=0