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Aug 25th, 2017
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  1. name: "CaffeNet"
  2. layers {
  3. name: "data"
  4. type: DATA
  5. top: "data"
  6. top: "label"
  7. data_param {
  8. source: "PATH1"
  9. backend: LMDB
  10. batch_size: 30
  11. }
  12. transform_param {
  13. crop_size: 224
  14. mean_file: "PATH3"
  15. mirror: true
  16. }
  17. include: { phase: TRAIN }
  18. }
  19. layers {
  20. name: "data"
  21. type: DATA
  22. top: "data"
  23. top: "label"
  24. data_param {
  25. source: "PATH2"
  26. backend: LMDB
  27. batch_size: 20
  28. }
  29. transform_param {
  30. crop_size: 224
  31. mean_file: "PATH3"
  32. mirror: false
  33. }
  34. include: { phase: TEST }
  35. }
  36. layers {
  37. name: "conv1"
  38. type: CONVOLUTION
  39. bottom: "data"
  40. top: "conv1"
  41. blobs_lr: 1
  42. blobs_lr: 2
  43. weight_decay: 1
  44. weight_decay: 0
  45. convolution_param {
  46. num_output: 96
  47. kernel_size: 7
  48. stride: 2
  49. weight_filler {
  50. type: "gaussian"
  51. std: 0.01
  52. }
  53. bias_filler {
  54. type: "constant"
  55. value: 0
  56. }
  57. }
  58. }
  59. layers {
  60. name: "relu1"
  61. type: RELU
  62. bottom: "conv1"
  63. top: "conv1"
  64. }
  65. layers {
  66. name: "norm1"
  67. type: LRN
  68. bottom: "conv1"
  69. top: "norm1"
  70. lrn_param {
  71. local_size: 5
  72. alpha: 0.0005
  73. beta: 0.75
  74. }
  75. }
  76. layers {
  77. name: "pool1"
  78. type: POOLING
  79. bottom: "norm1"
  80. top: "pool1"
  81. pooling_param {
  82. pool: MAX
  83. kernel_size: 3
  84. stride: 3
  85. }
  86. }
  87. layers {
  88. name: "conv2"
  89. type: CONVOLUTION
  90. bottom: "pool1"
  91. top: "conv2"
  92. blobs_lr: 1
  93. blobs_lr: 2
  94. weight_decay: 1
  95. weight_decay: 0
  96. convolution_param {
  97. num_output: 256
  98. pad: 2
  99. kernel_size: 5
  100. weight_filler {
  101. type: "gaussian"
  102. std: 0.01
  103. }
  104. bias_filler {
  105. type: "constant"
  106. value: 1
  107. }
  108. }
  109. }
  110. layers {
  111. name: "relu2"
  112. type: RELU
  113. bottom: "conv2"
  114. top: "conv2"
  115. }
  116. layers {
  117. name: "pool2"
  118. type: POOLING
  119. bottom: "conv2"
  120. top: "pool2"
  121. pooling_param {
  122. pool: MAX
  123. kernel_size: 2
  124. stride: 2
  125. }
  126. }
  127. layers {
  128. name: "conv3"
  129. type: CONVOLUTION
  130. bottom: "pool2"
  131. top: "conv3"
  132. blobs_lr: 1
  133. blobs_lr: 2
  134. weight_decay: 1
  135. weight_decay: 0
  136. convolution_param {
  137. num_output: 512
  138. pad: 1
  139. kernel_size: 3
  140. weight_filler {
  141. type: "gaussian"
  142. std: 0.01
  143. }
  144. bias_filler {
  145. type: "constant"
  146. value: 0
  147. }
  148. }
  149. }
  150. layers {
  151. name: "relu3"
  152. type: RELU
  153. bottom: "conv3"
  154. top: "conv3"
  155. }
  156. layers {
  157. name: "conv4"
  158. type: CONVOLUTION
  159. bottom: "conv3"
  160. top: "conv4"
  161. blobs_lr: 1
  162. blobs_lr: 2
  163. weight_decay: 1
  164. weight_decay: 0
  165. convolution_param {
  166. num_output: 512
  167. pad: 1
  168. kernel_size: 3
  169. weight_filler {
  170. type: "gaussian"
  171. std: 0.01
  172. }
  173. bias_filler {
  174. type: "constant"
  175. value: 1
  176. }
  177. }
  178. }
  179. layers {
  180. name: "relu4"
  181. type: RELU
  182. bottom: "conv4"
  183. top: "conv4"
  184. }
  185. layers {
  186. name: "conv5"
  187. type: CONVOLUTION
  188. bottom: "conv4"
  189. top: "conv5"
  190. blobs_lr: 1
  191. blobs_lr: 2
  192. weight_decay: 1
  193. weight_decay: 0
  194. convolution_param {
  195. num_output: 512
  196. pad: 1
  197. kernel_size: 3
  198. weight_filler {
  199. type: "gaussian"
  200. std: 0.01
  201. }
  202. bias_filler {
  203. type: "constant"
  204. value: 1
  205. }
  206. }
  207. }
  208. layers {
  209. name: "relu5"
  210. type: RELU
  211. bottom: "conv5"
  212. top: "conv5"
  213. }
  214. layers {
  215. name: "pool5"
  216. type: POOLING
  217. bottom: "conv5"
  218. top: "pool5"
  219. pooling_param {
  220. pool: MAX
  221. kernel_size: 3
  222. stride: 3
  223. }
  224. }
  225. layers {
  226. name: "fc6"
  227. type: INNER_PRODUCT
  228. bottom: "pool5"
  229. top: "fc6"
  230. blobs_lr: 1
  231. blobs_lr: 2
  232. weight_decay: 1
  233. weight_decay: 0
  234. inner_product_param {
  235. num_output: 4096
  236. weight_filler {
  237. type: "gaussian"
  238. std: 0.005
  239. }
  240. bias_filler {
  241. type: "constant"
  242. value: 1
  243. }
  244. }
  245. }
  246. layers {
  247. name: "relu6"
  248. type: RELU
  249. bottom: "fc6"
  250. top: "fc6"
  251. }
  252. layers {
  253. name: "drop6"
  254. type: DROPOUT
  255. bottom: "fc6"
  256. top: "fc6"
  257. dropout_param {
  258. dropout_ratio: 0.7
  259. }
  260. }
  261. layers {
  262. name: "fc7"
  263. type: INNER_PRODUCT
  264. bottom: "fc6"
  265. top: "fc7"
  266. blobs_lr: 9
  267. blobs_lr: 18
  268. weight_decay: 1
  269. weight_decay: 0
  270. inner_product_param {
  271. num_output: 4096
  272. weight_filler {
  273. type: "gaussian"
  274. std: 0.005
  275. }
  276. bias_filler {
  277. type: "constant"
  278. value: 1
  279. }
  280. }
  281. }
  282. layers {
  283. name: "relu7"
  284. type: RELU
  285. bottom: "fc7"
  286. top: "fc7"
  287. }
  288. layers {
  289. name: "drop7"
  290. type: DROPOUT
  291. bottom: "fc7"
  292. top: "fc7"
  293. dropout_param {
  294. dropout_ratio: 0.7
  295. }
  296. }
  297. layers {
  298. name: "fc8_test"
  299. type: INNER_PRODUCT
  300. bottom: "fc7"
  301. top: "fc8_test"
  302. blobs_lr: 12
  303. blobs_lr: 24
  304. weight_decay: 1
  305. weight_decay: 0
  306. inner_product_param {
  307. num_output: 8
  308. weight_filler {
  309. type: "gaussian"
  310. std: 0.01
  311. }
  312. bias_filler {
  313. type: "constant"
  314. value: 0
  315. }
  316. }
  317. }
  318. layers {
  319. name: "accuracy"
  320. type: ACCURACY
  321. bottom: "fc8_test"
  322. bottom: "label"
  323. top: "accuracy"
  324. include: { phase: TEST }
  325. }
  326. layers {
  327. name: "loss"
  328. type: SOFTMAX_LOSS
  329. bottom: "fc8_test"
  330. bottom: "label"
  331. top: "loss"
  332. }
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