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Jan 13th, 2016
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  1. name: "mv_16f"
  2. layer {
  3. name: "data"
  4. type: "HDF5Data"
  5. top: "data"
  6. top: "label"
  7. include {
  8. phase: TRAIN
  9. }
  10. hdf5_data_param {
  11. source: "/home/anilil/caffe/models/mv16f/list.txt"
  12. batch_size: 100
  13. }
  14. }
  15. layer {
  16. name: "data"
  17. type: "HDF5Data"
  18. top: "data"
  19. top: "label"
  20. include {
  21. phase: TEST
  22. }
  23. hdf5_data_param {
  24. source: "/home/anilil/caffe/models/mv16f/list.txt"
  25. batch_size: 5
  26. }
  27. }
  28. #####################Conv Layer Start##################################
  29. layer {
  30. name: "conv1"
  31. type: "Convolution"
  32. bottom: "data"
  33. top: "conv1"
  34. param {
  35. lr_mult: 1
  36. decay_mult: 1
  37. }
  38. param {
  39. lr_mult: 1
  40. decay_mult: 1
  41. }
  42. convolution_param {
  43. num_output: 64
  44. kernel_size: 3
  45. weight_filler {
  46. type: "xavier"
  47. }
  48. bias_filler {
  49. type: "constant"
  50. value: 0
  51. }
  52. }
  53. }
  54. layer {
  55. name: "relu1"
  56. type: "ReLU"
  57. bottom: "conv1"
  58. top: "conv1"
  59. }
  60. layer {
  61. name: "pool1"
  62. type: "Pooling"
  63. bottom: "conv1"
  64. top: "pool1"
  65. pooling_param {
  66. pool: MAX
  67. kernel_size: 2
  68. stride: 2
  69. }
  70. }
  71. #####################Conv Layer Start##################################
  72. layer {
  73. name: "conv2"
  74. type: "Convolution"
  75. bottom: "pool1"
  76. top: "conv2"
  77. param {
  78. lr_mult: 1
  79. decay_mult: 1
  80. }
  81. param {
  82. lr_mult: 1
  83. decay_mult: 1
  84. }
  85. convolution_param {
  86. num_output: 128
  87. kernel_size: 3
  88. stride: 1
  89. weight_filler {
  90. type: "xavier"
  91. }
  92. bias_filler {
  93. type: "constant"
  94. value: 0
  95. }
  96. }
  97. }
  98. layer {
  99. name: "relu2"
  100. type: "ReLU"
  101. bottom: "conv2"
  102. top: "conv2"
  103. }
  104. layer {
  105. name: "pool2"
  106. type: "Pooling"
  107. bottom: "conv2"
  108. top: "pool2"
  109. pooling_param {
  110. pool: MAX
  111. kernel_size: 2
  112. stride: 2
  113. }
  114. }
  115.  
  116. #####################Conv Layer Start##################################
  117. layer {
  118. name: "conv3"
  119. type: "Convolution"
  120. bottom: "pool2"
  121. top: "conv3"
  122. param {
  123. lr_mult: 1
  124. decay_mult: 1
  125. }
  126. param {
  127. lr_mult: 1
  128. decay_mult: 1
  129. }
  130. convolution_param {
  131. num_output: 256
  132. kernel_size: 3
  133. stride: 1
  134. weight_filler {
  135. type: "xavier"
  136. }
  137. bias_filler {
  138. type: "constant"
  139. value: 0
  140. }
  141. }
  142. }
  143. layer {
  144. name: "relu3"
  145. type: "ReLU"
  146. bottom: "conv3"
  147. top: "conv3"
  148. }
  149. layer {
  150. name: "pool3"
  151. type: "Pooling"
  152. bottom: "conv3"
  153. top: "pool3"
  154. pooling_param {
  155. pool: MAX
  156. kernel_size: 2
  157. stride: 2
  158. }
  159. }
  160. #####################Conv Layer Start##################################
  161. layer {
  162. name: "conv4"
  163. type: "Convolution"
  164. bottom: "pool3"
  165. top: "conv4"
  166. param {
  167. lr_mult: 1
  168. decay_mult: 1
  169. }
  170. param {
  171. lr_mult: 1
  172. decay_mult: 1
  173. }
  174. convolution_param {
  175. num_output: 256
  176. kernel_size: 3
  177. stride: 1
  178. weight_filler {
  179. type: "xavier"
  180. }
  181. bias_filler {
  182. type: "constant"
  183. value: 0
  184. }
  185. }
  186. }
  187. layer {
  188. name: "relu4"
  189. type: "ReLU"
  190. bottom: "conv4"
  191. top: "conv4"
  192. }
  193. layer {
  194. name: "pool4"
  195. type: "Pooling"
  196. bottom: "conv4"
  197. top: "pool4"
  198. pooling_param {
  199. pool: MAX
  200. kernel_size: 2
  201. stride: 2
  202. }
  203. }
  204. ##################### IP Layer Start##################################
  205. layer {
  206. name: "fc6"
  207. type: "InnerProduct"
  208. bottom: "pool4"
  209. top: "fc6"
  210. param {
  211. lr_mult: 1
  212. decay_mult: 1
  213. }
  214. param {
  215. lr_mult: 2
  216. decay_mult: 0
  217. }
  218. inner_product_param {
  219. num_output: 2048
  220. weight_filler {
  221. type: "gaussian"
  222. std: 0.005
  223. }
  224. bias_filler {
  225. type: "constant"
  226. value: 0.1
  227. }
  228. }
  229. }
  230. layer {
  231. name: "relu6"
  232. type: "ReLU"
  233. bottom: "fc6"
  234. top: "fc6"
  235. }
  236. layer {
  237. name: "drop6"
  238. type: "Dropout"
  239. bottom: "fc6"
  240. top: "fc6"
  241. dropout_param {
  242. dropout_ratio: 0.5
  243. }
  244. }
  245. ##################### IP Layer Start##################################
  246.  
  247. layer {
  248. name: "fc7"
  249. type: "InnerProduct"
  250. bottom: "fc6"
  251. top: "fc7"
  252. param {
  253. lr_mult: 1
  254. decay_mult: 1
  255. }
  256. param {
  257. lr_mult: 2
  258. decay_mult: 0
  259. }
  260. inner_product_param {
  261. num_output: 4096
  262. weight_filler {
  263. type: "gaussian"
  264. std: 0.005
  265. }
  266. bias_filler {
  267. type: "constant"
  268. value: 0.1
  269. }
  270. }
  271. }
  272. layer {
  273. name: "relu7"
  274. type: "ReLU"
  275. bottom: "fc7"
  276. top: "fc7"
  277. }
  278. layer {
  279. name: "drop7"
  280. type: "Dropout"
  281. bottom: "fc7"
  282. top: "fc7"
  283. dropout_param {
  284. dropout_ratio: 0.5
  285. }
  286. }
  287. ##################### IP Layer Start##################################
  288.  
  289. layer {
  290. name: "fc8"
  291. type: "InnerProduct"
  292. bottom: "fc7"
  293. top: "fc8"
  294. param {
  295. lr_mult: 1
  296. decay_mult: 1
  297. }
  298. param {
  299. lr_mult: 2
  300. decay_mult: 0
  301. }
  302. inner_product_param {
  303. num_output: 101
  304. weight_filler {
  305. type: "xavier"
  306. }
  307. bias_filler {
  308. type: "constant"
  309. value: 0
  310. }
  311. }
  312. }
  313. layer {
  314. name: "accuracy"
  315. type: "Accuracy"
  316. bottom: "fc8"
  317. bottom: "label"
  318. top: "accuracy"
  319. include {
  320. phase: TEST
  321. }
  322. }
  323. layer {
  324. name: "loss"
  325. type: "SoftmaxWithLoss"
  326. bottom: "fc8"
  327. bottom: "label"
  328. top: "loss"
  329. }
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