resnet50.cfg 5.1 KB

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  1. [net]
  2. # Training
  3. # batch=128
  4. # subdivisions=4
  5. # Testing
  6. batch=1
  7. subdivisions=1
  8. height=256
  9. width=256
  10. max_crop=448
  11. channels=3
  12. momentum=0.9
  13. decay=0.0005
  14. burn_in=1000
  15. learning_rate=0.1
  16. policy=poly
  17. power=4
  18. max_batches=1600000
  19. angle=7
  20. hue=.1
  21. saturation=.75
  22. exposure=.75
  23. aspect=.75
  24. [convolutional]
  25. batch_normalize=1
  26. filters=64
  27. size=7
  28. stride=2
  29. pad=1
  30. activation=leaky
  31. [maxpool]
  32. size=2
  33. stride=2
  34. [convolutional]
  35. batch_normalize=1
  36. filters=64
  37. size=1
  38. stride=1
  39. pad=1
  40. activation=leaky
  41. [convolutional]
  42. batch_normalize=1
  43. filters=64
  44. size=3
  45. stride=1
  46. pad=1
  47. activation=leaky
  48. [convolutional]
  49. batch_normalize=1
  50. filters=256
  51. size=1
  52. stride=1
  53. pad=1
  54. activation=linear
  55. [shortcut]
  56. from=-4
  57. activation=leaky
  58. [convolutional]
  59. batch_normalize=1
  60. filters=64
  61. size=1
  62. stride=1
  63. pad=1
  64. activation=leaky
  65. [convolutional]
  66. batch_normalize=1
  67. filters=64
  68. size=3
  69. stride=1
  70. pad=1
  71. activation=leaky
  72. [convolutional]
  73. batch_normalize=1
  74. filters=256
  75. size=1
  76. stride=1
  77. pad=1
  78. activation=linear
  79. [shortcut]
  80. from=-4
  81. activation=leaky
  82. [convolutional]
  83. batch_normalize=1
  84. filters=64
  85. size=1
  86. stride=1
  87. pad=1
  88. activation=leaky
  89. [convolutional]
  90. batch_normalize=1
  91. filters=64
  92. size=3
  93. stride=1
  94. pad=1
  95. activation=leaky
  96. [convolutional]
  97. batch_normalize=1
  98. filters=256
  99. size=1
  100. stride=1
  101. pad=1
  102. activation=linear
  103. [shortcut]
  104. from=-4
  105. activation=leaky
  106. [convolutional]
  107. batch_normalize=1
  108. filters=128
  109. size=1
  110. stride=1
  111. pad=1
  112. activation=leaky
  113. [convolutional]
  114. batch_normalize=1
  115. filters=128
  116. size=3
  117. stride=2
  118. pad=1
  119. activation=leaky
  120. [convolutional]
  121. batch_normalize=1
  122. filters=512
  123. size=1
  124. stride=1
  125. pad=1
  126. activation=linear
  127. [shortcut]
  128. from=-4
  129. activation=leaky
  130. [convolutional]
  131. batch_normalize=1
  132. filters=128
  133. size=1
  134. stride=1
  135. pad=1
  136. activation=leaky
  137. [convolutional]
  138. batch_normalize=1
  139. filters=128
  140. size=3
  141. stride=1
  142. pad=1
  143. activation=leaky
  144. [convolutional]
  145. batch_normalize=1
  146. filters=512
  147. size=1
  148. stride=1
  149. pad=1
  150. activation=linear
  151. [shortcut]
  152. from=-4
  153. activation=leaky
  154. [convolutional]
  155. batch_normalize=1
  156. filters=128
  157. size=1
  158. stride=1
  159. pad=1
  160. activation=leaky
  161. [convolutional]
  162. batch_normalize=1
  163. filters=128
  164. size=3
  165. stride=1
  166. pad=1
  167. activation=leaky
  168. [convolutional]
  169. batch_normalize=1
  170. filters=512
  171. size=1
  172. stride=1
  173. pad=1
  174. activation=linear
  175. [shortcut]
  176. from=-4
  177. activation=leaky
  178. [convolutional]
  179. batch_normalize=1
  180. filters=128
  181. size=1
  182. stride=1
  183. pad=1
  184. activation=leaky
  185. [convolutional]
  186. batch_normalize=1
  187. filters=128
  188. size=3
  189. stride=1
  190. pad=1
  191. activation=leaky
  192. [convolutional]
  193. batch_normalize=1
  194. filters=512
  195. size=1
  196. stride=1
  197. pad=1
  198. activation=linear
  199. [shortcut]
  200. from=-4
  201. activation=leaky
  202. # Conv 4
  203. [convolutional]
  204. batch_normalize=1
  205. filters=256
  206. size=1
  207. stride=1
  208. pad=1
  209. activation=leaky
  210. [convolutional]
  211. batch_normalize=1
  212. filters=256
  213. size=3
  214. stride=2
  215. pad=1
  216. activation=leaky
  217. [convolutional]
  218. batch_normalize=1
  219. filters=1024
  220. size=1
  221. stride=1
  222. pad=1
  223. activation=linear
  224. [shortcut]
  225. from=-4
  226. activation=leaky
  227. [convolutional]
  228. batch_normalize=1
  229. filters=256
  230. size=1
  231. stride=1
  232. pad=1
  233. activation=leaky
  234. [convolutional]
  235. batch_normalize=1
  236. filters=256
  237. size=3
  238. stride=1
  239. pad=1
  240. activation=leaky
  241. [convolutional]
  242. batch_normalize=1
  243. filters=1024
  244. size=1
  245. stride=1
  246. pad=1
  247. activation=linear
  248. [shortcut]
  249. from=-4
  250. activation=leaky
  251. [convolutional]
  252. batch_normalize=1
  253. filters=256
  254. size=1
  255. stride=1
  256. pad=1
  257. activation=leaky
  258. [convolutional]
  259. batch_normalize=1
  260. filters=256
  261. size=3
  262. stride=1
  263. pad=1
  264. activation=leaky
  265. [convolutional]
  266. batch_normalize=1
  267. filters=1024
  268. size=1
  269. stride=1
  270. pad=1
  271. activation=linear
  272. [shortcut]
  273. from=-4
  274. activation=leaky
  275. [convolutional]
  276. batch_normalize=1
  277. filters=256
  278. size=1
  279. stride=1
  280. pad=1
  281. activation=leaky
  282. [convolutional]
  283. batch_normalize=1
  284. filters=256
  285. size=3
  286. stride=1
  287. pad=1
  288. activation=leaky
  289. [convolutional]
  290. batch_normalize=1
  291. filters=1024
  292. size=1
  293. stride=1
  294. pad=1
  295. activation=linear
  296. [shortcut]
  297. from=-4
  298. activation=leaky
  299. [convolutional]
  300. batch_normalize=1
  301. filters=256
  302. size=1
  303. stride=1
  304. pad=1
  305. activation=leaky
  306. [convolutional]
  307. batch_normalize=1
  308. filters=256
  309. size=3
  310. stride=1
  311. pad=1
  312. activation=leaky
  313. [convolutional]
  314. batch_normalize=1
  315. filters=1024
  316. size=1
  317. stride=1
  318. pad=1
  319. activation=linear
  320. [shortcut]
  321. from=-4
  322. activation=leaky
  323. [convolutional]
  324. batch_normalize=1
  325. filters=256
  326. size=1
  327. stride=1
  328. pad=1
  329. activation=leaky
  330. [convolutional]
  331. batch_normalize=1
  332. filters=256
  333. size=3
  334. stride=1
  335. pad=1
  336. activation=leaky
  337. [convolutional]
  338. batch_normalize=1
  339. filters=1024
  340. size=1
  341. stride=1
  342. pad=1
  343. activation=linear
  344. [shortcut]
  345. from=-4
  346. activation=leaky
  347. #Conv 5
  348. [convolutional]
  349. batch_normalize=1
  350. filters=512
  351. size=1
  352. stride=1
  353. pad=1
  354. activation=leaky
  355. [convolutional]
  356. batch_normalize=1
  357. filters=512
  358. size=3
  359. stride=2
  360. pad=1
  361. activation=leaky
  362. [convolutional]
  363. batch_normalize=1
  364. filters=2048
  365. size=1
  366. stride=1
  367. pad=1
  368. activation=linear
  369. [shortcut]
  370. from=-4
  371. activation=leaky
  372. [convolutional]
  373. batch_normalize=1
  374. filters=512
  375. size=1
  376. stride=1
  377. pad=1
  378. activation=leaky
  379. [convolutional]
  380. batch_normalize=1
  381. filters=512
  382. size=3
  383. stride=1
  384. pad=1
  385. activation=leaky
  386. [convolutional]
  387. batch_normalize=1
  388. filters=2048
  389. size=1
  390. stride=1
  391. pad=1
  392. activation=linear
  393. [shortcut]
  394. from=-4
  395. activation=leaky
  396. [convolutional]
  397. batch_normalize=1
  398. filters=512
  399. size=1
  400. stride=1
  401. pad=1
  402. activation=leaky
  403. [convolutional]
  404. batch_normalize=1
  405. filters=512
  406. size=3
  407. stride=1
  408. pad=1
  409. activation=leaky
  410. [convolutional]
  411. batch_normalize=1
  412. filters=2048
  413. size=1
  414. stride=1
  415. pad=1
  416. activation=linear
  417. [shortcut]
  418. from=-4
  419. activation=leaky
  420. [convolutional]
  421. filters=1000
  422. size=1
  423. stride=1
  424. pad=1
  425. activation=linear
  426. [avgpool]
  427. [softmax]
  428. groups=1
  429. [cost]
  430. type=sse