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. channels=3
  11. min_crop=128
  12. max_crop=448
  13. burn_in=1000
  14. learning_rate=0.1
  15. policy=poly
  16. power=4
  17. max_batches=800000
  18. momentum=0.9
  19. decay=0.0005
  20. angle=7
  21. hue=.1
  22. saturation=.75
  23. exposure=.75
  24. aspect=.75
  25. [convolutional]
  26. batch_normalize=1
  27. filters=64
  28. size=7
  29. stride=2
  30. pad=1
  31. activation=leaky
  32. [maxpool]
  33. size=2
  34. stride=2
  35. [convolutional]
  36. batch_normalize=1
  37. filters=64
  38. size=1
  39. stride=1
  40. pad=1
  41. activation=leaky
  42. [convolutional]
  43. batch_normalize=1
  44. filters=64
  45. size=3
  46. stride=1
  47. pad=1
  48. activation=leaky
  49. [convolutional]
  50. batch_normalize=1
  51. filters=256
  52. size=1
  53. stride=1
  54. pad=1
  55. activation=linear
  56. [shortcut]
  57. from=-4
  58. activation=leaky
  59. [convolutional]
  60. batch_normalize=1
  61. filters=64
  62. size=1
  63. stride=1
  64. pad=1
  65. activation=leaky
  66. [convolutional]
  67. batch_normalize=1
  68. filters=64
  69. size=3
  70. stride=1
  71. pad=1
  72. activation=leaky
  73. [convolutional]
  74. batch_normalize=1
  75. filters=256
  76. size=1
  77. stride=1
  78. pad=1
  79. activation=linear
  80. [shortcut]
  81. from=-4
  82. activation=leaky
  83. [convolutional]
  84. batch_normalize=1
  85. filters=64
  86. size=1
  87. stride=1
  88. pad=1
  89. activation=leaky
  90. [convolutional]
  91. batch_normalize=1
  92. filters=64
  93. size=3
  94. stride=1
  95. pad=1
  96. activation=leaky
  97. [convolutional]
  98. batch_normalize=1
  99. filters=256
  100. size=1
  101. stride=1
  102. pad=1
  103. activation=linear
  104. [shortcut]
  105. from=-4
  106. activation=leaky
  107. [convolutional]
  108. batch_normalize=1
  109. filters=128
  110. size=1
  111. stride=1
  112. pad=1
  113. activation=leaky
  114. [convolutional]
  115. batch_normalize=1
  116. filters=128
  117. size=3
  118. stride=2
  119. pad=1
  120. activation=leaky
  121. [convolutional]
  122. batch_normalize=1
  123. filters=512
  124. size=1
  125. stride=1
  126. pad=1
  127. activation=linear
  128. [shortcut]
  129. from=-4
  130. activation=leaky
  131. [convolutional]
  132. batch_normalize=1
  133. filters=128
  134. size=1
  135. stride=1
  136. pad=1
  137. activation=leaky
  138. [convolutional]
  139. batch_normalize=1
  140. filters=128
  141. size=3
  142. stride=1
  143. pad=1
  144. activation=leaky
  145. [convolutional]
  146. batch_normalize=1
  147. filters=512
  148. size=1
  149. stride=1
  150. pad=1
  151. activation=linear
  152. [shortcut]
  153. from=-4
  154. activation=leaky
  155. [convolutional]
  156. batch_normalize=1
  157. filters=128
  158. size=1
  159. stride=1
  160. pad=1
  161. activation=leaky
  162. [convolutional]
  163. batch_normalize=1
  164. filters=128
  165. size=3
  166. stride=1
  167. pad=1
  168. activation=leaky
  169. [convolutional]
  170. batch_normalize=1
  171. filters=512
  172. size=1
  173. stride=1
  174. pad=1
  175. activation=linear
  176. [shortcut]
  177. from=-4
  178. activation=leaky
  179. [convolutional]
  180. batch_normalize=1
  181. filters=128
  182. size=1
  183. stride=1
  184. pad=1
  185. activation=leaky
  186. [convolutional]
  187. batch_normalize=1
  188. filters=128
  189. size=3
  190. stride=1
  191. pad=1
  192. activation=leaky
  193. [convolutional]
  194. batch_normalize=1
  195. filters=512
  196. size=1
  197. stride=1
  198. pad=1
  199. activation=linear
  200. [shortcut]
  201. from=-4
  202. activation=leaky
  203. # Conv 4
  204. [convolutional]
  205. batch_normalize=1
  206. filters=256
  207. size=1
  208. stride=1
  209. pad=1
  210. activation=leaky
  211. [convolutional]
  212. batch_normalize=1
  213. filters=256
  214. size=3
  215. stride=2
  216. pad=1
  217. activation=leaky
  218. [convolutional]
  219. batch_normalize=1
  220. filters=1024
  221. size=1
  222. stride=1
  223. pad=1
  224. activation=linear
  225. [shortcut]
  226. from=-4
  227. activation=leaky
  228. [convolutional]
  229. batch_normalize=1
  230. filters=256
  231. size=1
  232. stride=1
  233. pad=1
  234. activation=leaky
  235. [convolutional]
  236. batch_normalize=1
  237. filters=256
  238. size=3
  239. stride=1
  240. pad=1
  241. activation=leaky
  242. [convolutional]
  243. batch_normalize=1
  244. filters=1024
  245. size=1
  246. stride=1
  247. pad=1
  248. activation=linear
  249. [shortcut]
  250. from=-4
  251. activation=leaky
  252. [convolutional]
  253. batch_normalize=1
  254. filters=256
  255. size=1
  256. stride=1
  257. pad=1
  258. activation=leaky
  259. [convolutional]
  260. batch_normalize=1
  261. filters=256
  262. size=3
  263. stride=1
  264. pad=1
  265. activation=leaky
  266. [convolutional]
  267. batch_normalize=1
  268. filters=1024
  269. size=1
  270. stride=1
  271. pad=1
  272. activation=linear
  273. [shortcut]
  274. from=-4
  275. activation=leaky
  276. [convolutional]
  277. batch_normalize=1
  278. filters=256
  279. size=1
  280. stride=1
  281. pad=1
  282. activation=leaky
  283. [convolutional]
  284. batch_normalize=1
  285. filters=256
  286. size=3
  287. stride=1
  288. pad=1
  289. activation=leaky
  290. [convolutional]
  291. batch_normalize=1
  292. filters=1024
  293. size=1
  294. stride=1
  295. pad=1
  296. activation=linear
  297. [shortcut]
  298. from=-4
  299. activation=leaky
  300. [convolutional]
  301. batch_normalize=1
  302. filters=256
  303. size=1
  304. stride=1
  305. pad=1
  306. activation=leaky
  307. [convolutional]
  308. batch_normalize=1
  309. filters=256
  310. size=3
  311. stride=1
  312. pad=1
  313. activation=leaky
  314. [convolutional]
  315. batch_normalize=1
  316. filters=1024
  317. size=1
  318. stride=1
  319. pad=1
  320. activation=linear
  321. [shortcut]
  322. from=-4
  323. activation=leaky
  324. [convolutional]
  325. batch_normalize=1
  326. filters=256
  327. size=1
  328. stride=1
  329. pad=1
  330. activation=leaky
  331. [convolutional]
  332. batch_normalize=1
  333. filters=256
  334. size=3
  335. stride=1
  336. pad=1
  337. activation=leaky
  338. [convolutional]
  339. batch_normalize=1
  340. filters=1024
  341. size=1
  342. stride=1
  343. pad=1
  344. activation=linear
  345. [shortcut]
  346. from=-4
  347. activation=leaky
  348. #Conv 5
  349. [convolutional]
  350. batch_normalize=1
  351. filters=512
  352. size=1
  353. stride=1
  354. pad=1
  355. activation=leaky
  356. [convolutional]
  357. batch_normalize=1
  358. filters=512
  359. size=3
  360. stride=2
  361. pad=1
  362. activation=leaky
  363. [convolutional]
  364. batch_normalize=1
  365. filters=2048
  366. size=1
  367. stride=1
  368. pad=1
  369. activation=linear
  370. [shortcut]
  371. from=-4
  372. activation=leaky
  373. [convolutional]
  374. batch_normalize=1
  375. filters=512
  376. size=1
  377. stride=1
  378. pad=1
  379. activation=leaky
  380. [convolutional]
  381. batch_normalize=1
  382. filters=512
  383. size=3
  384. stride=1
  385. pad=1
  386. activation=leaky
  387. [convolutional]
  388. batch_normalize=1
  389. filters=2048
  390. size=1
  391. stride=1
  392. pad=1
  393. activation=linear
  394. [shortcut]
  395. from=-4
  396. activation=leaky
  397. [convolutional]
  398. batch_normalize=1
  399. filters=512
  400. size=1
  401. stride=1
  402. pad=1
  403. activation=leaky
  404. [convolutional]
  405. batch_normalize=1
  406. filters=512
  407. size=3
  408. stride=1
  409. pad=1
  410. activation=leaky
  411. [convolutional]
  412. batch_normalize=1
  413. filters=2048
  414. size=1
  415. stride=1
  416. pad=1
  417. activation=linear
  418. [shortcut]
  419. from=-4
  420. activation=leaky
  421. [avgpool]
  422. [convolutional]
  423. filters=1000
  424. size=1
  425. stride=1
  426. pad=1
  427. activation=linear
  428. [softmax]
  429. groups=1