yolov3-spp.cfg 8.4 KB

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  1. [net]
  2. # Testing
  3. batch=1
  4. subdivisions=1
  5. # Training
  6. # batch=64
  7. # subdivisions=16
  8. width=608
  9. height=608
  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. learning_rate=0.001
  18. burn_in=1000
  19. max_batches = 500200
  20. policy=steps
  21. steps=400000,450000
  22. scales=.1,.1
  23. [convolutional]
  24. batch_normalize=1
  25. filters=32
  26. size=3
  27. stride=1
  28. pad=1
  29. activation=leaky
  30. # Downsample
  31. [convolutional]
  32. batch_normalize=1
  33. filters=64
  34. size=3
  35. stride=2
  36. pad=1
  37. activation=leaky
  38. [convolutional]
  39. batch_normalize=1
  40. filters=32
  41. size=1
  42. stride=1
  43. pad=1
  44. activation=leaky
  45. [convolutional]
  46. batch_normalize=1
  47. filters=64
  48. size=3
  49. stride=1
  50. pad=1
  51. activation=leaky
  52. [shortcut]
  53. from=-3
  54. activation=linear
  55. # Downsample
  56. [convolutional]
  57. batch_normalize=1
  58. filters=128
  59. size=3
  60. stride=2
  61. pad=1
  62. activation=leaky
  63. [convolutional]
  64. batch_normalize=1
  65. filters=64
  66. size=1
  67. stride=1
  68. pad=1
  69. activation=leaky
  70. [convolutional]
  71. batch_normalize=1
  72. filters=128
  73. size=3
  74. stride=1
  75. pad=1
  76. activation=leaky
  77. [shortcut]
  78. from=-3
  79. activation=linear
  80. [convolutional]
  81. batch_normalize=1
  82. filters=64
  83. size=1
  84. stride=1
  85. pad=1
  86. activation=leaky
  87. [convolutional]
  88. batch_normalize=1
  89. filters=128
  90. size=3
  91. stride=1
  92. pad=1
  93. activation=leaky
  94. [shortcut]
  95. from=-3
  96. activation=linear
  97. # Downsample
  98. [convolutional]
  99. batch_normalize=1
  100. filters=256
  101. size=3
  102. stride=2
  103. pad=1
  104. activation=leaky
  105. [convolutional]
  106. batch_normalize=1
  107. filters=128
  108. size=1
  109. stride=1
  110. pad=1
  111. activation=leaky
  112. [convolutional]
  113. batch_normalize=1
  114. filters=256
  115. size=3
  116. stride=1
  117. pad=1
  118. activation=leaky
  119. [shortcut]
  120. from=-3
  121. activation=linear
  122. [convolutional]
  123. batch_normalize=1
  124. filters=128
  125. size=1
  126. stride=1
  127. pad=1
  128. activation=leaky
  129. [convolutional]
  130. batch_normalize=1
  131. filters=256
  132. size=3
  133. stride=1
  134. pad=1
  135. activation=leaky
  136. [shortcut]
  137. from=-3
  138. activation=linear
  139. [convolutional]
  140. batch_normalize=1
  141. filters=128
  142. size=1
  143. stride=1
  144. pad=1
  145. activation=leaky
  146. [convolutional]
  147. batch_normalize=1
  148. filters=256
  149. size=3
  150. stride=1
  151. pad=1
  152. activation=leaky
  153. [shortcut]
  154. from=-3
  155. activation=linear
  156. [convolutional]
  157. batch_normalize=1
  158. filters=128
  159. size=1
  160. stride=1
  161. pad=1
  162. activation=leaky
  163. [convolutional]
  164. batch_normalize=1
  165. filters=256
  166. size=3
  167. stride=1
  168. pad=1
  169. activation=leaky
  170. [shortcut]
  171. from=-3
  172. activation=linear
  173. [convolutional]
  174. batch_normalize=1
  175. filters=128
  176. size=1
  177. stride=1
  178. pad=1
  179. activation=leaky
  180. [convolutional]
  181. batch_normalize=1
  182. filters=256
  183. size=3
  184. stride=1
  185. pad=1
  186. activation=leaky
  187. [shortcut]
  188. from=-3
  189. activation=linear
  190. [convolutional]
  191. batch_normalize=1
  192. filters=128
  193. size=1
  194. stride=1
  195. pad=1
  196. activation=leaky
  197. [convolutional]
  198. batch_normalize=1
  199. filters=256
  200. size=3
  201. stride=1
  202. pad=1
  203. activation=leaky
  204. [shortcut]
  205. from=-3
  206. activation=linear
  207. [convolutional]
  208. batch_normalize=1
  209. filters=128
  210. size=1
  211. stride=1
  212. pad=1
  213. activation=leaky
  214. [convolutional]
  215. batch_normalize=1
  216. filters=256
  217. size=3
  218. stride=1
  219. pad=1
  220. activation=leaky
  221. [shortcut]
  222. from=-3
  223. activation=linear
  224. [convolutional]
  225. batch_normalize=1
  226. filters=128
  227. size=1
  228. stride=1
  229. pad=1
  230. activation=leaky
  231. [convolutional]
  232. batch_normalize=1
  233. filters=256
  234. size=3
  235. stride=1
  236. pad=1
  237. activation=leaky
  238. [shortcut]
  239. from=-3
  240. activation=linear
  241. # Downsample
  242. [convolutional]
  243. batch_normalize=1
  244. filters=512
  245. size=3
  246. stride=2
  247. pad=1
  248. activation=leaky
  249. [convolutional]
  250. batch_normalize=1
  251. filters=256
  252. size=1
  253. stride=1
  254. pad=1
  255. activation=leaky
  256. [convolutional]
  257. batch_normalize=1
  258. filters=512
  259. size=3
  260. stride=1
  261. pad=1
  262. activation=leaky
  263. [shortcut]
  264. from=-3
  265. activation=linear
  266. [convolutional]
  267. batch_normalize=1
  268. filters=256
  269. size=1
  270. stride=1
  271. pad=1
  272. activation=leaky
  273. [convolutional]
  274. batch_normalize=1
  275. filters=512
  276. size=3
  277. stride=1
  278. pad=1
  279. activation=leaky
  280. [shortcut]
  281. from=-3
  282. activation=linear
  283. [convolutional]
  284. batch_normalize=1
  285. filters=256
  286. size=1
  287. stride=1
  288. pad=1
  289. activation=leaky
  290. [convolutional]
  291. batch_normalize=1
  292. filters=512
  293. size=3
  294. stride=1
  295. pad=1
  296. activation=leaky
  297. [shortcut]
  298. from=-3
  299. activation=linear
  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=512
  310. size=3
  311. stride=1
  312. pad=1
  313. activation=leaky
  314. [shortcut]
  315. from=-3
  316. activation=linear
  317. [convolutional]
  318. batch_normalize=1
  319. filters=256
  320. size=1
  321. stride=1
  322. pad=1
  323. activation=leaky
  324. [convolutional]
  325. batch_normalize=1
  326. filters=512
  327. size=3
  328. stride=1
  329. pad=1
  330. activation=leaky
  331. [shortcut]
  332. from=-3
  333. activation=linear
  334. [convolutional]
  335. batch_normalize=1
  336. filters=256
  337. size=1
  338. stride=1
  339. pad=1
  340. activation=leaky
  341. [convolutional]
  342. batch_normalize=1
  343. filters=512
  344. size=3
  345. stride=1
  346. pad=1
  347. activation=leaky
  348. [shortcut]
  349. from=-3
  350. activation=linear
  351. [convolutional]
  352. batch_normalize=1
  353. filters=256
  354. size=1
  355. stride=1
  356. pad=1
  357. activation=leaky
  358. [convolutional]
  359. batch_normalize=1
  360. filters=512
  361. size=3
  362. stride=1
  363. pad=1
  364. activation=leaky
  365. [shortcut]
  366. from=-3
  367. activation=linear
  368. [convolutional]
  369. batch_normalize=1
  370. filters=256
  371. size=1
  372. stride=1
  373. pad=1
  374. activation=leaky
  375. [convolutional]
  376. batch_normalize=1
  377. filters=512
  378. size=3
  379. stride=1
  380. pad=1
  381. activation=leaky
  382. [shortcut]
  383. from=-3
  384. activation=linear
  385. # Downsample
  386. [convolutional]
  387. batch_normalize=1
  388. filters=1024
  389. size=3
  390. stride=2
  391. pad=1
  392. activation=leaky
  393. [convolutional]
  394. batch_normalize=1
  395. filters=512
  396. size=1
  397. stride=1
  398. pad=1
  399. activation=leaky
  400. [convolutional]
  401. batch_normalize=1
  402. filters=1024
  403. size=3
  404. stride=1
  405. pad=1
  406. activation=leaky
  407. [shortcut]
  408. from=-3
  409. activation=linear
  410. [convolutional]
  411. batch_normalize=1
  412. filters=512
  413. size=1
  414. stride=1
  415. pad=1
  416. activation=leaky
  417. [convolutional]
  418. batch_normalize=1
  419. filters=1024
  420. size=3
  421. stride=1
  422. pad=1
  423. activation=leaky
  424. [shortcut]
  425. from=-3
  426. activation=linear
  427. [convolutional]
  428. batch_normalize=1
  429. filters=512
  430. size=1
  431. stride=1
  432. pad=1
  433. activation=leaky
  434. [convolutional]
  435. batch_normalize=1
  436. filters=1024
  437. size=3
  438. stride=1
  439. pad=1
  440. activation=leaky
  441. [shortcut]
  442. from=-3
  443. activation=linear
  444. [convolutional]
  445. batch_normalize=1
  446. filters=512
  447. size=1
  448. stride=1
  449. pad=1
  450. activation=leaky
  451. [convolutional]
  452. batch_normalize=1
  453. filters=1024
  454. size=3
  455. stride=1
  456. pad=1
  457. activation=leaky
  458. [shortcut]
  459. from=-3
  460. activation=linear
  461. ######################
  462. [convolutional]
  463. batch_normalize=1
  464. filters=512
  465. size=1
  466. stride=1
  467. pad=1
  468. activation=leaky
  469. [convolutional]
  470. batch_normalize=1
  471. size=3
  472. stride=1
  473. pad=1
  474. filters=1024
  475. activation=leaky
  476. [convolutional]
  477. batch_normalize=1
  478. filters=512
  479. size=1
  480. stride=1
  481. pad=1
  482. activation=leaky
  483. ### SPP ###
  484. [maxpool]
  485. stride=1
  486. size=5
  487. [route]
  488. layers=-2
  489. [maxpool]
  490. stride=1
  491. size=9
  492. [route]
  493. layers=-4
  494. [maxpool]
  495. stride=1
  496. size=13
  497. [route]
  498. layers=-1,-3,-5,-6
  499. ### End SPP ###
  500. [convolutional]
  501. batch_normalize=1
  502. filters=512
  503. size=1
  504. stride=1
  505. pad=1
  506. activation=leaky
  507. [convolutional]
  508. batch_normalize=1
  509. size=3
  510. stride=1
  511. pad=1
  512. filters=1024
  513. activation=leaky
  514. [convolutional]
  515. batch_normalize=1
  516. filters=512
  517. size=1
  518. stride=1
  519. pad=1
  520. activation=leaky
  521. [convolutional]
  522. batch_normalize=1
  523. size=3
  524. stride=1
  525. pad=1
  526. filters=1024
  527. activation=leaky
  528. [convolutional]
  529. size=1
  530. stride=1
  531. pad=1
  532. filters=255
  533. activation=linear
  534. [yolo]
  535. mask = 6,7,8
  536. anchors = 10,13, 16,30, 33,23, 30,61, 62,45, 59,119, 116,90, 156,198, 373,326
  537. classes=80
  538. num=9
  539. jitter=.3
  540. ignore_thresh = .7
  541. truth_thresh = 1
  542. random=1
  543. [route]
  544. layers = -4
  545. [convolutional]
  546. batch_normalize=1
  547. filters=256
  548. size=1
  549. stride=1
  550. pad=1
  551. activation=leaky
  552. [upsample]
  553. stride=2
  554. [route]
  555. layers = -1, 61
  556. [convolutional]
  557. batch_normalize=1
  558. filters=256
  559. size=1
  560. stride=1
  561. pad=1
  562. activation=leaky
  563. [convolutional]
  564. batch_normalize=1
  565. size=3
  566. stride=1
  567. pad=1
  568. filters=512
  569. activation=leaky
  570. [convolutional]
  571. batch_normalize=1
  572. filters=256
  573. size=1
  574. stride=1
  575. pad=1
  576. activation=leaky
  577. [convolutional]
  578. batch_normalize=1
  579. size=3
  580. stride=1
  581. pad=1
  582. filters=512
  583. activation=leaky
  584. [convolutional]
  585. batch_normalize=1
  586. filters=256
  587. size=1
  588. stride=1
  589. pad=1
  590. activation=leaky
  591. [convolutional]
  592. batch_normalize=1
  593. size=3
  594. stride=1
  595. pad=1
  596. filters=512
  597. activation=leaky
  598. [convolutional]
  599. size=1
  600. stride=1
  601. pad=1
  602. filters=255
  603. activation=linear
  604. [yolo]
  605. mask = 3,4,5
  606. anchors = 10,13, 16,30, 33,23, 30,61, 62,45, 59,119, 116,90, 156,198, 373,326
  607. classes=80
  608. num=9
  609. jitter=.3
  610. ignore_thresh = .7
  611. truth_thresh = 1
  612. random=1
  613. [route]
  614. layers = -4
  615. [convolutional]
  616. batch_normalize=1
  617. filters=128
  618. size=1
  619. stride=1
  620. pad=1
  621. activation=leaky
  622. [upsample]
  623. stride=2
  624. [route]
  625. layers = -1, 36
  626. [convolutional]
  627. batch_normalize=1
  628. filters=128
  629. size=1
  630. stride=1
  631. pad=1
  632. activation=leaky
  633. [convolutional]
  634. batch_normalize=1
  635. size=3
  636. stride=1
  637. pad=1
  638. filters=256
  639. activation=leaky
  640. [convolutional]
  641. batch_normalize=1
  642. filters=128
  643. size=1
  644. stride=1
  645. pad=1
  646. activation=leaky
  647. [convolutional]
  648. batch_normalize=1
  649. size=3
  650. stride=1
  651. pad=1
  652. filters=256
  653. activation=leaky
  654. [convolutional]
  655. batch_normalize=1
  656. filters=128
  657. size=1
  658. stride=1
  659. pad=1
  660. activation=leaky
  661. [convolutional]
  662. batch_normalize=1
  663. size=3
  664. stride=1
  665. pad=1
  666. filters=256
  667. activation=leaky
  668. [convolutional]
  669. size=1
  670. stride=1
  671. pad=1
  672. filters=255
  673. activation=linear
  674. [yolo]
  675. mask = 0,1,2
  676. anchors = 10,13, 16,30, 33,23, 30,61, 62,45, 59,119, 116,90, 156,198, 373,326
  677. classes=80
  678. num=9
  679. jitter=.3
  680. ignore_thresh = .7
  681. truth_thresh = 1
  682. random=1