yolov3-voc.yolov3-giou-40.cfg 8.5 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=416
  9. height=416
  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. ## single gpu
  18. learning_rate=0.001
  19. burn_in=1000
  20. max_batches = 100400
  21. ## 2x
  22. #learning_rate=0.0005
  23. #burn_in=2000
  24. #max_batches = 100400
  25. #max_batches = 200800
  26. ## 4x
  27. #learning_rate=0.00025
  28. #burn_in=4000
  29. #max_batches = 50200
  30. ##max_batches = 200800
  31. policy=steps
  32. steps=40000,45000
  33. scales=.1,.1
  34. [convolutional]
  35. batch_normalize=1
  36. filters=32
  37. size=3
  38. stride=1
  39. pad=1
  40. activation=leaky
  41. # Downsample
  42. [convolutional]
  43. batch_normalize=1
  44. filters=64
  45. size=3
  46. stride=2
  47. pad=1
  48. activation=leaky
  49. [convolutional]
  50. batch_normalize=1
  51. filters=32
  52. size=1
  53. stride=1
  54. pad=1
  55. activation=leaky
  56. [convolutional]
  57. batch_normalize=1
  58. filters=64
  59. size=3
  60. stride=1
  61. pad=1
  62. activation=leaky
  63. [shortcut]
  64. from=-3
  65. activation=linear
  66. # Downsample
  67. [convolutional]
  68. batch_normalize=1
  69. filters=128
  70. size=3
  71. stride=2
  72. pad=1
  73. activation=leaky
  74. [convolutional]
  75. batch_normalize=1
  76. filters=64
  77. size=1
  78. stride=1
  79. pad=1
  80. activation=leaky
  81. [convolutional]
  82. batch_normalize=1
  83. filters=128
  84. size=3
  85. stride=1
  86. pad=1
  87. activation=leaky
  88. [shortcut]
  89. from=-3
  90. activation=linear
  91. [convolutional]
  92. batch_normalize=1
  93. filters=64
  94. size=1
  95. stride=1
  96. pad=1
  97. activation=leaky
  98. [convolutional]
  99. batch_normalize=1
  100. filters=128
  101. size=3
  102. stride=1
  103. pad=1
  104. activation=leaky
  105. [shortcut]
  106. from=-3
  107. activation=linear
  108. # Downsample
  109. [convolutional]
  110. batch_normalize=1
  111. filters=256
  112. size=3
  113. stride=2
  114. pad=1
  115. activation=leaky
  116. [convolutional]
  117. batch_normalize=1
  118. filters=128
  119. size=1
  120. stride=1
  121. pad=1
  122. activation=leaky
  123. [convolutional]
  124. batch_normalize=1
  125. filters=256
  126. size=3
  127. stride=1
  128. pad=1
  129. activation=leaky
  130. [shortcut]
  131. from=-3
  132. activation=linear
  133. [convolutional]
  134. batch_normalize=1
  135. filters=128
  136. size=1
  137. stride=1
  138. pad=1
  139. activation=leaky
  140. [convolutional]
  141. batch_normalize=1
  142. filters=256
  143. size=3
  144. stride=1
  145. pad=1
  146. activation=leaky
  147. [shortcut]
  148. from=-3
  149. activation=linear
  150. [convolutional]
  151. batch_normalize=1
  152. filters=128
  153. size=1
  154. stride=1
  155. pad=1
  156. activation=leaky
  157. [convolutional]
  158. batch_normalize=1
  159. filters=256
  160. size=3
  161. stride=1
  162. pad=1
  163. activation=leaky
  164. [shortcut]
  165. from=-3
  166. activation=linear
  167. [convolutional]
  168. batch_normalize=1
  169. filters=128
  170. size=1
  171. stride=1
  172. pad=1
  173. activation=leaky
  174. [convolutional]
  175. batch_normalize=1
  176. filters=256
  177. size=3
  178. stride=1
  179. pad=1
  180. activation=leaky
  181. [shortcut]
  182. from=-3
  183. activation=linear
  184. [convolutional]
  185. batch_normalize=1
  186. filters=128
  187. size=1
  188. stride=1
  189. pad=1
  190. activation=leaky
  191. [convolutional]
  192. batch_normalize=1
  193. filters=256
  194. size=3
  195. stride=1
  196. pad=1
  197. activation=leaky
  198. [shortcut]
  199. from=-3
  200. activation=linear
  201. [convolutional]
  202. batch_normalize=1
  203. filters=128
  204. size=1
  205. stride=1
  206. pad=1
  207. activation=leaky
  208. [convolutional]
  209. batch_normalize=1
  210. filters=256
  211. size=3
  212. stride=1
  213. pad=1
  214. activation=leaky
  215. [shortcut]
  216. from=-3
  217. activation=linear
  218. [convolutional]
  219. batch_normalize=1
  220. filters=128
  221. size=1
  222. stride=1
  223. pad=1
  224. activation=leaky
  225. [convolutional]
  226. batch_normalize=1
  227. filters=256
  228. size=3
  229. stride=1
  230. pad=1
  231. activation=leaky
  232. [shortcut]
  233. from=-3
  234. activation=linear
  235. [convolutional]
  236. batch_normalize=1
  237. filters=128
  238. size=1
  239. stride=1
  240. pad=1
  241. activation=leaky
  242. [convolutional]
  243. batch_normalize=1
  244. filters=256
  245. size=3
  246. stride=1
  247. pad=1
  248. activation=leaky
  249. [shortcut]
  250. from=-3
  251. activation=linear
  252. # Downsample
  253. [convolutional]
  254. batch_normalize=1
  255. filters=512
  256. size=3
  257. stride=2
  258. pad=1
  259. activation=leaky
  260. [convolutional]
  261. batch_normalize=1
  262. filters=256
  263. size=1
  264. stride=1
  265. pad=1
  266. activation=leaky
  267. [convolutional]
  268. batch_normalize=1
  269. filters=512
  270. size=3
  271. stride=1
  272. pad=1
  273. activation=leaky
  274. [shortcut]
  275. from=-3
  276. activation=linear
  277. [convolutional]
  278. batch_normalize=1
  279. filters=256
  280. size=1
  281. stride=1
  282. pad=1
  283. activation=leaky
  284. [convolutional]
  285. batch_normalize=1
  286. filters=512
  287. size=3
  288. stride=1
  289. pad=1
  290. activation=leaky
  291. [shortcut]
  292. from=-3
  293. activation=linear
  294. [convolutional]
  295. batch_normalize=1
  296. filters=256
  297. size=1
  298. stride=1
  299. pad=1
  300. activation=leaky
  301. [convolutional]
  302. batch_normalize=1
  303. filters=512
  304. size=3
  305. stride=1
  306. pad=1
  307. activation=leaky
  308. [shortcut]
  309. from=-3
  310. activation=linear
  311. [convolutional]
  312. batch_normalize=1
  313. filters=256
  314. size=1
  315. stride=1
  316. pad=1
  317. activation=leaky
  318. [convolutional]
  319. batch_normalize=1
  320. filters=512
  321. size=3
  322. stride=1
  323. pad=1
  324. activation=leaky
  325. [shortcut]
  326. from=-3
  327. activation=linear
  328. [convolutional]
  329. batch_normalize=1
  330. filters=256
  331. size=1
  332. stride=1
  333. pad=1
  334. activation=leaky
  335. [convolutional]
  336. batch_normalize=1
  337. filters=512
  338. size=3
  339. stride=1
  340. pad=1
  341. activation=leaky
  342. [shortcut]
  343. from=-3
  344. activation=linear
  345. [convolutional]
  346. batch_normalize=1
  347. filters=256
  348. size=1
  349. stride=1
  350. pad=1
  351. activation=leaky
  352. [convolutional]
  353. batch_normalize=1
  354. filters=512
  355. size=3
  356. stride=1
  357. pad=1
  358. activation=leaky
  359. [shortcut]
  360. from=-3
  361. activation=linear
  362. [convolutional]
  363. batch_normalize=1
  364. filters=256
  365. size=1
  366. stride=1
  367. pad=1
  368. activation=leaky
  369. [convolutional]
  370. batch_normalize=1
  371. filters=512
  372. size=3
  373. stride=1
  374. pad=1
  375. activation=leaky
  376. [shortcut]
  377. from=-3
  378. activation=linear
  379. [convolutional]
  380. batch_normalize=1
  381. filters=256
  382. size=1
  383. stride=1
  384. pad=1
  385. activation=leaky
  386. [convolutional]
  387. batch_normalize=1
  388. filters=512
  389. size=3
  390. stride=1
  391. pad=1
  392. activation=leaky
  393. [shortcut]
  394. from=-3
  395. activation=linear
  396. # Downsample
  397. [convolutional]
  398. batch_normalize=1
  399. filters=1024
  400. size=3
  401. stride=2
  402. pad=1
  403. activation=leaky
  404. [convolutional]
  405. batch_normalize=1
  406. filters=512
  407. size=1
  408. stride=1
  409. pad=1
  410. activation=leaky
  411. [convolutional]
  412. batch_normalize=1
  413. filters=1024
  414. size=3
  415. stride=1
  416. pad=1
  417. activation=leaky
  418. [shortcut]
  419. from=-3
  420. activation=linear
  421. [convolutional]
  422. batch_normalize=1
  423. filters=512
  424. size=1
  425. stride=1
  426. pad=1
  427. activation=leaky
  428. [convolutional]
  429. batch_normalize=1
  430. filters=1024
  431. size=3
  432. stride=1
  433. pad=1
  434. activation=leaky
  435. [shortcut]
  436. from=-3
  437. activation=linear
  438. [convolutional]
  439. batch_normalize=1
  440. filters=512
  441. size=1
  442. stride=1
  443. pad=1
  444. activation=leaky
  445. [convolutional]
  446. batch_normalize=1
  447. filters=1024
  448. size=3
  449. stride=1
  450. pad=1
  451. activation=leaky
  452. [shortcut]
  453. from=-3
  454. activation=linear
  455. [convolutional]
  456. batch_normalize=1
  457. filters=512
  458. size=1
  459. stride=1
  460. pad=1
  461. activation=leaky
  462. [convolutional]
  463. batch_normalize=1
  464. filters=1024
  465. size=3
  466. stride=1
  467. pad=1
  468. activation=leaky
  469. [shortcut]
  470. from=-3
  471. activation=linear
  472. ######################
  473. [convolutional]
  474. batch_normalize=1
  475. filters=512
  476. size=1
  477. stride=1
  478. pad=1
  479. activation=leaky
  480. [convolutional]
  481. batch_normalize=1
  482. size=3
  483. stride=1
  484. pad=1
  485. filters=1024
  486. activation=leaky
  487. [convolutional]
  488. batch_normalize=1
  489. filters=512
  490. size=1
  491. stride=1
  492. pad=1
  493. activation=leaky
  494. [convolutional]
  495. batch_normalize=1
  496. size=3
  497. stride=1
  498. pad=1
  499. filters=1024
  500. activation=leaky
  501. [convolutional]
  502. batch_normalize=1
  503. filters=512
  504. size=1
  505. stride=1
  506. pad=1
  507. activation=leaky
  508. [convolutional]
  509. batch_normalize=1
  510. size=3
  511. stride=1
  512. pad=1
  513. filters=1024
  514. activation=leaky
  515. [convolutional]
  516. size=1
  517. stride=1
  518. pad=1
  519. filters=75
  520. activation=linear
  521. [yolo]
  522. mask = 6,7,8
  523. anchors = 10,13, 16,30, 33,23, 30,61, 62,45, 59,119, 116,90, 156,198, 373,326
  524. classes=20
  525. num=9
  526. jitter=.3
  527. ignore_thresh = .5
  528. truth_thresh = 1
  529. random=1
  530. iou_normalizer=0.25
  531. cls_normalizer=1.0
  532. iou_loss=giou
  533. [route]
  534. layers = -4
  535. [convolutional]
  536. batch_normalize=1
  537. filters=256
  538. size=1
  539. stride=1
  540. pad=1
  541. activation=leaky
  542. [upsample]
  543. stride=2
  544. [route]
  545. layers = -1, 61
  546. [convolutional]
  547. batch_normalize=1
  548. filters=256
  549. size=1
  550. stride=1
  551. pad=1
  552. activation=leaky
  553. [convolutional]
  554. batch_normalize=1
  555. size=3
  556. stride=1
  557. pad=1
  558. filters=512
  559. activation=leaky
  560. [convolutional]
  561. batch_normalize=1
  562. filters=256
  563. size=1
  564. stride=1
  565. pad=1
  566. activation=leaky
  567. [convolutional]
  568. batch_normalize=1
  569. size=3
  570. stride=1
  571. pad=1
  572. filters=512
  573. activation=leaky
  574. [convolutional]
  575. batch_normalize=1
  576. filters=256
  577. size=1
  578. stride=1
  579. pad=1
  580. activation=leaky
  581. [convolutional]
  582. batch_normalize=1
  583. size=3
  584. stride=1
  585. pad=1
  586. filters=512
  587. activation=leaky
  588. [convolutional]
  589. size=1
  590. stride=1
  591. pad=1
  592. filters=75
  593. activation=linear
  594. [yolo]
  595. mask = 3,4,5
  596. anchors = 10,13, 16,30, 33,23, 30,61, 62,45, 59,119, 116,90, 156,198, 373,326
  597. classes=20
  598. num=9
  599. jitter=.3
  600. ignore_thresh = .5
  601. truth_thresh = 1
  602. random=1
  603. iou_normalizer=0.25
  604. cls_normalizer=1.0
  605. iou_loss=giou
  606. [route]
  607. layers = -4
  608. [convolutional]
  609. batch_normalize=1
  610. filters=128
  611. size=1
  612. stride=1
  613. pad=1
  614. activation=leaky
  615. [upsample]
  616. stride=2
  617. [route]
  618. layers = -1, 36
  619. [convolutional]
  620. batch_normalize=1
  621. filters=128
  622. size=1
  623. stride=1
  624. pad=1
  625. activation=leaky
  626. [convolutional]
  627. batch_normalize=1
  628. size=3
  629. stride=1
  630. pad=1
  631. filters=256
  632. activation=leaky
  633. [convolutional]
  634. batch_normalize=1
  635. filters=128
  636. size=1
  637. stride=1
  638. pad=1
  639. activation=leaky
  640. [convolutional]
  641. batch_normalize=1
  642. size=3
  643. stride=1
  644. pad=1
  645. filters=256
  646. activation=leaky
  647. [convolutional]
  648. batch_normalize=1
  649. filters=128
  650. size=1
  651. stride=1
  652. pad=1
  653. activation=leaky
  654. [convolutional]
  655. batch_normalize=1
  656. size=3
  657. stride=1
  658. pad=1
  659. filters=256
  660. activation=leaky
  661. [convolutional]
  662. size=1
  663. stride=1
  664. pad=1
  665. filters=75
  666. activation=linear
  667. [yolo]
  668. mask = 0,1,2
  669. anchors = 10,13, 16,30, 33,23, 30,61, 62,45, 59,119, 116,90, 156,198, 373,326
  670. classes=20
  671. num=9
  672. jitter=.3
  673. ignore_thresh = .5
  674. truth_thresh = 1
  675. random=1
  676. iou_normalizer=0.25
  677. cls_normalizer=1.0
  678. iou_loss=giou