yolov3.coco-giou-12.cfg 8.4 KB

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154155156157158159160161162163164165166167168169170171172173174175176177178179180181182183184185186187188189190191192193194195196197198199200201202203204205206207208209210211212213214215216217218219220221222223224225226227228229230231232233234235236237238239240241242243244245246247248249250251252253254255256257258259260261262263264265266267268269270271272273274275276277278279280281282283284285286287288289290291292293294295296297298299300301302303304305306307308309310311312313314315316317318319320321322323324325326327328329330331332333334335336337338339340341342343344345346347348349350351352353354355356357358359360361362363364365366367368369370371372373374375376377378379380381382383384385386387388389390391392393394395396397398399400401402403404405406407408409410411412413414415416417418419420421422423424425426427428429430431432433434435436437438439440441442443444445446447448449450451452453454455456457458459460461462463464465466467468469470471472473474475476477478479480481482483484485486487488489490491492493494495496497498499500501502503504505506507508509510511512513514515516517518519520521522523524525526527528529530531532533534535536537538539540541542543544545546547548549550551552553554555556557558559560561562563564565566567568569570571572573574575576577578579580581582583584585586587588589590591592593594595596597598599600601602603604605606607608609610611612613614615616617618619620621622623624625626627628629630631632633634635636637638639640641642643644645646647648649650651652653654655656657658659660661662663664665666667668669670671672673674675676677678679680681682683684685686687688689690691692693694695696697698699700701702703704705706707708709710711712713714715716717718719720721722723724725726727728729730731732733734735736737738739740741742743744745746747748749750751752753754755756757758759760761762763764765766767768769770771772773774775776777778779780781782783784785786787788789790791792793794795796797798799800801802803804805806
  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. ## single gpu
  18. learning_rate=0.001
  19. burn_in=1000
  20. max_batches = 550400
  21. ## 2 gpu
  22. #learning_rate=0.0005
  23. #burn_in=2000
  24. #max_batches = 500200
  25. ## 4 gpu
  26. #learning_rate=0.00025
  27. #burn_in=4000
  28. #max_batches = 500200
  29. ###max_batches = 2000800
  30. policy=steps
  31. steps=400000,450000
  32. scales=.1,.1
  33. [convolutional]
  34. batch_normalize=1
  35. filters=32
  36. size=3
  37. stride=1
  38. pad=1
  39. activation=leaky
  40. # Downsample
  41. [convolutional]
  42. batch_normalize=1
  43. filters=64
  44. size=3
  45. stride=2
  46. pad=1
  47. activation=leaky
  48. [convolutional]
  49. batch_normalize=1
  50. filters=32
  51. size=1
  52. stride=1
  53. pad=1
  54. activation=leaky
  55. [convolutional]
  56. batch_normalize=1
  57. filters=64
  58. size=3
  59. stride=1
  60. pad=1
  61. activation=leaky
  62. [shortcut]
  63. from=-3
  64. activation=linear
  65. # Downsample
  66. [convolutional]
  67. batch_normalize=1
  68. filters=128
  69. size=3
  70. stride=2
  71. pad=1
  72. activation=leaky
  73. [convolutional]
  74. batch_normalize=1
  75. filters=64
  76. size=1
  77. stride=1
  78. pad=1
  79. activation=leaky
  80. [convolutional]
  81. batch_normalize=1
  82. filters=128
  83. size=3
  84. stride=1
  85. pad=1
  86. activation=leaky
  87. [shortcut]
  88. from=-3
  89. activation=linear
  90. [convolutional]
  91. batch_normalize=1
  92. filters=64
  93. size=1
  94. stride=1
  95. pad=1
  96. activation=leaky
  97. [convolutional]
  98. batch_normalize=1
  99. filters=128
  100. size=3
  101. stride=1
  102. pad=1
  103. activation=leaky
  104. [shortcut]
  105. from=-3
  106. activation=linear
  107. # Downsample
  108. [convolutional]
  109. batch_normalize=1
  110. filters=256
  111. size=3
  112. stride=2
  113. pad=1
  114. activation=leaky
  115. [convolutional]
  116. batch_normalize=1
  117. filters=128
  118. size=1
  119. stride=1
  120. pad=1
  121. activation=leaky
  122. [convolutional]
  123. batch_normalize=1
  124. filters=256
  125. size=3
  126. stride=1
  127. pad=1
  128. activation=leaky
  129. [shortcut]
  130. from=-3
  131. activation=linear
  132. [convolutional]
  133. batch_normalize=1
  134. filters=128
  135. size=1
  136. stride=1
  137. pad=1
  138. activation=leaky
  139. [convolutional]
  140. batch_normalize=1
  141. filters=256
  142. size=3
  143. stride=1
  144. pad=1
  145. activation=leaky
  146. [shortcut]
  147. from=-3
  148. activation=linear
  149. [convolutional]
  150. batch_normalize=1
  151. filters=128
  152. size=1
  153. stride=1
  154. pad=1
  155. activation=leaky
  156. [convolutional]
  157. batch_normalize=1
  158. filters=256
  159. size=3
  160. stride=1
  161. pad=1
  162. activation=leaky
  163. [shortcut]
  164. from=-3
  165. activation=linear
  166. [convolutional]
  167. batch_normalize=1
  168. filters=128
  169. size=1
  170. stride=1
  171. pad=1
  172. activation=leaky
  173. [convolutional]
  174. batch_normalize=1
  175. filters=256
  176. size=3
  177. stride=1
  178. pad=1
  179. activation=leaky
  180. [shortcut]
  181. from=-3
  182. activation=linear
  183. [convolutional]
  184. batch_normalize=1
  185. filters=128
  186. size=1
  187. stride=1
  188. pad=1
  189. activation=leaky
  190. [convolutional]
  191. batch_normalize=1
  192. filters=256
  193. size=3
  194. stride=1
  195. pad=1
  196. activation=leaky
  197. [shortcut]
  198. from=-3
  199. activation=linear
  200. [convolutional]
  201. batch_normalize=1
  202. filters=128
  203. size=1
  204. stride=1
  205. pad=1
  206. activation=leaky
  207. [convolutional]
  208. batch_normalize=1
  209. filters=256
  210. size=3
  211. stride=1
  212. pad=1
  213. activation=leaky
  214. [shortcut]
  215. from=-3
  216. activation=linear
  217. [convolutional]
  218. batch_normalize=1
  219. filters=128
  220. size=1
  221. stride=1
  222. pad=1
  223. activation=leaky
  224. [convolutional]
  225. batch_normalize=1
  226. filters=256
  227. size=3
  228. stride=1
  229. pad=1
  230. activation=leaky
  231. [shortcut]
  232. from=-3
  233. activation=linear
  234. [convolutional]
  235. batch_normalize=1
  236. filters=128
  237. size=1
  238. stride=1
  239. pad=1
  240. activation=leaky
  241. [convolutional]
  242. batch_normalize=1
  243. filters=256
  244. size=3
  245. stride=1
  246. pad=1
  247. activation=leaky
  248. [shortcut]
  249. from=-3
  250. activation=linear
  251. # Downsample
  252. [convolutional]
  253. batch_normalize=1
  254. filters=512
  255. size=3
  256. stride=2
  257. pad=1
  258. activation=leaky
  259. [convolutional]
  260. batch_normalize=1
  261. filters=256
  262. size=1
  263. stride=1
  264. pad=1
  265. activation=leaky
  266. [convolutional]
  267. batch_normalize=1
  268. filters=512
  269. size=3
  270. stride=1
  271. pad=1
  272. activation=leaky
  273. [shortcut]
  274. from=-3
  275. activation=linear
  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=512
  286. size=3
  287. stride=1
  288. pad=1
  289. activation=leaky
  290. [shortcut]
  291. from=-3
  292. activation=linear
  293. [convolutional]
  294. batch_normalize=1
  295. filters=256
  296. size=1
  297. stride=1
  298. pad=1
  299. activation=leaky
  300. [convolutional]
  301. batch_normalize=1
  302. filters=512
  303. size=3
  304. stride=1
  305. pad=1
  306. activation=leaky
  307. [shortcut]
  308. from=-3
  309. activation=linear
  310. [convolutional]
  311. batch_normalize=1
  312. filters=256
  313. size=1
  314. stride=1
  315. pad=1
  316. activation=leaky
  317. [convolutional]
  318. batch_normalize=1
  319. filters=512
  320. size=3
  321. stride=1
  322. pad=1
  323. activation=leaky
  324. [shortcut]
  325. from=-3
  326. activation=linear
  327. [convolutional]
  328. batch_normalize=1
  329. filters=256
  330. size=1
  331. stride=1
  332. pad=1
  333. activation=leaky
  334. [convolutional]
  335. batch_normalize=1
  336. filters=512
  337. size=3
  338. stride=1
  339. pad=1
  340. activation=leaky
  341. [shortcut]
  342. from=-3
  343. activation=linear
  344. [convolutional]
  345. batch_normalize=1
  346. filters=256
  347. size=1
  348. stride=1
  349. pad=1
  350. activation=leaky
  351. [convolutional]
  352. batch_normalize=1
  353. filters=512
  354. size=3
  355. stride=1
  356. pad=1
  357. activation=leaky
  358. [shortcut]
  359. from=-3
  360. activation=linear
  361. [convolutional]
  362. batch_normalize=1
  363. filters=256
  364. size=1
  365. stride=1
  366. pad=1
  367. activation=leaky
  368. [convolutional]
  369. batch_normalize=1
  370. filters=512
  371. size=3
  372. stride=1
  373. pad=1
  374. activation=leaky
  375. [shortcut]
  376. from=-3
  377. activation=linear
  378. [convolutional]
  379. batch_normalize=1
  380. filters=256
  381. size=1
  382. stride=1
  383. pad=1
  384. activation=leaky
  385. [convolutional]
  386. batch_normalize=1
  387. filters=512
  388. size=3
  389. stride=1
  390. pad=1
  391. activation=leaky
  392. [shortcut]
  393. from=-3
  394. activation=linear
  395. # Downsample
  396. [convolutional]
  397. batch_normalize=1
  398. filters=1024
  399. size=3
  400. stride=2
  401. pad=1
  402. activation=leaky
  403. [convolutional]
  404. batch_normalize=1
  405. filters=512
  406. size=1
  407. stride=1
  408. pad=1
  409. activation=leaky
  410. [convolutional]
  411. batch_normalize=1
  412. filters=1024
  413. size=3
  414. stride=1
  415. pad=1
  416. activation=leaky
  417. [shortcut]
  418. from=-3
  419. activation=linear
  420. [convolutional]
  421. batch_normalize=1
  422. filters=512
  423. size=1
  424. stride=1
  425. pad=1
  426. activation=leaky
  427. [convolutional]
  428. batch_normalize=1
  429. filters=1024
  430. size=3
  431. stride=1
  432. pad=1
  433. activation=leaky
  434. [shortcut]
  435. from=-3
  436. activation=linear
  437. [convolutional]
  438. batch_normalize=1
  439. filters=512
  440. size=1
  441. stride=1
  442. pad=1
  443. activation=leaky
  444. [convolutional]
  445. batch_normalize=1
  446. filters=1024
  447. size=3
  448. stride=1
  449. pad=1
  450. activation=leaky
  451. [shortcut]
  452. from=-3
  453. activation=linear
  454. [convolutional]
  455. batch_normalize=1
  456. filters=512
  457. size=1
  458. stride=1
  459. pad=1
  460. activation=leaky
  461. [convolutional]
  462. batch_normalize=1
  463. filters=1024
  464. size=3
  465. stride=1
  466. pad=1
  467. activation=leaky
  468. [shortcut]
  469. from=-3
  470. activation=linear
  471. ######################
  472. [convolutional]
  473. batch_normalize=1
  474. filters=512
  475. size=1
  476. stride=1
  477. pad=1
  478. activation=leaky
  479. [convolutional]
  480. batch_normalize=1
  481. size=3
  482. stride=1
  483. pad=1
  484. filters=1024
  485. activation=leaky
  486. [convolutional]
  487. batch_normalize=1
  488. filters=512
  489. size=1
  490. stride=1
  491. pad=1
  492. activation=leaky
  493. [convolutional]
  494. batch_normalize=1
  495. size=3
  496. stride=1
  497. pad=1
  498. filters=1024
  499. activation=leaky
  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. size=1
  516. stride=1
  517. pad=1
  518. filters=255
  519. activation=linear
  520. [yolo]
  521. mask = 6,7,8
  522. anchors = 10,13, 16,30, 33,23, 30,61, 62,45, 59,119, 116,90, 156,198, 373,326
  523. classes=80
  524. num=9
  525. jitter=.3
  526. ignore_thresh = .7
  527. truth_thresh = 1
  528. random=1
  529. iou_normalizer=0.5
  530. iou_loss=giou
  531. [route]
  532. layers = -4
  533. [convolutional]
  534. batch_normalize=1
  535. filters=256
  536. size=1
  537. stride=1
  538. pad=1
  539. activation=leaky
  540. [upsample]
  541. stride=2
  542. [route]
  543. layers = -1, 61
  544. [convolutional]
  545. batch_normalize=1
  546. filters=256
  547. size=1
  548. stride=1
  549. pad=1
  550. activation=leaky
  551. [convolutional]
  552. batch_normalize=1
  553. size=3
  554. stride=1
  555. pad=1
  556. filters=512
  557. activation=leaky
  558. [convolutional]
  559. batch_normalize=1
  560. filters=256
  561. size=1
  562. stride=1
  563. pad=1
  564. activation=leaky
  565. [convolutional]
  566. batch_normalize=1
  567. size=3
  568. stride=1
  569. pad=1
  570. filters=512
  571. activation=leaky
  572. [convolutional]
  573. batch_normalize=1
  574. filters=256
  575. size=1
  576. stride=1
  577. pad=1
  578. activation=leaky
  579. [convolutional]
  580. batch_normalize=1
  581. size=3
  582. stride=1
  583. pad=1
  584. filters=512
  585. activation=leaky
  586. [convolutional]
  587. size=1
  588. stride=1
  589. pad=1
  590. filters=255
  591. activation=linear
  592. [yolo]
  593. mask = 3,4,5
  594. anchors = 10,13, 16,30, 33,23, 30,61, 62,45, 59,119, 116,90, 156,198, 373,326
  595. classes=80
  596. num=9
  597. jitter=.3
  598. ignore_thresh = .7
  599. truth_thresh = 1
  600. random=1
  601. iou_normalizer=0.5
  602. iou_loss=giou
  603. [route]
  604. layers = -4
  605. [convolutional]
  606. batch_normalize=1
  607. filters=128
  608. size=1
  609. stride=1
  610. pad=1
  611. activation=leaky
  612. [upsample]
  613. stride=2
  614. [route]
  615. layers = -1, 36
  616. [convolutional]
  617. batch_normalize=1
  618. filters=128
  619. size=1
  620. stride=1
  621. pad=1
  622. activation=leaky
  623. [convolutional]
  624. batch_normalize=1
  625. size=3
  626. stride=1
  627. pad=1
  628. filters=256
  629. activation=leaky
  630. [convolutional]
  631. batch_normalize=1
  632. filters=128
  633. size=1
  634. stride=1
  635. pad=1
  636. activation=leaky
  637. [convolutional]
  638. batch_normalize=1
  639. size=3
  640. stride=1
  641. pad=1
  642. filters=256
  643. activation=leaky
  644. [convolutional]
  645. batch_normalize=1
  646. filters=128
  647. size=1
  648. stride=1
  649. pad=1
  650. activation=leaky
  651. [convolutional]
  652. batch_normalize=1
  653. size=3
  654. stride=1
  655. pad=1
  656. filters=256
  657. activation=leaky
  658. [convolutional]
  659. size=1
  660. stride=1
  661. pad=1
  662. filters=255
  663. activation=linear
  664. [yolo]
  665. mask = 0,1,2
  666. anchors = 10,13, 16,30, 33,23, 30,61, 62,45, 59,119, 116,90, 156,198, 373,326
  667. classes=80
  668. num=9
  669. jitter=.3
  670. ignore_thresh = .7
  671. truth_thresh = 1
  672. random=1
  673. iou_normalizer=0.5
  674. iou_loss=giou