csresnext50-panet-spp.cfg 10 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=512
  9. height=512
  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 = 500500
  20. policy=steps
  21. steps=400000,450000
  22. scales=.1,.1
  23. #19:104x104 38:52x52 65:26x26 80:13x13 for 416
  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=128
  37. size=1
  38. stride=1
  39. pad=1
  40. activation=leaky
  41. [route]
  42. layers = -2
  43. [convolutional]
  44. batch_normalize=1
  45. filters=64
  46. size=1
  47. stride=1
  48. pad=1
  49. activation=leaky
  50. # 1-1
  51. [convolutional]
  52. batch_normalize=1
  53. filters=128
  54. size=1
  55. stride=1
  56. pad=1
  57. activation=leaky
  58. [convolutional]
  59. batch_normalize=1
  60. filters=128
  61. size=3
  62. groups=32
  63. stride=1
  64. pad=1
  65. activation=leaky
  66. [convolutional]
  67. batch_normalize=1
  68. filters=128
  69. size=1
  70. stride=1
  71. pad=1
  72. activation=linear
  73. [shortcut]
  74. from=-4
  75. activation=leaky
  76. # 1-2
  77. [convolutional]
  78. batch_normalize=1
  79. filters=128
  80. size=1
  81. stride=1
  82. pad=1
  83. activation=leaky
  84. [convolutional]
  85. batch_normalize=1
  86. filters=128
  87. size=3
  88. groups=32
  89. stride=1
  90. pad=1
  91. activation=leaky
  92. [convolutional]
  93. batch_normalize=1
  94. filters=128
  95. size=1
  96. stride=1
  97. pad=1
  98. activation=linear
  99. [shortcut]
  100. from=-4
  101. activation=leaky
  102. # 1-3
  103. [convolutional]
  104. batch_normalize=1
  105. filters=128
  106. size=1
  107. stride=1
  108. pad=1
  109. activation=leaky
  110. [convolutional]
  111. batch_normalize=1
  112. filters=128
  113. size=3
  114. groups=32
  115. stride=1
  116. pad=1
  117. activation=leaky
  118. [convolutional]
  119. batch_normalize=1
  120. filters=128
  121. size=1
  122. stride=1
  123. pad=1
  124. activation=linear
  125. [shortcut]
  126. from=-4
  127. activation=leaky
  128. # 1-T
  129. [convolutional]
  130. batch_normalize=1
  131. filters=128
  132. size=1
  133. stride=1
  134. pad=1
  135. activation=leaky
  136. [route]
  137. layers = -1,-16
  138. [convolutional]
  139. batch_normalize=1
  140. filters=256
  141. size=1
  142. stride=1
  143. pad=1
  144. activation=leaky
  145. [convolutional]
  146. batch_normalize=1
  147. filters=256
  148. size=3
  149. groups=32
  150. stride=2
  151. pad=1
  152. activation=leaky
  153. [convolutional]
  154. batch_normalize=1
  155. filters=256
  156. size=1
  157. stride=1
  158. pad=1
  159. activation=linear
  160. [route]
  161. layers = -2
  162. [convolutional]
  163. batch_normalize=1
  164. filters=256
  165. size=1
  166. stride=1
  167. pad=1
  168. activation=linear
  169. # 2-1
  170. [convolutional]
  171. batch_normalize=1
  172. filters=256
  173. size=1
  174. stride=1
  175. pad=1
  176. activation=leaky
  177. [convolutional]
  178. batch_normalize=1
  179. filters=256
  180. size=3
  181. groups=32
  182. stride=1
  183. pad=1
  184. activation=leaky
  185. [convolutional]
  186. batch_normalize=1
  187. filters=256
  188. size=1
  189. stride=1
  190. pad=1
  191. activation=linear
  192. [shortcut]
  193. from=-4
  194. activation=leaky
  195. # 2-2
  196. [convolutional]
  197. batch_normalize=1
  198. filters=256
  199. size=1
  200. stride=1
  201. pad=1
  202. activation=leaky
  203. [convolutional]
  204. batch_normalize=1
  205. filters=256
  206. size=3
  207. groups=32
  208. stride=1
  209. pad=1
  210. activation=leaky
  211. [convolutional]
  212. batch_normalize=1
  213. filters=256
  214. size=1
  215. stride=1
  216. pad=1
  217. activation=linear
  218. [shortcut]
  219. from=-4
  220. activation=leaky
  221. # 2-3
  222. [convolutional]
  223. batch_normalize=1
  224. filters=256
  225. size=1
  226. stride=1
  227. pad=1
  228. activation=leaky
  229. [convolutional]
  230. batch_normalize=1
  231. filters=256
  232. size=3
  233. groups=32
  234. stride=1
  235. pad=1
  236. activation=leaky
  237. [convolutional]
  238. batch_normalize=1
  239. filters=256
  240. size=1
  241. stride=1
  242. pad=1
  243. activation=linear
  244. [shortcut]
  245. from=-4
  246. activation=leaky
  247. # 2-T
  248. [convolutional]
  249. batch_normalize=1
  250. filters=256
  251. size=1
  252. stride=1
  253. pad=1
  254. activation=leaky
  255. [route]
  256. layers = -1,-16
  257. [convolutional]
  258. batch_normalize=1
  259. filters=512
  260. size=1
  261. stride=1
  262. pad=1
  263. activation=leaky
  264. [convolutional]
  265. batch_normalize=1
  266. filters=512
  267. size=3
  268. groups=32
  269. stride=2
  270. pad=1
  271. activation=leaky
  272. [convolutional]
  273. batch_normalize=1
  274. filters=512
  275. size=1
  276. stride=1
  277. pad=1
  278. activation=linear
  279. [route]
  280. layers = -2
  281. [convolutional]
  282. batch_normalize=1
  283. filters=512
  284. size=1
  285. stride=1
  286. pad=1
  287. activation=linear
  288. # 3-1
  289. [convolutional]
  290. batch_normalize=1
  291. filters=512
  292. size=1
  293. stride=1
  294. pad=1
  295. activation=leaky
  296. [convolutional]
  297. batch_normalize=1
  298. filters=512
  299. size=3
  300. groups=32
  301. stride=1
  302. pad=1
  303. activation=leaky
  304. [convolutional]
  305. batch_normalize=1
  306. filters=512
  307. size=1
  308. stride=1
  309. pad=1
  310. activation=linear
  311. [shortcut]
  312. from=-4
  313. activation=leaky
  314. # 3-2
  315. [convolutional]
  316. batch_normalize=1
  317. filters=512
  318. size=1
  319. stride=1
  320. pad=1
  321. activation=leaky
  322. [convolutional]
  323. batch_normalize=1
  324. filters=512
  325. size=3
  326. groups=32
  327. stride=1
  328. pad=1
  329. activation=leaky
  330. [convolutional]
  331. batch_normalize=1
  332. filters=512
  333. size=1
  334. stride=1
  335. pad=1
  336. activation=linear
  337. [shortcut]
  338. from=-4
  339. activation=leaky
  340. # 3-3
  341. [convolutional]
  342. batch_normalize=1
  343. filters=512
  344. size=1
  345. stride=1
  346. pad=1
  347. activation=leaky
  348. [convolutional]
  349. batch_normalize=1
  350. filters=512
  351. size=3
  352. groups=32
  353. stride=1
  354. pad=1
  355. activation=leaky
  356. [convolutional]
  357. batch_normalize=1
  358. filters=512
  359. size=1
  360. stride=1
  361. pad=1
  362. activation=linear
  363. [shortcut]
  364. from=-4
  365. activation=leaky
  366. # 3-4
  367. [convolutional]
  368. batch_normalize=1
  369. filters=512
  370. size=1
  371. stride=1
  372. pad=1
  373. activation=leaky
  374. [convolutional]
  375. batch_normalize=1
  376. filters=512
  377. size=3
  378. groups=32
  379. stride=1
  380. pad=1
  381. activation=leaky
  382. [convolutional]
  383. batch_normalize=1
  384. filters=512
  385. size=1
  386. stride=1
  387. pad=1
  388. activation=linear
  389. [shortcut]
  390. from=-4
  391. activation=leaky
  392. # 3-5
  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=512
  403. size=3
  404. groups=32
  405. stride=1
  406. pad=1
  407. activation=leaky
  408. [convolutional]
  409. batch_normalize=1
  410. filters=512
  411. size=1
  412. stride=1
  413. pad=1
  414. activation=linear
  415. [shortcut]
  416. from=-4
  417. activation=leaky
  418. # 3-T
  419. [convolutional]
  420. batch_normalize=1
  421. filters=512
  422. size=1
  423. stride=1
  424. pad=1
  425. activation=leaky
  426. [route]
  427. layers = -1,-24
  428. [convolutional]
  429. batch_normalize=1
  430. filters=1024
  431. size=1
  432. stride=1
  433. pad=1
  434. activation=leaky
  435. [convolutional]
  436. batch_normalize=1
  437. filters=1024
  438. size=3
  439. groups=32
  440. stride=2
  441. pad=1
  442. activation=leaky
  443. [convolutional]
  444. batch_normalize=1
  445. filters=1024
  446. size=1
  447. stride=1
  448. pad=1
  449. activation=leaky
  450. [route]
  451. layers = -2
  452. [convolutional]
  453. batch_normalize=1
  454. filters=1024
  455. size=1
  456. stride=1
  457. pad=1
  458. activation=leaky
  459. # 4-1
  460. [convolutional]
  461. batch_normalize=1
  462. filters=1024
  463. size=1
  464. stride=1
  465. pad=1
  466. activation=leaky
  467. [convolutional]
  468. batch_normalize=1
  469. filters=1024
  470. size=3
  471. groups=32
  472. stride=1
  473. pad=1
  474. activation=leaky
  475. [convolutional]
  476. batch_normalize=1
  477. filters=1024
  478. size=1
  479. stride=1
  480. pad=1
  481. activation=linear
  482. [shortcut]
  483. from=-4
  484. activation=leaky
  485. # 4-2
  486. [convolutional]
  487. batch_normalize=1
  488. filters=1024
  489. size=1
  490. stride=1
  491. pad=1
  492. activation=leaky
  493. [convolutional]
  494. batch_normalize=1
  495. filters=1024
  496. size=3
  497. groups=32
  498. stride=1
  499. pad=1
  500. activation=leaky
  501. [convolutional]
  502. batch_normalize=1
  503. filters=1024
  504. size=1
  505. stride=1
  506. pad=1
  507. activation=linear
  508. [shortcut]
  509. from=-4
  510. activation=leaky
  511. # 4-T
  512. [convolutional]
  513. batch_normalize=1
  514. filters=1024
  515. size=1
  516. stride=1
  517. pad=1
  518. activation=leaky
  519. [route]
  520. layers = -1,-12
  521. [convolutional]
  522. batch_normalize=1
  523. filters=2048
  524. size=1
  525. stride=1
  526. pad=1
  527. activation=leaky
  528. ##########################
  529. [convolutional]
  530. batch_normalize=1
  531. filters=512
  532. size=1
  533. stride=1
  534. pad=1
  535. activation=leaky
  536. [convolutional]
  537. batch_normalize=1
  538. size=3
  539. stride=1
  540. pad=1
  541. filters=1024
  542. activation=leaky
  543. [convolutional]
  544. batch_normalize=1
  545. filters=512
  546. size=1
  547. stride=1
  548. pad=1
  549. activation=leaky
  550. ### SPP ###
  551. [maxpool]
  552. stride=1
  553. size=5
  554. [route]
  555. layers=-2
  556. [maxpool]
  557. stride=1
  558. size=9
  559. [route]
  560. layers=-4
  561. [maxpool]
  562. stride=1
  563. size=13
  564. [route]
  565. layers=-1,-3,-5,-6
  566. ### End SPP ###
  567. [convolutional]
  568. batch_normalize=1
  569. filters=512
  570. size=1
  571. stride=1
  572. pad=1
  573. activation=leaky
  574. [convolutional]
  575. batch_normalize=1
  576. size=3
  577. stride=1
  578. pad=1
  579. filters=1024
  580. activation=leaky
  581. [convolutional]
  582. batch_normalize=1
  583. filters=512
  584. size=1
  585. stride=1
  586. pad=1
  587. activation=leaky
  588. [convolutional]
  589. batch_normalize=1
  590. filters=256
  591. size=1
  592. stride=1
  593. pad=1
  594. activation=leaky
  595. [upsample]
  596. stride=2
  597. [route]
  598. layers = 65
  599. [convolutional]
  600. batch_normalize=1
  601. filters=256
  602. size=1
  603. stride=1
  604. pad=1
  605. activation=leaky
  606. [route]
  607. layers = -1, -3
  608. [convolutional]
  609. batch_normalize=1
  610. filters=256
  611. size=1
  612. stride=1
  613. pad=1
  614. activation=leaky
  615. [convolutional]
  616. batch_normalize=1
  617. size=3
  618. stride=1
  619. pad=1
  620. filters=512
  621. activation=leaky
  622. [convolutional]
  623. batch_normalize=1
  624. filters=256
  625. size=1
  626. stride=1
  627. pad=1
  628. activation=leaky
  629. [convolutional]
  630. batch_normalize=1
  631. size=3
  632. stride=1
  633. pad=1
  634. filters=512
  635. activation=leaky
  636. [convolutional]
  637. batch_normalize=1
  638. filters=256
  639. size=1
  640. stride=1
  641. pad=1
  642. activation=leaky
  643. [convolutional]
  644. batch_normalize=1
  645. filters=128
  646. size=1
  647. stride=1
  648. pad=1
  649. activation=leaky
  650. [upsample]
  651. stride=2
  652. [route]
  653. layers = 38
  654. [convolutional]
  655. batch_normalize=1
  656. filters=128
  657. size=1
  658. stride=1
  659. pad=1
  660. activation=leaky
  661. [route]
  662. layers = -1, -3
  663. [convolutional]
  664. batch_normalize=1
  665. filters=128
  666. size=1
  667. stride=1
  668. pad=1
  669. activation=leaky
  670. [convolutional]
  671. batch_normalize=1
  672. size=3
  673. stride=1
  674. pad=1
  675. filters=256
  676. activation=leaky
  677. [convolutional]
  678. batch_normalize=1
  679. filters=128
  680. size=1
  681. stride=1
  682. pad=1
  683. activation=leaky
  684. [convolutional]
  685. batch_normalize=1
  686. size=3
  687. stride=1
  688. pad=1
  689. filters=256
  690. activation=leaky
  691. [convolutional]
  692. batch_normalize=1
  693. filters=128
  694. size=1
  695. stride=1
  696. pad=1
  697. activation=leaky
  698. ##########################
  699. [convolutional]
  700. batch_normalize=1
  701. size=3
  702. stride=1
  703. pad=1
  704. filters=256
  705. activation=leaky
  706. [convolutional]
  707. size=1
  708. stride=1
  709. pad=1
  710. filters=255
  711. activation=linear
  712. [yolo]
  713. mask = 0,1,2
  714. anchors = 10,13, 16,30, 33,23, 30,61, 62,45, 59,119, 116,90, 156,198, 373,326
  715. classes=80
  716. num=9
  717. jitter=.3
  718. ignore_thresh = .7
  719. truth_thresh = 1
  720. random=1
  721. [route]
  722. layers = -4
  723. [convolutional]
  724. batch_normalize=1
  725. size=3
  726. stride=2
  727. pad=1
  728. filters=256
  729. activation=leaky
  730. [route]
  731. layers = -1, -16
  732. [convolutional]
  733. batch_normalize=1
  734. filters=256
  735. size=1
  736. stride=1
  737. pad=1
  738. activation=leaky
  739. [convolutional]
  740. batch_normalize=1
  741. size=3
  742. stride=1
  743. pad=1
  744. filters=512
  745. activation=leaky
  746. [convolutional]
  747. batch_normalize=1
  748. filters=256
  749. size=1
  750. stride=1
  751. pad=1
  752. activation=leaky
  753. [convolutional]
  754. batch_normalize=1
  755. size=3
  756. stride=1
  757. pad=1
  758. filters=512
  759. activation=leaky
  760. [convolutional]
  761. batch_normalize=1
  762. filters=256
  763. size=1
  764. stride=1
  765. pad=1
  766. activation=leaky
  767. [convolutional]
  768. batch_normalize=1
  769. size=3
  770. stride=1
  771. pad=1
  772. filters=512
  773. activation=leaky
  774. [convolutional]
  775. size=1
  776. stride=1
  777. pad=1
  778. filters=255
  779. activation=linear
  780. [yolo]
  781. mask = 3,4,5
  782. anchors = 10,13, 16,30, 33,23, 30,61, 62,45, 59,119, 116,90, 156,198, 373,326
  783. classes=80
  784. num=9
  785. jitter=.3
  786. ignore_thresh = .7
  787. truth_thresh = 1
  788. random=1
  789. [route]
  790. layers = -4
  791. [convolutional]
  792. batch_normalize=1
  793. size=3
  794. stride=2
  795. pad=1
  796. filters=512
  797. activation=leaky
  798. [route]
  799. layers = -1, -37
  800. [convolutional]
  801. batch_normalize=1
  802. filters=512
  803. size=1
  804. stride=1
  805. pad=1
  806. activation=leaky
  807. [convolutional]
  808. batch_normalize=1
  809. size=3
  810. stride=1
  811. pad=1
  812. filters=1024
  813. activation=leaky
  814. [convolutional]
  815. batch_normalize=1
  816. filters=512
  817. size=1
  818. stride=1
  819. pad=1
  820. activation=leaky
  821. [convolutional]
  822. batch_normalize=1
  823. size=3
  824. stride=1
  825. pad=1
  826. filters=1024
  827. activation=leaky
  828. [convolutional]
  829. batch_normalize=1
  830. filters=512
  831. size=1
  832. stride=1
  833. pad=1
  834. activation=leaky
  835. [convolutional]
  836. batch_normalize=1
  837. size=3
  838. stride=1
  839. pad=1
  840. filters=1024
  841. activation=leaky
  842. [convolutional]
  843. size=1
  844. stride=1
  845. pad=1
  846. filters=255
  847. activation=linear
  848. [yolo]
  849. mask = 6,7,8
  850. anchors = 10,13, 16,30, 33,23, 30,61, 62,45, 59,119, 116,90, 156,198, 373,326
  851. classes=80
  852. num=9
  853. jitter=.3
  854. ignore_thresh = .7
  855. truth_thresh = 1
  856. random=1