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  1. [net]
  2. # Testing
  3. #batch=1
  4. #subdivisions=1
  5. # Training
  6. batch=32
  7. subdivisions=16
  8. width=416
  9. height=416
  10. channels=3
  11. momentum=0.949
  12. decay=0.0005
  13. angle=0
  14. saturation = 1.5
  15. exposure = 1.5
  16. hue=.1
  17.  
  18. learning_rate=0.001
  19. burn_in=1000
  20. max_batches = 6000
  21. policy=steps
  22. steps=4800,5400
  23. scales=.1,.1
  24.  
  25. #cutmix=1
  26. mosaic=1
  27.  
  28. #:104x104 54:52x52 85:26x26 104:13x13 for 416
  29.  
  30. [convolutional]
  31. batch_normalize=1
  32. filters=32
  33. size=3
  34. stride=1
  35. pad=1
  36. activation=mish
  37.  
  38. # Downsample
  39.  
  40. [convolutional]
  41. batch_normalize=1
  42. filters=64
  43. size=3
  44. stride=2
  45. pad=1
  46. activation=mish
  47.  
  48. [convolutional]
  49. batch_normalize=1
  50. filters=64
  51. size=1
  52. stride=1
  53. pad=1
  54. activation=mish
  55.  
  56. [route]
  57. layers = -2
  58.  
  59. [convolutional]
  60. batch_normalize=1
  61. filters=64
  62. size=1
  63. stride=1
  64. pad=1
  65. activation=mish
  66.  
  67. [convolutional]
  68. batch_normalize=1
  69. filters=32
  70. size=1
  71. stride=1
  72. pad=1
  73. activation=mish
  74.  
  75. [convolutional]
  76. batch_normalize=1
  77. filters=64
  78. size=3
  79. stride=1
  80. pad=1
  81. activation=mish
  82.  
  83. [shortcut]
  84. from=-3
  85. activation=linear
  86.  
  87. [convolutional]
  88. batch_normalize=1
  89. filters=64
  90. size=1
  91. stride=1
  92. pad=1
  93. activation=mish
  94.  
  95. [route]
  96. layers = -1,-7
  97.  
  98. [convolutional]
  99. batch_normalize=1
  100. filters=64
  101. size=1
  102. stride=1
  103. pad=1
  104. activation=mish
  105.  
  106. # Downsample
  107.  
  108. [convolutional]
  109. batch_normalize=1
  110. filters=128
  111. size=3
  112. stride=2
  113. pad=1
  114. activation=mish
  115.  
  116. [convolutional]
  117. batch_normalize=1
  118. filters=64
  119. size=1
  120. stride=1
  121. pad=1
  122. activation=mish
  123.  
  124. [route]
  125. layers = -2
  126.  
  127. [convolutional]
  128. batch_normalize=1
  129. filters=64
  130. size=1
  131. stride=1
  132. pad=1
  133. activation=mish
  134.  
  135. [convolutional]
  136. batch_normalize=1
  137. filters=64
  138. size=1
  139. stride=1
  140. pad=1
  141. activation=mish
  142.  
  143. [convolutional]
  144. batch_normalize=1
  145. filters=64
  146. size=3
  147. stride=1
  148. pad=1
  149. activation=mish
  150.  
  151. [shortcut]
  152. from=-3
  153. activation=linear
  154.  
  155. [convolutional]
  156. batch_normalize=1
  157. filters=64
  158. size=1
  159. stride=1
  160. pad=1
  161. activation=mish
  162.  
  163. [convolutional]
  164. batch_normalize=1
  165. filters=64
  166. size=3
  167. stride=1
  168. pad=1
  169. activation=mish
  170.  
  171. [shortcut]
  172. from=-3
  173. activation=linear
  174.  
  175. [convolutional]
  176. batch_normalize=1
  177. filters=64
  178. size=1
  179. stride=1
  180. pad=1
  181. activation=mish
  182.  
  183. [route]
  184. layers = -1,-10
  185.  
  186. [convolutional]
  187. batch_normalize=1
  188. filters=128
  189. size=1
  190. stride=1
  191. pad=1
  192. activation=mish
  193.  
  194. # Downsample
  195.  
  196. [convolutional]
  197. batch_normalize=1
  198. filters=256
  199. size=3
  200. stride=2
  201. pad=1
  202. activation=mish
  203.  
  204. [convolutional]
  205. batch_normalize=1
  206. filters=128
  207. size=1
  208. stride=1
  209. pad=1
  210. activation=mish
  211.  
  212. [route]
  213. layers = -2
  214.  
  215. [convolutional]
  216. batch_normalize=1
  217. filters=128
  218. size=1
  219. stride=1
  220. pad=1
  221. activation=mish
  222.  
  223. [convolutional]
  224. batch_normalize=1
  225. filters=128
  226. size=1
  227. stride=1
  228. pad=1
  229. activation=mish
  230.  
  231. [convolutional]
  232. batch_normalize=1
  233. filters=128
  234. size=3
  235. stride=1
  236. pad=1
  237. activation=mish
  238.  
  239. [shortcut]
  240. from=-3
  241. activation=linear
  242.  
  243. [convolutional]
  244. batch_normalize=1
  245. filters=128
  246. size=1
  247. stride=1
  248. pad=1
  249. activation=mish
  250.  
  251. [convolutional]
  252. batch_normalize=1
  253. filters=128
  254. size=3
  255. stride=1
  256. pad=1
  257. activation=mish
  258.  
  259. [shortcut]
  260. from=-3
  261. activation=linear
  262.  
  263. [convolutional]
  264. batch_normalize=1
  265. filters=128
  266. size=1
  267. stride=1
  268. pad=1
  269. activation=mish
  270.  
  271. [convolutional]
  272. batch_normalize=1
  273. filters=128
  274. size=3
  275. stride=1
  276. pad=1
  277. activation=mish
  278.  
  279. [shortcut]
  280. from=-3
  281. activation=linear
  282.  
  283. [convolutional]
  284. batch_normalize=1
  285. filters=128
  286. size=1
  287. stride=1
  288. pad=1
  289. activation=mish
  290.  
  291. [convolutional]
  292. batch_normalize=1
  293. filters=128
  294. size=3
  295. stride=1
  296. pad=1
  297. activation=mish
  298.  
  299. [shortcut]
  300. from=-3
  301. activation=linear
  302.  
  303.  
  304. [convolutional]
  305. batch_normalize=1
  306. filters=128
  307. size=1
  308. stride=1
  309. pad=1
  310. activation=mish
  311.  
  312. [convolutional]
  313. batch_normalize=1
  314. filters=128
  315. size=3
  316. stride=1
  317. pad=1
  318. activation=mish
  319.  
  320. [shortcut]
  321. from=-3
  322. activation=linear
  323.  
  324. [convolutional]
  325. batch_normalize=1
  326. filters=128
  327. size=1
  328. stride=1
  329. pad=1
  330. activation=mish
  331.  
  332. [convolutional]
  333. batch_normalize=1
  334. filters=128
  335. size=3
  336. stride=1
  337. pad=1
  338. activation=mish
  339.  
  340. [shortcut]
  341. from=-3
  342. activation=linear
  343.  
  344. [convolutional]
  345. batch_normalize=1
  346. filters=128
  347. size=1
  348. stride=1
  349. pad=1
  350. activation=mish
  351.  
  352. [convolutional]
  353. batch_normalize=1
  354. filters=128
  355. size=3
  356. stride=1
  357. pad=1
  358. activation=mish
  359.  
  360. [shortcut]
  361. from=-3
  362. activation=linear
  363.  
  364. [convolutional]
  365. batch_normalize=1
  366. filters=128
  367. size=1
  368. stride=1
  369. pad=1
  370. activation=mish
  371.  
  372. [convolutional]
  373. batch_normalize=1
  374. filters=128
  375. size=3
  376. stride=1
  377. pad=1
  378. activation=mish
  379.  
  380. [shortcut]
  381. from=-3
  382. activation=linear
  383.  
  384. [convolutional]
  385. batch_normalize=1
  386. filters=128
  387. size=1
  388. stride=1
  389. pad=1
  390. activation=mish
  391.  
  392. [route]
  393. layers = -1,-28
  394.  
  395. [convolutional]
  396. batch_normalize=1
  397. filters=256
  398. size=1
  399. stride=1
  400. pad=1
  401. activation=mish
  402.  
  403. # Downsample
  404.  
  405. [convolutional]
  406. batch_normalize=1
  407. filters=512
  408. size=3
  409. stride=2
  410. pad=1
  411. activation=mish
  412.  
  413. [convolutional]
  414. batch_normalize=1
  415. filters=256
  416. size=1
  417. stride=1
  418. pad=1
  419. activation=mish
  420.  
  421. [route]
  422. layers = -2
  423.  
  424. [convolutional]
  425. batch_normalize=1
  426. filters=256
  427. size=1
  428. stride=1
  429. pad=1
  430. activation=mish
  431.  
  432. [convolutional]
  433. batch_normalize=1
  434. filters=256
  435. size=1
  436. stride=1
  437. pad=1
  438. activation=mish
  439.  
  440. [convolutional]
  441. batch_normalize=1
  442. filters=256
  443. size=3
  444. stride=1
  445. pad=1
  446. activation=mish
  447.  
  448. [shortcut]
  449. from=-3
  450. activation=linear
  451.  
  452.  
  453. [convolutional]
  454. batch_normalize=1
  455. filters=256
  456. size=1
  457. stride=1
  458. pad=1
  459. activation=mish
  460.  
  461. [convolutional]
  462. batch_normalize=1
  463. filters=256
  464. size=3
  465. stride=1
  466. pad=1
  467. activation=mish
  468.  
  469. [shortcut]
  470. from=-3
  471. activation=linear
  472.  
  473.  
  474. [convolutional]
  475. batch_normalize=1
  476. filters=256
  477. size=1
  478. stride=1
  479. pad=1
  480. activation=mish
  481.  
  482. [convolutional]
  483. batch_normalize=1
  484. filters=256
  485. size=3
  486. stride=1
  487. pad=1
  488. activation=mish
  489.  
  490. [shortcut]
  491. from=-3
  492. activation=linear
  493.  
  494.  
  495. [convolutional]
  496. batch_normalize=1
  497. filters=256
  498. size=1
  499. stride=1
  500. pad=1
  501. activation=mish
  502.  
  503. [convolutional]
  504. batch_normalize=1
  505. filters=256
  506. size=3
  507. stride=1
  508. pad=1
  509. activation=mish
  510.  
  511. [shortcut]
  512. from=-3
  513. activation=linear
  514.  
  515.  
  516. [convolutional]
  517. batch_normalize=1
  518. filters=256
  519. size=1
  520. stride=1
  521. pad=1
  522. activation=mish
  523.  
  524. [convolutional]
  525. batch_normalize=1
  526. filters=256
  527. size=3
  528. stride=1
  529. pad=1
  530. activation=mish
  531.  
  532. [shortcut]
  533. from=-3
  534. activation=linear
  535.  
  536.  
  537. [convolutional]
  538. batch_normalize=1
  539. filters=256
  540. size=1
  541. stride=1
  542. pad=1
  543. activation=mish
  544.  
  545. [convolutional]
  546. batch_normalize=1
  547. filters=256
  548. size=3
  549. stride=1
  550. pad=1
  551. activation=mish
  552.  
  553. [shortcut]
  554. from=-3
  555. activation=linear
  556.  
  557.  
  558. [convolutional]
  559. batch_normalize=1
  560. filters=256
  561. size=1
  562. stride=1
  563. pad=1
  564. activation=mish
  565.  
  566. [convolutional]
  567. batch_normalize=1
  568. filters=256
  569. size=3
  570. stride=1
  571. pad=1
  572. activation=mish
  573.  
  574. [shortcut]
  575. from=-3
  576. activation=linear
  577.  
  578. [convolutional]
  579. batch_normalize=1
  580. filters=256
  581. size=1
  582. stride=1
  583. pad=1
  584. activation=mish
  585.  
  586. [convolutional]
  587. batch_normalize=1
  588. filters=256
  589. size=3
  590. stride=1
  591. pad=1
  592. activation=mish
  593.  
  594. [shortcut]
  595. from=-3
  596. activation=linear
  597.  
  598. [convolutional]
  599. batch_normalize=1
  600. filters=256
  601. size=1
  602. stride=1
  603. pad=1
  604. activation=mish
  605.  
  606. [route]
  607. layers = -1,-28
  608.  
  609. [convolutional]
  610. batch_normalize=1
  611. filters=512
  612. size=1
  613. stride=1
  614. pad=1
  615. activation=mish
  616.  
  617. # Downsample
  618.  
  619. [convolutional]
  620. batch_normalize=1
  621. filters=1024
  622. size=3
  623. stride=2
  624. pad=1
  625. activation=mish
  626.  
  627. [convolutional]
  628. batch_normalize=1
  629. filters=512
  630. size=1
  631. stride=1
  632. pad=1
  633. activation=mish
  634.  
  635. [route]
  636. layers = -2
  637.  
  638. [convolutional]
  639. batch_normalize=1
  640. filters=512
  641. size=1
  642. stride=1
  643. pad=1
  644. activation=mish
  645.  
  646. [convolutional]
  647. batch_normalize=1
  648. filters=512
  649. size=1
  650. stride=1
  651. pad=1
  652. activation=mish
  653.  
  654. [convolutional]
  655. batch_normalize=1
  656. filters=512
  657. size=3
  658. stride=1
  659. pad=1
  660. activation=mish
  661.  
  662. [shortcut]
  663. from=-3
  664. activation=linear
  665.  
  666. [convolutional]
  667. batch_normalize=1
  668. filters=512
  669. size=1
  670. stride=1
  671. pad=1
  672. activation=mish
  673.  
  674. [convolutional]
  675. batch_normalize=1
  676. filters=512
  677. size=3
  678. stride=1
  679. pad=1
  680. activation=mish
  681.  
  682. [shortcut]
  683. from=-3
  684. activation=linear
  685.  
  686. [convolutional]
  687. batch_normalize=1
  688. filters=512
  689. size=1
  690. stride=1
  691. pad=1
  692. activation=mish
  693.  
  694. [convolutional]
  695. batch_normalize=1
  696. filters=512
  697. size=3
  698. stride=1
  699. pad=1
  700. activation=mish
  701.  
  702. [shortcut]
  703. from=-3
  704. activation=linear
  705.  
  706. [convolutional]
  707. batch_normalize=1
  708. filters=512
  709. size=1
  710. stride=1
  711. pad=1
  712. activation=mish
  713.  
  714. [convolutional]
  715. batch_normalize=1
  716. filters=512
  717. size=3
  718. stride=1
  719. pad=1
  720. activation=mish
  721.  
  722. [shortcut]
  723. from=-3
  724. activation=linear
  725.  
  726. [convolutional]
  727. batch_normalize=1
  728. filters=512
  729. size=1
  730. stride=1
  731. pad=1
  732. activation=mish
  733.  
  734. [route]
  735. layers = -1,-16
  736.  
  737. [convolutional]
  738. batch_normalize=1
  739. filters=1024
  740. size=1
  741. stride=1
  742. pad=1
  743. activation=mish
  744. stopbackward=800
  745.  
  746. ##########################
  747.  
  748. [convolutional]
  749. batch_normalize=1
  750. filters=512
  751. size=1
  752. stride=1
  753. pad=1
  754. activation=leaky
  755.  
  756. [convolutional]
  757. batch_normalize=1
  758. size=3
  759. stride=1
  760. pad=1
  761. filters=1024
  762. activation=leaky
  763.  
  764. [convolutional]
  765. batch_normalize=1
  766. filters=512
  767. size=1
  768. stride=1
  769. pad=1
  770. activation=leaky
  771.  
  772. ### SPP ###
  773. [maxpool]
  774. stride=1
  775. size=5
  776.  
  777. [route]
  778. layers=-2
  779.  
  780. [maxpool]
  781. stride=1
  782. size=9
  783.  
  784. [route]
  785. layers=-4
  786.  
  787. [maxpool]
  788. stride=1
  789. size=13
  790.  
  791. [route]
  792. layers=-1,-3,-5,-6
  793. ### End SPP ###
  794.  
  795. [convolutional]
  796. batch_normalize=1
  797. filters=512
  798. size=1
  799. stride=1
  800. pad=1
  801. activation=leaky
  802.  
  803. [convolutional]
  804. batch_normalize=1
  805. size=3
  806. stride=1
  807. pad=1
  808. filters=1024
  809. activation=leaky
  810.  
  811. [convolutional]
  812. batch_normalize=1
  813. filters=512
  814. size=1
  815. stride=1
  816. pad=1
  817. activation=leaky
  818.  
  819. [convolutional]
  820. batch_normalize=1
  821. filters=256
  822. size=1
  823. stride=1
  824. pad=1
  825. activation=leaky
  826.  
  827. [upsample]
  828. stride=2
  829.  
  830. [route]
  831. layers = 85
  832.  
  833. [convolutional]
  834. batch_normalize=1
  835. filters=256
  836. size=1
  837. stride=1
  838. pad=1
  839. activation=leaky
  840.  
  841. [route]
  842. layers = -1, -3
  843.  
  844. [convolutional]
  845. batch_normalize=1
  846. filters=256
  847. size=1
  848. stride=1
  849. pad=1
  850. activation=leaky
  851.  
  852. [convolutional]
  853. batch_normalize=1
  854. size=3
  855. stride=1
  856. pad=1
  857. filters=512
  858. activation=leaky
  859.  
  860. [convolutional]
  861. batch_normalize=1
  862. filters=256
  863. size=1
  864. stride=1
  865. pad=1
  866. activation=leaky
  867.  
  868. [convolutional]
  869. batch_normalize=1
  870. size=3
  871. stride=1
  872. pad=1
  873. filters=512
  874. activation=leaky
  875.  
  876. [convolutional]
  877. batch_normalize=1
  878. filters=256
  879. size=1
  880. stride=1
  881. pad=1
  882. activation=leaky
  883.  
  884. [convolutional]
  885. batch_normalize=1
  886. filters=128
  887. size=1
  888. stride=1
  889. pad=1
  890. activation=leaky
  891.  
  892. [upsample]
  893. stride=2
  894.  
  895. [route]
  896. layers = 54
  897.  
  898. [convolutional]
  899. batch_normalize=1
  900. filters=128
  901. size=1
  902. stride=1
  903. pad=1
  904. activation=leaky
  905.  
  906. [route]
  907. layers = -1, -3
  908.  
  909. [convolutional]
  910. batch_normalize=1
  911. filters=128
  912. size=1
  913. stride=1
  914. pad=1
  915. activation=leaky
  916.  
  917. [convolutional]
  918. batch_normalize=1
  919. size=3
  920. stride=1
  921. pad=1
  922. filters=256
  923. activation=leaky
  924.  
  925. [convolutional]
  926. batch_normalize=1
  927. filters=128
  928. size=1
  929. stride=1
  930. pad=1
  931. activation=leaky
  932.  
  933. [convolutional]
  934. batch_normalize=1
  935. size=3
  936. stride=1
  937. pad=1
  938. filters=256
  939. activation=leaky
  940.  
  941. [convolutional]
  942. batch_normalize=1
  943. filters=128
  944. size=1
  945. stride=1
  946. pad=1
  947. activation=leaky
  948.  
  949. ##########################
  950.  
  951. [convolutional]
  952. batch_normalize=1
  953. size=3
  954. stride=1
  955. pad=1
  956. filters=256
  957. activation=leaky
  958.  
  959. [convolutional]
  960. size=1
  961. stride=1
  962. pad=1
  963. filters=21
  964. activation=linear
  965.  
  966.  
  967. [yolo]
  968. mask = 0,1,2
  969. anchors = 12, 16, 19, 36, 40, 28, 36, 75, 76, 55, 72, 146, 142, 110, 192, 243, 459, 401
  970. classes=2
  971. num=9
  972. jitter=.3
  973. ignore_thresh = .7
  974. truth_thresh = 1
  975. scale_x_y = 1.2
  976. iou_thresh=0.213
  977. cls_normalizer=1.0
  978. iou_normalizer=0.07
  979. iou_loss=ciou
  980. nms_kind=greedynms
  981. beta_nms=0.6
  982. max_delta=5
  983.  
  984.  
  985. [route]
  986. layers = -4
  987.  
  988. [convolutional]
  989. batch_normalize=1
  990. size=3
  991. stride=2
  992. pad=1
  993. filters=256
  994. activation=leaky
  995.  
  996. [route]
  997. layers = -1, -16
  998.  
  999. [convolutional]
  1000. batch_normalize=1
  1001. filters=256
  1002. size=1
  1003. stride=1
  1004. pad=1
  1005. activation=leaky
  1006.  
  1007. [convolutional]
  1008. batch_normalize=1
  1009. size=3
  1010. stride=1
  1011. pad=1
  1012. filters=512
  1013. activation=leaky
  1014.  
  1015. [convolutional]
  1016. batch_normalize=1
  1017. filters=256
  1018. size=1
  1019. stride=1
  1020. pad=1
  1021. activation=leaky
  1022.  
  1023. [convolutional]
  1024. batch_normalize=1
  1025. size=3
  1026. stride=1
  1027. pad=1
  1028. filters=512
  1029. activation=leaky
  1030.  
  1031. [convolutional]
  1032. batch_normalize=1
  1033. filters=256
  1034. size=1
  1035. stride=1
  1036. pad=1
  1037. activation=leaky
  1038.  
  1039. [convolutional]
  1040. batch_normalize=1
  1041. size=3
  1042. stride=1
  1043. pad=1
  1044. filters=512
  1045. activation=leaky
  1046.  
  1047. [convolutional]
  1048. size=1
  1049. stride=1
  1050. pad=1
  1051. filters=21
  1052. activation=linear
  1053.  
  1054.  
  1055. [yolo]
  1056. mask = 3,4,5
  1057. anchors = 12, 16, 19, 36, 40, 28, 36, 75, 76, 55, 72, 146, 142, 110, 192, 243, 459, 401
  1058. classes=2
  1059. num=9
  1060. jitter=.3
  1061. ignore_thresh = .7
  1062. truth_thresh = 1
  1063. scale_x_y = 1.1
  1064. iou_thresh=0.213
  1065. cls_normalizer=1.0
  1066. iou_normalizer=0.07
  1067. iou_loss=ciou
  1068. nms_kind=greedynms
  1069. beta_nms=0.6
  1070. max_delta=5
  1071.  
  1072.  
  1073. [route]
  1074. layers = -4
  1075.  
  1076. [convolutional]
  1077. batch_normalize=1
  1078. size=3
  1079. stride=2
  1080. pad=1
  1081. filters=512
  1082. activation=leaky
  1083.  
  1084. [route]
  1085. layers = -1, -37
  1086.  
  1087. [convolutional]
  1088. batch_normalize=1
  1089. filters=512
  1090. size=1
  1091. stride=1
  1092. pad=1
  1093. activation=leaky
  1094.  
  1095. [convolutional]
  1096. batch_normalize=1
  1097. size=3
  1098. stride=1
  1099. pad=1
  1100. filters=1024
  1101. activation=leaky
  1102.  
  1103. [convolutional]
  1104. batch_normalize=1
  1105. filters=512
  1106. size=1
  1107. stride=1
  1108. pad=1
  1109. activation=leaky
  1110.  
  1111. [convolutional]
  1112. batch_normalize=1
  1113. size=3
  1114. stride=1
  1115. pad=1
  1116. filters=1024
  1117. activation=leaky
  1118.  
  1119. [convolutional]
  1120. batch_normalize=1
  1121. filters=512
  1122. size=1
  1123. stride=1
  1124. pad=1
  1125. activation=leaky
  1126.  
  1127. [convolutional]
  1128. batch_normalize=1
  1129. size=3
  1130. stride=1
  1131. pad=1
  1132. filters=1024
  1133. activation=leaky
  1134.  
  1135. [convolutional]
  1136. size=1
  1137. stride=1
  1138. pad=1
  1139. filters=21
  1140. activation=linear
  1141.  
  1142.  
  1143. [yolo]
  1144. mask = 6,7,8
  1145. anchors = 12, 16, 19, 36, 40, 28, 36, 75, 76, 55, 72, 146, 142, 110, 192, 243, 459, 401
  1146. classes=2
  1147. num=9
  1148. jitter=.3
  1149. ignore_thresh = .7
  1150. truth_thresh = 1
  1151. random=1
  1152. scale_x_y = 1.05
  1153. iou_thresh=0.213
  1154. cls_normalizer=1.0
  1155. iou_normalizer=0.07
  1156. iou_loss=ciou
  1157. nms_kind=greedynms
  1158. beta_nms=0.6
  1159. max_delta=5
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