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  1. name: "pspnet101_cityscapes_713"
  2. input: "data"
  3. input_dim: 1
  4. input_dim: 3
  5. input_dim: 713
  6. input_dim: 713
  7.  
  8. layer {
  9. name: "conv1_1_3x3_s2"
  10. type: "Convolution"
  11. bottom: "data"
  12. top: "conv1_1_3x3_s2"
  13. param {
  14. lr_mult: 1
  15. decay_mult: 1
  16. }
  17. convolution_param {
  18. num_output: 64
  19. pad: 1
  20. kernel_size: 3
  21. stride: 2
  22. weight_filler {
  23. type: "msra"
  24. }
  25. bias_term: false
  26. }
  27. }
  28. layer {
  29. name: "conv1_1_3x3_s2/bn"
  30. type: "BN"
  31. bottom: "conv1_1_3x3_s2"
  32. top: "conv1_1_3x3_s2"
  33. param {
  34. lr_mult: 1
  35. decay_mult: 0
  36. }
  37. param {
  38. lr_mult: 1
  39. decay_mult: 0
  40. }
  41. param {
  42. lr_mult: 0
  43. decay_mult: 0
  44. }
  45. param {
  46. lr_mult: 0
  47. decay_mult: 0
  48. }
  49. bn_param {
  50. slope_filler {
  51. type: "constant"
  52. value: 1
  53. }
  54. bias_filler {
  55. type: "constant"
  56. value: 0
  57. }
  58. frozen: true
  59. momentum: 0.95
  60. }
  61. }
  62. layer {
  63. name: "conv1_1_3x3_s2/relu"
  64. type: "ReLU"
  65. bottom: "conv1_1_3x3_s2"
  66. top: "conv1_1_3x3_s2"
  67. }
  68. layer {
  69. name: "conv1_2_3x3"
  70. type: "Convolution"
  71. bottom: "conv1_1_3x3_s2"
  72. top: "conv1_2_3x3"
  73. param {
  74. lr_mult: 1
  75. decay_mult: 1
  76. }
  77. convolution_param {
  78. num_output: 64
  79. pad: 1
  80. kernel_size: 3
  81. stride: 1
  82. weight_filler {
  83. type: "msra"
  84. }
  85. bias_term: false
  86. }
  87. }
  88. layer {
  89. name: "conv1_2_3x3/bn"
  90. type: "BN"
  91. bottom: "conv1_2_3x3"
  92. top: "conv1_2_3x3"
  93. param {
  94. lr_mult: 1
  95. decay_mult: 0
  96. }
  97. param {
  98. lr_mult: 1
  99. decay_mult: 0
  100. }
  101. param {
  102. lr_mult: 0
  103. decay_mult: 0
  104. }
  105. param {
  106. lr_mult: 0
  107. decay_mult: 0
  108. }
  109. bn_param {
  110. slope_filler {
  111. type: "constant"
  112. value: 1
  113. }
  114. bias_filler {
  115. type: "constant"
  116. value: 0
  117. }
  118. frozen: true
  119. momentum: 0.95
  120. }
  121. }
  122. layer {
  123. name: "conv1_2_3x3/relu"
  124. type: "ReLU"
  125. bottom: "conv1_2_3x3"
  126. top: "conv1_2_3x3"
  127. }
  128. layer {
  129. name: "conv1_3_3x3"
  130. type: "Convolution"
  131. bottom: "conv1_2_3x3"
  132. top: "conv1_3_3x3"
  133. param {
  134. lr_mult: 1
  135. decay_mult: 1
  136. }
  137. convolution_param {
  138. num_output: 128
  139. pad: 1
  140. kernel_size: 3
  141. stride: 1
  142. weight_filler {
  143. type: "msra"
  144. }
  145. bias_term: false
  146. }
  147. }
  148. layer {
  149. name: "conv1_3_3x3/bn"
  150. type: "BN"
  151. bottom: "conv1_3_3x3"
  152. top: "conv1_3_3x3"
  153. param {
  154. lr_mult: 1
  155. decay_mult: 0
  156. }
  157. param {
  158. lr_mult: 1
  159. decay_mult: 0
  160. }
  161. param {
  162. lr_mult: 0
  163. decay_mult: 0
  164. }
  165. param {
  166. lr_mult: 0
  167. decay_mult: 0
  168. }
  169. bn_param {
  170. slope_filler {
  171. type: "constant"
  172. value: 1
  173. }
  174. bias_filler {
  175. type: "constant"
  176. value: 0
  177. }
  178. frozen: true
  179. momentum: 0.95
  180. }
  181. }
  182. layer {
  183. name: "conv1_3_3x3/relu"
  184. type: "ReLU"
  185. bottom: "conv1_3_3x3"
  186. top: "conv1_3_3x3"
  187. }
  188. layer {
  189. name: "pool1_3x3_s2"
  190. type: "Pooling"
  191. bottom: "conv1_3_3x3"
  192. top: "pool1_3x3_s2"
  193. pooling_param {
  194. pool: MAX
  195. kernel_size: 3
  196. stride: 2
  197. pad: 1
  198. }
  199. }
  200. layer {
  201. name: "conv2_1_1x1_reduce"
  202. type: "Convolution"
  203. bottom: "pool1_3x3_s2"
  204. top: "conv2_1_1x1_reduce"
  205. param {
  206. lr_mult: 1
  207. decay_mult: 1
  208. }
  209. convolution_param {
  210. num_output: 64
  211. pad: 0
  212. kernel_size: 1
  213. stride: 1
  214. weight_filler {
  215. type: "msra"
  216. }
  217. bias_term: false
  218. }
  219. }
  220. layer {
  221. name: "conv2_1_1x1_reduce/bn"
  222. type: "BN"
  223. bottom: "conv2_1_1x1_reduce"
  224. top: "conv2_1_1x1_reduce"
  225. param {
  226. lr_mult: 1
  227. decay_mult: 0
  228. }
  229. param {
  230. lr_mult: 1
  231. decay_mult: 0
  232. }
  233. param {
  234. lr_mult: 0
  235. decay_mult: 0
  236. }
  237. param {
  238. lr_mult: 0
  239. decay_mult: 0
  240. }
  241. bn_param {
  242. slope_filler {
  243. type: "constant"
  244. value: 1
  245. }
  246. bias_filler {
  247. type: "constant"
  248. value: 0
  249. }
  250. frozen: true
  251. momentum: 0.95
  252. }
  253. }
  254. layer {
  255. name: "conv2_1_1x1_reduce/relu"
  256. type: "ReLU"
  257. bottom: "conv2_1_1x1_reduce"
  258. top: "conv2_1_1x1_reduce"
  259. }
  260. layer {
  261. name: "conv2_1_3x3"
  262. type: "Convolution"
  263. bottom: "conv2_1_1x1_reduce"
  264. top: "conv2_1_3x3"
  265. param {
  266. lr_mult: 1
  267. decay_mult: 1
  268. }
  269. convolution_param {
  270. num_output: 64
  271. pad: 1
  272. kernel_size: 3
  273. stride: 1
  274. weight_filler {
  275. type: "msra"
  276. }
  277. bias_term: false
  278. }
  279. }
  280. layer {
  281. name: "conv2_1_3x3/bn"
  282. type: "BN"
  283. bottom: "conv2_1_3x3"
  284. top: "conv2_1_3x3"
  285. param {
  286. lr_mult: 1
  287. decay_mult: 0
  288. }
  289. param {
  290. lr_mult: 1
  291. decay_mult: 0
  292. }
  293. param {
  294. lr_mult: 0
  295. decay_mult: 0
  296. }
  297. param {
  298. lr_mult: 0
  299. decay_mult: 0
  300. }
  301. bn_param {
  302. slope_filler {
  303. type: "constant"
  304. value: 1
  305. }
  306. bias_filler {
  307. type: "constant"
  308. value: 0
  309. }
  310. frozen: true
  311. momentum: 0.95
  312. }
  313. }
  314. layer {
  315. name: "conv2_1_3x3/relu"
  316. type: "ReLU"
  317. bottom: "conv2_1_3x3"
  318. top: "conv2_1_3x3"
  319. }
  320. layer {
  321. name: "conv2_1_1x1_increase"
  322. type: "Convolution"
  323. bottom: "conv2_1_3x3"
  324. top: "conv2_1_1x1_increase"
  325. param {
  326. lr_mult: 1
  327. decay_mult: 1
  328. }
  329. convolution_param {
  330. num_output: 256
  331. pad: 0
  332. kernel_size: 1
  333. stride: 1
  334. weight_filler {
  335. type: "msra"
  336. }
  337. bias_term: false
  338. }
  339. }
  340. layer {
  341. name: "conv2_1_1x1_increase/bn"
  342. type: "BN"
  343. bottom: "conv2_1_1x1_increase"
  344. top: "conv2_1_1x1_increase"
  345. param {
  346. lr_mult: 1
  347. decay_mult: 0
  348. }
  349. param {
  350. lr_mult: 1
  351. decay_mult: 0
  352. }
  353. param {
  354. lr_mult: 0
  355. decay_mult: 0
  356. }
  357. param {
  358. lr_mult: 0
  359. decay_mult: 0
  360. }
  361. bn_param {
  362. slope_filler {
  363. type: "constant"
  364. value: 1
  365. }
  366. bias_filler {
  367. type: "constant"
  368. value: 0
  369. }
  370. frozen: true
  371. momentum: 0.95
  372. }
  373. }
  374. layer {
  375. name: "conv2_1_1x1_proj"
  376. type: "Convolution"
  377. bottom: "pool1_3x3_s2"
  378. top: "conv2_1_1x1_proj"
  379. param {
  380. lr_mult: 1
  381. decay_mult: 1
  382. }
  383. convolution_param {
  384. num_output: 256
  385. pad: 0
  386. kernel_size: 1
  387. stride: 1
  388. weight_filler {
  389. type: "msra"
  390. }
  391. bias_term: false
  392. }
  393. }
  394. layer {
  395. name: "conv2_1_1x1_proj/bn"
  396. type: "BN"
  397. bottom: "conv2_1_1x1_proj"
  398. top: "conv2_1_1x1_proj"
  399. param {
  400. lr_mult: 1
  401. decay_mult: 0
  402. }
  403. param {
  404. lr_mult: 1
  405. decay_mult: 0
  406. }
  407. param {
  408. lr_mult: 0
  409. decay_mult: 0
  410. }
  411. param {
  412. lr_mult: 0
  413. decay_mult: 0
  414. }
  415. bn_param {
  416. slope_filler {
  417. type: "constant"
  418. value: 1
  419. }
  420. bias_filler {
  421. type: "constant"
  422. value: 0
  423. }
  424. frozen: true
  425. momentum: 0.95
  426. }
  427. }
  428. layer {
  429. name: "conv2_1"
  430. type: "Eltwise"
  431. bottom: "conv2_1_1x1_proj"
  432. bottom: "conv2_1_1x1_increase"
  433. top: "conv2_1"
  434. eltwise_param {
  435. operation: SUM
  436. }
  437. }
  438. layer {
  439. name: "conv2_1/relu"
  440. type: "ReLU"
  441. bottom: "conv2_1"
  442. top: "conv2_1"
  443. }
  444. layer {
  445. name: "conv2_2_1x1_reduce"
  446. type: "Convolution"
  447. bottom: "conv2_1"
  448. top: "conv2_2_1x1_reduce"
  449. param {
  450. lr_mult: 1
  451. decay_mult: 1
  452. }
  453. convolution_param {
  454. num_output: 64
  455. pad: 0
  456. kernel_size: 1
  457. stride: 1
  458. weight_filler {
  459. type: "msra"
  460. }
  461. bias_term: false
  462. }
  463. }
  464. layer {
  465. name: "conv2_2_1x1_reduce/bn"
  466. type: "BN"
  467. bottom: "conv2_2_1x1_reduce"
  468. top: "conv2_2_1x1_reduce"
  469. param {
  470. lr_mult: 1
  471. decay_mult: 0
  472. }
  473. param {
  474. lr_mult: 1
  475. decay_mult: 0
  476. }
  477. param {
  478. lr_mult: 0
  479. decay_mult: 0
  480. }
  481. param {
  482. lr_mult: 0
  483. decay_mult: 0
  484. }
  485. bn_param {
  486. slope_filler {
  487. type: "constant"
  488. value: 1
  489. }
  490. bias_filler {
  491. type: "constant"
  492. value: 0
  493. }
  494. frozen: true
  495. momentum: 0.95
  496. }
  497. }
  498. layer {
  499. name: "conv2_2_1x1_reduce/relu"
  500. type: "ReLU"
  501. bottom: "conv2_2_1x1_reduce"
  502. top: "conv2_2_1x1_reduce"
  503. }
  504. layer {
  505. name: "conv2_2_3x3"
  506. type: "Convolution"
  507. bottom: "conv2_2_1x1_reduce"
  508. top: "conv2_2_3x3"
  509. param {
  510. lr_mult: 1
  511. decay_mult: 1
  512. }
  513. convolution_param {
  514. num_output: 64
  515. pad: 1
  516. kernel_size: 3
  517. stride: 1
  518. weight_filler {
  519. type: "msra"
  520. }
  521. bias_term: false
  522. }
  523. }
  524. layer {
  525. name: "conv2_2_3x3/bn"
  526. type: "BN"
  527. bottom: "conv2_2_3x3"
  528. top: "conv2_2_3x3"
  529. param {
  530. lr_mult: 1
  531. decay_mult: 0
  532. }
  533. param {
  534. lr_mult: 1
  535. decay_mult: 0
  536. }
  537. param {
  538. lr_mult: 0
  539. decay_mult: 0
  540. }
  541. param {
  542. lr_mult: 0
  543. decay_mult: 0
  544. }
  545. bn_param {
  546. slope_filler {
  547. type: "constant"
  548. value: 1
  549. }
  550. bias_filler {
  551. type: "constant"
  552. value: 0
  553. }
  554. frozen: true
  555. momentum: 0.95
  556. }
  557. }
  558. layer {
  559. name: "conv2_2_3x3/relu"
  560. type: "ReLU"
  561. bottom: "conv2_2_3x3"
  562. top: "conv2_2_3x3"
  563. }
  564. layer {
  565. name: "conv2_2_1x1_increase"
  566. type: "Convolution"
  567. bottom: "conv2_2_3x3"
  568. top: "conv2_2_1x1_increase"
  569. param {
  570. lr_mult: 1
  571. decay_mult: 1
  572. }
  573. convolution_param {
  574. num_output: 256
  575. pad: 0
  576. kernel_size: 1
  577. stride: 1
  578. weight_filler {
  579. type: "msra"
  580. }
  581. bias_term: false
  582. }
  583. }
  584. layer {
  585. name: "conv2_2_1x1_increase/bn"
  586. type: "BN"
  587. bottom: "conv2_2_1x1_increase"
  588. top: "conv2_2_1x1_increase"
  589. param {
  590. lr_mult: 1
  591. decay_mult: 0
  592. }
  593. param {
  594. lr_mult: 1
  595. decay_mult: 0
  596. }
  597. param {
  598. lr_mult: 0
  599. decay_mult: 0
  600. }
  601. param {
  602. lr_mult: 0
  603. decay_mult: 0
  604. }
  605. bn_param {
  606. slope_filler {
  607. type: "constant"
  608. value: 1
  609. }
  610. bias_filler {
  611. type: "constant"
  612. value: 0
  613. }
  614. frozen: true
  615. momentum: 0.95
  616. }
  617. }
  618. layer {
  619. name: "conv2_2"
  620. type: "Eltwise"
  621. bottom: "conv2_1"
  622. bottom: "conv2_2_1x1_increase"
  623. top: "conv2_2"
  624. eltwise_param {
  625. operation: SUM
  626. }
  627. }
  628. layer {
  629. name: "conv2_2/relu"
  630. type: "ReLU"
  631. bottom: "conv2_2"
  632. top: "conv2_2"
  633. }
  634. layer {
  635. name: "conv2_3_1x1_reduce"
  636. type: "Convolution"
  637. bottom: "conv2_2"
  638. top: "conv2_3_1x1_reduce"
  639. param {
  640. lr_mult: 1
  641. decay_mult: 1
  642. }
  643. convolution_param {
  644. num_output: 64
  645. pad: 0
  646. kernel_size: 1
  647. stride: 1
  648. weight_filler {
  649. type: "msra"
  650. }
  651. bias_term: false
  652. }
  653. }
  654. layer {
  655. name: "conv2_3_1x1_reduce/bn"
  656. type: "BN"
  657. bottom: "conv2_3_1x1_reduce"
  658. top: "conv2_3_1x1_reduce"
  659. param {
  660. lr_mult: 1
  661. decay_mult: 0
  662. }
  663. param {
  664. lr_mult: 1
  665. decay_mult: 0
  666. }
  667. param {
  668. lr_mult: 0
  669. decay_mult: 0
  670. }
  671. param {
  672. lr_mult: 0
  673. decay_mult: 0
  674. }
  675. bn_param {
  676. slope_filler {
  677. type: "constant"
  678. value: 1
  679. }
  680. bias_filler {
  681. type: "constant"
  682. value: 0
  683. }
  684. frozen: true
  685. momentum: 0.95
  686. }
  687. }
  688. layer {
  689. name: "conv2_3_1x1_reduce/relu"
  690. type: "ReLU"
  691. bottom: "conv2_3_1x1_reduce"
  692. top: "conv2_3_1x1_reduce"
  693. }
  694. layer {
  695. name: "conv2_3_3x3"
  696. type: "Convolution"
  697. bottom: "conv2_3_1x1_reduce"
  698. top: "conv2_3_3x3"
  699. param {
  700. lr_mult: 1
  701. decay_mult: 1
  702. }
  703. convolution_param {
  704. num_output: 64
  705. pad: 1
  706. kernel_size: 3
  707. stride: 1
  708. weight_filler {
  709. type: "msra"
  710. }
  711. bias_term: false
  712. }
  713. }
  714. layer {
  715. name: "conv2_3_3x3/bn"
  716. type: "BN"
  717. bottom: "conv2_3_3x3"
  718. top: "conv2_3_3x3"
  719. param {
  720. lr_mult: 1
  721. decay_mult: 0
  722. }
  723. param {
  724. lr_mult: 1
  725. decay_mult: 0
  726. }
  727. param {
  728. lr_mult: 0
  729. decay_mult: 0
  730. }
  731. param {
  732. lr_mult: 0
  733. decay_mult: 0
  734. }
  735. bn_param {
  736. slope_filler {
  737. type: "constant"
  738. value: 1
  739. }
  740. bias_filler {
  741. type: "constant"
  742. value: 0
  743. }
  744. frozen: true
  745. momentum: 0.95
  746. }
  747. }
  748. layer {
  749. name: "conv2_3_3x3/relu"
  750. type: "ReLU"
  751. bottom: "conv2_3_3x3"
  752. top: "conv2_3_3x3"
  753. }
  754. layer {
  755. name: "conv2_3_1x1_increase"
  756. type: "Convolution"
  757. bottom: "conv2_3_3x3"
  758. top: "conv2_3_1x1_increase"
  759. param {
  760. lr_mult: 1
  761. decay_mult: 1
  762. }
  763. convolution_param {
  764. num_output: 256
  765. pad: 0
  766. kernel_size: 1
  767. stride: 1
  768. weight_filler {
  769. type: "msra"
  770. }
  771. bias_term: false
  772. }
  773. }
  774. layer {
  775. name: "conv2_3_1x1_increase/bn"
  776. type: "BN"
  777. bottom: "conv2_3_1x1_increase"
  778. top: "conv2_3_1x1_increase"
  779. param {
  780. lr_mult: 1
  781. decay_mult: 0
  782. }
  783. param {
  784. lr_mult: 1
  785. decay_mult: 0
  786. }
  787. param {
  788. lr_mult: 0
  789. decay_mult: 0
  790. }
  791. param {
  792. lr_mult: 0
  793. decay_mult: 0
  794. }
  795. bn_param {
  796. slope_filler {
  797. type: "constant"
  798. value: 1
  799. }
  800. bias_filler {
  801. type: "constant"
  802. value: 0
  803. }
  804. frozen: true
  805. momentum: 0.95
  806. }
  807. }
  808. layer {
  809. name: "conv2_3"
  810. type: "Eltwise"
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  1568. layer {
  1569. name: "conv3_4_1x1_increase"
  1570. type: "Convolution"
  1571. bottom: "conv3_4_3x3"
  1572. top: "conv3_4_1x1_increase"
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  1575. decay_mult: 1
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  1579. pad: 0
  1580. kernel_size: 1
  1581. stride: 1
  1582. weight_filler {
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  1584. }
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  1586. }
  1587. }
  1588. layer {
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  1590. type: "BN"
  1591. bottom: "conv3_4_1x1_increase"
  1592. top: "conv3_4_1x1_increase"
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  1595. decay_mult: 0
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  1619. momentum: 0.95
  1620. }
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  1622. layer {
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  1624. type: "Eltwise"
  1625. bottom: "conv3_3"
  1626. bottom: "conv3_4_1x1_increase"
  1627. top: "conv3_4"
  1628. eltwise_param {
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  1630. }
  1631. }
  1632. layer {
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  1634. type: "ReLU"
  1635. bottom: "conv3_4"
  1636. top: "conv3_4"
  1637. }
  1638. layer {
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  1640. type: "Convolution"
  1641. bottom: "conv3_4"
  1642. top: "conv4_1_1x1_reduce"
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  1645. decay_mult: 1
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  1649. pad: 0
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  1651. stride: 1
  1652. weight_filler {
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  1655. bias_term: false
  1656. }
  1657. }
  1658. layer {
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  1660. type: "BN"
  1661. bottom: "conv4_1_1x1_reduce"
  1662. top: "conv4_1_1x1_reduce"
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  1665. decay_mult: 0
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  1694. type: "ReLU"
  1695. bottom: "conv4_1_1x1_reduce"
  1696. top: "conv4_1_1x1_reduce"
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  1698. layer {
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  1700. type: "Convolution"
  1701. bottom: "conv4_1_1x1_reduce"
  1702. top: "conv4_1_3x3"
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  1705. decay_mult: 1
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  1709. pad: 2
  1710. dilation: 2
  1711. kernel_size: 3
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  1721. type: "BN"
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  1723. top: "conv4_1_3x3"
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  1750. momentum: 0.95
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  1755. type: "ReLU"
  1756. bottom: "conv4_1_3x3"
  1757. top: "conv4_1_3x3"
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  1759. layer {
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  1763. top: "conv4_1_1x1_increase"
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  1766. decay_mult: 1
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  1771. kernel_size: 1
  1772. stride: 1
  1773. weight_filler {
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  1783. top: "conv4_1_1x1_increase"
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  1816. bottom: "conv3_4"
  1817. top: "conv4_1_1x1_proj"
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  1820. decay_mult: 1
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  1825. kernel_size: 1
  1826. stride: 1
  1827. weight_filler {
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  1833. layer {
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  1836. bottom: "conv4_1_1x1_proj"
  1837. top: "conv4_1_1x1_proj"
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  1870. bottom: "conv4_1_1x1_proj"
  1871. bottom: "conv4_1_1x1_increase"
  1872. top: "conv4_1"
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  1879. type: "ReLU"
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  1881. top: "conv4_1"
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  1887. top: "conv4_2_1x1_reduce"
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  1907. top: "conv4_2_1x1_reduce"
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  1943. layer {
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  2004. layer {
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  2027. bottom: "conv4_2_1x1_increase"
  2028. top: "conv4_2_1x1_increase"
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  2062. bottom: "conv4_2_1x1_increase"
  2063. top: "conv4_2"
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  2071. bottom: "conv4_2"
  2072. top: "conv4_2"
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  2077. bottom: "conv4_2"
  2078. top: "conv4_3_1x1_reduce"
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  2131. bottom: "conv4_3_1x1_reduce"
  2132. top: "conv4_3_1x1_reduce"
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  2134. layer {
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  2138. top: "conv4_3_3x3"
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  2192. bottom: "conv4_3_3x3"
  2193. top: "conv4_3_3x3"
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  2195. layer {
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  2199. top: "conv4_3_1x1_increase"
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  2208. stride: 1
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  2254. top: "conv4_3"
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  2263. top: "conv4_3"
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  6795. bottom: "conv5_3"
  6796. top: "conv5_3_pool2"
  6797. pooling_param {
  6798. pool: AVE
  6799. kernel_size: 45
  6800. stride: 45
  6801. }
  6802. }
  6803. layer {
  6804. name: "conv5_3_pool2_conv"
  6805. type: "Convolution"
  6806. bottom: "conv5_3_pool2"
  6807. top: "conv5_3_pool2_conv"
  6808. param {
  6809. lr_mult: 10
  6810. decay_mult: 1
  6811. }
  6812. convolution_param {
  6813. num_output: 512
  6814. kernel_size: 1
  6815. stride: 1
  6816. weight_filler {
  6817. type: "msra"
  6818. }
  6819. bias_term: false
  6820. }
  6821. }
  6822. layer {
  6823. name: "conv5_3_pool2_conv/bn"
  6824. type: "BN"
  6825. bottom: "conv5_3_pool2_conv"
  6826. top: "conv5_3_pool2_conv"
  6827. param {
  6828. lr_mult: 10
  6829. decay_mult: 0
  6830. }
  6831. param {
  6832. lr_mult: 10
  6833. decay_mult: 0
  6834. }
  6835. param {
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  6837. decay_mult: 0
  6838. }
  6839. param {
  6840. lr_mult: 0
  6841. decay_mult: 0
  6842. }
  6843. bn_param {
  6844. slope_filler {
  6845. type: "constant"
  6846. value: 1
  6847. }
  6848. bias_filler {
  6849. type: "constant"
  6850. value: 0
  6851. }
  6852. frozen: true
  6853. momentum: 0.95
  6854. }
  6855. }
  6856. layer {
  6857. name: "conv5_3_pool2_conv/relu"
  6858. type: "ReLU"
  6859. bottom: "conv5_3_pool2_conv"
  6860. top: "conv5_3_pool2_conv"
  6861. }
  6862. layer {
  6863. name: "conv5_3_pool2_interp"
  6864. type: "Interp"
  6865. bottom: "conv5_3_pool2_conv"
  6866. top: "conv5_3_pool2_interp"
  6867. interp_param {
  6868. height: 90
  6869. width: 90
  6870. }
  6871. }
  6872. layer {
  6873. name: "conv5_3_pool3"
  6874. type: "Pooling"
  6875. bottom: "conv5_3"
  6876. top: "conv5_3_pool3"
  6877. pooling_param {
  6878. pool: AVE
  6879. kernel_size: 30
  6880. stride: 30
  6881. }
  6882. }
  6883. layer {
  6884. name: "conv5_3_pool3_conv"
  6885. type: "Convolution"
  6886. bottom: "conv5_3_pool3"
  6887. top: "conv5_3_pool3_conv"
  6888. param {
  6889. lr_mult: 10
  6890. decay_mult: 1
  6891. }
  6892. convolution_param {
  6893. num_output: 512
  6894. kernel_size: 1
  6895. stride: 1
  6896. weight_filler {
  6897. type: "msra"
  6898. }
  6899. bias_term: false
  6900. }
  6901. }
  6902. layer {
  6903. name: "conv5_3_pool3_conv/bn"
  6904. type: "BN"
  6905. bottom: "conv5_3_pool3_conv"
  6906. top: "conv5_3_pool3_conv"
  6907. param {
  6908. lr_mult: 10
  6909. decay_mult: 0
  6910. }
  6911. param {
  6912. lr_mult: 10
  6913. decay_mult: 0
  6914. }
  6915. param {
  6916. lr_mult: 0
  6917. decay_mult: 0
  6918. }
  6919. param {
  6920. lr_mult: 0
  6921. decay_mult: 0
  6922. }
  6923. bn_param {
  6924. slope_filler {
  6925. type: "constant"
  6926. value: 1
  6927. }
  6928. bias_filler {
  6929. type: "constant"
  6930. value: 0
  6931. }
  6932. frozen: true
  6933. momentum: 0.95
  6934. }
  6935. }
  6936. layer {
  6937. name: "conv5_3_pool3_conv/relu"
  6938. type: "ReLU"
  6939. bottom: "conv5_3_pool3_conv"
  6940. top: "conv5_3_pool3_conv"
  6941. }
  6942. layer {
  6943. name: "conv5_3_pool3_interp"
  6944. type: "Interp"
  6945. bottom: "conv5_3_pool3_conv"
  6946. top: "conv5_3_pool3_interp"
  6947. interp_param {
  6948. height: 90
  6949. width: 90
  6950. }
  6951. }
  6952. layer {
  6953. name: "conv5_3_pool6"
  6954. type: "Pooling"
  6955. bottom: "conv5_3"
  6956. top: "conv5_3_pool6"
  6957. pooling_param {
  6958. pool: AVE
  6959. kernel_size: 15
  6960. stride: 15
  6961. }
  6962. }
  6963. layer {
  6964. name: "conv5_3_pool6_conv"
  6965. type: "Convolution"
  6966. bottom: "conv5_3_pool6"
  6967. top: "conv5_3_pool6_conv"
  6968. param {
  6969. lr_mult: 10
  6970. decay_mult: 1
  6971. }
  6972. convolution_param {
  6973. num_output: 512
  6974. kernel_size: 1
  6975. stride: 1
  6976. weight_filler {
  6977. type: "msra"
  6978. }
  6979. bias_term: false
  6980. }
  6981. }
  6982. layer {
  6983. name: "conv5_3_pool6_conv/bn"
  6984. type: "BN"
  6985. bottom: "conv5_3_pool6_conv"
  6986. top: "conv5_3_pool6_conv"
  6987. param {
  6988. lr_mult: 10
  6989. decay_mult: 0
  6990. }
  6991. param {
  6992. lr_mult: 10
  6993. decay_mult: 0
  6994. }
  6995. param {
  6996. lr_mult: 0
  6997. decay_mult: 0
  6998. }
  6999. param {
  7000. lr_mult: 0
  7001. decay_mult: 0
  7002. }
  7003. bn_param {
  7004. slope_filler {
  7005. type: "constant"
  7006. value: 1
  7007. }
  7008. bias_filler {
  7009. type: "constant"
  7010. value: 0
  7011. }
  7012. frozen: true
  7013. momentum: 0.95
  7014. }
  7015. }
  7016. layer {
  7017. name: "conv5_3_pool6_conv/relu"
  7018. type: "ReLU"
  7019. bottom: "conv5_3_pool6_conv"
  7020. top: "conv5_3_pool6_conv"
  7021. }
  7022. layer {
  7023. name: "conv5_3_pool6_interp"
  7024. type: "Interp"
  7025. bottom: "conv5_3_pool6_conv"
  7026. top: "conv5_3_pool6_interp"
  7027. interp_param {
  7028. height: 90
  7029. width: 90
  7030. }
  7031. }
  7032. layer {
  7033. name: "conv5_3_concat"
  7034. type: "Concat"
  7035. bottom: "conv5_3"
  7036. bottom: "conv5_3_pool6_interp"
  7037. bottom: "conv5_3_pool3_interp"
  7038. bottom: "conv5_3_pool2_interp"
  7039. bottom: "conv5_3_pool1_interp"
  7040. top: "conv5_3_concat"
  7041. }
  7042. layer {
  7043. name: "conv5_4"
  7044. type: "Convolution"
  7045. bottom: "conv5_3_concat"
  7046. top: "conv5_4"
  7047. param {
  7048. lr_mult: 10
  7049. decay_mult: 1
  7050. }
  7051. convolution_param {
  7052. num_output: 512
  7053. kernel_size: 3
  7054. stride: 1
  7055. pad: 1
  7056. weight_filler {
  7057. type: "msra"
  7058. }
  7059. bias_term: false
  7060. }
  7061. }
  7062. layer {
  7063. name: "conv5_4/bn"
  7064. type: "BN"
  7065. bottom: "conv5_4"
  7066. top: "conv5_4"
  7067. param {
  7068. lr_mult: 10
  7069. decay_mult: 0
  7070. }
  7071. param {
  7072. lr_mult: 10
  7073. decay_mult: 0
  7074. }
  7075. param {
  7076. lr_mult: 0
  7077. decay_mult: 0
  7078. }
  7079. param {
  7080. lr_mult: 0
  7081. decay_mult: 0
  7082. }
  7083. bn_param {
  7084. slope_filler {
  7085. type: "constant"
  7086. value: 1
  7087. }
  7088. bias_filler {
  7089. type: "constant"
  7090. value: 0
  7091. }
  7092. frozen: true
  7093. momentum: 0.95
  7094. }
  7095. }
  7096. layer {
  7097. name: "conv5_4/relu"
  7098. type: "ReLU"
  7099. bottom: "conv5_4"
  7100. top: "conv5_4"
  7101. }
  7102. layer {
  7103. name: "conv5_4/dropout"
  7104. type: "Dropout"
  7105. bottom: "conv5_4"
  7106. top: "conv5_4"
  7107. dropout_param {
  7108. dropout_ratio: 0.1
  7109. }
  7110. }
  7111. layer {
  7112. name: "conv6"
  7113. type: "Convolution"
  7114. bottom: "conv5_4"
  7115. top: "conv6"
  7116. param {
  7117. lr_mult: 10
  7118. decay_mult: 1
  7119. }
  7120. param {
  7121. lr_mult: 20
  7122. decay_mult: 1
  7123. }
  7124. convolution_param {
  7125. num_output: 19
  7126. kernel_size: 1
  7127. stride: 1
  7128. weight_filler {
  7129. type: "msra"
  7130. }
  7131. }
  7132. }
  7133. layer {
  7134. name: "conv6_interp"
  7135. type: "Interp"
  7136. bottom: "conv6"
  7137. top: "conv6_interp"
  7138. interp_param {
  7139. zoom_factor: 8
  7140. }
  7141. }
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