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  1. name: "ResNet-50"
  2. layer {
  3. name: 'input-data'
  4. type: 'Python'
  5. top: 'data'
  6. top: 'im_info'
  7. top: 'gt_boxes'
  8. python_param {
  9. module: 'roi_data_layer.layer'
  10. layer: 'RoIDataLayer'
  11. param_str: "'num_classes': 2"
  12. }
  13. }
  14.  
  15. # ------------------------ conv1 -----------------------------
  16. layer {
  17. bottom: "data"
  18. top: "conv1"
  19. name: "conv1"
  20. type: "Convolution"
  21. convolution_param {
  22. num_output: 64
  23. kernel_size: 7
  24. pad: 3
  25. stride: 2
  26. }
  27. param {
  28. lr_mult: 0.0
  29. }
  30. param {
  31. lr_mult: 0.0
  32. }
  33.  
  34. }
  35.  
  36. layer {
  37. bottom: "conv1"
  38. top: "conv1"
  39. name: "bn_conv1"
  40. type: "BatchNorm"
  41. batch_norm_param {
  42. use_global_stats: true
  43. }
  44. param {
  45. lr_mult: 0.0
  46. decay_mult: 0.0
  47. }
  48. param {
  49. lr_mult: 0.0
  50. decay_mult: 0.0
  51. }
  52. param {
  53. lr_mult: 0.0
  54. decay_mult: 0.0
  55. }
  56. }
  57.  
  58. layer {
  59. bottom: "conv1"
  60. top: "conv1"
  61. name: "scale_conv1"
  62. type: "Scale"
  63. scale_param {
  64. bias_term: true
  65. }
  66. param {
  67. lr_mult: 0.0
  68. decay_mult: 0.0
  69. }
  70. param {
  71. lr_mult: 0.0
  72. decay_mult: 0.0
  73. }
  74. }
  75.  
  76. layer {
  77. bottom: "conv1"
  78. top: "conv1"
  79. name: "conv1_relu"
  80. type: "ReLU"
  81. }
  82.  
  83. layer {
  84. bottom: "conv1"
  85. top: "pool1"
  86. name: "pool1"
  87. type: "Pooling"
  88. pooling_param {
  89. kernel_size: 3
  90. stride: 2
  91. pool: MAX
  92. }
  93. }
  94.  
  95. layer {
  96. bottom: "pool1"
  97. top: "res2a_branch1"
  98. name: "res2a_branch1"
  99. type: "Convolution"
  100. convolution_param {
  101. num_output: 256
  102. kernel_size: 1
  103. pad: 0
  104. stride: 1
  105. bias_term: false
  106. }
  107. param {
  108. lr_mult: 0.0
  109. }
  110. }
  111.  
  112. layer {
  113. bottom: "res2a_branch1"
  114. top: "res2a_branch1"
  115. name: "bn2a_branch1"
  116. type: "BatchNorm"
  117. batch_norm_param {
  118. use_global_stats: true
  119. }
  120. param {
  121. lr_mult: 0.0
  122. decay_mult: 0.0
  123. }
  124. param {
  125. lr_mult: 0.0
  126. decay_mult: 0.0
  127. }
  128. param {
  129. lr_mult: 0.0
  130. decay_mult: 0.0
  131. }
  132. }
  133.  
  134. layer {
  135. bottom: "res2a_branch1"
  136. top: "res2a_branch1"
  137. name: "scale2a_branch1"
  138. type: "Scale"
  139. scale_param {
  140. bias_term: true
  141. }
  142. param {
  143. lr_mult: 0.0
  144. decay_mult: 0.0
  145. }
  146. param {
  147. lr_mult: 0.0
  148. decay_mult: 0.0
  149. }
  150. }
  151.  
  152. layer {
  153. bottom: "pool1"
  154. top: "res2a_branch2a"
  155. name: "res2a_branch2a"
  156. type: "Convolution"
  157. convolution_param {
  158. num_output: 64
  159. kernel_size: 1
  160. pad: 0
  161. stride: 1
  162. bias_term: false
  163. }
  164. param {
  165. lr_mult: 0.0
  166. }
  167. }
  168.  
  169. layer {
  170. bottom: "res2a_branch2a"
  171. top: "res2a_branch2a"
  172. name: "bn2a_branch2a"
  173. type: "BatchNorm"
  174. batch_norm_param {
  175. use_global_stats: true
  176. }
  177. param {
  178. lr_mult: 0.0
  179. decay_mult: 0.0
  180. }
  181. param {
  182. lr_mult: 0.0
  183. decay_mult: 0.0
  184. }
  185. param {
  186. lr_mult: 0.0
  187. decay_mult: 0.0
  188. }
  189. }
  190.  
  191. layer {
  192. bottom: "res2a_branch2a"
  193. top: "res2a_branch2a"
  194. name: "scale2a_branch2a"
  195. type: "Scale"
  196. scale_param {
  197. bias_term: true
  198. }
  199. param {
  200. lr_mult: 0.0
  201. decay_mult: 0.0
  202. }
  203. param {
  204. lr_mult: 0.0
  205. decay_mult: 0.0
  206. }
  207. }
  208.  
  209. layer {
  210. bottom: "res2a_branch2a"
  211. top: "res2a_branch2a"
  212. name: "res2a_branch2a_relu"
  213. type: "ReLU"
  214. }
  215.  
  216. layer {
  217. bottom: "res2a_branch2a"
  218. top: "res2a_branch2b"
  219. name: "res2a_branch2b"
  220. type: "Convolution"
  221. convolution_param {
  222. num_output: 64
  223. kernel_size: 3
  224. pad: 1
  225. stride: 1
  226. bias_term: false
  227. }
  228. param {
  229. lr_mult: 0.0
  230. }
  231. }
  232.  
  233. layer {
  234. bottom: "res2a_branch2b"
  235. top: "res2a_branch2b"
  236. name: "bn2a_branch2b"
  237. type: "BatchNorm"
  238. batch_norm_param {
  239. use_global_stats: true
  240. }
  241. param {
  242. lr_mult: 0.0
  243. decay_mult: 0.0
  244. }
  245. param {
  246. lr_mult: 0.0
  247. decay_mult: 0.0
  248. }
  249. param {
  250. lr_mult: 0.0
  251. decay_mult: 0.0
  252. }
  253. }
  254.  
  255. layer {
  256. bottom: "res2a_branch2b"
  257. top: "res2a_branch2b"
  258. name: "scale2a_branch2b"
  259. type: "Scale"
  260. scale_param {
  261. bias_term: true
  262. }
  263. param {
  264. lr_mult: 0.0
  265. decay_mult: 0.0
  266. }
  267. param {
  268. lr_mult: 0.0
  269. decay_mult: 0.0
  270. }
  271. }
  272.  
  273. layer {
  274. bottom: "res2a_branch2b"
  275. top: "res2a_branch2b"
  276. name: "res2a_branch2b_relu"
  277. type: "ReLU"
  278. }
  279.  
  280. layer {
  281. bottom: "res2a_branch2b"
  282. top: "res2a_branch2c"
  283. name: "res2a_branch2c"
  284. type: "Convolution"
  285. convolution_param {
  286. num_output: 256
  287. kernel_size: 1
  288. pad: 0
  289. stride: 1
  290. bias_term: false
  291. }
  292. param {
  293. lr_mult: 0.0
  294. }
  295. }
  296.  
  297. layer {
  298. bottom: "res2a_branch2c"
  299. top: "res2a_branch2c"
  300. name: "bn2a_branch2c"
  301. type: "BatchNorm"
  302. batch_norm_param {
  303. use_global_stats: true
  304. }
  305. param {
  306. lr_mult: 0.0
  307. decay_mult: 0.0
  308. }
  309. param {
  310. lr_mult: 0.0
  311. decay_mult: 0.0
  312. }
  313. param {
  314. lr_mult: 0.0
  315. decay_mult: 0.0
  316. }
  317. }
  318.  
  319. layer {
  320. bottom: "res2a_branch2c"
  321. top: "res2a_branch2c"
  322. name: "scale2a_branch2c"
  323. type: "Scale"
  324. scale_param {
  325. bias_term: true
  326. }
  327. param {
  328. lr_mult: 0.0
  329. decay_mult: 0.0
  330. }
  331. param {
  332. lr_mult: 0.0
  333. decay_mult: 0.0
  334. }
  335. }
  336.  
  337. layer {
  338. bottom: "res2a_branch1"
  339. bottom: "res2a_branch2c"
  340. top: "res2a"
  341. name: "res2a"
  342. type: "Eltwise"
  343. }
  344.  
  345. layer {
  346. bottom: "res2a"
  347. top: "res2a"
  348. name: "res2a_relu"
  349. type: "ReLU"
  350. }
  351.  
  352. layer {
  353. bottom: "res2a"
  354. top: "res2b_branch2a"
  355. name: "res2b_branch2a"
  356. type: "Convolution"
  357. convolution_param {
  358. num_output: 64
  359. kernel_size: 1
  360. pad: 0
  361. stride: 1
  362. bias_term: false
  363. }
  364. param {
  365. lr_mult: 0.0
  366. }
  367. }
  368.  
  369. layer {
  370. bottom: "res2b_branch2a"
  371. top: "res2b_branch2a"
  372. name: "bn2b_branch2a"
  373. type: "BatchNorm"
  374. batch_norm_param {
  375. use_global_stats: true
  376. }
  377. param {
  378. lr_mult: 0.0
  379. decay_mult: 0.0
  380. }
  381. param {
  382. lr_mult: 0.0
  383. decay_mult: 0.0
  384. }
  385. param {
  386. lr_mult: 0.0
  387. decay_mult: 0.0
  388. }
  389. }
  390.  
  391. layer {
  392. bottom: "res2b_branch2a"
  393. top: "res2b_branch2a"
  394. name: "scale2b_branch2a"
  395. type: "Scale"
  396. scale_param {
  397. bias_term: true
  398. }
  399. param {
  400. lr_mult: 0.0
  401. decay_mult: 0.0
  402. }
  403. param {
  404. lr_mult: 0.0
  405. decay_mult: 0.0
  406. }
  407. }
  408.  
  409. layer {
  410. bottom: "res2b_branch2a"
  411. top: "res2b_branch2a"
  412. name: "res2b_branch2a_relu"
  413. type: "ReLU"
  414. }
  415.  
  416. layer {
  417. bottom: "res2b_branch2a"
  418. top: "res2b_branch2b"
  419. name: "res2b_branch2b"
  420. type: "Convolution"
  421. convolution_param {
  422. num_output: 64
  423. kernel_size: 3
  424. pad: 1
  425. stride: 1
  426. bias_term: false
  427. }
  428. param {
  429. lr_mult: 0.0
  430. }
  431. }
  432.  
  433. layer {
  434. bottom: "res2b_branch2b"
  435. top: "res2b_branch2b"
  436. name: "bn2b_branch2b"
  437. type: "BatchNorm"
  438. batch_norm_param {
  439. use_global_stats: true
  440. }
  441. param {
  442. lr_mult: 0.0
  443. decay_mult: 0.0
  444. }
  445. param {
  446. lr_mult: 0.0
  447. decay_mult: 0.0
  448. }
  449. param {
  450. lr_mult: 0.0
  451. decay_mult: 0.0
  452. }
  453. }
  454.  
  455. layer {
  456. bottom: "res2b_branch2b"
  457. top: "res2b_branch2b"
  458. name: "scale2b_branch2b"
  459. type: "Scale"
  460. scale_param {
  461. bias_term: true
  462. }
  463. param {
  464. lr_mult: 0.0
  465. decay_mult: 0.0
  466. }
  467. param {
  468. lr_mult: 0.0
  469. decay_mult: 0.0
  470. }
  471. }
  472.  
  473. layer {
  474. bottom: "res2b_branch2b"
  475. top: "res2b_branch2b"
  476. name: "res2b_branch2b_relu"
  477. type: "ReLU"
  478. }
  479.  
  480. layer {
  481. bottom: "res2b_branch2b"
  482. top: "res2b_branch2c"
  483. name: "res2b_branch2c"
  484. type: "Convolution"
  485. convolution_param {
  486. num_output: 256
  487. kernel_size: 1
  488. pad: 0
  489. stride: 1
  490. bias_term: false
  491. }
  492. param {
  493. lr_mult: 0.0
  494. }
  495. }
  496.  
  497. layer {
  498. bottom: "res2b_branch2c"
  499. top: "res2b_branch2c"
  500. name: "bn2b_branch2c"
  501. type: "BatchNorm"
  502. batch_norm_param {
  503. use_global_stats: true
  504. }
  505. param {
  506. lr_mult: 0.0
  507. decay_mult: 0.0
  508. }
  509. param {
  510. lr_mult: 0.0
  511. decay_mult: 0.0
  512. }
  513. param {
  514. lr_mult: 0.0
  515. decay_mult: 0.0
  516. }
  517. }
  518.  
  519. layer {
  520. bottom: "res2b_branch2c"
  521. top: "res2b_branch2c"
  522. name: "scale2b_branch2c"
  523. type: "Scale"
  524. scale_param {
  525. bias_term: true
  526. }
  527. param {
  528. lr_mult: 0.0
  529. decay_mult: 0.0
  530. }
  531. param {
  532. lr_mult: 0.0
  533. decay_mult: 0.0
  534. }
  535. }
  536.  
  537. layer {
  538. bottom: "res2a"
  539. bottom: "res2b_branch2c"
  540. top: "res2b"
  541. name: "res2b"
  542. type: "Eltwise"
  543. }
  544.  
  545. layer {
  546. bottom: "res2b"
  547. top: "res2b"
  548. name: "res2b_relu"
  549. type: "ReLU"
  550. }
  551.  
  552. layer {
  553. bottom: "res2b"
  554. top: "res2c_branch2a"
  555. name: "res2c_branch2a"
  556. type: "Convolution"
  557. convolution_param {
  558. num_output: 64
  559. kernel_size: 1
  560. pad: 0
  561. stride: 1
  562. bias_term: false
  563. }
  564. param {
  565. lr_mult: 0.0
  566. }
  567. }
  568.  
  569. layer {
  570. bottom: "res2c_branch2a"
  571. top: "res2c_branch2a"
  572. name: "bn2c_branch2a"
  573. type: "BatchNorm"
  574. batch_norm_param {
  575. use_global_stats: true
  576. }
  577. param {
  578. lr_mult: 0.0
  579. decay_mult: 0.0
  580. }
  581. param {
  582. lr_mult: 0.0
  583. decay_mult: 0.0
  584. }
  585. param {
  586. lr_mult: 0.0
  587. decay_mult: 0.0
  588. }
  589. }
  590.  
  591. layer {
  592. bottom: "res2c_branch2a"
  593. top: "res2c_branch2a"
  594. name: "scale2c_branch2a"
  595. type: "Scale"
  596. scale_param {
  597. bias_term: true
  598. }
  599. param {
  600. lr_mult: 0.0
  601. decay_mult: 0.0
  602. }
  603. param {
  604. lr_mult: 0.0
  605. decay_mult: 0.0
  606. }
  607. }
  608.  
  609. layer {
  610. bottom: "res2c_branch2a"
  611. top: "res2c_branch2a"
  612. name: "res2c_branch2a_relu"
  613. type: "ReLU"
  614. }
  615.  
  616. layer {
  617. bottom: "res2c_branch2a"
  618. top: "res2c_branch2b"
  619. name: "res2c_branch2b"
  620. type: "Convolution"
  621. convolution_param {
  622. num_output: 64
  623. kernel_size: 3
  624. pad: 1
  625. stride: 1
  626. bias_term: false
  627. }
  628. param {
  629. lr_mult: 0.0
  630. }
  631. }
  632.  
  633. layer {
  634. bottom: "res2c_branch2b"
  635. top: "res2c_branch2b"
  636. name: "bn2c_branch2b"
  637. type: "BatchNorm"
  638. batch_norm_param {
  639. use_global_stats: true
  640. }
  641. param {
  642. lr_mult: 0.0
  643. decay_mult: 0.0
  644. }
  645. param {
  646. lr_mult: 0.0
  647. decay_mult: 0.0
  648. }
  649. param {
  650. lr_mult: 0.0
  651. decay_mult: 0.0
  652. }
  653. }
  654.  
  655. layer {
  656. bottom: "res2c_branch2b"
  657. top: "res2c_branch2b"
  658. name: "scale2c_branch2b"
  659. type: "Scale"
  660. scale_param {
  661. bias_term: true
  662. }
  663. param {
  664. lr_mult: 0.0
  665. decay_mult: 0.0
  666. }
  667. param {
  668. lr_mult: 0.0
  669. decay_mult: 0.0
  670. }
  671. }
  672.  
  673. layer {
  674. bottom: "res2c_branch2b"
  675. top: "res2c_branch2b"
  676. name: "res2c_branch2b_relu"
  677. type: "ReLU"
  678. }
  679.  
  680. layer {
  681. bottom: "res2c_branch2b"
  682. top: "res2c_branch2c"
  683. name: "res2c_branch2c"
  684. type: "Convolution"
  685. convolution_param {
  686. num_output: 256
  687. kernel_size: 1
  688. pad: 0
  689. stride: 1
  690. bias_term: false
  691. }
  692. param {
  693. lr_mult: 0.0
  694. }
  695. }
  696.  
  697. layer {
  698. bottom: "res2c_branch2c"
  699. top: "res2c_branch2c"
  700. name: "bn2c_branch2c"
  701. type: "BatchNorm"
  702. batch_norm_param {
  703. use_global_stats: true
  704. }
  705. param {
  706. lr_mult: 0.0
  707. decay_mult: 0.0
  708. }
  709. param {
  710. lr_mult: 0.0
  711. decay_mult: 0.0
  712. }
  713. param {
  714. lr_mult: 0.0
  715. decay_mult: 0.0
  716. }
  717. }
  718.  
  719. layer {
  720. bottom: "res2c_branch2c"
  721. top: "res2c_branch2c"
  722. name: "scale2c_branch2c"
  723. type: "Scale"
  724. scale_param {
  725. bias_term: true
  726. }
  727. param {
  728. lr_mult: 0.0
  729. decay_mult: 0.0
  730. }
  731. param {
  732. lr_mult: 0.0
  733. decay_mult: 0.0
  734. }
  735. }
  736.  
  737. layer {
  738. bottom: "res2b"
  739. bottom: "res2c_branch2c"
  740. top: "res2c"
  741. name: "res2c"
  742. type: "Eltwise"
  743. }
  744.  
  745. layer {
  746. bottom: "res2c"
  747. top: "res2c"
  748. name: "res2c_relu"
  749. type: "ReLU"
  750. }
  751.  
  752. layer {
  753. bottom: "res2c"
  754. top: "res3a_branch1"
  755. name: "res3a_branch1"
  756. type: "Convolution"
  757. convolution_param {
  758. num_output: 512
  759. kernel_size: 1
  760. pad: 0
  761. stride: 2
  762. bias_term: false
  763. }
  764. param {
  765. lr_mult: 1.0
  766. }
  767. }
  768.  
  769. layer {
  770. bottom: "res3a_branch1"
  771. top: "res3a_branch1"
  772. name: "bn3a_branch1"
  773. type: "BatchNorm"
  774. batch_norm_param {
  775. use_global_stats: true
  776. }
  777. param {
  778. lr_mult: 0.0
  779. decay_mult: 0.0
  780. }
  781. param {
  782. lr_mult: 0.0
  783. decay_mult: 0.0
  784. }
  785. param {
  786. lr_mult: 0.0
  787. decay_mult: 0.0
  788. }
  789. }
  790.  
  791. layer {
  792. bottom: "res3a_branch1"
  793. top: "res3a_branch1"
  794. name: "scale3a_branch1"
  795. type: "Scale"
  796. scale_param {
  797. bias_term: true
  798. }
  799. param {
  800. lr_mult: 0.0
  801. decay_mult: 0.0
  802. }
  803. param {
  804. lr_mult: 0.0
  805. decay_mult: 0.0
  806. }
  807. }
  808.  
  809. layer {
  810. bottom: "res2c"
  811. top: "res3a_branch2a"
  812. name: "res3a_branch2a"
  813. type: "Convolution"
  814. convolution_param {
  815. num_output: 128
  816. kernel_size: 1
  817. pad: 0
  818. stride: 2
  819. bias_term: false
  820. }
  821. param {
  822. lr_mult: 1.0
  823. }
  824. }
  825.  
  826. layer {
  827. bottom: "res3a_branch2a"
  828. top: "res3a_branch2a"
  829. name: "bn3a_branch2a"
  830. type: "BatchNorm"
  831. batch_norm_param {
  832. use_global_stats: true
  833. }
  834. param {
  835. lr_mult: 0.0
  836. decay_mult: 0.0
  837. }
  838. param {
  839. lr_mult: 0.0
  840. decay_mult: 0.0
  841. }
  842. param {
  843. lr_mult: 0.0
  844. decay_mult: 0.0
  845. }
  846. }
  847.  
  848. layer {
  849. bottom: "res3a_branch2a"
  850. top: "res3a_branch2a"
  851. name: "scale3a_branch2a"
  852. type: "Scale"
  853. scale_param {
  854. bias_term: true
  855. }
  856. param {
  857. lr_mult: 0.0
  858. decay_mult: 0.0
  859. }
  860. param {
  861. lr_mult: 0.0
  862. decay_mult: 0.0
  863. }
  864. }
  865.  
  866. layer {
  867. bottom: "res3a_branch2a"
  868. top: "res3a_branch2a"
  869. name: "res3a_branch2a_relu"
  870. type: "ReLU"
  871. }
  872.  
  873. layer {
  874. bottom: "res3a_branch2a"
  875. top: "res3a_branch2b"
  876. name: "res3a_branch2b"
  877. type: "Convolution"
  878. convolution_param {
  879. num_output: 128
  880. kernel_size: 3
  881. pad: 1
  882. stride: 1
  883. bias_term: false
  884. }
  885. param {
  886. lr_mult: 1.0
  887. }
  888. }
  889.  
  890. layer {
  891. bottom: "res3a_branch2b"
  892. top: "res3a_branch2b"
  893. name: "bn3a_branch2b"
  894. type: "BatchNorm"
  895. batch_norm_param {
  896. use_global_stats: true
  897. }
  898. param {
  899. lr_mult: 0.0
  900. decay_mult: 0.0
  901. }
  902. param {
  903. lr_mult: 0.0
  904. decay_mult: 0.0
  905. }
  906. param {
  907. lr_mult: 0.0
  908. decay_mult: 0.0
  909. }
  910. }
  911.  
  912. layer {
  913. bottom: "res3a_branch2b"
  914. top: "res3a_branch2b"
  915. name: "scale3a_branch2b"
  916. type: "Scale"
  917. scale_param {
  918. bias_term: true
  919. }
  920. param {
  921. lr_mult: 0.0
  922. decay_mult: 0.0
  923. }
  924. param {
  925. lr_mult: 0.0
  926. decay_mult: 0.0
  927. }
  928. }
  929.  
  930. layer {
  931. bottom: "res3a_branch2b"
  932. top: "res3a_branch2b"
  933. name: "res3a_branch2b_relu"
  934. type: "ReLU"
  935. }
  936.  
  937. layer {
  938. bottom: "res3a_branch2b"
  939. top: "res3a_branch2c"
  940. name: "res3a_branch2c"
  941. type: "Convolution"
  942. convolution_param {
  943. num_output: 512
  944. kernel_size: 1
  945. pad: 0
  946. stride: 1
  947. bias_term: false
  948. }
  949. param {
  950. lr_mult: 1.0
  951. }
  952. }
  953.  
  954. layer {
  955. bottom: "res3a_branch2c"
  956. top: "res3a_branch2c"
  957. name: "bn3a_branch2c"
  958. type: "BatchNorm"
  959. batch_norm_param {
  960. use_global_stats: true
  961. }
  962. param {
  963. lr_mult: 0.0
  964. decay_mult: 0.0
  965. }
  966. param {
  967. lr_mult: 0.0
  968. decay_mult: 0.0
  969. }
  970. param {
  971. lr_mult: 0.0
  972. decay_mult: 0.0
  973. }
  974. }
  975.  
  976. layer {
  977. bottom: "res3a_branch2c"
  978. top: "res3a_branch2c"
  979. name: "scale3a_branch2c"
  980. type: "Scale"
  981. scale_param {
  982. bias_term: true
  983. }
  984. param {
  985. lr_mult: 0.0
  986. decay_mult: 0.0
  987. }
  988. param {
  989. lr_mult: 0.0
  990. decay_mult: 0.0
  991. }
  992. }
  993.  
  994. layer {
  995. bottom: "res3a_branch1"
  996. bottom: "res3a_branch2c"
  997. top: "res3a"
  998. name: "res3a"
  999. type: "Eltwise"
  1000. }
  1001.  
  1002. layer {
  1003. bottom: "res3a"
  1004. top: "res3a"
  1005. name: "res3a_relu"
  1006. type: "ReLU"
  1007. }
  1008.  
  1009. layer {
  1010. bottom: "res3a"
  1011. top: "res3b_branch2a"
  1012. name: "res3b_branch2a"
  1013. type: "Convolution"
  1014. convolution_param {
  1015. num_output: 128
  1016. kernel_size: 1
  1017. pad: 0
  1018. stride: 1
  1019. bias_term: false
  1020. }
  1021. param {
  1022. lr_mult: 1.0
  1023. }
  1024. }
  1025.  
  1026. layer {
  1027. bottom: "res3b_branch2a"
  1028. top: "res3b_branch2a"
  1029. name: "bn3b_branch2a"
  1030. type: "BatchNorm"
  1031. batch_norm_param {
  1032. use_global_stats: true
  1033. }
  1034. param {
  1035. lr_mult: 0.0
  1036. decay_mult: 0.0
  1037. }
  1038. param {
  1039. lr_mult: 0.0
  1040. decay_mult: 0.0
  1041. }
  1042. param {
  1043. lr_mult: 0.0
  1044. decay_mult: 0.0
  1045. }
  1046. }
  1047.  
  1048. layer {
  1049. bottom: "res3b_branch2a"
  1050. top: "res3b_branch2a"
  1051. name: "scale3b_branch2a"
  1052. type: "Scale"
  1053. scale_param {
  1054. bias_term: true
  1055. }
  1056. param {
  1057. lr_mult: 0.0
  1058. decay_mult: 0.0
  1059. }
  1060. param {
  1061. lr_mult: 0.0
  1062. decay_mult: 0.0
  1063. }
  1064. }
  1065.  
  1066. layer {
  1067. bottom: "res3b_branch2a"
  1068. top: "res3b_branch2a"
  1069. name: "res3b_branch2a_relu"
  1070. type: "ReLU"
  1071. }
  1072.  
  1073. layer {
  1074. bottom: "res3b_branch2a"
  1075. top: "res3b_branch2b"
  1076. name: "res3b_branch2b"
  1077. type: "Convolution"
  1078. convolution_param {
  1079. num_output: 128
  1080. kernel_size: 3
  1081. pad: 1
  1082. stride: 1
  1083. bias_term: false
  1084. }
  1085. param {
  1086. lr_mult: 1.0
  1087. }
  1088. }
  1089.  
  1090. layer {
  1091. bottom: "res3b_branch2b"
  1092. top: "res3b_branch2b"
  1093. name: "bn3b_branch2b"
  1094. type: "BatchNorm"
  1095. batch_norm_param {
  1096. use_global_stats: true
  1097. }
  1098. param {
  1099. lr_mult: 0.0
  1100. decay_mult: 0.0
  1101. }
  1102. param {
  1103. lr_mult: 0.0
  1104. decay_mult: 0.0
  1105. }
  1106. param {
  1107. lr_mult: 0.0
  1108. decay_mult: 0.0
  1109. }
  1110. }
  1111.  
  1112. layer {
  1113. bottom: "res3b_branch2b"
  1114. top: "res3b_branch2b"
  1115. name: "scale3b_branch2b"
  1116. type: "Scale"
  1117. scale_param {
  1118. bias_term: true
  1119. }
  1120. param {
  1121. lr_mult: 0.0
  1122. decay_mult: 0.0
  1123. }
  1124. param {
  1125. lr_mult: 0.0
  1126. decay_mult: 0.0
  1127. }
  1128. }
  1129.  
  1130. layer {
  1131. bottom: "res3b_branch2b"
  1132. top: "res3b_branch2b"
  1133. name: "res3b_branch2b_relu"
  1134. type: "ReLU"
  1135. }
  1136.  
  1137. layer {
  1138. bottom: "res3b_branch2b"
  1139. top: "res3b_branch2c"
  1140. name: "res3b_branch2c"
  1141. type: "Convolution"
  1142. convolution_param {
  1143. num_output: 512
  1144. kernel_size: 1
  1145. pad: 0
  1146. stride: 1
  1147. bias_term: false
  1148. }
  1149. param {
  1150. lr_mult: 1.0
  1151. }
  1152. }
  1153.  
  1154. layer {
  1155. bottom: "res3b_branch2c"
  1156. top: "res3b_branch2c"
  1157. name: "bn3b_branch2c"
  1158. type: "BatchNorm"
  1159. batch_norm_param {
  1160. use_global_stats: true
  1161. }
  1162. param {
  1163. lr_mult: 0.0
  1164. decay_mult: 0.0
  1165. }
  1166. param {
  1167. lr_mult: 0.0
  1168. decay_mult: 0.0
  1169. }
  1170. param {
  1171. lr_mult: 0.0
  1172. decay_mult: 0.0
  1173. }
  1174. }
  1175.  
  1176. layer {
  1177. bottom: "res3b_branch2c"
  1178. top: "res3b_branch2c"
  1179. name: "scale3b_branch2c"
  1180. type: "Scale"
  1181. scale_param {
  1182. bias_term: true
  1183. }
  1184. param {
  1185. lr_mult: 0.0
  1186. decay_mult: 0.0
  1187. }
  1188. param {
  1189. lr_mult: 0.0
  1190. decay_mult: 0.0
  1191. }
  1192. }
  1193.  
  1194. layer {
  1195. bottom: "res3a"
  1196. bottom: "res3b_branch2c"
  1197. top: "res3b"
  1198. name: "res3b"
  1199. type: "Eltwise"
  1200. }
  1201.  
  1202. layer {
  1203. bottom: "res3b"
  1204. top: "res3b"
  1205. name: "res3b_relu"
  1206. type: "ReLU"
  1207. }
  1208.  
  1209. layer {
  1210. bottom: "res3b"
  1211. top: "res3c_branch2a"
  1212. name: "res3c_branch2a"
  1213. type: "Convolution"
  1214. convolution_param {
  1215. num_output: 128
  1216. kernel_size: 1
  1217. pad: 0
  1218. stride: 1
  1219. bias_term: false
  1220. }
  1221. param {
  1222. lr_mult: 1.0
  1223. }
  1224. }
  1225.  
  1226. layer {
  1227. bottom: "res3c_branch2a"
  1228. top: "res3c_branch2a"
  1229. name: "bn3c_branch2a"
  1230. type: "BatchNorm"
  1231. batch_norm_param {
  1232. use_global_stats: true
  1233. }
  1234. param {
  1235. lr_mult: 0.0
  1236. decay_mult: 0.0
  1237. }
  1238. param {
  1239. lr_mult: 0.0
  1240. decay_mult: 0.0
  1241. }
  1242. param {
  1243. lr_mult: 0.0
  1244. decay_mult: 0.0
  1245. }
  1246. }
  1247.  
  1248. layer {
  1249. bottom: "res3c_branch2a"
  1250. top: "res3c_branch2a"
  1251. name: "scale3c_branch2a"
  1252. type: "Scale"
  1253. scale_param {
  1254. bias_term: true
  1255. }
  1256. param {
  1257. lr_mult: 0.0
  1258. decay_mult: 0.0
  1259. }
  1260. param {
  1261. lr_mult: 0.0
  1262. decay_mult: 0.0
  1263. }
  1264. }
  1265.  
  1266. layer {
  1267. bottom: "res3c_branch2a"
  1268. top: "res3c_branch2a"
  1269. name: "res3c_branch2a_relu"
  1270. type: "ReLU"
  1271. }
  1272.  
  1273. layer {
  1274. bottom: "res3c_branch2a"
  1275. top: "res3c_branch2b"
  1276. name: "res3c_branch2b"
  1277. type: "Convolution"
  1278. convolution_param {
  1279. num_output: 128
  1280. kernel_size: 3
  1281. pad: 1
  1282. stride: 1
  1283. bias_term: false
  1284. }
  1285. param {
  1286. lr_mult: 1.0
  1287. }
  1288. }
  1289.  
  1290. layer {
  1291. bottom: "res3c_branch2b"
  1292. top: "res3c_branch2b"
  1293. name: "bn3c_branch2b"
  1294. type: "BatchNorm"
  1295. batch_norm_param {
  1296. use_global_stats: true
  1297. }
  1298. param {
  1299. lr_mult: 0.0
  1300. decay_mult: 0.0
  1301. }
  1302. param {
  1303. lr_mult: 0.0
  1304. decay_mult: 0.0
  1305. }
  1306. param {
  1307. lr_mult: 0.0
  1308. decay_mult: 0.0
  1309. }
  1310. }
  1311.  
  1312. layer {
  1313. bottom: "res3c_branch2b"
  1314. top: "res3c_branch2b"
  1315. name: "scale3c_branch2b"
  1316. type: "Scale"
  1317. scale_param {
  1318. bias_term: true
  1319. }
  1320. param {
  1321. lr_mult: 0.0
  1322. decay_mult: 0.0
  1323. }
  1324. param {
  1325. lr_mult: 0.0
  1326. decay_mult: 0.0
  1327. }
  1328. }
  1329.  
  1330. layer {
  1331. bottom: "res3c_branch2b"
  1332. top: "res3c_branch2b"
  1333. name: "res3c_branch2b_relu"
  1334. type: "ReLU"
  1335. }
  1336.  
  1337. layer {
  1338. bottom: "res3c_branch2b"
  1339. top: "res3c_branch2c"
  1340. name: "res3c_branch2c"
  1341. type: "Convolution"
  1342. convolution_param {
  1343. num_output: 512
  1344. kernel_size: 1
  1345. pad: 0
  1346. stride: 1
  1347. bias_term: false
  1348. }
  1349. param {
  1350. lr_mult: 1.0
  1351. }
  1352. }
  1353.  
  1354. layer {
  1355. bottom: "res3c_branch2c"
  1356. top: "res3c_branch2c"
  1357. name: "bn3c_branch2c"
  1358. type: "BatchNorm"
  1359. batch_norm_param {
  1360. use_global_stats: true
  1361. }
  1362. param {
  1363. lr_mult: 0.0
  1364. decay_mult: 0.0
  1365. }
  1366. param {
  1367. lr_mult: 0.0
  1368. decay_mult: 0.0
  1369. }
  1370. param {
  1371. lr_mult: 0.0
  1372. decay_mult: 0.0
  1373. }
  1374. }
  1375.  
  1376. layer {
  1377. bottom: "res3c_branch2c"
  1378. top: "res3c_branch2c"
  1379. name: "scale3c_branch2c"
  1380. type: "Scale"
  1381. scale_param {
  1382. bias_term: true
  1383. }
  1384. param {
  1385. lr_mult: 0.0
  1386. decay_mult: 0.0
  1387. }
  1388. param {
  1389. lr_mult: 0.0
  1390. decay_mult: 0.0
  1391. }
  1392. }
  1393.  
  1394. layer {
  1395. bottom: "res3b"
  1396. bottom: "res3c_branch2c"
  1397. top: "res3c"
  1398. name: "res3c"
  1399. type: "Eltwise"
  1400. }
  1401.  
  1402. layer {
  1403. bottom: "res3c"
  1404. top: "res3c"
  1405. name: "res3c_relu"
  1406. type: "ReLU"
  1407. }
  1408.  
  1409. layer {
  1410. bottom: "res3c"
  1411. top: "res3d_branch2a"
  1412. name: "res3d_branch2a"
  1413. type: "Convolution"
  1414. convolution_param {
  1415. num_output: 128
  1416. kernel_size: 1
  1417. pad: 0
  1418. stride: 1
  1419. bias_term: false
  1420. }
  1421. param {
  1422. lr_mult: 1.0
  1423. }
  1424. }
  1425.  
  1426. layer {
  1427. bottom: "res3d_branch2a"
  1428. top: "res3d_branch2a"
  1429. name: "bn3d_branch2a"
  1430. type: "BatchNorm"
  1431. batch_norm_param {
  1432. use_global_stats: true
  1433. }
  1434. param {
  1435. lr_mult: 0.0
  1436. decay_mult: 0.0
  1437. }
  1438. param {
  1439. lr_mult: 0.0
  1440. decay_mult: 0.0
  1441. }
  1442. param {
  1443. lr_mult: 0.0
  1444. decay_mult: 0.0
  1445. }
  1446. }
  1447.  
  1448. layer {
  1449. bottom: "res3d_branch2a"
  1450. top: "res3d_branch2a"
  1451. name: "scale3d_branch2a"
  1452. type: "Scale"
  1453. scale_param {
  1454. bias_term: true
  1455. }
  1456. param {
  1457. lr_mult: 0.0
  1458. decay_mult: 0.0
  1459. }
  1460. param {
  1461. lr_mult: 0.0
  1462. decay_mult: 0.0
  1463. }
  1464. }
  1465.  
  1466. layer {
  1467. bottom: "res3d_branch2a"
  1468. top: "res3d_branch2a"
  1469. name: "res3d_branch2a_relu"
  1470. type: "ReLU"
  1471. }
  1472.  
  1473. layer {
  1474. bottom: "res3d_branch2a"
  1475. top: "res3d_branch2b"
  1476. name: "res3d_branch2b"
  1477. type: "Convolution"
  1478. convolution_param {
  1479. num_output: 128
  1480. kernel_size: 3
  1481. pad: 1
  1482. stride: 1
  1483. bias_term: false
  1484. }
  1485. param {
  1486. lr_mult: 1.0
  1487. }
  1488. }
  1489.  
  1490. layer {
  1491. bottom: "res3d_branch2b"
  1492. top: "res3d_branch2b"
  1493. name: "bn3d_branch2b"
  1494. type: "BatchNorm"
  1495. batch_norm_param {
  1496. use_global_stats: true
  1497. }
  1498. param {
  1499. lr_mult: 0.0
  1500. decay_mult: 0.0
  1501. }
  1502. param {
  1503. lr_mult: 0.0
  1504. decay_mult: 0.0
  1505. }
  1506. param {
  1507. lr_mult: 0.0
  1508. decay_mult: 0.0
  1509. }
  1510. }
  1511.  
  1512. layer {
  1513. bottom: "res3d_branch2b"
  1514. top: "res3d_branch2b"
  1515. name: "scale3d_branch2b"
  1516. type: "Scale"
  1517. scale_param {
  1518. bias_term: true
  1519. }
  1520. param {
  1521. lr_mult: 0.0
  1522. decay_mult: 0.0
  1523. }
  1524. param {
  1525. lr_mult: 0.0
  1526. decay_mult: 0.0
  1527. }
  1528. }
  1529.  
  1530. layer {
  1531. bottom: "res3d_branch2b"
  1532. top: "res3d_branch2b"
  1533. name: "res3d_branch2b_relu"
  1534. type: "ReLU"
  1535. }
  1536.  
  1537. layer {
  1538. bottom: "res3d_branch2b"
  1539. top: "res3d_branch2c"
  1540. name: "res3d_branch2c"
  1541. type: "Convolution"
  1542. convolution_param {
  1543. num_output: 512
  1544. kernel_size: 1
  1545. pad: 0
  1546. stride: 1
  1547. bias_term: false
  1548. }
  1549. param {
  1550. lr_mult: 1.0
  1551. }
  1552. }
  1553.  
  1554. layer {
  1555. bottom: "res3d_branch2c"
  1556. top: "res3d_branch2c"
  1557. name: "bn3d_branch2c"
  1558. type: "BatchNorm"
  1559. batch_norm_param {
  1560. use_global_stats: true
  1561. }
  1562. param {
  1563. lr_mult: 0.0
  1564. decay_mult: 0.0
  1565. }
  1566. param {
  1567. lr_mult: 0.0
  1568. decay_mult: 0.0
  1569. }
  1570. param {
  1571. lr_mult: 0.0
  1572. decay_mult: 0.0
  1573. }
  1574. }
  1575.  
  1576. layer {
  1577. bottom: "res3d_branch2c"
  1578. top: "res3d_branch2c"
  1579. name: "scale3d_branch2c"
  1580. type: "Scale"
  1581. scale_param {
  1582. bias_term: true
  1583. }
  1584. param {
  1585. lr_mult: 0.0
  1586. decay_mult: 0.0
  1587. }
  1588. param {
  1589. lr_mult: 0.0
  1590. decay_mult: 0.0
  1591. }
  1592. }
  1593.  
  1594. layer {
  1595. bottom: "res3c"
  1596. bottom: "res3d_branch2c"
  1597. top: "res3d"
  1598. name: "res3d"
  1599. type: "Eltwise"
  1600. }
  1601.  
  1602. layer {
  1603. bottom: "res3d"
  1604. top: "res3d"
  1605. name: "res3d_relu"
  1606. type: "ReLU"
  1607. }
  1608.  
  1609. layer {
  1610. bottom: "res3d"
  1611. top: "res4a_branch1"
  1612. name: "res4a_branch1"
  1613. type: "Convolution"
  1614. convolution_param {
  1615. num_output: 1024
  1616. kernel_size: 1
  1617. pad: 0
  1618. stride: 2
  1619. bias_term: false
  1620. }
  1621. param {
  1622. lr_mult: 1.0
  1623. }
  1624. }
  1625.  
  1626. layer {
  1627. bottom: "res4a_branch1"
  1628. top: "res4a_branch1"
  1629. name: "bn4a_branch1"
  1630. type: "BatchNorm"
  1631. batch_norm_param {
  1632. use_global_stats: true
  1633. }
  1634. param {
  1635. lr_mult: 0.0
  1636. decay_mult: 0.0
  1637. }
  1638. param {
  1639. lr_mult: 0.0
  1640. decay_mult: 0.0
  1641. }
  1642. param {
  1643. lr_mult: 0.0
  1644. decay_mult: 0.0
  1645. }
  1646. }
  1647.  
  1648. layer {
  1649. bottom: "res4a_branch1"
  1650. top: "res4a_branch1"
  1651. name: "scale4a_branch1"
  1652. type: "Scale"
  1653. scale_param {
  1654. bias_term: true
  1655. }
  1656. param {
  1657. lr_mult: 0.0
  1658. decay_mult: 0.0
  1659. }
  1660. param {
  1661. lr_mult: 0.0
  1662. decay_mult: 0.0
  1663. }
  1664. }
  1665.  
  1666. layer {
  1667. bottom: "res3d"
  1668. top: "res4a_branch2a"
  1669. name: "res4a_branch2a"
  1670. type: "Convolution"
  1671. convolution_param {
  1672. num_output: 256
  1673. kernel_size: 1
  1674. pad: 0
  1675. stride: 2
  1676. bias_term: false
  1677. }
  1678. param {
  1679. lr_mult: 1.0
  1680. }
  1681. }
  1682.  
  1683. layer {
  1684. bottom: "res4a_branch2a"
  1685. top: "res4a_branch2a"
  1686. name: "bn4a_branch2a"
  1687. type: "BatchNorm"
  1688. batch_norm_param {
  1689. use_global_stats: true
  1690. }
  1691. param {
  1692. lr_mult: 0.0
  1693. decay_mult: 0.0
  1694. }
  1695. param {
  1696. lr_mult: 0.0
  1697. decay_mult: 0.0
  1698. }
  1699. param {
  1700. lr_mult: 0.0
  1701. decay_mult: 0.0
  1702. }
  1703. }
  1704.  
  1705. layer {
  1706. bottom: "res4a_branch2a"
  1707. top: "res4a_branch2a"
  1708. name: "scale4a_branch2a"
  1709. type: "Scale"
  1710. scale_param {
  1711. bias_term: true
  1712. }
  1713. param {
  1714. lr_mult: 0.0
  1715. decay_mult: 0.0
  1716. }
  1717. param {
  1718. lr_mult: 0.0
  1719. decay_mult: 0.0
  1720. }
  1721. }
  1722.  
  1723. layer {
  1724. bottom: "res4a_branch2a"
  1725. top: "res4a_branch2a"
  1726. name: "res4a_branch2a_relu"
  1727. type: "ReLU"
  1728. }
  1729.  
  1730. layer {
  1731. bottom: "res4a_branch2a"
  1732. top: "res4a_branch2b"
  1733. name: "res4a_branch2b"
  1734. type: "Convolution"
  1735. convolution_param {
  1736. num_output: 256
  1737. kernel_size: 3
  1738. pad: 1
  1739. stride: 1
  1740. bias_term: false
  1741. }
  1742. param {
  1743. lr_mult: 1.0
  1744. }
  1745. }
  1746.  
  1747. layer {
  1748. bottom: "res4a_branch2b"
  1749. top: "res4a_branch2b"
  1750. name: "bn4a_branch2b"
  1751. type: "BatchNorm"
  1752. batch_norm_param {
  1753. use_global_stats: true
  1754. }
  1755. param {
  1756. lr_mult: 0.0
  1757. decay_mult: 0.0
  1758. }
  1759. param {
  1760. lr_mult: 0.0
  1761. decay_mult: 0.0
  1762. }
  1763. param {
  1764. lr_mult: 0.0
  1765. decay_mult: 0.0
  1766. }
  1767. }
  1768.  
  1769. layer {
  1770. bottom: "res4a_branch2b"
  1771. top: "res4a_branch2b"
  1772. name: "scale4a_branch2b"
  1773. type: "Scale"
  1774. scale_param {
  1775. bias_term: true
  1776. }
  1777. param {
  1778. lr_mult: 0.0
  1779. decay_mult: 0.0
  1780. }
  1781. param {
  1782. lr_mult: 0.0
  1783. decay_mult: 0.0
  1784. }
  1785. }
  1786.  
  1787. layer {
  1788. bottom: "res4a_branch2b"
  1789. top: "res4a_branch2b"
  1790. name: "res4a_branch2b_relu"
  1791. type: "ReLU"
  1792. }
  1793.  
  1794. layer {
  1795. bottom: "res4a_branch2b"
  1796. top: "res4a_branch2c"
  1797. name: "res4a_branch2c"
  1798. type: "Convolution"
  1799. convolution_param {
  1800. num_output: 1024
  1801. kernel_size: 1
  1802. pad: 0
  1803. stride: 1
  1804. bias_term: false
  1805. }
  1806. param {
  1807. lr_mult: 1.0
  1808. }
  1809. }
  1810.  
  1811. layer {
  1812. bottom: "res4a_branch2c"
  1813. top: "res4a_branch2c"
  1814. name: "bn4a_branch2c"
  1815. type: "BatchNorm"
  1816. batch_norm_param {
  1817. use_global_stats: true
  1818. }
  1819. param {
  1820. lr_mult: 0.0
  1821. decay_mult: 0.0
  1822. }
  1823. param {
  1824. lr_mult: 0.0
  1825. decay_mult: 0.0
  1826. }
  1827. param {
  1828. lr_mult: 0.0
  1829. decay_mult: 0.0
  1830. }
  1831. }
  1832.  
  1833. layer {
  1834. bottom: "res4a_branch2c"
  1835. top: "res4a_branch2c"
  1836. name: "scale4a_branch2c"
  1837. type: "Scale"
  1838. scale_param {
  1839. bias_term: true
  1840. }
  1841. param {
  1842. lr_mult: 0.0
  1843. decay_mult: 0.0
  1844. }
  1845. param {
  1846. lr_mult: 0.0
  1847. decay_mult: 0.0
  1848. }
  1849. }
  1850.  
  1851. layer {
  1852. bottom: "res4a_branch1"
  1853. bottom: "res4a_branch2c"
  1854. top: "res4a"
  1855. name: "res4a"
  1856. type: "Eltwise"
  1857. }
  1858.  
  1859. layer {
  1860. bottom: "res4a"
  1861. top: "res4a"
  1862. name: "res4a_relu"
  1863. type: "ReLU"
  1864. }
  1865.  
  1866. layer {
  1867. bottom: "res4a"
  1868. top: "res4b_branch2a"
  1869. name: "res4b_branch2a"
  1870. type: "Convolution"
  1871. convolution_param {
  1872. num_output: 256
  1873. kernel_size: 1
  1874. pad: 0
  1875. stride: 1
  1876. bias_term: false
  1877. }
  1878. param {
  1879. lr_mult: 1.0
  1880. }
  1881. }
  1882.  
  1883. layer {
  1884. bottom: "res4b_branch2a"
  1885. top: "res4b_branch2a"
  1886. name: "bn4b_branch2a"
  1887. type: "BatchNorm"
  1888. batch_norm_param {
  1889. use_global_stats: true
  1890. }
  1891. param {
  1892. lr_mult: 0.0
  1893. decay_mult: 0.0
  1894. }
  1895. param {
  1896. lr_mult: 0.0
  1897. decay_mult: 0.0
  1898. }
  1899. param {
  1900. lr_mult: 0.0
  1901. decay_mult: 0.0
  1902. }
  1903. }
  1904.  
  1905. layer {
  1906. bottom: "res4b_branch2a"
  1907. top: "res4b_branch2a"
  1908. name: "scale4b_branch2a"
  1909. type: "Scale"
  1910. scale_param {
  1911. bias_term: true
  1912. }
  1913. param {
  1914. lr_mult: 0.0
  1915. decay_mult: 0.0
  1916. }
  1917. param {
  1918. lr_mult: 0.0
  1919. decay_mult: 0.0
  1920. }
  1921. }
  1922.  
  1923. layer {
  1924. bottom: "res4b_branch2a"
  1925. top: "res4b_branch2a"
  1926. name: "res4b_branch2a_relu"
  1927. type: "ReLU"
  1928. }
  1929.  
  1930. layer {
  1931. bottom: "res4b_branch2a"
  1932. top: "res4b_branch2b"
  1933. name: "res4b_branch2b"
  1934. type: "Convolution"
  1935. convolution_param {
  1936. num_output: 256
  1937. kernel_size: 3
  1938. pad: 1
  1939. stride: 1
  1940. bias_term: false
  1941. }
  1942. param {
  1943. lr_mult: 1.0
  1944. }
  1945. }
  1946.  
  1947. layer {
  1948. bottom: "res4b_branch2b"
  1949. top: "res4b_branch2b"
  1950. name: "bn4b_branch2b"
  1951. type: "BatchNorm"
  1952. batch_norm_param {
  1953. use_global_stats: true
  1954. }
  1955. param {
  1956. lr_mult: 0.0
  1957. decay_mult: 0.0
  1958. }
  1959. param {
  1960. lr_mult: 0.0
  1961. decay_mult: 0.0
  1962. }
  1963. param {
  1964. lr_mult: 0.0
  1965. decay_mult: 0.0
  1966. }
  1967. }
  1968.  
  1969. layer {
  1970. bottom: "res4b_branch2b"
  1971. top: "res4b_branch2b"
  1972. name: "scale4b_branch2b"
  1973. type: "Scale"
  1974. scale_param {
  1975. bias_term: true
  1976. }
  1977. param {
  1978. lr_mult: 0.0
  1979. decay_mult: 0.0
  1980. }
  1981. param {
  1982. lr_mult: 0.0
  1983. decay_mult: 0.0
  1984. }
  1985. }
  1986.  
  1987. layer {
  1988. bottom: "res4b_branch2b"
  1989. top: "res4b_branch2b"
  1990. name: "res4b_branch2b_relu"
  1991. type: "ReLU"
  1992. }
  1993.  
  1994. layer {
  1995. bottom: "res4b_branch2b"
  1996. top: "res4b_branch2c"
  1997. name: "res4b_branch2c"
  1998. type: "Convolution"
  1999. convolution_param {
  2000. num_output: 1024
  2001. kernel_size: 1
  2002. pad: 0
  2003. stride: 1
  2004. bias_term: false
  2005. }
  2006. param {
  2007. lr_mult: 1.0
  2008. }
  2009. }
  2010.  
  2011. layer {
  2012. bottom: "res4b_branch2c"
  2013. top: "res4b_branch2c"
  2014. name: "bn4b_branch2c"
  2015. type: "BatchNorm"
  2016. batch_norm_param {
  2017. use_global_stats: true
  2018. }
  2019. param {
  2020. lr_mult: 0.0
  2021. decay_mult: 0.0
  2022. }
  2023. param {
  2024. lr_mult: 0.0
  2025. decay_mult: 0.0
  2026. }
  2027. param {
  2028. lr_mult: 0.0
  2029. decay_mult: 0.0
  2030. }
  2031. }
  2032.  
  2033. layer {
  2034. bottom: "res4b_branch2c"
  2035. top: "res4b_branch2c"
  2036. name: "scale4b_branch2c"
  2037. type: "Scale"
  2038. scale_param {
  2039. bias_term: true
  2040. }
  2041. param {
  2042. lr_mult: 0.0
  2043. decay_mult: 0.0
  2044. }
  2045. param {
  2046. lr_mult: 0.0
  2047. decay_mult: 0.0
  2048. }
  2049. }
  2050.  
  2051. layer {
  2052. bottom: "res4a"
  2053. bottom: "res4b_branch2c"
  2054. top: "res4b"
  2055. name: "res4b"
  2056. type: "Eltwise"
  2057. }
  2058.  
  2059. layer {
  2060. bottom: "res4b"
  2061. top: "res4b"
  2062. name: "res4b_relu"
  2063. type: "ReLU"
  2064. }
  2065.  
  2066. layer {
  2067. bottom: "res4b"
  2068. top: "res4c_branch2a"
  2069. name: "res4c_branch2a"
  2070. type: "Convolution"
  2071. convolution_param {
  2072. num_output: 256
  2073. kernel_size: 1
  2074. pad: 0
  2075. stride: 1
  2076. bias_term: false
  2077. }
  2078. param {
  2079. lr_mult: 1.0
  2080. }
  2081. }
  2082.  
  2083. layer {
  2084. bottom: "res4c_branch2a"
  2085. top: "res4c_branch2a"
  2086. name: "bn4c_branch2a"
  2087. type: "BatchNorm"
  2088. batch_norm_param {
  2089. use_global_stats: true
  2090. }
  2091. param {
  2092. lr_mult: 0.0
  2093. decay_mult: 0.0
  2094. }
  2095. param {
  2096. lr_mult: 0.0
  2097. decay_mult: 0.0
  2098. }
  2099. param {
  2100. lr_mult: 0.0
  2101. decay_mult: 0.0
  2102. }
  2103. }
  2104.  
  2105. layer {
  2106. bottom: "res4c_branch2a"
  2107. top: "res4c_branch2a"
  2108. name: "scale4c_branch2a"
  2109. type: "Scale"
  2110. scale_param {
  2111. bias_term: true
  2112. }
  2113. param {
  2114. lr_mult: 0.0
  2115. decay_mult: 0.0
  2116. }
  2117. param {
  2118. lr_mult: 0.0
  2119. decay_mult: 0.0
  2120. }
  2121. }
  2122.  
  2123. layer {
  2124. bottom: "res4c_branch2a"
  2125. top: "res4c_branch2a"
  2126. name: "res4c_branch2a_relu"
  2127. type: "ReLU"
  2128. }
  2129.  
  2130. layer {
  2131. bottom: "res4c_branch2a"
  2132. top: "res4c_branch2b"
  2133. name: "res4c_branch2b"
  2134. type: "Convolution"
  2135. convolution_param {
  2136. num_output: 256
  2137. kernel_size: 3
  2138. pad: 1
  2139. stride: 1
  2140. bias_term: false
  2141. }
  2142. param {
  2143. lr_mult: 1.0
  2144. }
  2145. }
  2146.  
  2147. layer {
  2148. bottom: "res4c_branch2b"
  2149. top: "res4c_branch2b"
  2150. name: "bn4c_branch2b"
  2151. type: "BatchNorm"
  2152. batch_norm_param {
  2153. use_global_stats: true
  2154. }
  2155. param {
  2156. lr_mult: 0.0
  2157. decay_mult: 0.0
  2158. }
  2159. param {
  2160. lr_mult: 0.0
  2161. decay_mult: 0.0
  2162. }
  2163. param {
  2164. lr_mult: 0.0
  2165. decay_mult: 0.0
  2166. }
  2167. }
  2168.  
  2169. layer {
  2170. bottom: "res4c_branch2b"
  2171. top: "res4c_branch2b"
  2172. name: "scale4c_branch2b"
  2173. type: "Scale"
  2174. scale_param {
  2175. bias_term: true
  2176. }
  2177. param {
  2178. lr_mult: 0.0
  2179. decay_mult: 0.0
  2180. }
  2181. param {
  2182. lr_mult: 0.0
  2183. decay_mult: 0.0
  2184. }
  2185. }
  2186.  
  2187. layer {
  2188. bottom: "res4c_branch2b"
  2189. top: "res4c_branch2b"
  2190. name: "res4c_branch2b_relu"
  2191. type: "ReLU"
  2192. }
  2193.  
  2194. layer {
  2195. bottom: "res4c_branch2b"
  2196. top: "res4c_branch2c"
  2197. name: "res4c_branch2c"
  2198. type: "Convolution"
  2199. convolution_param {
  2200. num_output: 1024
  2201. kernel_size: 1
  2202. pad: 0
  2203. stride: 1
  2204. bias_term: false
  2205. }
  2206. param {
  2207. lr_mult: 1.0
  2208. }
  2209. }
  2210.  
  2211. layer {
  2212. bottom: "res4c_branch2c"
  2213. top: "res4c_branch2c"
  2214. name: "bn4c_branch2c"
  2215. type: "BatchNorm"
  2216. batch_norm_param {
  2217. use_global_stats: true
  2218. }
  2219. param {
  2220. lr_mult: 0.0
  2221. decay_mult: 0.0
  2222. }
  2223. param {
  2224. lr_mult: 0.0
  2225. decay_mult: 0.0
  2226. }
  2227. param {
  2228. lr_mult: 0.0
  2229. decay_mult: 0.0
  2230. }
  2231. }
  2232.  
  2233. layer {
  2234. bottom: "res4c_branch2c"
  2235. top: "res4c_branch2c"
  2236. name: "scale4c_branch2c"
  2237. type: "Scale"
  2238. scale_param {
  2239. bias_term: true
  2240. }
  2241. param {
  2242. lr_mult: 0.0
  2243. decay_mult: 0.0
  2244. }
  2245. param {
  2246. lr_mult: 0.0
  2247. decay_mult: 0.0
  2248. }
  2249. }
  2250.  
  2251. layer {
  2252. bottom: "res4b"
  2253. bottom: "res4c_branch2c"
  2254. top: "res4c"
  2255. name: "res4c"
  2256. type: "Eltwise"
  2257. }
  2258.  
  2259. layer {
  2260. bottom: "res4c"
  2261. top: "res4c"
  2262. name: "res4c_relu"
  2263. type: "ReLU"
  2264. }
  2265.  
  2266. layer {
  2267. bottom: "res4c"
  2268. top: "res4d_branch2a"
  2269. name: "res4d_branch2a"
  2270. type: "Convolution"
  2271. convolution_param {
  2272. num_output: 256
  2273. kernel_size: 1
  2274. pad: 0
  2275. stride: 1
  2276. bias_term: false
  2277. }
  2278. param {
  2279. lr_mult: 1.0
  2280. }
  2281. }
  2282.  
  2283. layer {
  2284. bottom: "res4d_branch2a"
  2285. top: "res4d_branch2a"
  2286. name: "bn4d_branch2a"
  2287. type: "BatchNorm"
  2288. batch_norm_param {
  2289. use_global_stats: true
  2290. }
  2291. param {
  2292. lr_mult: 0.0
  2293. decay_mult: 0.0
  2294. }
  2295. param {
  2296. lr_mult: 0.0
  2297. decay_mult: 0.0
  2298. }
  2299. param {
  2300. lr_mult: 0.0
  2301. decay_mult: 0.0
  2302. }
  2303. }
  2304.  
  2305. layer {
  2306. bottom: "res4d_branch2a"
  2307. top: "res4d_branch2a"
  2308. name: "scale4d_branch2a"
  2309. type: "Scale"
  2310. scale_param {
  2311. bias_term: true
  2312. }
  2313. param {
  2314. lr_mult: 0.0
  2315. decay_mult: 0.0
  2316. }
  2317. param {
  2318. lr_mult: 0.0
  2319. decay_mult: 0.0
  2320. }
  2321. }
  2322.  
  2323. layer {
  2324. bottom: "res4d_branch2a"
  2325. top: "res4d_branch2a"
  2326. name: "res4d_branch2a_relu"
  2327. type: "ReLU"
  2328. }
  2329.  
  2330. layer {
  2331. bottom: "res4d_branch2a"
  2332. top: "res4d_branch2b"
  2333. name: "res4d_branch2b"
  2334. type: "Convolution"
  2335. convolution_param {
  2336. num_output: 256
  2337. kernel_size: 3
  2338. pad: 1
  2339. stride: 1
  2340. bias_term: false
  2341. }
  2342. param {
  2343. lr_mult: 1.0
  2344. }
  2345. }
  2346.  
  2347. layer {
  2348. bottom: "res4d_branch2b"
  2349. top: "res4d_branch2b"
  2350. name: "bn4d_branch2b"
  2351. type: "BatchNorm"
  2352. batch_norm_param {
  2353. use_global_stats: true
  2354. }
  2355. param {
  2356. lr_mult: 0.0
  2357. decay_mult: 0.0
  2358. }
  2359. param {
  2360. lr_mult: 0.0
  2361. decay_mult: 0.0
  2362. }
  2363. param {
  2364. lr_mult: 0.0
  2365. decay_mult: 0.0
  2366. }
  2367. }
  2368.  
  2369. layer {
  2370. bottom: "res4d_branch2b"
  2371. top: "res4d_branch2b"
  2372. name: "scale4d_branch2b"
  2373. type: "Scale"
  2374. scale_param {
  2375. bias_term: true
  2376. }
  2377. param {
  2378. lr_mult: 0.0
  2379. decay_mult: 0.0
  2380. }
  2381. param {
  2382. lr_mult: 0.0
  2383. decay_mult: 0.0
  2384. }
  2385. }
  2386.  
  2387. layer {
  2388. bottom: "res4d_branch2b"
  2389. top: "res4d_branch2b"
  2390. name: "res4d_branch2b_relu"
  2391. type: "ReLU"
  2392. }
  2393.  
  2394. layer {
  2395. bottom: "res4d_branch2b"
  2396. top: "res4d_branch2c"
  2397. name: "res4d_branch2c"
  2398. type: "Convolution"
  2399. convolution_param {
  2400. num_output: 1024
  2401. kernel_size: 1
  2402. pad: 0
  2403. stride: 1
  2404. bias_term: false
  2405. }
  2406. param {
  2407. lr_mult: 1.0
  2408. }
  2409. }
  2410.  
  2411. layer {
  2412. bottom: "res4d_branch2c"
  2413. top: "res4d_branch2c"
  2414. name: "bn4d_branch2c"
  2415. type: "BatchNorm"
  2416. batch_norm_param {
  2417. use_global_stats: true
  2418. }
  2419. param {
  2420. lr_mult: 0.0
  2421. decay_mult: 0.0
  2422. }
  2423. param {
  2424. lr_mult: 0.0
  2425. decay_mult: 0.0
  2426. }
  2427. param {
  2428. lr_mult: 0.0
  2429. decay_mult: 0.0
  2430. }
  2431. }
  2432.  
  2433. layer {
  2434. bottom: "res4d_branch2c"
  2435. top: "res4d_branch2c"
  2436. name: "scale4d_branch2c"
  2437. type: "Scale"
  2438. scale_param {
  2439. bias_term: true
  2440. }
  2441. param {
  2442. lr_mult: 0.0
  2443. decay_mult: 0.0
  2444. }
  2445. param {
  2446. lr_mult: 0.0
  2447. decay_mult: 0.0
  2448. }
  2449. }
  2450.  
  2451. layer {
  2452. bottom: "res4c"
  2453. bottom: "res4d_branch2c"
  2454. top: "res4d"
  2455. name: "res4d"
  2456. type: "Eltwise"
  2457. }
  2458.  
  2459. layer {
  2460. bottom: "res4d"
  2461. top: "res4d"
  2462. name: "res4d_relu"
  2463. type: "ReLU"
  2464. }
  2465.  
  2466. layer {
  2467. bottom: "res4d"
  2468. top: "res4e_branch2a"
  2469. name: "res4e_branch2a"
  2470. type: "Convolution"
  2471. convolution_param {
  2472. num_output: 256
  2473. kernel_size: 1
  2474. pad: 0
  2475. stride: 1
  2476. bias_term: false
  2477. }
  2478. param {
  2479. lr_mult: 1.0
  2480. }
  2481. }
  2482.  
  2483. layer {
  2484. bottom: "res4e_branch2a"
  2485. top: "res4e_branch2a"
  2486. name: "bn4e_branch2a"
  2487. type: "BatchNorm"
  2488. batch_norm_param {
  2489. use_global_stats: true
  2490. }
  2491. param {
  2492. lr_mult: 0.0
  2493. decay_mult: 0.0
  2494. }
  2495. param {
  2496. lr_mult: 0.0
  2497. decay_mult: 0.0
  2498. }
  2499. param {
  2500. lr_mult: 0.0
  2501. decay_mult: 0.0
  2502. }
  2503. }
  2504.  
  2505. layer {
  2506. bottom: "res4e_branch2a"
  2507. top: "res4e_branch2a"
  2508. name: "scale4e_branch2a"
  2509. type: "Scale"
  2510. scale_param {
  2511. bias_term: true
  2512. }
  2513. param {
  2514. lr_mult: 0.0
  2515. decay_mult: 0.0
  2516. }
  2517. param {
  2518. lr_mult: 0.0
  2519. decay_mult: 0.0
  2520. }
  2521. }
  2522.  
  2523. layer {
  2524. bottom: "res4e_branch2a"
  2525. top: "res4e_branch2a"
  2526. name: "res4e_branch2a_relu"
  2527. type: "ReLU"
  2528. }
  2529.  
  2530. layer {
  2531. bottom: "res4e_branch2a"
  2532. top: "res4e_branch2b"
  2533. name: "res4e_branch2b"
  2534. type: "Convolution"
  2535. convolution_param {
  2536. num_output: 256
  2537. kernel_size: 3
  2538. pad: 1
  2539. stride: 1
  2540. bias_term: false
  2541. }
  2542. param {
  2543. lr_mult: 1.0
  2544. }
  2545. }
  2546.  
  2547. layer {
  2548. bottom: "res4e_branch2b"
  2549. top: "res4e_branch2b"
  2550. name: "bn4e_branch2b"
  2551. type: "BatchNorm"
  2552. batch_norm_param {
  2553. use_global_stats: true
  2554. }
  2555. param {
  2556. lr_mult: 0.0
  2557. decay_mult: 0.0
  2558. }
  2559. param {
  2560. lr_mult: 0.0
  2561. decay_mult: 0.0
  2562. }
  2563. param {
  2564. lr_mult: 0.0
  2565. decay_mult: 0.0
  2566. }
  2567. }
  2568.  
  2569. layer {
  2570. bottom: "res4e_branch2b"
  2571. top: "res4e_branch2b"
  2572. name: "scale4e_branch2b"
  2573. type: "Scale"
  2574. scale_param {
  2575. bias_term: true
  2576. }
  2577. param {
  2578. lr_mult: 0.0
  2579. decay_mult: 0.0
  2580. }
  2581. param {
  2582. lr_mult: 0.0
  2583. decay_mult: 0.0
  2584. }
  2585. }
  2586.  
  2587. layer {
  2588. bottom: "res4e_branch2b"
  2589. top: "res4e_branch2b"
  2590. name: "res4e_branch2b_relu"
  2591. type: "ReLU"
  2592. }
  2593.  
  2594. layer {
  2595. bottom: "res4e_branch2b"
  2596. top: "res4e_branch2c"
  2597. name: "res4e_branch2c"
  2598. type: "Convolution"
  2599. convolution_param {
  2600. num_output: 1024
  2601. kernel_size: 1
  2602. pad: 0
  2603. stride: 1
  2604. bias_term: false
  2605. }
  2606. param {
  2607. lr_mult: 1.0
  2608. }
  2609. }
  2610.  
  2611. layer {
  2612. bottom: "res4e_branch2c"
  2613. top: "res4e_branch2c"
  2614. name: "bn4e_branch2c"
  2615. type: "BatchNorm"
  2616. batch_norm_param {
  2617. use_global_stats: true
  2618. }
  2619. param {
  2620. lr_mult: 0.0
  2621. decay_mult: 0.0
  2622. }
  2623. param {
  2624. lr_mult: 0.0
  2625. decay_mult: 0.0
  2626. }
  2627. param {
  2628. lr_mult: 0.0
  2629. decay_mult: 0.0
  2630. }
  2631. }
  2632.  
  2633. layer {
  2634. bottom: "res4e_branch2c"
  2635. top: "res4e_branch2c"
  2636. name: "scale4e_branch2c"
  2637. type: "Scale"
  2638. scale_param {
  2639. bias_term: true
  2640. }
  2641. param {
  2642. lr_mult: 0.0
  2643. decay_mult: 0.0
  2644. }
  2645. param {
  2646. lr_mult: 0.0
  2647. decay_mult: 0.0
  2648. }
  2649. }
  2650.  
  2651. layer {
  2652. bottom: "res4d"
  2653. bottom: "res4e_branch2c"
  2654. top: "res4e"
  2655. name: "res4e"
  2656. type: "Eltwise"
  2657. }
  2658.  
  2659. layer {
  2660. bottom: "res4e"
  2661. top: "res4e"
  2662. name: "res4e_relu"
  2663. type: "ReLU"
  2664. }
  2665.  
  2666. layer {
  2667. bottom: "res4e"
  2668. top: "res4f_branch2a"
  2669. name: "res4f_branch2a"
  2670. type: "Convolution"
  2671. convolution_param {
  2672. num_output: 256
  2673. kernel_size: 1
  2674. pad: 0
  2675. stride: 1
  2676. bias_term: false
  2677. }
  2678. param {
  2679. lr_mult: 1.0
  2680. }
  2681. }
  2682.  
  2683. layer {
  2684. bottom: "res4f_branch2a"
  2685. top: "res4f_branch2a"
  2686. name: "bn4f_branch2a"
  2687. type: "BatchNorm"
  2688. batch_norm_param {
  2689. use_global_stats: true
  2690. }
  2691. param {
  2692. lr_mult: 0.0
  2693. decay_mult: 0.0
  2694. }
  2695. param {
  2696. lr_mult: 0.0
  2697. decay_mult: 0.0
  2698. }
  2699. param {
  2700. lr_mult: 0.0
  2701. decay_mult: 0.0
  2702. }
  2703. }
  2704.  
  2705. layer {
  2706. bottom: "res4f_branch2a"
  2707. top: "res4f_branch2a"
  2708. name: "scale4f_branch2a"
  2709. type: "Scale"
  2710. scale_param {
  2711. bias_term: true
  2712. }
  2713. param {
  2714. lr_mult: 0.0
  2715. decay_mult: 0.0
  2716. }
  2717. param {
  2718. lr_mult: 0.0
  2719. decay_mult: 0.0
  2720. }
  2721. }
  2722.  
  2723. layer {
  2724. bottom: "res4f_branch2a"
  2725. top: "res4f_branch2a"
  2726. name: "res4f_branch2a_relu"
  2727. type: "ReLU"
  2728. }
  2729.  
  2730. layer {
  2731. bottom: "res4f_branch2a"
  2732. top: "res4f_branch2b"
  2733. name: "res4f_branch2b"
  2734. type: "Convolution"
  2735. convolution_param {
  2736. num_output: 256
  2737. kernel_size: 3
  2738. pad: 1
  2739. stride: 1
  2740. bias_term: false
  2741. }
  2742. param {
  2743. lr_mult: 1.0
  2744. }
  2745. }
  2746.  
  2747. layer {
  2748. bottom: "res4f_branch2b"
  2749. top: "res4f_branch2b"
  2750. name: "bn4f_branch2b"
  2751. type: "BatchNorm"
  2752. batch_norm_param {
  2753. use_global_stats: true
  2754. }
  2755. param {
  2756. lr_mult: 0.0
  2757. decay_mult: 0.0
  2758. }
  2759. param {
  2760. lr_mult: 0.0
  2761. decay_mult: 0.0
  2762. }
  2763. param {
  2764. lr_mult: 0.0
  2765. decay_mult: 0.0
  2766. }
  2767. }
  2768.  
  2769. layer {
  2770. bottom: "res4f_branch2b"
  2771. top: "res4f_branch2b"
  2772. name: "scale4f_branch2b"
  2773. type: "Scale"
  2774. scale_param {
  2775. bias_term: true
  2776. }
  2777. param {
  2778. lr_mult: 0.0
  2779. decay_mult: 0.0
  2780. }
  2781. param {
  2782. lr_mult: 0.0
  2783. decay_mult: 0.0
  2784. }
  2785. }
  2786.  
  2787. layer {
  2788. bottom: "res4f_branch2b"
  2789. top: "res4f_branch2b"
  2790. name: "res4f_branch2b_relu"
  2791. type: "ReLU"
  2792. }
  2793.  
  2794. layer {
  2795. bottom: "res4f_branch2b"
  2796. top: "res4f_branch2c"
  2797. name: "res4f_branch2c"
  2798. type: "Convolution"
  2799. convolution_param {
  2800. num_output: 1024
  2801. kernel_size: 1
  2802. pad: 0
  2803. stride: 1
  2804. bias_term: false
  2805. }
  2806. param {
  2807. lr_mult: 1.0
  2808. }
  2809. }
  2810.  
  2811. layer {
  2812. bottom: "res4f_branch2c"
  2813. top: "res4f_branch2c"
  2814. name: "bn4f_branch2c"
  2815. type: "BatchNorm"
  2816. batch_norm_param {
  2817. use_global_stats: true
  2818. }
  2819. param {
  2820. lr_mult: 0.0
  2821. decay_mult: 0.0
  2822. }
  2823. param {
  2824. lr_mult: 0.0
  2825. decay_mult: 0.0
  2826. }
  2827. param {
  2828. lr_mult: 0.0
  2829. decay_mult: 0.0
  2830. }
  2831. }
  2832.  
  2833. layer {
  2834. bottom: "res4f_branch2c"
  2835. top: "res4f_branch2c"
  2836. name: "scale4f_branch2c"
  2837. type: "Scale"
  2838. scale_param {
  2839. bias_term: true
  2840. }
  2841. param {
  2842. lr_mult: 0.0
  2843. decay_mult: 0.0
  2844. }
  2845. param {
  2846. lr_mult: 0.0
  2847. decay_mult: 0.0
  2848. }
  2849. }
  2850.  
  2851. layer {
  2852. bottom: "res4e"
  2853. bottom: "res4f_branch2c"
  2854. top: "res4f"
  2855. name: "res4f"
  2856. type: "Eltwise"
  2857. }
  2858.  
  2859. layer {
  2860. bottom: "res4f"
  2861. top: "res4f"
  2862. name: "res4f_relu"
  2863. type: "ReLU"
  2864. }
  2865.  
  2866. layer {
  2867. bottom: "res4f"
  2868. top: "res5a_branch1"
  2869. name: "res5a_branch1"
  2870. type: "Convolution"
  2871. convolution_param {
  2872. num_output: 2048
  2873. kernel_size: 1
  2874. pad: 0
  2875. stride: 1
  2876. bias_term: false
  2877. }
  2878. param {
  2879. lr_mult: 1.0
  2880. }
  2881. }
  2882.  
  2883. layer {
  2884. bottom: "res5a_branch1"
  2885. top: "res5a_branch1"
  2886. name: "bn5a_branch1"
  2887. type: "BatchNorm"
  2888. batch_norm_param {
  2889. use_global_stats: true
  2890. }
  2891. param {
  2892. lr_mult: 0.0
  2893. decay_mult: 0.0
  2894. }
  2895. param {
  2896. lr_mult: 0.0
  2897. decay_mult: 0.0
  2898. }
  2899. param {
  2900. lr_mult: 0.0
  2901. decay_mult: 0.0
  2902. }
  2903. }
  2904.  
  2905. layer {
  2906. bottom: "res5a_branch1"
  2907. top: "res5a_branch1"
  2908. name: "scale5a_branch1"
  2909. type: "Scale"
  2910. scale_param {
  2911. bias_term: true
  2912. }
  2913. param {
  2914. lr_mult: 0.0
  2915. decay_mult: 0.0
  2916. }
  2917. param {
  2918. lr_mult: 0.0
  2919. decay_mult: 0.0
  2920. }
  2921. }
  2922.  
  2923. layer {
  2924. bottom: "res4f"
  2925. top: "res5a_branch2a"
  2926. name: "res5a_branch2a"
  2927. type: "Convolution"
  2928. convolution_param {
  2929. num_output: 512
  2930. kernel_size: 1
  2931. pad: 0
  2932. stride: 1
  2933. bias_term: false
  2934. }
  2935. param {
  2936. lr_mult: 1.0
  2937. }
  2938. }
  2939.  
  2940. layer {
  2941. bottom: "res5a_branch2a"
  2942. top: "res5a_branch2a"
  2943. name: "bn5a_branch2a"
  2944. type: "BatchNorm"
  2945. batch_norm_param {
  2946. use_global_stats: true
  2947. }
  2948. param {
  2949. lr_mult: 0.0
  2950. decay_mult: 0.0
  2951. }
  2952. param {
  2953. lr_mult: 0.0
  2954. decay_mult: 0.0
  2955. }
  2956. param {
  2957. lr_mult: 0.0
  2958. decay_mult: 0.0
  2959. }
  2960. }
  2961.  
  2962. layer {
  2963. bottom: "res5a_branch2a"
  2964. top: "res5a_branch2a"
  2965. name: "scale5a_branch2a"
  2966. type: "Scale"
  2967. scale_param {
  2968. bias_term: true
  2969. }
  2970. param {
  2971. lr_mult: 0.0
  2972. decay_mult: 0.0
  2973. }
  2974. param {
  2975. lr_mult: 0.0
  2976. decay_mult: 0.0
  2977. }
  2978. }
  2979.  
  2980. layer {
  2981. bottom: "res5a_branch2a"
  2982. top: "res5a_branch2a"
  2983. name: "res5a_branch2a_relu"
  2984. type: "ReLU"
  2985. }
  2986.  
  2987. layer {
  2988. bottom: "res5a_branch2a"
  2989. top: "res5a_branch2b"
  2990. name: "res5a_branch2b"
  2991. type: "Convolution"
  2992. convolution_param {
  2993. num_output: 512
  2994. kernel_size: 3
  2995. dilation: 2
  2996. pad: 2
  2997. stride: 1
  2998. bias_term: false
  2999. }
  3000. param {
  3001. lr_mult: 1.0
  3002. }
  3003. }
  3004.  
  3005. layer {
  3006. bottom: "res5a_branch2b"
  3007. top: "res5a_branch2b"
  3008. name: "bn5a_branch2b"
  3009. type: "BatchNorm"
  3010. batch_norm_param {
  3011. use_global_stats: true
  3012. }
  3013. param {
  3014. lr_mult: 0.0
  3015. decay_mult: 0.0
  3016. }
  3017. param {
  3018. lr_mult: 0.0
  3019. decay_mult: 0.0
  3020. }
  3021. param {
  3022. lr_mult: 0.0
  3023. decay_mult: 0.0
  3024. }
  3025. }
  3026.  
  3027. layer {
  3028. bottom: "res5a_branch2b"
  3029. top: "res5a_branch2b"
  3030. name: "scale5a_branch2b"
  3031. type: "Scale"
  3032. scale_param {
  3033. bias_term: true
  3034. }
  3035. param {
  3036. lr_mult: 0.0
  3037. decay_mult: 0.0
  3038. }
  3039. param {
  3040. lr_mult: 0.0
  3041. decay_mult: 0.0
  3042. }
  3043. }
  3044.  
  3045. layer {
  3046. bottom: "res5a_branch2b"
  3047. top: "res5a_branch2b"
  3048. name: "res5a_branch2b_relu"
  3049. type: "ReLU"
  3050. }
  3051.  
  3052. layer {
  3053. bottom: "res5a_branch2b"
  3054. top: "res5a_branch2c"
  3055. name: "res5a_branch2c"
  3056. type: "Convolution"
  3057. convolution_param {
  3058. num_output: 2048
  3059. kernel_size: 1
  3060. pad: 0
  3061. stride: 1
  3062. bias_term: false
  3063. }
  3064. param {
  3065. lr_mult: 1.0
  3066. }
  3067. }
  3068.  
  3069. layer {
  3070. bottom: "res5a_branch2c"
  3071. top: "res5a_branch2c"
  3072. name: "bn5a_branch2c"
  3073. type: "BatchNorm"
  3074. batch_norm_param {
  3075. use_global_stats: true
  3076. }
  3077. param {
  3078. lr_mult: 0.0
  3079. decay_mult: 0.0
  3080. }
  3081. param {
  3082. lr_mult: 0.0
  3083. decay_mult: 0.0
  3084. }
  3085. param {
  3086. lr_mult: 0.0
  3087. decay_mult: 0.0
  3088. }
  3089. }
  3090.  
  3091. layer {
  3092. bottom: "res5a_branch2c"
  3093. top: "res5a_branch2c"
  3094. name: "scale5a_branch2c"
  3095. type: "Scale"
  3096. scale_param {
  3097. bias_term: true
  3098. }
  3099. param {
  3100. lr_mult: 0.0
  3101. decay_mult: 0.0
  3102. }
  3103. param {
  3104. lr_mult: 0.0
  3105. decay_mult: 0.0
  3106. }
  3107. }
  3108.  
  3109. layer {
  3110. bottom: "res5a_branch1"
  3111. bottom: "res5a_branch2c"
  3112. top: "res5a"
  3113. name: "res5a"
  3114. type: "Eltwise"
  3115. }
  3116.  
  3117. layer {
  3118. bottom: "res5a"
  3119. top: "res5a"
  3120. name: "res5a_relu"
  3121. type: "ReLU"
  3122. }
  3123.  
  3124. layer {
  3125. bottom: "res5a"
  3126. top: "res5b_branch2a"
  3127. name: "res5b_branch2a"
  3128. type: "Convolution"
  3129. convolution_param {
  3130. num_output: 512
  3131. kernel_size: 1
  3132. pad: 0
  3133. stride: 1
  3134. bias_term: false
  3135. }
  3136. param {
  3137. lr_mult: 1.0
  3138. }
  3139. }
  3140.  
  3141. layer {
  3142. bottom: "res5b_branch2a"
  3143. top: "res5b_branch2a"
  3144. name: "bn5b_branch2a"
  3145. type: "BatchNorm"
  3146. batch_norm_param {
  3147. use_global_stats: true
  3148. }
  3149. param {
  3150. lr_mult: 0.0
  3151. decay_mult: 0.0
  3152. }
  3153. param {
  3154. lr_mult: 0.0
  3155. decay_mult: 0.0
  3156. }
  3157. param {
  3158. lr_mult: 0.0
  3159. decay_mult: 0.0
  3160. }
  3161. }
  3162.  
  3163. layer {
  3164. bottom: "res5b_branch2a"
  3165. top: "res5b_branch2a"
  3166. name: "scale5b_branch2a"
  3167. type: "Scale"
  3168. scale_param {
  3169. bias_term: true
  3170. }
  3171. param {
  3172. lr_mult: 0.0
  3173. decay_mult: 0.0
  3174. }
  3175. param {
  3176. lr_mult: 0.0
  3177. decay_mult: 0.0
  3178. }
  3179. }
  3180.  
  3181. layer {
  3182. bottom: "res5b_branch2a"
  3183. top: "res5b_branch2a"
  3184. name: "res5b_branch2a_relu"
  3185. type: "ReLU"
  3186. }
  3187.  
  3188. layer {
  3189. bottom: "res5b_branch2a"
  3190. top: "res5b_branch2b"
  3191. name: "res5b_branch2b"
  3192. type: "Convolution"
  3193. convolution_param {
  3194. num_output: 512
  3195. kernel_size: 3
  3196. dilation: 2
  3197. pad: 2
  3198. stride: 1
  3199. bias_term: false
  3200. }
  3201. param {
  3202. lr_mult: 1.0
  3203. }
  3204. }
  3205.  
  3206. layer {
  3207. bottom: "res5b_branch2b"
  3208. top: "res5b_branch2b"
  3209. name: "bn5b_branch2b"
  3210. type: "BatchNorm"
  3211. batch_norm_param {
  3212. use_global_stats: true
  3213. }
  3214. param {
  3215. lr_mult: 0.0
  3216. decay_mult: 0.0
  3217. }
  3218. param {
  3219. lr_mult: 0.0
  3220. decay_mult: 0.0
  3221. }
  3222. param {
  3223. lr_mult: 0.0
  3224. decay_mult: 0.0
  3225. }
  3226. }
  3227.  
  3228. layer {
  3229. bottom: "res5b_branch2b"
  3230. top: "res5b_branch2b"
  3231. name: "scale5b_branch2b"
  3232. type: "Scale"
  3233. scale_param {
  3234. bias_term: true
  3235. }
  3236. param {
  3237. lr_mult: 0.0
  3238. decay_mult: 0.0
  3239. }
  3240. param {
  3241. lr_mult: 0.0
  3242. decay_mult: 0.0
  3243. }
  3244. }
  3245.  
  3246. layer {
  3247. bottom: "res5b_branch2b"
  3248. top: "res5b_branch2b"
  3249. name: "res5b_branch2b_relu"
  3250. type: "ReLU"
  3251. }
  3252.  
  3253. layer {
  3254. bottom: "res5b_branch2b"
  3255. top: "res5b_branch2c"
  3256. name: "res5b_branch2c"
  3257. type: "Convolution"
  3258. convolution_param {
  3259. num_output: 2048
  3260. kernel_size: 1
  3261. pad: 0
  3262. stride: 1
  3263. bias_term: false
  3264. }
  3265. param {
  3266. lr_mult: 1.0
  3267. }
  3268. }
  3269.  
  3270. layer {
  3271. bottom: "res5b_branch2c"
  3272. top: "res5b_branch2c"
  3273. name: "bn5b_branch2c"
  3274. type: "BatchNorm"
  3275. batch_norm_param {
  3276. use_global_stats: true
  3277. }
  3278. param {
  3279. lr_mult: 0.0
  3280. decay_mult: 0.0
  3281. }
  3282. param {
  3283. lr_mult: 0.0
  3284. decay_mult: 0.0
  3285. }
  3286. param {
  3287. lr_mult: 0.0
  3288. decay_mult: 0.0
  3289. }
  3290. }
  3291.  
  3292. layer {
  3293. bottom: "res5b_branch2c"
  3294. top: "res5b_branch2c"
  3295. name: "scale5b_branch2c"
  3296. type: "Scale"
  3297. scale_param {
  3298. bias_term: true
  3299. }
  3300. param {
  3301. lr_mult: 0.0
  3302. decay_mult: 0.0
  3303. }
  3304. param {
  3305. lr_mult: 0.0
  3306. decay_mult: 0.0
  3307. }
  3308. }
  3309.  
  3310. layer {
  3311. bottom: "res5a"
  3312. bottom: "res5b_branch2c"
  3313. top: "res5b"
  3314. name: "res5b"
  3315. type: "Eltwise"
  3316. }
  3317.  
  3318. layer {
  3319. bottom: "res5b"
  3320. top: "res5b"
  3321. name: "res5b_relu"
  3322. type: "ReLU"
  3323. }
  3324.  
  3325. layer {
  3326. bottom: "res5b"
  3327. top: "res5c_branch2a"
  3328. name: "res5c_branch2a"
  3329. type: "Convolution"
  3330. convolution_param {
  3331. num_output: 512
  3332. kernel_size: 1
  3333. pad: 0
  3334. stride: 1
  3335. bias_term: false
  3336. }
  3337. param {
  3338. lr_mult: 1.0
  3339. }
  3340. }
  3341.  
  3342. layer {
  3343. bottom: "res5c_branch2a"
  3344. top: "res5c_branch2a"
  3345. name: "bn5c_branch2a"
  3346. type: "BatchNorm"
  3347. batch_norm_param {
  3348. use_global_stats: true
  3349. }
  3350. param {
  3351. lr_mult: 0.0
  3352. decay_mult: 0.0
  3353. }
  3354. param {
  3355. lr_mult: 0.0
  3356. decay_mult: 0.0
  3357. }
  3358. param {
  3359. lr_mult: 0.0
  3360. decay_mult: 0.0
  3361. }
  3362. }
  3363.  
  3364. layer {
  3365. bottom: "res5c_branch2a"
  3366. top: "res5c_branch2a"
  3367. name: "scale5c_branch2a"
  3368. type: "Scale"
  3369. scale_param {
  3370. bias_term: true
  3371. }
  3372. param {
  3373. lr_mult: 0.0
  3374. decay_mult: 0.0
  3375. }
  3376. param {
  3377. lr_mult: 0.0
  3378. decay_mult: 0.0
  3379. }
  3380. }
  3381.  
  3382. layer {
  3383. bottom: "res5c_branch2a"
  3384. top: "res5c_branch2a"
  3385. name: "res5c_branch2a_relu"
  3386. type: "ReLU"
  3387. }
  3388.  
  3389. layer {
  3390. bottom: "res5c_branch2a"
  3391. top: "res5c_branch2b"
  3392. name: "res5c_branch2b"
  3393. type: "Convolution"
  3394. convolution_param {
  3395. num_output: 512
  3396. kernel_size: 3
  3397. dilation: 2
  3398. pad: 2
  3399. stride: 1
  3400. bias_term: false
  3401. }
  3402. param {
  3403. lr_mult: 1.0
  3404. }
  3405. }
  3406.  
  3407. layer {
  3408. bottom: "res5c_branch2b"
  3409. top: "res5c_branch2b"
  3410. name: "bn5c_branch2b"
  3411. type: "BatchNorm"
  3412. batch_norm_param {
  3413. use_global_stats: true
  3414. }
  3415. param {
  3416. lr_mult: 0.0
  3417. decay_mult: 0.0
  3418. }
  3419. param {
  3420. lr_mult: 0.0
  3421. decay_mult: 0.0
  3422. }
  3423. param {
  3424. lr_mult: 0.0
  3425. decay_mult: 0.0
  3426. }
  3427. }
  3428.  
  3429. layer {
  3430. bottom: "res5c_branch2b"
  3431. top: "res5c_branch2b"
  3432. name: "scale5c_branch2b"
  3433. type: "Scale"
  3434. scale_param {
  3435. bias_term: true
  3436. }
  3437. param {
  3438. lr_mult: 0.0
  3439. decay_mult: 0.0
  3440. }
  3441. param {
  3442. lr_mult: 0.0
  3443. decay_mult: 0.0
  3444. }
  3445. }
  3446.  
  3447. layer {
  3448. bottom: "res5c_branch2b"
  3449. top: "res5c_branch2b"
  3450. name: "res5c_branch2b_relu"
  3451. type: "ReLU"
  3452. }
  3453.  
  3454. layer {
  3455. bottom: "res5c_branch2b"
  3456. top: "res5c_branch2c"
  3457. name: "res5c_branch2c"
  3458. type: "Convolution"
  3459. convolution_param {
  3460. num_output: 2048
  3461. kernel_size: 1
  3462. pad: 0
  3463. stride: 1
  3464. bias_term: false
  3465. }
  3466. param {
  3467. lr_mult: 1.0
  3468. }
  3469. }
  3470.  
  3471. layer {
  3472. bottom: "res5c_branch2c"
  3473. top: "res5c_branch2c"
  3474. name: "bn5c_branch2c"
  3475. type: "BatchNorm"
  3476. batch_norm_param {
  3477. use_global_stats: true
  3478. }
  3479. param {
  3480. lr_mult: 0.0
  3481. decay_mult: 0.0
  3482. }
  3483. param {
  3484. lr_mult: 0.0
  3485. decay_mult: 0.0
  3486. }
  3487. param {
  3488. lr_mult: 0.0
  3489. decay_mult: 0.0
  3490. }
  3491. }
  3492.  
  3493. layer {
  3494. bottom: "res5c_branch2c"
  3495. top: "res5c_branch2c"
  3496. name: "scale5c_branch2c"
  3497. type: "Scale"
  3498. scale_param {
  3499. bias_term: true
  3500. }
  3501. param {
  3502. lr_mult: 0.0
  3503. decay_mult: 0.0
  3504. }
  3505. param {
  3506. lr_mult: 0.0
  3507. decay_mult: 0.0
  3508. }
  3509. }
  3510.  
  3511. layer {
  3512. bottom: "res5b"
  3513. bottom: "res5c_branch2c"
  3514. top: "res5c"
  3515. name: "res5c"
  3516. type: "Eltwise"
  3517. }
  3518.  
  3519. layer {
  3520. bottom: "res5c"
  3521. top: "res5c"
  3522. name: "res5c_relu"
  3523. type: "ReLU"
  3524. }
  3525.  
  3526.  
  3527. #========= RPN ============
  3528.  
  3529. layer {
  3530. name: "rpn_conv/3x3"
  3531. type: "Convolution"
  3532. bottom: "res4f"
  3533. top: "rpn/output"
  3534. param { lr_mult: 1.0 }
  3535. param { lr_mult: 2.0 }
  3536. convolution_param {
  3537. num_output: 512
  3538. kernel_size: 3 pad: 1 stride: 1
  3539. weight_filler { type: "gaussian" std: 0.01 }
  3540. bias_filler { type: "constant" value: 0 }
  3541. }
  3542. }
  3543. layer {
  3544. name: "rpn_relu/3x3"
  3545. type: "ReLU"
  3546. bottom: "rpn/output"
  3547. top: "rpn/output"
  3548. }
  3549.  
  3550. layer {
  3551. name: "rpn_cls_score"
  3552. type: "Convolution"
  3553. bottom: "rpn/output"
  3554. top: "rpn_cls_score"
  3555. param { lr_mult: 1.0 }
  3556. param { lr_mult: 2.0 }
  3557. convolution_param {
  3558. num_output: 18 # 2(bg/fg) * 9(anchors)
  3559. kernel_size: 1 pad: 0 stride: 1
  3560. weight_filler { type: "gaussian" std: 0.01 }
  3561. bias_filler { type: "constant" value: 0 }
  3562. }
  3563. }
  3564.  
  3565. layer {
  3566. name: "rpn_bbox_pred"
  3567. type: "Convolution"
  3568. bottom: "rpn/output"
  3569. top: "rpn_bbox_pred"
  3570. param { lr_mult: 1.0 }
  3571. param { lr_mult: 2.0 }
  3572. convolution_param {
  3573. num_output: 36 # 4 * 9(anchors)
  3574. kernel_size: 1 pad: 0 stride: 1
  3575. weight_filler { type: "gaussian" std: 0.01 }
  3576. bias_filler { type: "constant" value: 0 }
  3577. }
  3578. }
  3579.  
  3580. layer {
  3581. bottom: "rpn_cls_score"
  3582. top: "rpn_cls_score_reshape"
  3583. name: "rpn_cls_score_reshape"
  3584. type: "Reshape"
  3585. reshape_param { shape { dim: 0 dim: 2 dim: -1 dim: 0 } }
  3586. }
  3587.  
  3588. layer {
  3589. name: 'rpn-data'
  3590. type: 'Python'
  3591. bottom: 'rpn_cls_score'
  3592. bottom: 'gt_boxes'
  3593. bottom: 'im_info'
  3594. bottom: 'data'
  3595. top: 'rpn_labels'
  3596. top: 'rpn_bbox_targets'
  3597. top: 'rpn_bbox_inside_weights'
  3598. top: 'rpn_bbox_outside_weights'
  3599. python_param {
  3600. module: 'rpn.anchor_target_layer'
  3601. layer: 'AnchorTargetLayer'
  3602. param_str: "'feat_stride': 16"
  3603. }
  3604. }
  3605.  
  3606. layer {
  3607. name: "rpn_loss_cls"
  3608. type: "SoftmaxWithLoss"
  3609. bottom: "rpn_cls_score_reshape"
  3610. bottom: "rpn_labels"
  3611. propagate_down: 1
  3612. propagate_down: 0
  3613. top: "rpn_cls_loss"
  3614. loss_weight: 1
  3615. loss_param {
  3616. ignore_label: -1
  3617. normalize: true
  3618. }
  3619. }
  3620.  
  3621. layer {
  3622. name: "rpn_loss_bbox"
  3623. type: "SmoothL1Loss"
  3624. bottom: "rpn_bbox_pred"
  3625. bottom: "rpn_bbox_targets"
  3626. bottom: 'rpn_bbox_inside_weights'
  3627. bottom: 'rpn_bbox_outside_weights'
  3628. top: "rpn_loss_bbox"
  3629. loss_weight: 1
  3630. smooth_l1_loss_param { sigma: 3.0 }
  3631. }
  3632.  
  3633. #========= RoI Proposal ============
  3634.  
  3635. layer {
  3636. name: "rpn_cls_prob"
  3637. type: "Softmax"
  3638. bottom: "rpn_cls_score_reshape"
  3639. top: "rpn_cls_prob"
  3640. }
  3641.  
  3642. layer {
  3643. name: 'rpn_cls_prob_reshape'
  3644. type: 'Reshape'
  3645. bottom: 'rpn_cls_prob'
  3646. top: 'rpn_cls_prob_reshape'
  3647. reshape_param { shape { dim: 0 dim: 18 dim: -1 dim: 0 } }
  3648. }
  3649.  
  3650. layer {
  3651. name: 'proposal'
  3652. type: 'Python'
  3653. bottom: 'rpn_cls_prob_reshape'
  3654. bottom: 'rpn_bbox_pred'
  3655. bottom: 'im_info'
  3656. top: 'rpn_rois'
  3657. # top: 'rpn_scores'
  3658. python_param {
  3659. module: 'rpn.proposal_layer'
  3660. layer: 'ProposalLayer'
  3661. param_str: "'feat_stride': 16"
  3662. }
  3663. }
  3664.  
  3665. #layer {
  3666. # name: 'debug-data'
  3667. # type: 'Python'
  3668. # bottom: 'data'
  3669. # bottom: 'rpn_rois'
  3670. # bottom: 'rpn_scores'
  3671. # python_param {
  3672. # module: 'rpn.debug_layer'
  3673. # layer: 'RPNDebugLayer'
  3674. # }
  3675. #}
  3676.  
  3677. layer {
  3678. name: 'roi-data'
  3679. type: 'Python'
  3680. bottom: 'rpn_rois'
  3681. bottom: 'gt_boxes'
  3682. top: 'rois'
  3683. top: 'labels'
  3684. top: 'bbox_targets'
  3685. top: 'bbox_inside_weights'
  3686. top: 'bbox_outside_weights'
  3687. python_param {
  3688. module: 'rpn.proposal_target_layer'
  3689. layer: 'ProposalTargetLayer'
  3690. param_str: "'num_classes': 2"
  3691. }
  3692. }
  3693.  
  3694. #----------------------new conv layer------------------
  3695. layer {
  3696. bottom: "res5c"
  3697. top: "conv_new_1"
  3698. name: "conv_new_1"
  3699. type: "Convolution"
  3700. convolution_param {
  3701. num_output: 1024
  3702. kernel_size: 1
  3703. pad: 0
  3704. weight_filler {
  3705. type: "gaussian"
  3706. std: 0.01
  3707. }
  3708. bias_filler {
  3709. type: "constant"
  3710. value: 0
  3711. }
  3712. }
  3713. param {
  3714. lr_mult: 1.0
  3715. }
  3716. param {
  3717. lr_mult: 2.0
  3718. }
  3719. }
  3720.  
  3721. layer {
  3722. bottom: "conv_new_1"
  3723. top: "conv_new_1"
  3724. name: "conv_new_1_relu"
  3725. type: "ReLU"
  3726. }
  3727.  
  3728. layer {
  3729. bottom: "conv_new_1"
  3730. top: "rfcn_cls"
  3731. name: "rfcn_cls"
  3732. type: "Convolution"
  3733. convolution_param {
  3734. num_output: 98 #2*(7^2) cls_num*(score_maps_size^2)
  3735. kernel_size: 1
  3736. pad: 0
  3737. weight_filler {
  3738. type: "gaussian"
  3739. std: 0.01
  3740. }
  3741. bias_filler {
  3742. type: "constant"
  3743. value: 0
  3744. }
  3745. }
  3746. param {
  3747. lr_mult: 1.0
  3748. }
  3749. param {
  3750. lr_mult: 2.0
  3751. }
  3752. }
  3753. layer {
  3754. bottom: "conv_new_1"
  3755. top: "rfcn_bbox"
  3756. name: "rfcn_bbox"
  3757. type: "Convolution"
  3758. convolution_param {
  3759. num_output: 392 #8*(7^2) cls_num*(score_maps_size^2)
  3760. kernel_size: 1
  3761. pad: 0
  3762. weight_filler {
  3763. type: "gaussian"
  3764. std: 0.01
  3765. }
  3766. bias_filler {
  3767. type: "constant"
  3768. value: 0
  3769. }
  3770. }
  3771. param {
  3772. lr_mult: 1.0
  3773. }
  3774. param {
  3775. lr_mult: 2.0
  3776. }
  3777. }
  3778.  
  3779. #--------------position sensitive RoI pooling--------------
  3780. layer {
  3781. bottom: "rfcn_cls"
  3782. bottom: "rois"
  3783. top: "psroipooled_cls_rois"
  3784. name: "psroipooled_cls_rois"
  3785. type: "PSROIPooling"
  3786. psroi_pooling_param {
  3787. spatial_scale: 0.0625
  3788. output_dim: 2
  3789. group_size: 7
  3790. }
  3791. }
  3792.  
  3793. layer {
  3794. bottom: "psroipooled_cls_rois"
  3795. top: "cls_score"
  3796. name: "ave_cls_score_rois"
  3797. type: "Pooling"
  3798. pooling_param {
  3799. pool: AVE
  3800. kernel_size: 7
  3801. stride: 7
  3802. }
  3803. }
  3804.  
  3805.  
  3806. layer {
  3807. bottom: "rfcn_bbox"
  3808. bottom: "rois"
  3809. top: "psroipooled_loc_rois"
  3810. name: "psroipooled_loc_rois"
  3811. type: "PSROIPooling"
  3812. psroi_pooling_param {
  3813. spatial_scale: 0.0625
  3814. output_dim: 8
  3815. group_size: 7
  3816. }
  3817. }
  3818.  
  3819. layer {
  3820. bottom: "psroipooled_loc_rois"
  3821. top: "bbox_pred"
  3822. name: "ave_bbox_pred_rois"
  3823. type: "Pooling"
  3824. pooling_param {
  3825. pool: AVE
  3826. kernel_size: 7
  3827. stride: 7
  3828. }
  3829. }
  3830.  
  3831.  
  3832. #-----------------------output------------------------
  3833. layer {
  3834. name: "loss"
  3835. type: "SoftmaxWithLoss"
  3836. bottom: "cls_score"
  3837. bottom: "labels"
  3838. top: "loss_cls"
  3839. loss_weight: 1
  3840. propagate_down: true
  3841. propagate_down: false
  3842. }
  3843.  
  3844. layer {
  3845. name: "accuarcy"
  3846. type: "Accuracy"
  3847. bottom: "cls_score"
  3848. bottom: "labels"
  3849. top: "accuarcy"
  3850. #include: { phase: TEST }
  3851. propagate_down: false
  3852. propagate_down: false
  3853. }
  3854.  
  3855. layer {
  3856. name: "loss_bbox"
  3857. type: "SmoothL1LossOHEM"
  3858. bottom: "bbox_pred"
  3859. bottom: "bbox_targets"
  3860. bottom: 'bbox_inside_weights'
  3861. top: "loss_bbox"
  3862. loss_weight: 1
  3863. loss_param {
  3864. normalization: PRE_FIXED
  3865. pre_fixed_normalizer: 128
  3866. }
  3867. propagate_down: true
  3868. propagate_down: false
  3869. propagate_down: false
  3870. }
  3871.  
  3872. layer {
  3873. name: "silence"
  3874. type: "Silence"
  3875. bottom: "bbox_outside_weights"
  3876. }
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