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  1. name: "ResNet50"
  2.  
  3. input: "data"
  4. input_shape {
  5. dim: 1
  6. dim: 3
  7. dim: 224
  8. dim: 224
  9. }
  10.  
  11. input: "im_info"
  12. input_shape {
  13. dim: 1
  14. dim: 3
  15. }
  16. # ------------------------ conv1 -----------------------------
  17. layer {
  18. bottom: "data"
  19. top: "conv1"
  20. name: "conv1"
  21. type: "Convolution"
  22. convolution_param {
  23. num_output: 64
  24. kernel_size: 7
  25. pad: 3
  26. stride: 2
  27. }
  28. param {
  29. lr_mult: 0.0
  30. }
  31. param {
  32. lr_mult: 0.0
  33. }
  34.  
  35. }
  36.  
  37. layer {
  38. bottom: "conv1"
  39. top: "conv1"
  40. name: "bn_conv1"
  41. type: "BatchNorm"
  42. batch_norm_param {
  43. use_global_stats: true
  44. }
  45. param {
  46. lr_mult: 0.0
  47. decay_mult: 0.0
  48. }
  49. param {
  50. lr_mult: 0.0
  51. decay_mult: 0.0
  52. }
  53. param {
  54. lr_mult: 0.0
  55. decay_mult: 0.0
  56. }
  57. }
  58.  
  59. layer {
  60. bottom: "conv1"
  61. top: "conv1"
  62. name: "scale_conv1"
  63. type: "Scale"
  64. scale_param {
  65. bias_term: true
  66. }
  67. param {
  68. lr_mult: 0.0
  69. decay_mult: 0.0
  70. }
  71. param {
  72. lr_mult: 0.0
  73. decay_mult: 0.0
  74. }
  75. }
  76.  
  77. layer {
  78. bottom: "conv1"
  79. top: "conv1"
  80. name: "conv1_relu"
  81. type: "ReLU"
  82. }
  83.  
  84. layer {
  85. bottom: "conv1"
  86. top: "pool1"
  87. name: "pool1"
  88. type: "Pooling"
  89. pooling_param {
  90. kernel_size: 3
  91. stride: 2
  92. pool: MAX
  93. }
  94. }
  95.  
  96. layer {
  97. bottom: "pool1"
  98. top: "res2a_branch1"
  99. name: "res2a_branch1"
  100. type: "Convolution"
  101. convolution_param {
  102. num_output: 256
  103. kernel_size: 1
  104. pad: 0
  105. stride: 1
  106. bias_term: false
  107. }
  108. param {
  109. lr_mult: 0.0
  110. }
  111. }
  112.  
  113. layer {
  114. bottom: "res2a_branch1"
  115. top: "res2a_branch1"
  116. name: "bn2a_branch1"
  117. type: "BatchNorm"
  118. batch_norm_param {
  119. use_global_stats: true
  120. }
  121. param {
  122. lr_mult: 0.0
  123. decay_mult: 0.0
  124. }
  125. param {
  126. lr_mult: 0.0
  127. decay_mult: 0.0
  128. }
  129. param {
  130. lr_mult: 0.0
  131. decay_mult: 0.0
  132. }
  133. }
  134.  
  135. layer {
  136. bottom: "res2a_branch1"
  137. top: "res2a_branch1"
  138. name: "scale2a_branch1"
  139. type: "Scale"
  140. scale_param {
  141. bias_term: true
  142. }
  143. param {
  144. lr_mult: 0.0
  145. decay_mult: 0.0
  146. }
  147. param {
  148. lr_mult: 0.0
  149. decay_mult: 0.0
  150. }
  151. }
  152.  
  153. layer {
  154. bottom: "pool1"
  155. top: "res2a_branch2a"
  156. name: "res2a_branch2a"
  157. type: "Convolution"
  158. convolution_param {
  159. num_output: 64
  160. kernel_size: 1
  161. pad: 0
  162. stride: 1
  163. bias_term: false
  164. }
  165. param {
  166. lr_mult: 0.0
  167. }
  168. }
  169.  
  170. layer {
  171. bottom: "res2a_branch2a"
  172. top: "res2a_branch2a"
  173. name: "bn2a_branch2a"
  174. type: "BatchNorm"
  175. batch_norm_param {
  176. use_global_stats: true
  177. }
  178. param {
  179. lr_mult: 0.0
  180. decay_mult: 0.0
  181. }
  182. param {
  183. lr_mult: 0.0
  184. decay_mult: 0.0
  185. }
  186. param {
  187. lr_mult: 0.0
  188. decay_mult: 0.0
  189. }
  190. }
  191.  
  192. layer {
  193. bottom: "res2a_branch2a"
  194. top: "res2a_branch2a"
  195. name: "scale2a_branch2a"
  196. type: "Scale"
  197. scale_param {
  198. bias_term: true
  199. }
  200. param {
  201. lr_mult: 0.0
  202. decay_mult: 0.0
  203. }
  204. param {
  205. lr_mult: 0.0
  206. decay_mult: 0.0
  207. }
  208. }
  209.  
  210. layer {
  211. bottom: "res2a_branch2a"
  212. top: "res2a_branch2a"
  213. name: "res2a_branch2a_relu"
  214. type: "ReLU"
  215. }
  216.  
  217. layer {
  218. bottom: "res2a_branch2a"
  219. top: "res2a_branch2b"
  220. name: "res2a_branch2b"
  221. type: "Convolution"
  222. convolution_param {
  223. num_output: 64
  224. kernel_size: 3
  225. pad: 1
  226. stride: 1
  227. bias_term: false
  228. }
  229. param {
  230. lr_mult: 0.0
  231. }
  232. }
  233.  
  234. layer {
  235. bottom: "res2a_branch2b"
  236. top: "res2a_branch2b"
  237. name: "bn2a_branch2b"
  238. type: "BatchNorm"
  239. batch_norm_param {
  240. use_global_stats: true
  241. }
  242. param {
  243. lr_mult: 0.0
  244. decay_mult: 0.0
  245. }
  246. param {
  247. lr_mult: 0.0
  248. decay_mult: 0.0
  249. }
  250. param {
  251. lr_mult: 0.0
  252. decay_mult: 0.0
  253. }
  254. }
  255.  
  256. layer {
  257. bottom: "res2a_branch2b"
  258. top: "res2a_branch2b"
  259. name: "scale2a_branch2b"
  260. type: "Scale"
  261. scale_param {
  262. bias_term: true
  263. }
  264. param {
  265. lr_mult: 0.0
  266. decay_mult: 0.0
  267. }
  268. param {
  269. lr_mult: 0.0
  270. decay_mult: 0.0
  271. }
  272. }
  273.  
  274. layer {
  275. bottom: "res2a_branch2b"
  276. top: "res2a_branch2b"
  277. name: "res2a_branch2b_relu"
  278. type: "ReLU"
  279. }
  280.  
  281. layer {
  282. bottom: "res2a_branch2b"
  283. top: "res2a_branch2c"
  284. name: "res2a_branch2c"
  285. type: "Convolution"
  286. convolution_param {
  287. num_output: 256
  288. kernel_size: 1
  289. pad: 0
  290. stride: 1
  291. bias_term: false
  292. }
  293. param {
  294. lr_mult: 0.0
  295. }
  296. }
  297.  
  298. layer {
  299. bottom: "res2a_branch2c"
  300. top: "res2a_branch2c"
  301. name: "bn2a_branch2c"
  302. type: "BatchNorm"
  303. batch_norm_param {
  304. use_global_stats: true
  305. }
  306. param {
  307. lr_mult: 0.0
  308. decay_mult: 0.0
  309. }
  310. param {
  311. lr_mult: 0.0
  312. decay_mult: 0.0
  313. }
  314. param {
  315. lr_mult: 0.0
  316. decay_mult: 0.0
  317. }
  318. }
  319.  
  320. layer {
  321. bottom: "res2a_branch2c"
  322. top: "res2a_branch2c"
  323. name: "scale2a_branch2c"
  324. type: "Scale"
  325. scale_param {
  326. bias_term: true
  327. }
  328. param {
  329. lr_mult: 0.0
  330. decay_mult: 0.0
  331. }
  332. param {
  333. lr_mult: 0.0
  334. decay_mult: 0.0
  335. }
  336. }
  337.  
  338. layer {
  339. bottom: "res2a_branch1"
  340. bottom: "res2a_branch2c"
  341. top: "res2a"
  342. name: "res2a"
  343. type: "Eltwise"
  344. }
  345.  
  346. layer {
  347. bottom: "res2a"
  348. top: "res2a"
  349. name: "res2a_relu"
  350. type: "ReLU"
  351. }
  352.  
  353. layer {
  354. bottom: "res2a"
  355. top: "res2b_branch2a"
  356. name: "res2b_branch2a"
  357. type: "Convolution"
  358. convolution_param {
  359. num_output: 64
  360. kernel_size: 1
  361. pad: 0
  362. stride: 1
  363. bias_term: false
  364. }
  365. param {
  366. lr_mult: 0.0
  367. }
  368. }
  369.  
  370. layer {
  371. bottom: "res2b_branch2a"
  372. top: "res2b_branch2a"
  373. name: "bn2b_branch2a"
  374. type: "BatchNorm"
  375. batch_norm_param {
  376. use_global_stats: true
  377. }
  378. param {
  379. lr_mult: 0.0
  380. decay_mult: 0.0
  381. }
  382. param {
  383. lr_mult: 0.0
  384. decay_mult: 0.0
  385. }
  386. param {
  387. lr_mult: 0.0
  388. decay_mult: 0.0
  389. }
  390. }
  391.  
  392. layer {
  393. bottom: "res2b_branch2a"
  394. top: "res2b_branch2a"
  395. name: "scale2b_branch2a"
  396. type: "Scale"
  397. scale_param {
  398. bias_term: true
  399. }
  400. param {
  401. lr_mult: 0.0
  402. decay_mult: 0.0
  403. }
  404. param {
  405. lr_mult: 0.0
  406. decay_mult: 0.0
  407. }
  408. }
  409.  
  410. layer {
  411. bottom: "res2b_branch2a"
  412. top: "res2b_branch2a"
  413. name: "res2b_branch2a_relu"
  414. type: "ReLU"
  415. }
  416.  
  417. layer {
  418. bottom: "res2b_branch2a"
  419. top: "res2b_branch2b"
  420. name: "res2b_branch2b"
  421. type: "Convolution"
  422. convolution_param {
  423. num_output: 64
  424. kernel_size: 3
  425. pad: 1
  426. stride: 1
  427. bias_term: false
  428. }
  429. param {
  430. lr_mult: 0.0
  431. }
  432. }
  433.  
  434. layer {
  435. bottom: "res2b_branch2b"
  436. top: "res2b_branch2b"
  437. name: "bn2b_branch2b"
  438. type: "BatchNorm"
  439. batch_norm_param {
  440. use_global_stats: true
  441. }
  442. param {
  443. lr_mult: 0.0
  444. decay_mult: 0.0
  445. }
  446. param {
  447. lr_mult: 0.0
  448. decay_mult: 0.0
  449. }
  450. param {
  451. lr_mult: 0.0
  452. decay_mult: 0.0
  453. }
  454. }
  455.  
  456. layer {
  457. bottom: "res2b_branch2b"
  458. top: "res2b_branch2b"
  459. name: "scale2b_branch2b"
  460. type: "Scale"
  461. scale_param {
  462. bias_term: true
  463. }
  464. param {
  465. lr_mult: 0.0
  466. decay_mult: 0.0
  467. }
  468. param {
  469. lr_mult: 0.0
  470. decay_mult: 0.0
  471. }
  472. }
  473.  
  474. layer {
  475. bottom: "res2b_branch2b"
  476. top: "res2b_branch2b"
  477. name: "res2b_branch2b_relu"
  478. type: "ReLU"
  479. }
  480.  
  481. layer {
  482. bottom: "res2b_branch2b"
  483. top: "res2b_branch2c"
  484. name: "res2b_branch2c"
  485. type: "Convolution"
  486. convolution_param {
  487. num_output: 256
  488. kernel_size: 1
  489. pad: 0
  490. stride: 1
  491. bias_term: false
  492. }
  493. param {
  494. lr_mult: 0.0
  495. }
  496. }
  497.  
  498. layer {
  499. bottom: "res2b_branch2c"
  500. top: "res2b_branch2c"
  501. name: "bn2b_branch2c"
  502. type: "BatchNorm"
  503. batch_norm_param {
  504. use_global_stats: true
  505. }
  506. param {
  507. lr_mult: 0.0
  508. decay_mult: 0.0
  509. }
  510. param {
  511. lr_mult: 0.0
  512. decay_mult: 0.0
  513. }
  514. param {
  515. lr_mult: 0.0
  516. decay_mult: 0.0
  517. }
  518. }
  519.  
  520. layer {
  521. bottom: "res2b_branch2c"
  522. top: "res2b_branch2c"
  523. name: "scale2b_branch2c"
  524. type: "Scale"
  525. scale_param {
  526. bias_term: true
  527. }
  528. param {
  529. lr_mult: 0.0
  530. decay_mult: 0.0
  531. }
  532. param {
  533. lr_mult: 0.0
  534. decay_mult: 0.0
  535. }
  536. }
  537.  
  538. layer {
  539. bottom: "res2a"
  540. bottom: "res2b_branch2c"
  541. top: "res2b"
  542. name: "res2b"
  543. type: "Eltwise"
  544. }
  545.  
  546. layer {
  547. bottom: "res2b"
  548. top: "res2b"
  549. name: "res2b_relu"
  550. type: "ReLU"
  551. }
  552.  
  553. layer {
  554. bottom: "res2b"
  555. top: "res2c_branch2a"
  556. name: "res2c_branch2a"
  557. type: "Convolution"
  558. convolution_param {
  559. num_output: 64
  560. kernel_size: 1
  561. pad: 0
  562. stride: 1
  563. bias_term: false
  564. }
  565. param {
  566. lr_mult: 0.0
  567. }
  568. }
  569.  
  570. layer {
  571. bottom: "res2c_branch2a"
  572. top: "res2c_branch2a"
  573. name: "bn2c_branch2a"
  574. type: "BatchNorm"
  575. batch_norm_param {
  576. use_global_stats: true
  577. }
  578. param {
  579. lr_mult: 0.0
  580. decay_mult: 0.0
  581. }
  582. param {
  583. lr_mult: 0.0
  584. decay_mult: 0.0
  585. }
  586. param {
  587. lr_mult: 0.0
  588. decay_mult: 0.0
  589. }
  590. }
  591.  
  592. layer {
  593. bottom: "res2c_branch2a"
  594. top: "res2c_branch2a"
  595. name: "scale2c_branch2a"
  596. type: "Scale"
  597. scale_param {
  598. bias_term: true
  599. }
  600. param {
  601. lr_mult: 0.0
  602. decay_mult: 0.0
  603. }
  604. param {
  605. lr_mult: 0.0
  606. decay_mult: 0.0
  607. }
  608. }
  609.  
  610. layer {
  611. bottom: "res2c_branch2a"
  612. top: "res2c_branch2a"
  613. name: "res2c_branch2a_relu"
  614. type: "ReLU"
  615. }
  616.  
  617. layer {
  618. bottom: "res2c_branch2a"
  619. top: "res2c_branch2b"
  620. name: "res2c_branch2b"
  621. type: "Convolution"
  622. convolution_param {
  623. num_output: 64
  624. kernel_size: 3
  625. pad: 1
  626. stride: 1
  627. bias_term: false
  628. }
  629. param {
  630. lr_mult: 0.0
  631. }
  632. }
  633.  
  634. layer {
  635. bottom: "res2c_branch2b"
  636. top: "res2c_branch2b"
  637. name: "bn2c_branch2b"
  638. type: "BatchNorm"
  639. batch_norm_param {
  640. use_global_stats: true
  641. }
  642. param {
  643. lr_mult: 0.0
  644. decay_mult: 0.0
  645. }
  646. param {
  647. lr_mult: 0.0
  648. decay_mult: 0.0
  649. }
  650. param {
  651. lr_mult: 0.0
  652. decay_mult: 0.0
  653. }
  654. }
  655.  
  656. layer {
  657. bottom: "res2c_branch2b"
  658. top: "res2c_branch2b"
  659. name: "scale2c_branch2b"
  660. type: "Scale"
  661. scale_param {
  662. bias_term: true
  663. }
  664. param {
  665. lr_mult: 0.0
  666. decay_mult: 0.0
  667. }
  668. param {
  669. lr_mult: 0.0
  670. decay_mult: 0.0
  671. }
  672. }
  673.  
  674. layer {
  675. bottom: "res2c_branch2b"
  676. top: "res2c_branch2b"
  677. name: "res2c_branch2b_relu"
  678. type: "ReLU"
  679. }
  680.  
  681. layer {
  682. bottom: "res2c_branch2b"
  683. top: "res2c_branch2c"
  684. name: "res2c_branch2c"
  685. type: "Convolution"
  686. convolution_param {
  687. num_output: 256
  688. kernel_size: 1
  689. pad: 0
  690. stride: 1
  691. bias_term: false
  692. }
  693. param {
  694. lr_mult: 0.0
  695. }
  696. }
  697.  
  698. layer {
  699. bottom: "res2c_branch2c"
  700. top: "res2c_branch2c"
  701. name: "bn2c_branch2c"
  702. type: "BatchNorm"
  703. batch_norm_param {
  704. use_global_stats: true
  705. }
  706. param {
  707. lr_mult: 0.0
  708. decay_mult: 0.0
  709. }
  710. param {
  711. lr_mult: 0.0
  712. decay_mult: 0.0
  713. }
  714. param {
  715. lr_mult: 0.0
  716. decay_mult: 0.0
  717. }
  718. }
  719.  
  720. layer {
  721. bottom: "res2c_branch2c"
  722. top: "res2c_branch2c"
  723. name: "scale2c_branch2c"
  724. type: "Scale"
  725. scale_param {
  726. bias_term: true
  727. }
  728. param {
  729. lr_mult: 0.0
  730. decay_mult: 0.0
  731. }
  732. param {
  733. lr_mult: 0.0
  734. decay_mult: 0.0
  735. }
  736. }
  737.  
  738. layer {
  739. bottom: "res2b"
  740. bottom: "res2c_branch2c"
  741. top: "res2c"
  742. name: "res2c"
  743. type: "Eltwise"
  744. }
  745.  
  746. layer {
  747. bottom: "res2c"
  748. top: "res2c"
  749. name: "res2c_relu"
  750. type: "ReLU"
  751. }
  752.  
  753. layer {
  754. bottom: "res2c"
  755. top: "res3a_branch1"
  756. name: "res3a_branch1"
  757. type: "Convolution"
  758. convolution_param {
  759. num_output: 512
  760. kernel_size: 1
  761. pad: 0
  762. stride: 2
  763. bias_term: false
  764. }
  765. param {
  766. lr_mult: 1.0
  767. }
  768. }
  769.  
  770. layer {
  771. bottom: "res3a_branch1"
  772. top: "res3a_branch1"
  773. name: "bn3a_branch1"
  774. type: "BatchNorm"
  775. batch_norm_param {
  776. use_global_stats: true
  777. }
  778. param {
  779. lr_mult: 0.0
  780. decay_mult: 0.0
  781. }
  782. param {
  783. lr_mult: 0.0
  784. decay_mult: 0.0
  785. }
  786. param {
  787. lr_mult: 0.0
  788. decay_mult: 0.0
  789. }
  790. }
  791.  
  792. layer {
  793. bottom: "res3a_branch1"
  794. top: "res3a_branch1"
  795. name: "scale3a_branch1"
  796. type: "Scale"
  797. scale_param {
  798. bias_term: true
  799. }
  800. param {
  801. lr_mult: 0.0
  802. decay_mult: 0.0
  803. }
  804. param {
  805. lr_mult: 0.0
  806. decay_mult: 0.0
  807. }
  808. }
  809.  
  810. layer {
  811. bottom: "res2c"
  812. top: "res3a_branch2a"
  813. name: "res3a_branch2a"
  814. type: "Convolution"
  815. convolution_param {
  816. num_output: 128
  817. kernel_size: 1
  818. pad: 0
  819. stride: 2
  820. bias_term: false
  821. }
  822. param {
  823. lr_mult: 1.0
  824. }
  825. }
  826.  
  827. layer {
  828. bottom: "res3a_branch2a"
  829. top: "res3a_branch2a"
  830. name: "bn3a_branch2a"
  831. type: "BatchNorm"
  832. batch_norm_param {
  833. use_global_stats: true
  834. }
  835. param {
  836. lr_mult: 0.0
  837. decay_mult: 0.0
  838. }
  839. param {
  840. lr_mult: 0.0
  841. decay_mult: 0.0
  842. }
  843. param {
  844. lr_mult: 0.0
  845. decay_mult: 0.0
  846. }
  847. }
  848.  
  849. layer {
  850. bottom: "res3a_branch2a"
  851. top: "res3a_branch2a"
  852. name: "scale3a_branch2a"
  853. type: "Scale"
  854. scale_param {
  855. bias_term: true
  856. }
  857. param {
  858. lr_mult: 0.0
  859. decay_mult: 0.0
  860. }
  861. param {
  862. lr_mult: 0.0
  863. decay_mult: 0.0
  864. }
  865. }
  866.  
  867. layer {
  868. bottom: "res3a_branch2a"
  869. top: "res3a_branch2a"
  870. name: "res3a_branch2a_relu"
  871. type: "ReLU"
  872. }
  873.  
  874. layer {
  875. bottom: "res3a_branch2a"
  876. top: "res3a_branch2b"
  877. name: "res3a_branch2b"
  878. type: "Convolution"
  879. convolution_param {
  880. num_output: 128
  881. kernel_size: 3
  882. pad: 1
  883. stride: 1
  884. bias_term: false
  885. }
  886. param {
  887. lr_mult: 1.0
  888. }
  889. }
  890.  
  891. layer {
  892. bottom: "res3a_branch2b"
  893. top: "res3a_branch2b"
  894. name: "bn3a_branch2b"
  895. type: "BatchNorm"
  896. batch_norm_param {
  897. use_global_stats: true
  898. }
  899. param {
  900. lr_mult: 0.0
  901. decay_mult: 0.0
  902. }
  903. param {
  904. lr_mult: 0.0
  905. decay_mult: 0.0
  906. }
  907. param {
  908. lr_mult: 0.0
  909. decay_mult: 0.0
  910. }
  911. }
  912.  
  913. layer {
  914. bottom: "res3a_branch2b"
  915. top: "res3a_branch2b"
  916. name: "scale3a_branch2b"
  917. type: "Scale"
  918. scale_param {
  919. bias_term: true
  920. }
  921. param {
  922. lr_mult: 0.0
  923. decay_mult: 0.0
  924. }
  925. param {
  926. lr_mult: 0.0
  927. decay_mult: 0.0
  928. }
  929. }
  930.  
  931. layer {
  932. bottom: "res3a_branch2b"
  933. top: "res3a_branch2b"
  934. name: "res3a_branch2b_relu"
  935. type: "ReLU"
  936. }
  937.  
  938. layer {
  939. bottom: "res3a_branch2b"
  940. top: "res3a_branch2c"
  941. name: "res3a_branch2c"
  942. type: "Convolution"
  943. convolution_param {
  944. num_output: 512
  945. kernel_size: 1
  946. pad: 0
  947. stride: 1
  948. bias_term: false
  949. }
  950. param {
  951. lr_mult: 1.0
  952. }
  953. }
  954.  
  955. layer {
  956. bottom: "res3a_branch2c"
  957. top: "res3a_branch2c"
  958. name: "bn3a_branch2c"
  959. type: "BatchNorm"
  960. batch_norm_param {
  961. use_global_stats: true
  962. }
  963. param {
  964. lr_mult: 0.0
  965. decay_mult: 0.0
  966. }
  967. param {
  968. lr_mult: 0.0
  969. decay_mult: 0.0
  970. }
  971. param {
  972. lr_mult: 0.0
  973. decay_mult: 0.0
  974. }
  975. }
  976.  
  977. layer {
  978. bottom: "res3a_branch2c"
  979. top: "res3a_branch2c"
  980. name: "scale3a_branch2c"
  981. type: "Scale"
  982. scale_param {
  983. bias_term: true
  984. }
  985. param {
  986. lr_mult: 0.0
  987. decay_mult: 0.0
  988. }
  989. param {
  990. lr_mult: 0.0
  991. decay_mult: 0.0
  992. }
  993. }
  994.  
  995. layer {
  996. bottom: "res3a_branch1"
  997. bottom: "res3a_branch2c"
  998. top: "res3a"
  999. name: "res3a"
  1000. type: "Eltwise"
  1001. }
  1002.  
  1003. layer {
  1004. bottom: "res3a"
  1005. top: "res3a"
  1006. name: "res3a_relu"
  1007. type: "ReLU"
  1008. }
  1009.  
  1010. layer {
  1011. bottom: "res3a"
  1012. top: "res3b_branch2a"
  1013. name: "res3b_branch2a"
  1014. type: "Convolution"
  1015. convolution_param {
  1016. num_output: 128
  1017. kernel_size: 1
  1018. pad: 0
  1019. stride: 1
  1020. bias_term: false
  1021. }
  1022. param {
  1023. lr_mult: 1.0
  1024. }
  1025. }
  1026.  
  1027. layer {
  1028. bottom: "res3b_branch2a"
  1029. top: "res3b_branch2a"
  1030. name: "bn3b_branch2a"
  1031. type: "BatchNorm"
  1032. batch_norm_param {
  1033. use_global_stats: true
  1034. }
  1035. param {
  1036. lr_mult: 0.0
  1037. decay_mult: 0.0
  1038. }
  1039. param {
  1040. lr_mult: 0.0
  1041. decay_mult: 0.0
  1042. }
  1043. param {
  1044. lr_mult: 0.0
  1045. decay_mult: 0.0
  1046. }
  1047. }
  1048.  
  1049. layer {
  1050. bottom: "res3b_branch2a"
  1051. top: "res3b_branch2a"
  1052. name: "scale3b_branch2a"
  1053. type: "Scale"
  1054. scale_param {
  1055. bias_term: true
  1056. }
  1057. param {
  1058. lr_mult: 0.0
  1059. decay_mult: 0.0
  1060. }
  1061. param {
  1062. lr_mult: 0.0
  1063. decay_mult: 0.0
  1064. }
  1065. }
  1066.  
  1067. layer {
  1068. bottom: "res3b_branch2a"
  1069. top: "res3b_branch2a"
  1070. name: "res3b_branch2a_relu"
  1071. type: "ReLU"
  1072. }
  1073.  
  1074. layer {
  1075. bottom: "res3b_branch2a"
  1076. top: "res3b_branch2b"
  1077. name: "res3b_branch2b"
  1078. type: "Convolution"
  1079. convolution_param {
  1080. num_output: 128
  1081. kernel_size: 3
  1082. pad: 1
  1083. stride: 1
  1084. bias_term: false
  1085. }
  1086. param {
  1087. lr_mult: 1.0
  1088. }
  1089. }
  1090.  
  1091. layer {
  1092. bottom: "res3b_branch2b"
  1093. top: "res3b_branch2b"
  1094. name: "bn3b_branch2b"
  1095. type: "BatchNorm"
  1096. batch_norm_param {
  1097. use_global_stats: true
  1098. }
  1099. param {
  1100. lr_mult: 0.0
  1101. decay_mult: 0.0
  1102. }
  1103. param {
  1104. lr_mult: 0.0
  1105. decay_mult: 0.0
  1106. }
  1107. param {
  1108. lr_mult: 0.0
  1109. decay_mult: 0.0
  1110. }
  1111. }
  1112.  
  1113. layer {
  1114. bottom: "res3b_branch2b"
  1115. top: "res3b_branch2b"
  1116. name: "scale3b_branch2b"
  1117. type: "Scale"
  1118. scale_param {
  1119. bias_term: true
  1120. }
  1121. param {
  1122. lr_mult: 0.0
  1123. decay_mult: 0.0
  1124. }
  1125. param {
  1126. lr_mult: 0.0
  1127. decay_mult: 0.0
  1128. }
  1129. }
  1130.  
  1131. layer {
  1132. bottom: "res3b_branch2b"
  1133. top: "res3b_branch2b"
  1134. name: "res3b_branch2b_relu"
  1135. type: "ReLU"
  1136. }
  1137.  
  1138. layer {
  1139. bottom: "res3b_branch2b"
  1140. top: "res3b_branch2c"
  1141. name: "res3b_branch2c"
  1142. type: "Convolution"
  1143. convolution_param {
  1144. num_output: 512
  1145. kernel_size: 1
  1146. pad: 0
  1147. stride: 1
  1148. bias_term: false
  1149. }
  1150. param {
  1151. lr_mult: 1.0
  1152. }
  1153. }
  1154.  
  1155. layer {
  1156. bottom: "res3b_branch2c"
  1157. top: "res3b_branch2c"
  1158. name: "bn3b_branch2c"
  1159. type: "BatchNorm"
  1160. batch_norm_param {
  1161. use_global_stats: true
  1162. }
  1163. param {
  1164. lr_mult: 0.0
  1165. decay_mult: 0.0
  1166. }
  1167. param {
  1168. lr_mult: 0.0
  1169. decay_mult: 0.0
  1170. }
  1171. param {
  1172. lr_mult: 0.0
  1173. decay_mult: 0.0
  1174. }
  1175. }
  1176.  
  1177. layer {
  1178. bottom: "res3b_branch2c"
  1179. top: "res3b_branch2c"
  1180. name: "scale3b_branch2c"
  1181. type: "Scale"
  1182. scale_param {
  1183. bias_term: true
  1184. }
  1185. param {
  1186. lr_mult: 0.0
  1187. decay_mult: 0.0
  1188. }
  1189. param {
  1190. lr_mult: 0.0
  1191. decay_mult: 0.0
  1192. }
  1193. }
  1194.  
  1195. layer {
  1196. bottom: "res3a"
  1197. bottom: "res3b_branch2c"
  1198. top: "res3b"
  1199. name: "res3b"
  1200. type: "Eltwise"
  1201. }
  1202.  
  1203. layer {
  1204. bottom: "res3b"
  1205. top: "res3b"
  1206. name: "res3b_relu"
  1207. type: "ReLU"
  1208. }
  1209.  
  1210. layer {
  1211. bottom: "res3b"
  1212. top: "res3c_branch2a"
  1213. name: "res3c_branch2a"
  1214. type: "Convolution"
  1215. convolution_param {
  1216. num_output: 128
  1217. kernel_size: 1
  1218. pad: 0
  1219. stride: 1
  1220. bias_term: false
  1221. }
  1222. param {
  1223. lr_mult: 1.0
  1224. }
  1225. }
  1226.  
  1227. layer {
  1228. bottom: "res3c_branch2a"
  1229. top: "res3c_branch2a"
  1230. name: "bn3c_branch2a"
  1231. type: "BatchNorm"
  1232. batch_norm_param {
  1233. use_global_stats: true
  1234. }
  1235. param {
  1236. lr_mult: 0.0
  1237. decay_mult: 0.0
  1238. }
  1239. param {
  1240. lr_mult: 0.0
  1241. decay_mult: 0.0
  1242. }
  1243. param {
  1244. lr_mult: 0.0
  1245. decay_mult: 0.0
  1246. }
  1247. }
  1248.  
  1249. layer {
  1250. bottom: "res3c_branch2a"
  1251. top: "res3c_branch2a"
  1252. name: "scale3c_branch2a"
  1253. type: "Scale"
  1254. scale_param {
  1255. bias_term: true
  1256. }
  1257. param {
  1258. lr_mult: 0.0
  1259. decay_mult: 0.0
  1260. }
  1261. param {
  1262. lr_mult: 0.0
  1263. decay_mult: 0.0
  1264. }
  1265. }
  1266.  
  1267. layer {
  1268. bottom: "res3c_branch2a"
  1269. top: "res3c_branch2a"
  1270. name: "res3c_branch2a_relu"
  1271. type: "ReLU"
  1272. }
  1273.  
  1274. layer {
  1275. bottom: "res3c_branch2a"
  1276. top: "res3c_branch2b"
  1277. name: "res3c_branch2b"
  1278. type: "Convolution"
  1279. convolution_param {
  1280. num_output: 128
  1281. kernel_size: 3
  1282. pad: 1
  1283. stride: 1
  1284. bias_term: false
  1285. }
  1286. param {
  1287. lr_mult: 1.0
  1288. }
  1289. }
  1290.  
  1291. layer {
  1292. bottom: "res3c_branch2b"
  1293. top: "res3c_branch2b"
  1294. name: "bn3c_branch2b"
  1295. type: "BatchNorm"
  1296. batch_norm_param {
  1297. use_global_stats: true
  1298. }
  1299. param {
  1300. lr_mult: 0.0
  1301. decay_mult: 0.0
  1302. }
  1303. param {
  1304. lr_mult: 0.0
  1305. decay_mult: 0.0
  1306. }
  1307. param {
  1308. lr_mult: 0.0
  1309. decay_mult: 0.0
  1310. }
  1311. }
  1312.  
  1313. layer {
  1314. bottom: "res3c_branch2b"
  1315. top: "res3c_branch2b"
  1316. name: "scale3c_branch2b"
  1317. type: "Scale"
  1318. scale_param {
  1319. bias_term: true
  1320. }
  1321. param {
  1322. lr_mult: 0.0
  1323. decay_mult: 0.0
  1324. }
  1325. param {
  1326. lr_mult: 0.0
  1327. decay_mult: 0.0
  1328. }
  1329. }
  1330.  
  1331. layer {
  1332. bottom: "res3c_branch2b"
  1333. top: "res3c_branch2b"
  1334. name: "res3c_branch2b_relu"
  1335. type: "ReLU"
  1336. }
  1337.  
  1338. layer {
  1339. bottom: "res3c_branch2b"
  1340. top: "res3c_branch2c"
  1341. name: "res3c_branch2c"
  1342. type: "Convolution"
  1343. convolution_param {
  1344. num_output: 512
  1345. kernel_size: 1
  1346. pad: 0
  1347. stride: 1
  1348. bias_term: false
  1349. }
  1350. param {
  1351. lr_mult: 1.0
  1352. }
  1353. }
  1354.  
  1355. layer {
  1356. bottom: "res3c_branch2c"
  1357. top: "res3c_branch2c"
  1358. name: "bn3c_branch2c"
  1359. type: "BatchNorm"
  1360. batch_norm_param {
  1361. use_global_stats: true
  1362. }
  1363. param {
  1364. lr_mult: 0.0
  1365. decay_mult: 0.0
  1366. }
  1367. param {
  1368. lr_mult: 0.0
  1369. decay_mult: 0.0
  1370. }
  1371. param {
  1372. lr_mult: 0.0
  1373. decay_mult: 0.0
  1374. }
  1375. }
  1376.  
  1377. layer {
  1378. bottom: "res3c_branch2c"
  1379. top: "res3c_branch2c"
  1380. name: "scale3c_branch2c"
  1381. type: "Scale"
  1382. scale_param {
  1383. bias_term: true
  1384. }
  1385. param {
  1386. lr_mult: 0.0
  1387. decay_mult: 0.0
  1388. }
  1389. param {
  1390. lr_mult: 0.0
  1391. decay_mult: 0.0
  1392. }
  1393. }
  1394.  
  1395. layer {
  1396. bottom: "res3b"
  1397. bottom: "res3c_branch2c"
  1398. top: "res3c"
  1399. name: "res3c"
  1400. type: "Eltwise"
  1401. }
  1402.  
  1403. layer {
  1404. bottom: "res3c"
  1405. top: "res3c"
  1406. name: "res3c_relu"
  1407. type: "ReLU"
  1408. }
  1409.  
  1410. layer {
  1411. bottom: "res3c"
  1412. top: "res3d_branch2a"
  1413. name: "res3d_branch2a"
  1414. type: "Convolution"
  1415. convolution_param {
  1416. num_output: 128
  1417. kernel_size: 1
  1418. pad: 0
  1419. stride: 1
  1420. bias_term: false
  1421. }
  1422. param {
  1423. lr_mult: 1.0
  1424. }
  1425. }
  1426.  
  1427. layer {
  1428. bottom: "res3d_branch2a"
  1429. top: "res3d_branch2a"
  1430. name: "bn3d_branch2a"
  1431. type: "BatchNorm"
  1432. batch_norm_param {
  1433. use_global_stats: true
  1434. }
  1435. param {
  1436. lr_mult: 0.0
  1437. decay_mult: 0.0
  1438. }
  1439. param {
  1440. lr_mult: 0.0
  1441. decay_mult: 0.0
  1442. }
  1443. param {
  1444. lr_mult: 0.0
  1445. decay_mult: 0.0
  1446. }
  1447. }
  1448.  
  1449. layer {
  1450. bottom: "res3d_branch2a"
  1451. top: "res3d_branch2a"
  1452. name: "scale3d_branch2a"
  1453. type: "Scale"
  1454. scale_param {
  1455. bias_term: true
  1456. }
  1457. param {
  1458. lr_mult: 0.0
  1459. decay_mult: 0.0
  1460. }
  1461. param {
  1462. lr_mult: 0.0
  1463. decay_mult: 0.0
  1464. }
  1465. }
  1466.  
  1467. layer {
  1468. bottom: "res3d_branch2a"
  1469. top: "res3d_branch2a"
  1470. name: "res3d_branch2a_relu"
  1471. type: "ReLU"
  1472. }
  1473.  
  1474. layer {
  1475. bottom: "res3d_branch2a"
  1476. top: "res3d_branch2b"
  1477. name: "res3d_branch2b"
  1478. type: "Convolution"
  1479. convolution_param {
  1480. num_output: 128
  1481. kernel_size: 3
  1482. pad: 1
  1483. stride: 1
  1484. bias_term: false
  1485. }
  1486. param {
  1487. lr_mult: 1.0
  1488. }
  1489. }
  1490.  
  1491. layer {
  1492. bottom: "res3d_branch2b"
  1493. top: "res3d_branch2b"
  1494. name: "bn3d_branch2b"
  1495. type: "BatchNorm"
  1496. batch_norm_param {
  1497. use_global_stats: true
  1498. }
  1499. param {
  1500. lr_mult: 0.0
  1501. decay_mult: 0.0
  1502. }
  1503. param {
  1504. lr_mult: 0.0
  1505. decay_mult: 0.0
  1506. }
  1507. param {
  1508. lr_mult: 0.0
  1509. decay_mult: 0.0
  1510. }
  1511. }
  1512.  
  1513. layer {
  1514. bottom: "res3d_branch2b"
  1515. top: "res3d_branch2b"
  1516. name: "scale3d_branch2b"
  1517. type: "Scale"
  1518. scale_param {
  1519. bias_term: true
  1520. }
  1521. param {
  1522. lr_mult: 0.0
  1523. decay_mult: 0.0
  1524. }
  1525. param {
  1526. lr_mult: 0.0
  1527. decay_mult: 0.0
  1528. }
  1529. }
  1530.  
  1531. layer {
  1532. bottom: "res3d_branch2b"
  1533. top: "res3d_branch2b"
  1534. name: "res3d_branch2b_relu"
  1535. type: "ReLU"
  1536. }
  1537.  
  1538. layer {
  1539. bottom: "res3d_branch2b"
  1540. top: "res3d_branch2c"
  1541. name: "res3d_branch2c"
  1542. type: "Convolution"
  1543. convolution_param {
  1544. num_output: 512
  1545. kernel_size: 1
  1546. pad: 0
  1547. stride: 1
  1548. bias_term: false
  1549. }
  1550. param {
  1551. lr_mult: 1.0
  1552. }
  1553. }
  1554.  
  1555. layer {
  1556. bottom: "res3d_branch2c"
  1557. top: "res3d_branch2c"
  1558. name: "bn3d_branch2c"
  1559. type: "BatchNorm"
  1560. batch_norm_param {
  1561. use_global_stats: true
  1562. }
  1563. param {
  1564. lr_mult: 0.0
  1565. decay_mult: 0.0
  1566. }
  1567. param {
  1568. lr_mult: 0.0
  1569. decay_mult: 0.0
  1570. }
  1571. param {
  1572. lr_mult: 0.0
  1573. decay_mult: 0.0
  1574. }
  1575. }
  1576.  
  1577. layer {
  1578. bottom: "res3d_branch2c"
  1579. top: "res3d_branch2c"
  1580. name: "scale3d_branch2c"
  1581. type: "Scale"
  1582. scale_param {
  1583. bias_term: true
  1584. }
  1585. param {
  1586. lr_mult: 0.0
  1587. decay_mult: 0.0
  1588. }
  1589. param {
  1590. lr_mult: 0.0
  1591. decay_mult: 0.0
  1592. }
  1593. }
  1594.  
  1595. layer {
  1596. bottom: "res3c"
  1597. bottom: "res3d_branch2c"
  1598. top: "res3d"
  1599. name: "res3d"
  1600. type: "Eltwise"
  1601. }
  1602.  
  1603. layer {
  1604. bottom: "res3d"
  1605. top: "res3d"
  1606. name: "res3d_relu"
  1607. type: "ReLU"
  1608. }
  1609.  
  1610. layer {
  1611. bottom: "res3d"
  1612. top: "res4a_branch1"
  1613. name: "res4a_branch1"
  1614. type: "Convolution"
  1615. convolution_param {
  1616. num_output: 1024
  1617. kernel_size: 1
  1618. pad: 0
  1619. stride: 2
  1620. bias_term: false
  1621. }
  1622. param {
  1623. lr_mult: 1.0
  1624. }
  1625. }
  1626.  
  1627. layer {
  1628. bottom: "res4a_branch1"
  1629. top: "res4a_branch1"
  1630. name: "bn4a_branch1"
  1631. type: "BatchNorm"
  1632. batch_norm_param {
  1633. use_global_stats: true
  1634. }
  1635. param {
  1636. lr_mult: 0.0
  1637. decay_mult: 0.0
  1638. }
  1639. param {
  1640. lr_mult: 0.0
  1641. decay_mult: 0.0
  1642. }
  1643. param {
  1644. lr_mult: 0.0
  1645. decay_mult: 0.0
  1646. }
  1647. }
  1648.  
  1649. layer {
  1650. bottom: "res4a_branch1"
  1651. top: "res4a_branch1"
  1652. name: "scale4a_branch1"
  1653. type: "Scale"
  1654. scale_param {
  1655. bias_term: true
  1656. }
  1657. param {
  1658. lr_mult: 0.0
  1659. decay_mult: 0.0
  1660. }
  1661. param {
  1662. lr_mult: 0.0
  1663. decay_mult: 0.0
  1664. }
  1665. }
  1666.  
  1667. layer {
  1668. bottom: "res3d"
  1669. top: "res4a_branch2a"
  1670. name: "res4a_branch2a"
  1671. type: "Convolution"
  1672. convolution_param {
  1673. num_output: 256
  1674. kernel_size: 1
  1675. pad: 0
  1676. stride: 2
  1677. bias_term: false
  1678. }
  1679. param {
  1680. lr_mult: 1.0
  1681. }
  1682. }
  1683.  
  1684. layer {
  1685. bottom: "res4a_branch2a"
  1686. top: "res4a_branch2a"
  1687. name: "bn4a_branch2a"
  1688. type: "BatchNorm"
  1689. batch_norm_param {
  1690. use_global_stats: true
  1691. }
  1692. param {
  1693. lr_mult: 0.0
  1694. decay_mult: 0.0
  1695. }
  1696. param {
  1697. lr_mult: 0.0
  1698. decay_mult: 0.0
  1699. }
  1700. param {
  1701. lr_mult: 0.0
  1702. decay_mult: 0.0
  1703. }
  1704. }
  1705.  
  1706. layer {
  1707. bottom: "res4a_branch2a"
  1708. top: "res4a_branch2a"
  1709. name: "scale4a_branch2a"
  1710. type: "Scale"
  1711. scale_param {
  1712. bias_term: true
  1713. }
  1714. param {
  1715. lr_mult: 0.0
  1716. decay_mult: 0.0
  1717. }
  1718. param {
  1719. lr_mult: 0.0
  1720. decay_mult: 0.0
  1721. }
  1722. }
  1723.  
  1724. layer {
  1725. bottom: "res4a_branch2a"
  1726. top: "res4a_branch2a"
  1727. name: "res4a_branch2a_relu"
  1728. type: "ReLU"
  1729. }
  1730.  
  1731. layer {
  1732. bottom: "res4a_branch2a"
  1733. top: "res4a_branch2b"
  1734. name: "res4a_branch2b"
  1735. type: "Convolution"
  1736. convolution_param {
  1737. num_output: 256
  1738. kernel_size: 3
  1739. pad: 1
  1740. stride: 1
  1741. bias_term: false
  1742. }
  1743. param {
  1744. lr_mult: 1.0
  1745. }
  1746. }
  1747.  
  1748. layer {
  1749. bottom: "res4a_branch2b"
  1750. top: "res4a_branch2b"
  1751. name: "bn4a_branch2b"
  1752. type: "BatchNorm"
  1753. batch_norm_param {
  1754. use_global_stats: true
  1755. }
  1756. param {
  1757. lr_mult: 0.0
  1758. decay_mult: 0.0
  1759. }
  1760. param {
  1761. lr_mult: 0.0
  1762. decay_mult: 0.0
  1763. }
  1764. param {
  1765. lr_mult: 0.0
  1766. decay_mult: 0.0
  1767. }
  1768. }
  1769.  
  1770. layer {
  1771. bottom: "res4a_branch2b"
  1772. top: "res4a_branch2b"
  1773. name: "scale4a_branch2b"
  1774. type: "Scale"
  1775. scale_param {
  1776. bias_term: true
  1777. }
  1778. param {
  1779. lr_mult: 0.0
  1780. decay_mult: 0.0
  1781. }
  1782. param {
  1783. lr_mult: 0.0
  1784. decay_mult: 0.0
  1785. }
  1786. }
  1787.  
  1788. layer {
  1789. bottom: "res4a_branch2b"
  1790. top: "res4a_branch2b"
  1791. name: "res4a_branch2b_relu"
  1792. type: "ReLU"
  1793. }
  1794.  
  1795. layer {
  1796. bottom: "res4a_branch2b"
  1797. top: "res4a_branch2c"
  1798. name: "res4a_branch2c"
  1799. type: "Convolution"
  1800. convolution_param {
  1801. num_output: 1024
  1802. kernel_size: 1
  1803. pad: 0
  1804. stride: 1
  1805. bias_term: false
  1806. }
  1807. param {
  1808. lr_mult: 1.0
  1809. }
  1810. }
  1811.  
  1812. layer {
  1813. bottom: "res4a_branch2c"
  1814. top: "res4a_branch2c"
  1815. name: "bn4a_branch2c"
  1816. type: "BatchNorm"
  1817. batch_norm_param {
  1818. use_global_stats: true
  1819. }
  1820. param {
  1821. lr_mult: 0.0
  1822. decay_mult: 0.0
  1823. }
  1824. param {
  1825. lr_mult: 0.0
  1826. decay_mult: 0.0
  1827. }
  1828. param {
  1829. lr_mult: 0.0
  1830. decay_mult: 0.0
  1831. }
  1832. }
  1833.  
  1834. layer {
  1835. bottom: "res4a_branch2c"
  1836. top: "res4a_branch2c"
  1837. name: "scale4a_branch2c"
  1838. type: "Scale"
  1839. scale_param {
  1840. bias_term: true
  1841. }
  1842. param {
  1843. lr_mult: 0.0
  1844. decay_mult: 0.0
  1845. }
  1846. param {
  1847. lr_mult: 0.0
  1848. decay_mult: 0.0
  1849. }
  1850. }
  1851.  
  1852. layer {
  1853. bottom: "res4a_branch1"
  1854. bottom: "res4a_branch2c"
  1855. top: "res4a"
  1856. name: "res4a"
  1857. type: "Eltwise"
  1858. }
  1859.  
  1860. layer {
  1861. bottom: "res4a"
  1862. top: "res4a"
  1863. name: "res4a_relu"
  1864. type: "ReLU"
  1865. }
  1866.  
  1867. layer {
  1868. bottom: "res4a"
  1869. top: "res4b_branch2a_semi_scratch"
  1870. name: "res4b_branch2a_semi_scratch"
  1871. type: "Convolution"
  1872. convolution_param {
  1873. num_output: 256
  1874. kernel_size: 1
  1875. pad: 0
  1876. stride: 1
  1877. bias_term: false
  1878. }
  1879. param {
  1880. lr_mult: 1.0
  1881. }
  1882. }
  1883.  
  1884. layer {
  1885. bottom: "res4b_branch2a_semi_scratch"
  1886. top: "res4b_branch2a_semi_scratch"
  1887. name: "bn4b_branch2a_semi_scratch"
  1888. type: "BatchNorm"
  1889. batch_norm_param {
  1890. use_global_stats: true
  1891. }
  1892. param {
  1893. lr_mult: 0.0
  1894. decay_mult: 0.0
  1895. }
  1896. param {
  1897. lr_mult: 0.0
  1898. decay_mult: 0.0
  1899. }
  1900. param {
  1901. lr_mult: 0.0
  1902. decay_mult: 0.0
  1903. }
  1904. }
  1905.  
  1906. layer {
  1907. bottom: "res4b_branch2a_semi_scratch"
  1908. top: "res4b_branch2a_semi_scratch"
  1909. name: "scale4b_branch2a_semi_scratch"
  1910. type: "Scale"
  1911. scale_param {
  1912. bias_term: true
  1913. }
  1914. }
  1915.  
  1916. layer {
  1917. bottom: "res4b_branch2a_semi_scratch"
  1918. top: "res4b_branch2a_semi_scratch"
  1919. name: "res4b_branch2a_relu_semi_scratch"
  1920. type: "ReLU"
  1921. }
  1922.  
  1923. layer {
  1924. bottom: "res4b_branch2a_semi_scratch"
  1925. top: "res4b_branch2b_semi_scratch"
  1926. name: "res4b_branch2b_semi_scratch"
  1927. type: "Convolution"
  1928. convolution_param {
  1929. num_output: 256
  1930. kernel_size: 3
  1931. pad: 1
  1932. stride: 1
  1933. bias_term: false
  1934. }
  1935. param {
  1936. lr_mult: 1.0
  1937. }
  1938. }
  1939.  
  1940. layer {
  1941. bottom: "res4b_branch2b_semi_scratch"
  1942. top: "res4b_branch2b_semi_scratch"
  1943. name: "bn4b_branch2b_semi_scratch"
  1944. type: "BatchNorm"
  1945. batch_norm_param {
  1946. use_global_stats: true
  1947. }
  1948. param {
  1949. lr_mult: 0.0
  1950. decay_mult: 0.0
  1951. }
  1952. param {
  1953. lr_mult: 0.0
  1954. decay_mult: 0.0
  1955. }
  1956. param {
  1957. lr_mult: 0.0
  1958. decay_mult: 0.0
  1959. }
  1960. }
  1961.  
  1962. layer {
  1963. bottom: "res4b_branch2b_semi_scratch"
  1964. top: "res4b_branch2b_semi_scratch"
  1965. name: "scale4b_branch2b_semi_scratch"
  1966. type: "Scale"
  1967. scale_param {
  1968. bias_term: true
  1969. }
  1970. }
  1971.  
  1972. layer {
  1973. bottom: "res4b_branch2b_semi_scratch"
  1974. top: "res4b_branch2b_semi_scratch"
  1975. name: "res4b_branch2b_relu_semi_scratch"
  1976. type: "ReLU"
  1977. }
  1978.  
  1979. layer {
  1980. bottom: "res4b_branch2b_semi_scratch"
  1981. top: "res4b_branch2c_semi_scratch"
  1982. name: "res4b_branch2c_semi_scratch"
  1983. type: "Convolution"
  1984. convolution_param {
  1985. num_output: 1024
  1986. kernel_size: 1
  1987. pad: 0
  1988. stride: 1
  1989. bias_term: false
  1990. }
  1991. param {
  1992. lr_mult: 1.0
  1993. }
  1994. }
  1995.  
  1996. layer {
  1997. bottom: "res4b_branch2c_semi_scratch"
  1998. top: "res4b_branch2c_semi_scratch"
  1999. name: "bn4b_branch2c_semi_scratch"
  2000. type: "BatchNorm"
  2001. batch_norm_param {
  2002. use_global_stats: true
  2003. }
  2004. param {
  2005. lr_mult: 0.0
  2006. decay_mult: 0.0
  2007. }
  2008. param {
  2009. lr_mult: 0.0
  2010. decay_mult: 0.0
  2011. }
  2012. param {
  2013. lr_mult: 0.0
  2014. decay_mult: 0.0
  2015. }
  2016. }
  2017.  
  2018. layer {
  2019. bottom: "res4b_branch2c_semi_scratch"
  2020. top: "res4b_branch2c_semi_scratch"
  2021. name: "scale4b_branch2c_semi_scratch"
  2022. type: "Scale"
  2023. scale_param {
  2024. bias_term: true
  2025. }
  2026. }
  2027.  
  2028. layer {
  2029. bottom: "res4a"
  2030. bottom: "res4b_branch2c_semi_scratch"
  2031. top: "res4b_semi_scratch"
  2032. name: "res4b_semi_scratch"
  2033. type: "Eltwise"
  2034. }
  2035.  
  2036. layer {
  2037. bottom: "res4b_semi_scratch"
  2038. top: "res4b_semi_scratch"
  2039. name: "res4b_relu_semi_scratch"
  2040. type: "ReLU"
  2041. }
  2042.  
  2043. layer {
  2044. bottom: "res4b_semi_scratch"
  2045. top: "res4c_branch2a_semi_scratch"
  2046. name: "res4c_branch2a_semi_scratch"
  2047. type: "Convolution"
  2048. convolution_param {
  2049. num_output: 256
  2050. kernel_size: 1
  2051. pad: 0
  2052. stride: 1
  2053. bias_term: false
  2054. }
  2055. param {
  2056. lr_mult: 1.0
  2057. }
  2058. }
  2059.  
  2060. layer {
  2061. bottom: "res4c_branch2a_semi_scratch"
  2062. top: "res4c_branch2a_semi_scratch"
  2063. name: "bn4c_branch2a_semi_scratch"
  2064. type: "BatchNorm"
  2065. batch_norm_param {
  2066. use_global_stats: true
  2067. }
  2068. param {
  2069. lr_mult: 0.0
  2070. decay_mult: 0.0
  2071. }
  2072. param {
  2073. lr_mult: 0.0
  2074. decay_mult: 0.0
  2075. }
  2076. param {
  2077. lr_mult: 0.0
  2078. decay_mult: 0.0
  2079. }
  2080. }
  2081.  
  2082. layer {
  2083. bottom: "res4c_branch2a_semi_scratch"
  2084. top: "res4c_branch2a_semi_scratch"
  2085. name: "scale4c_branch2a_semi_scratch"
  2086. type: "Scale"
  2087. scale_param {
  2088. bias_term: true
  2089. }
  2090. }
  2091.  
  2092. layer {
  2093. bottom: "res4c_branch2a_semi_scratch"
  2094. top: "res4c_branch2a_semi_scratch"
  2095. name: "res4c_branch2a_relu_semi_scratch"
  2096. type: "ReLU"
  2097. }
  2098.  
  2099. layer {
  2100. bottom: "res4c_branch2a_semi_scratch"
  2101. top: "res4c_branch2b_semi_scratch"
  2102. name: "res4c_branch2b_semi_scratch"
  2103. type: "Convolution"
  2104. convolution_param {
  2105. num_output: 256
  2106. kernel_size: 3
  2107. pad: 1
  2108. stride: 1
  2109. bias_term: false
  2110. }
  2111. param {
  2112. lr_mult: 1.0
  2113. }
  2114. }
  2115.  
  2116. layer {
  2117. bottom: "res4c_branch2b_semi_scratch"
  2118. top: "res4c_branch2b_semi_scratch"
  2119. name: "bn4c_branch2b_semi_scratch"
  2120. type: "BatchNorm"
  2121. batch_norm_param {
  2122. use_global_stats: true
  2123. }
  2124. param {
  2125. lr_mult: 0.0
  2126. decay_mult: 0.0
  2127. }
  2128. param {
  2129. lr_mult: 0.0
  2130. decay_mult: 0.0
  2131. }
  2132. param {
  2133. lr_mult: 0.0
  2134. decay_mult: 0.0
  2135. }
  2136. }
  2137.  
  2138. layer {
  2139. bottom: "res4c_branch2b_semi_scratch"
  2140. top: "res4c_branch2b_semi_scratch"
  2141. name: "scale4c_branch2b_semi_scratch"
  2142. type: "Scale"
  2143. scale_param {
  2144. bias_term: true
  2145. }
  2146. }
  2147.  
  2148. layer {
  2149. bottom: "res4c_branch2b_semi_scratch"
  2150. top: "res4c_branch2b_semi_scratch"
  2151. name: "res4c_branch2b_relu_semi_scratch"
  2152. type: "ReLU"
  2153. }
  2154.  
  2155. layer {
  2156. bottom: "res4c_branch2b_semi_scratch"
  2157. top: "res4c_branch2c_semi_scratch"
  2158. name: "res4c_branch2c_semi_scratch"
  2159. type: "Convolution"
  2160. convolution_param {
  2161. num_output: 1024
  2162. kernel_size: 1
  2163. pad: 0
  2164. stride: 1
  2165. bias_term: false
  2166. }
  2167. param {
  2168. lr_mult: 1.0
  2169. }
  2170. }
  2171.  
  2172. layer {
  2173. bottom: "res4c_branch2c_semi_scratch"
  2174. top: "res4c_branch2c_semi_scratch"
  2175. name: "bn4c_branch2c_semi_scratch"
  2176. type: "BatchNorm"
  2177. batch_norm_param {
  2178. use_global_stats: true
  2179. }
  2180. param {
  2181. lr_mult: 0.0
  2182. decay_mult: 0.0
  2183. }
  2184. param {
  2185. lr_mult: 0.0
  2186. decay_mult: 0.0
  2187. }
  2188. param {
  2189. lr_mult: 0.0
  2190. decay_mult: 0.0
  2191. }
  2192. }
  2193.  
  2194. layer {
  2195. bottom: "res4c_branch2c_semi_scratch"
  2196. top: "res4c_branch2c_semi_scratch"
  2197. name: "scale4c_branch2c_semi_scratch"
  2198. type: "Scale"
  2199. scale_param {
  2200. bias_term: true
  2201. }
  2202. }
  2203.  
  2204. layer {
  2205. bottom: "res4b_semi_scratch"
  2206. bottom: "res4c_branch2c_semi_scratch"
  2207. top: "res4c_semi_scratch"
  2208. name: "res4c_semi_scratch"
  2209. type: "Eltwise"
  2210. }
  2211.  
  2212. layer {
  2213. bottom: "res4c_semi_scratch"
  2214. top: "res4c_semi_scratch"
  2215. name: "res4c_relu_semi_scratch"
  2216. type: "ReLU"
  2217. }
  2218.  
  2219. layer {
  2220. bottom: "res4c_semi_scratch"
  2221. top: "res4d_branch2a_semi_scratch"
  2222. name: "res4d_branch2a_semi_scratch"
  2223. type: "Convolution"
  2224. convolution_param {
  2225. num_output: 256
  2226. kernel_size: 1
  2227. pad: 0
  2228. stride: 1
  2229. bias_term: false
  2230. }
  2231. param {
  2232. lr_mult: 1.0
  2233. }
  2234. }
  2235.  
  2236. layer {
  2237. bottom: "res4d_branch2a_semi_scratch"
  2238. top: "res4d_branch2a_semi_scratch"
  2239. name: "bn4d_branch2a_semi_scratch"
  2240. type: "BatchNorm"
  2241. batch_norm_param {
  2242. use_global_stats: true
  2243. }
  2244. param {
  2245. lr_mult: 0.0
  2246. decay_mult: 0.0
  2247. }
  2248. param {
  2249. lr_mult: 0.0
  2250. decay_mult: 0.0
  2251. }
  2252. param {
  2253. lr_mult: 0.0
  2254. decay_mult: 0.0
  2255. }
  2256. }
  2257.  
  2258. layer {
  2259. bottom: "res4d_branch2a_semi_scratch"
  2260. top: "res4d_branch2a_semi_scratch"
  2261. name: "scale4d_branch2a_semi_scratch"
  2262. type: "Scale"
  2263. scale_param {
  2264. bias_term: true
  2265. }
  2266. }
  2267.  
  2268. layer {
  2269. bottom: "res4d_branch2a_semi_scratch"
  2270. top: "res4d_branch2a_semi_scratch"
  2271. name: "res4d_branch2a_relu_semi_scratch"
  2272. type: "ReLU"
  2273. }
  2274.  
  2275. layer {
  2276. bottom: "res4d_branch2a_semi_scratch"
  2277. top: "res4d_branch2b_semi_scratch"
  2278. name: "res4d_branch2b_semi_scratch"
  2279. type: "Convolution"
  2280. convolution_param {
  2281. num_output: 256
  2282. kernel_size: 3
  2283. pad: 1
  2284. stride: 1
  2285. bias_term: false
  2286. }
  2287. param {
  2288. lr_mult: 1.0
  2289. }
  2290. }
  2291.  
  2292. layer {
  2293. bottom: "res4d_branch2b_semi_scratch"
  2294. top: "res4d_branch2b_semi_scratch"
  2295. name: "bn4d_branch2b_semi_scratch"
  2296. type: "BatchNorm"
  2297. batch_norm_param {
  2298. use_global_stats: true
  2299. }
  2300. param {
  2301. lr_mult: 0.0
  2302. decay_mult: 0.0
  2303. }
  2304. param {
  2305. lr_mult: 0.0
  2306. decay_mult: 0.0
  2307. }
  2308. param {
  2309. lr_mult: 0.0
  2310. decay_mult: 0.0
  2311. }
  2312. }
  2313.  
  2314. layer {
  2315. bottom: "res4d_branch2b_semi_scratch"
  2316. top: "res4d_branch2b_semi_scratch"
  2317. name: "scale4d_branch2b_semi_scratch"
  2318. type: "Scale"
  2319. scale_param {
  2320. bias_term: true
  2321. }
  2322. }
  2323.  
  2324. layer {
  2325. bottom: "res4d_branch2b_semi_scratch"
  2326. top: "res4d_branch2b_semi_scratch"
  2327. name: "res4d_branch2b_relu_semi_scratch"
  2328. type: "ReLU"
  2329. }
  2330.  
  2331. layer {
  2332. bottom: "res4d_branch2b_semi_scratch"
  2333. top: "res4d_branch2c_semi_scratch"
  2334. name: "res4d_branch2c_semi_scratch"
  2335. type: "Convolution"
  2336. convolution_param {
  2337. num_output: 1024
  2338. kernel_size: 1
  2339. pad: 0
  2340. stride: 1
  2341. bias_term: false
  2342. }
  2343. param {
  2344. lr_mult: 1.0
  2345. }
  2346. }
  2347.  
  2348. layer {
  2349. bottom: "res4d_branch2c_semi_scratch"
  2350. top: "res4d_branch2c_semi_scratch"
  2351. name: "bn4d_branch2c_semi_scratch"
  2352. type: "BatchNorm"
  2353. batch_norm_param {
  2354. use_global_stats: true
  2355. }
  2356. param {
  2357. lr_mult: 0.0
  2358. decay_mult: 0.0
  2359. }
  2360. param {
  2361. lr_mult: 0.0
  2362. decay_mult: 0.0
  2363. }
  2364. param {
  2365. lr_mult: 0.0
  2366. decay_mult: 0.0
  2367. }
  2368. }
  2369.  
  2370. layer {
  2371. bottom: "res4d_branch2c_semi_scratch"
  2372. top: "res4d_branch2c_semi_scratch"
  2373. name: "scale4d_branch2c_semi_scratch"
  2374. type: "Scale"
  2375. scale_param {
  2376. bias_term: true
  2377. }
  2378. }
  2379.  
  2380. layer {
  2381. bottom: "res4c_semi_scratch"
  2382. bottom: "res4d_branch2c_semi_scratch"
  2383. top: "res4d_semi_scratch"
  2384. name: "res4d_semi_scratch"
  2385. type: "Eltwise"
  2386. }
  2387.  
  2388. layer {
  2389. bottom: "res4d_semi_scratch"
  2390. top: "res4d_semi_scratch"
  2391. name: "res4d_relu_semi_scratch"
  2392. type: "ReLU"
  2393. }
  2394.  
  2395. layer {
  2396. bottom: "res4d_semi_scratch"
  2397. top: "res4e_branch2a_semi_scratch"
  2398. name: "res4e_branch2a_semi_scratch"
  2399. type: "Convolution"
  2400. convolution_param {
  2401. num_output: 256
  2402. kernel_size: 1
  2403. pad: 0
  2404. stride: 1
  2405. bias_term: false
  2406. }
  2407. param {
  2408. lr_mult: 1.0
  2409. }
  2410. }
  2411.  
  2412. layer {
  2413. bottom: "res4e_branch2a_semi_scratch"
  2414. top: "res4e_branch2a_semi_scratch"
  2415. name: "bn4e_branch2a_semi_scratch"
  2416. type: "BatchNorm"
  2417. batch_norm_param {
  2418. use_global_stats: true
  2419. }
  2420. param {
  2421. lr_mult: 0.0
  2422. decay_mult: 0.0
  2423. }
  2424. param {
  2425. lr_mult: 0.0
  2426. decay_mult: 0.0
  2427. }
  2428. param {
  2429. lr_mult: 0.0
  2430. decay_mult: 0.0
  2431. }
  2432. }
  2433.  
  2434. layer {
  2435. bottom: "res4e_branch2a_semi_scratch"
  2436. top: "res4e_branch2a_semi_scratch"
  2437. name: "scale4e_branch2a_semi_scratch"
  2438. type: "Scale"
  2439. scale_param {
  2440. bias_term: true
  2441. }
  2442. }
  2443.  
  2444. layer {
  2445. bottom: "res4e_branch2a_semi_scratch"
  2446. top: "res4e_branch2a_semi_scratch"
  2447. name: "res4e_branch2a_relu_semi_scratch"
  2448. type: "ReLU"
  2449. }
  2450.  
  2451. layer {
  2452. bottom: "res4e_branch2a_semi_scratch"
  2453. top: "res4e_branch2b_semi_scratch"
  2454. name: "res4e_branch2b_semi_scratch"
  2455. type: "Convolution"
  2456. convolution_param {
  2457. num_output: 256
  2458. kernel_size: 3
  2459. pad: 1
  2460. stride: 1
  2461. bias_term: false
  2462. }
  2463. param {
  2464. lr_mult: 1.0
  2465. }
  2466. }
  2467.  
  2468. layer {
  2469. bottom: "res4e_branch2b_semi_scratch"
  2470. top: "res4e_branch2b_semi_scratch"
  2471. name: "bn4e_branch2b_semi_scratch"
  2472. type: "BatchNorm"
  2473. batch_norm_param {
  2474. use_global_stats: true
  2475. }
  2476. param {
  2477. lr_mult: 0.0
  2478. decay_mult: 0.0
  2479. }
  2480. param {
  2481. lr_mult: 0.0
  2482. decay_mult: 0.0
  2483. }
  2484. param {
  2485. lr_mult: 0.0
  2486. decay_mult: 0.0
  2487. }
  2488. }
  2489.  
  2490. layer {
  2491. bottom: "res4e_branch2b_semi_scratch"
  2492. top: "res4e_branch2b_semi_scratch"
  2493. name: "scale4e_branch2b_semi_scratch"
  2494. type: "Scale"
  2495. scale_param {
  2496. bias_term: true
  2497. }
  2498. }
  2499.  
  2500. layer {
  2501. bottom: "res4e_branch2b_semi_scratch"
  2502. top: "res4e_branch2b_semi_scratch"
  2503. name: "res4e_branch2b_relu_semi_scratch"
  2504. type: "ReLU"
  2505. }
  2506.  
  2507. layer {
  2508. bottom: "res4e_branch2b_semi_scratch"
  2509. top: "res4e_branch2c_semi_scratch"
  2510. name: "res4e_branch2c_semi_scratch"
  2511. type: "Convolution"
  2512. convolution_param {
  2513. num_output: 1024
  2514. kernel_size: 1
  2515. pad: 0
  2516. stride: 1
  2517. bias_term: false
  2518. }
  2519. param {
  2520. lr_mult: 1.0
  2521. }
  2522. }
  2523.  
  2524. layer {
  2525. bottom: "res4e_branch2c_semi_scratch"
  2526. top: "res4e_branch2c_semi_scratch"
  2527. name: "bn4e_branch2c_semi_scratch"
  2528. type: "BatchNorm"
  2529. batch_norm_param {
  2530. use_global_stats: true
  2531. }
  2532. param {
  2533. lr_mult: 0.0
  2534. decay_mult: 0.0
  2535. }
  2536. param {
  2537. lr_mult: 0.0
  2538. decay_mult: 0.0
  2539. }
  2540. param {
  2541. lr_mult: 0.0
  2542. decay_mult: 0.0
  2543. }
  2544. }
  2545.  
  2546. layer {
  2547. bottom: "res4e_branch2c_semi_scratch"
  2548. top: "res4e_branch2c_semi_scratch"
  2549. name: "scale4e_branch2c_semi_scratch"
  2550. type: "Scale"
  2551. scale_param {
  2552. bias_term: true
  2553. }
  2554. }
  2555.  
  2556. layer {
  2557. bottom: "res4d_semi_scratch"
  2558. bottom: "res4e_branch2c_semi_scratch"
  2559. top: "res4e_semi_scratch"
  2560. name: "res4e_semi_scratch"
  2561. type: "Eltwise"
  2562. }
  2563.  
  2564. layer {
  2565. bottom: "res4e_semi_scratch"
  2566. top: "res4e_semi_scratch"
  2567. name: "res4e_relu_semi_scratch"
  2568. type: "ReLU"
  2569. }
  2570.  
  2571. layer {
  2572. bottom: "res4e_semi_scratch"
  2573. top: "res4f_branch2a_semi_scratch"
  2574. name: "res4f_branch2a_semi_scratch"
  2575. type: "Convolution"
  2576. convolution_param {
  2577. num_output: 256
  2578. kernel_size: 1
  2579. pad: 0
  2580. stride: 1
  2581. bias_term: false
  2582. }
  2583. param {
  2584. lr_mult: 1.0
  2585. }
  2586. }
  2587.  
  2588. layer {
  2589. bottom: "res4f_branch2a_semi_scratch"
  2590. top: "res4f_branch2a_semi_scratch"
  2591. name: "bn4f_branch2a_semi_scratch"
  2592. type: "BatchNorm"
  2593. batch_norm_param {
  2594. use_global_stats: true
  2595. }
  2596. param {
  2597. lr_mult: 0.0
  2598. decay_mult: 0.0
  2599. }
  2600. param {
  2601. lr_mult: 0.0
  2602. decay_mult: 0.0
  2603. }
  2604. param {
  2605. lr_mult: 0.0
  2606. decay_mult: 0.0
  2607. }
  2608. }
  2609.  
  2610. layer {
  2611. bottom: "res4f_branch2a_semi_scratch"
  2612. top: "res4f_branch2a_semi_scratch"
  2613. name: "scale4f_branch2a_semi_scratch"
  2614. type: "Scale"
  2615. scale_param {
  2616. bias_term: true
  2617. }
  2618. }
  2619.  
  2620. layer {
  2621. bottom: "res4f_branch2a_semi_scratch"
  2622. top: "res4f_branch2a_semi_scratch"
  2623. name: "res4f_branch2a_relu_semi_scratch"
  2624. type: "ReLU"
  2625. }
  2626.  
  2627. layer {
  2628. bottom: "res4f_branch2a_semi_scratch"
  2629. top: "res4f_branch2b_semi_scratch"
  2630. name: "res4f_branch2b_semi_scratch"
  2631. type: "Convolution"
  2632. convolution_param {
  2633. num_output: 256
  2634. kernel_size: 3
  2635. pad: 1
  2636. stride: 1
  2637. bias_term: false
  2638. }
  2639. param {
  2640. lr_mult: 1.0
  2641. }
  2642. }
  2643.  
  2644. layer {
  2645. bottom: "res4f_branch2b_semi_scratch"
  2646. top: "res4f_branch2b_semi_scratch"
  2647. name: "bn4f_branch2b_semi_scratch"
  2648. type: "BatchNorm"
  2649. batch_norm_param {
  2650. use_global_stats: true
  2651. }
  2652. param {
  2653. lr_mult: 0.0
  2654. decay_mult: 0.0
  2655. }
  2656. param {
  2657. lr_mult: 0.0
  2658. decay_mult: 0.0
  2659. }
  2660. param {
  2661. lr_mult: 0.0
  2662. decay_mult: 0.0
  2663. }
  2664. }
  2665.  
  2666. layer {
  2667. bottom: "res4f_branch2b_semi_scratch"
  2668. top: "res4f_branch2b_semi_scratch"
  2669. name: "scale4f_branch2b_semi_scratch"
  2670. type: "Scale"
  2671. scale_param {
  2672. bias_term: true
  2673. }
  2674. }
  2675.  
  2676. layer {
  2677. bottom: "res4f_branch2b_semi_scratch"
  2678. top: "res4f_branch2b_semi_scratch"
  2679. name: "res4f_branch2b_relu_semi_scratch"
  2680. type: "ReLU"
  2681. }
  2682.  
  2683. layer {
  2684. bottom: "res4f_branch2b_semi_scratch"
  2685. top: "res4f_branch2c_semi_scratch"
  2686. name: "res4f_branch2c_semi_scratch"
  2687. type: "Convolution"
  2688. convolution_param {
  2689. num_output: 1024
  2690. kernel_size: 1
  2691. pad: 0
  2692. stride: 1
  2693. bias_term: false
  2694. }
  2695. param {
  2696. lr_mult: 1.0
  2697. }
  2698. }
  2699.  
  2700. layer {
  2701. bottom: "res4f_branch2c_semi_scratch"
  2702. top: "res4f_branch2c_semi_scratch"
  2703. name: "bn4f_branch2c_semi_scratch"
  2704. type: "BatchNorm"
  2705. batch_norm_param {
  2706. use_global_stats: true
  2707. }
  2708. param {
  2709. lr_mult: 0.0
  2710. decay_mult: 0.0
  2711. }
  2712. param {
  2713. lr_mult: 0.0
  2714. decay_mult: 0.0
  2715. }
  2716. param {
  2717. lr_mult: 0.0
  2718. decay_mult: 0.0
  2719. }
  2720. }
  2721.  
  2722. layer {
  2723. bottom: "res4f_branch2c_semi_scratch"
  2724. top: "res4f_branch2c_semi_scratch"
  2725. name: "scale4f_branch2c_semi_scratch"
  2726. type: "Scale"
  2727. scale_param {
  2728. bias_term: true
  2729. }
  2730. }
  2731.  
  2732. layer {
  2733. bottom: "res4e_semi_scratch"
  2734. bottom: "res4f_branch2c_semi_scratch"
  2735. top: "res4f_semi_scratch"
  2736. name: "res4f_semi_scratch"
  2737. type: "Eltwise"
  2738. }
  2739.  
  2740. layer {
  2741. bottom: "res4f_semi_scratch"
  2742. top: "res4f_semi_scratch"
  2743. name: "res4f_relu_semi_scratch"
  2744. type: "ReLU"
  2745. }
  2746.  
  2747. layer {
  2748. bottom: "res4f_semi_scratch"
  2749. top: "res5a_branch1_semi_scratch"
  2750. name: "res5a_branch1_semi_scratch"
  2751. type: "Convolution"
  2752. convolution_param {
  2753. num_output: 2048
  2754. kernel_size: 1
  2755. pad: 0
  2756. stride: 1
  2757. bias_term: false
  2758. }
  2759. param {
  2760. lr_mult: 1.0
  2761. }
  2762. }
  2763.  
  2764. layer {
  2765. bottom: "res5a_branch1_semi_scratch"
  2766. top: "res5a_branch1_semi_scratch"
  2767. name: "bn5a_branch1_semi_scratch"
  2768. type: "BatchNorm"
  2769. batch_norm_param {
  2770. use_global_stats: true
  2771. }
  2772. param {
  2773. lr_mult: 0.0
  2774. decay_mult: 0.0
  2775. }
  2776. param {
  2777. lr_mult: 0.0
  2778. decay_mult: 0.0
  2779. }
  2780. param {
  2781. lr_mult: 0.0
  2782. decay_mult: 0.0
  2783. }
  2784. }
  2785.  
  2786. layer {
  2787. bottom: "res5a_branch1_semi_scratch"
  2788. top: "res5a_branch1_semi_scratch"
  2789. name: "scale5a_branch1_semi_scratch"
  2790. type: "Scale"
  2791. scale_param {
  2792. bias_term: true
  2793. }
  2794. }
  2795.  
  2796. layer {
  2797. bottom: "res4f_semi_scratch"
  2798. top: "res5a_branch2a_semi_scratch"
  2799. name: "res5a_branch2a_semi_scratch"
  2800. type: "Convolution"
  2801. convolution_param {
  2802. num_output: 512
  2803. kernel_size: 1
  2804. pad: 0
  2805. stride: 1
  2806. bias_term: false
  2807. }
  2808. param {
  2809. lr_mult: 1.0
  2810. }
  2811. }
  2812.  
  2813. layer {
  2814. bottom: "res5a_branch2a_semi_scratch"
  2815. top: "res5a_branch2a_semi_scratch"
  2816. name: "bn5a_branch2a_semi_scratch"
  2817. type: "BatchNorm"
  2818. batch_norm_param {
  2819. use_global_stats: true
  2820. }
  2821. param {
  2822. lr_mult: 0.0
  2823. decay_mult: 0.0
  2824. }
  2825. param {
  2826. lr_mult: 0.0
  2827. decay_mult: 0.0
  2828. }
  2829. param {
  2830. lr_mult: 0.0
  2831. decay_mult: 0.0
  2832. }
  2833. }
  2834.  
  2835. layer {
  2836. bottom: "res5a_branch2a_semi_scratch"
  2837. top: "res5a_branch2a_semi_scratch"
  2838. name: "scale5a_branch2a_semi_scratch"
  2839. type: "Scale"
  2840. scale_param {
  2841. bias_term: true
  2842. }
  2843. }
  2844.  
  2845. layer {
  2846. bottom: "res5a_branch2a_semi_scratch"
  2847. top: "res5a_branch2a_semi_scratch"
  2848. name: "res5a_branch2a_relu_semi_scratch"
  2849. type: "ReLU"
  2850. }
  2851.  
  2852. layer {
  2853. bottom: "res5a_branch2a_semi_scratch"
  2854. top: "res5a_branch2b_semi_scratch"
  2855. name: "res5a_branch2b_semi_scratch"
  2856. type: "Convolution"
  2857. convolution_param {
  2858. num_output: 512
  2859. kernel_size: 3
  2860. dilation: 2
  2861. pad: 2
  2862. stride: 1
  2863. bias_term: false
  2864. }
  2865. param {
  2866. lr_mult: 1.0
  2867. }
  2868. }
  2869.  
  2870. layer {
  2871. bottom: "res5a_branch2b_semi_scratch"
  2872. top: "res5a_branch2b_semi_scratch"
  2873. name: "bn5a_branch2b_semi_scratch"
  2874. type: "BatchNorm"
  2875. batch_norm_param {
  2876. use_global_stats: true
  2877. }
  2878. param {
  2879. lr_mult: 0.0
  2880. decay_mult: 0.0
  2881. }
  2882. param {
  2883. lr_mult: 0.0
  2884. decay_mult: 0.0
  2885. }
  2886. param {
  2887. lr_mult: 0.0
  2888. decay_mult: 0.0
  2889. }
  2890. }
  2891.  
  2892. layer {
  2893. bottom: "res5a_branch2b_semi_scratch"
  2894. top: "res5a_branch2b_semi_scratch"
  2895. name: "scale5a_branch2b_semi_scratch"
  2896. type: "Scale"
  2897. scale_param {
  2898. bias_term: true
  2899. }
  2900. }
  2901.  
  2902. layer {
  2903. bottom: "res5a_branch2b_semi_scratch"
  2904. top: "res5a_branch2b_semi_scratch"
  2905. name: "res5a_branch2b_relu_semi_scratch"
  2906. type: "ReLU"
  2907. }
  2908.  
  2909. layer {
  2910. bottom: "res5a_branch2b_semi_scratch"
  2911. top: "res5a_branch2c_semi_scratch"
  2912. name: "res5a_branch2c_semi_scratch"
  2913. type: "Convolution"
  2914. convolution_param {
  2915. num_output: 2048
  2916. kernel_size: 1
  2917. pad: 0
  2918. stride: 1
  2919. bias_term: false
  2920. }
  2921. param {
  2922. lr_mult: 1.0
  2923. }
  2924. }
  2925.  
  2926. layer {
  2927. bottom: "res5a_branch2c_semi_scratch"
  2928. top: "res5a_branch2c_semi_scratch"
  2929. name: "bn5a_branch2c_semi_scratch"
  2930. type: "BatchNorm"
  2931. batch_norm_param {
  2932. use_global_stats: true
  2933. }
  2934. param {
  2935. lr_mult: 0.0
  2936. decay_mult: 0.0
  2937. }
  2938. param {
  2939. lr_mult: 0.0
  2940. decay_mult: 0.0
  2941. }
  2942. param {
  2943. lr_mult: 0.0
  2944. decay_mult: 0.0
  2945. }
  2946. }
  2947.  
  2948. layer {
  2949. bottom: "res5a_branch2c_semi_scratch"
  2950. top: "res5a_branch2c_semi_scratch"
  2951. name: "scale5a_branch2c_semi_scratch"
  2952. type: "Scale"
  2953. scale_param {
  2954. bias_term: true
  2955. }
  2956. }
  2957.  
  2958. layer {
  2959. bottom: "res5a_branch1_semi_scratch"
  2960. bottom: "res5a_branch2c_semi_scratch"
  2961. top: "res5a_semi_scratch"
  2962. name: "res5a_semi_scratch"
  2963. type: "Eltwise"
  2964. }
  2965.  
  2966. layer {
  2967. bottom: "res5a_semi_scratch"
  2968. top: "res5a_semi_scratch"
  2969. name: "res5a_relu_semi_scratch"
  2970. type: "ReLU"
  2971. }
  2972.  
  2973. layer {
  2974. bottom: "res5a_semi_scratch"
  2975. top: "res5b_branch2a_semi_scratch"
  2976. name: "res5b_branch2a_semi_scratch"
  2977. type: "Convolution"
  2978. convolution_param {
  2979. num_output: 512
  2980. kernel_size: 1
  2981. pad: 0
  2982. stride: 1
  2983. bias_term: false
  2984. }
  2985. param {
  2986. lr_mult: 1.0
  2987. }
  2988. }
  2989.  
  2990. layer {
  2991. bottom: "res5b_branch2a_semi_scratch"
  2992. top: "res5b_branch2a_semi_scratch"
  2993. name: "bn5b_branch2a_semi_scratch"
  2994. type: "BatchNorm"
  2995. batch_norm_param {
  2996. use_global_stats: true
  2997. }
  2998. param {
  2999. lr_mult: 0.0
  3000. decay_mult: 0.0
  3001. }
  3002. param {
  3003. lr_mult: 0.0
  3004. decay_mult: 0.0
  3005. }
  3006. param {
  3007. lr_mult: 0.0
  3008. decay_mult: 0.0
  3009. }
  3010. }
  3011.  
  3012. layer {
  3013. bottom: "res5b_branch2a_semi_scratch"
  3014. top: "res5b_branch2a_semi_scratch"
  3015. name: "scale5b_branch2a_semi_scratch"
  3016. type: "Scale"
  3017. scale_param {
  3018. bias_term: true
  3019. }
  3020. }
  3021.  
  3022. layer {
  3023. bottom: "res5b_branch2a_semi_scratch"
  3024. top: "res5b_branch2a_semi_scratch"
  3025. name: "res5b_branch2a_relu_semi_scratch"
  3026. type: "ReLU"
  3027. }
  3028.  
  3029. layer {
  3030. bottom: "res5b_branch2a_semi_scratch"
  3031. top: "res5b_branch2b_semi_scratch"
  3032. name: "res5b_branch2b_semi_scratch"
  3033. type: "Convolution"
  3034. convolution_param {
  3035. num_output: 512
  3036. kernel_size: 3
  3037. dilation: 2
  3038. pad: 2
  3039. stride: 1
  3040. bias_term: false
  3041. }
  3042. param {
  3043. lr_mult: 1.0
  3044. }
  3045. }
  3046.  
  3047. layer {
  3048. bottom: "res5b_branch2b_semi_scratch"
  3049. top: "res5b_branch2b_semi_scratch"
  3050. name: "bn5b_branch2b_semi_scratch"
  3051. type: "BatchNorm"
  3052. batch_norm_param {
  3053. use_global_stats: true
  3054. }
  3055. param {
  3056. lr_mult: 0.0
  3057. decay_mult: 0.0
  3058. }
  3059. param {
  3060. lr_mult: 0.0
  3061. decay_mult: 0.0
  3062. }
  3063. param {
  3064. lr_mult: 0.0
  3065. decay_mult: 0.0
  3066. }
  3067. }
  3068.  
  3069. layer {
  3070. bottom: "res5b_branch2b_semi_scratch"
  3071. top: "res5b_branch2b_semi_scratch"
  3072. name: "scale5b_branch2b_semi_scratch"
  3073. type: "Scale"
  3074. scale_param {
  3075. bias_term: true
  3076. }
  3077. }
  3078.  
  3079. layer {
  3080. bottom: "res5b_branch2b_semi_scratch"
  3081. top: "res5b_branch2b_semi_scratch"
  3082. name: "res5b_branch2b_relu_semi_scratch"
  3083. type: "ReLU"
  3084. }
  3085.  
  3086. layer {
  3087. bottom: "res5b_branch2b_semi_scratch"
  3088. top: "res5b_branch2c_semi_scratch"
  3089. name: "res5b_branch2c_semi_scratch"
  3090. type: "Convolution"
  3091. convolution_param {
  3092. num_output: 2048
  3093. kernel_size: 1
  3094. pad: 0
  3095. stride: 1
  3096. bias_term: false
  3097. }
  3098. param {
  3099. lr_mult: 1.0
  3100. }
  3101. }
  3102.  
  3103. layer {
  3104. bottom: "res5b_branch2c_semi_scratch"
  3105. top: "res5b_branch2c_semi_scratch"
  3106. name: "bn5b_branch2c_semi_scratch"
  3107. type: "BatchNorm"
  3108. batch_norm_param {
  3109. use_global_stats: true
  3110. }
  3111. param {
  3112. lr_mult: 0.0
  3113. decay_mult: 0.0
  3114. }
  3115. param {
  3116. lr_mult: 0.0
  3117. decay_mult: 0.0
  3118. }
  3119. param {
  3120. lr_mult: 0.0
  3121. decay_mult: 0.0
  3122. }
  3123. }
  3124.  
  3125. layer {
  3126. bottom: "res5b_branch2c_semi_scratch"
  3127. top: "res5b_branch2c_semi_scratch"
  3128. name: "scale5b_branch2c_semi_scratch"
  3129. type: "Scale"
  3130. scale_param {
  3131. bias_term: true
  3132. }
  3133. }
  3134.  
  3135. layer {
  3136. bottom: "res5a_semi_scratch"
  3137. bottom: "res5b_branch2c_semi_scratch"
  3138. top: "res5b_semi_scratch"
  3139. name: "res5b_semi_scratch"
  3140. type: "Eltwise"
  3141. }
  3142.  
  3143. layer {
  3144. bottom: "res5b_semi_scratch"
  3145. top: "res5b_semi_scratch"
  3146. name: "res5b_relu_semi_scratch"
  3147. type: "ReLU"
  3148. }
  3149.  
  3150. layer {
  3151. bottom: "res5b_semi_scratch"
  3152. top: "res5c_branch2a_semi_scratch"
  3153. name: "res5c_branch2a_semi_scratch"
  3154. type: "Convolution"
  3155. convolution_param {
  3156. num_output: 512
  3157. kernel_size: 1
  3158. pad: 0
  3159. stride: 1
  3160. bias_term: false
  3161. }
  3162. param {
  3163. lr_mult: 1.0
  3164. }
  3165. }
  3166.  
  3167. layer {
  3168. bottom: "res5c_branch2a_semi_scratch"
  3169. top: "res5c_branch2a_semi_scratch"
  3170. name: "bn5c_branch2a_semi_scratch"
  3171. type: "BatchNorm"
  3172. batch_norm_param {
  3173. use_global_stats: true
  3174. }
  3175. param {
  3176. lr_mult: 0.0
  3177. decay_mult: 0.0
  3178. }
  3179. param {
  3180. lr_mult: 0.0
  3181. decay_mult: 0.0
  3182. }
  3183. param {
  3184. lr_mult: 0.0
  3185. decay_mult: 0.0
  3186. }
  3187. }
  3188.  
  3189. layer {
  3190. bottom: "res5c_branch2a_semi_scratch"
  3191. top: "res5c_branch2a_semi_scratch"
  3192. name: "scale5c_branch2a_semi_scratch"
  3193. type: "Scale"
  3194. scale_param {
  3195. bias_term: true
  3196. }
  3197. }
  3198.  
  3199. layer {
  3200. bottom: "res5c_branch2a_semi_scratch"
  3201. top: "res5c_branch2a_semi_scratch"
  3202. name: "res5c_branch2a_relu_semi_scratch"
  3203. type: "ReLU"
  3204. }
  3205.  
  3206. layer {
  3207. bottom: "res5c_branch2a_semi_scratch"
  3208. top: "res5c_branch2b_semi_scratch"
  3209. name: "res5c_branch2b_semi_scratch"
  3210. type: "Convolution"
  3211. convolution_param {
  3212. num_output: 512
  3213. kernel_size: 3
  3214. dilation: 2
  3215. pad: 2
  3216. stride: 1
  3217. bias_term: false
  3218. }
  3219. param {
  3220. lr_mult: 1.0
  3221. }
  3222. }
  3223.  
  3224. layer {
  3225. bottom: "res5c_branch2b_semi_scratch"
  3226. top: "res5c_branch2b_semi_scratch"
  3227. name: "bn5c_branch2b_semi_scratch"
  3228. type: "BatchNorm"
  3229. batch_norm_param {
  3230. use_global_stats: true
  3231. }
  3232. param {
  3233. lr_mult: 0.0
  3234. decay_mult: 0.0
  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: "res5c_branch2b_semi_scratch"
  3248. top: "res5c_branch2b_semi_scratch"
  3249. name: "scale5c_branch2b_semi_scratch"
  3250. type: "Scale"
  3251. scale_param {
  3252. bias_term: true
  3253. }
  3254. }
  3255.  
  3256. layer {
  3257. bottom: "res5c_branch2b_semi_scratch"
  3258. top: "res5c_branch2b_semi_scratch"
  3259. name: "res5c_branch2b_relu_semi_scratch"
  3260. type: "ReLU"
  3261. }
  3262.  
  3263. layer {
  3264. bottom: "res5c_branch2b_semi_scratch"
  3265. top: "res5c_branch2c_semi_scratch"
  3266. name: "res5c_branch2c_semi_scratch"
  3267. type: "Convolution"
  3268. convolution_param {
  3269. num_output: 2048
  3270. kernel_size: 1
  3271. pad: 0
  3272. stride: 1
  3273. bias_term: false
  3274. }
  3275. param {
  3276. lr_mult: 1.0
  3277. }
  3278. }
  3279.  
  3280. layer {
  3281. bottom: "res5c_branch2c_semi_scratch"
  3282. top: "res5c_branch2c_semi_scratch"
  3283. name: "bn5c_branch2c_semi_scratch"
  3284. type: "BatchNorm"
  3285. batch_norm_param {
  3286. use_global_stats: true
  3287. }
  3288. param {
  3289. lr_mult: 0.0
  3290. decay_mult: 0.0
  3291. }
  3292. param {
  3293. lr_mult: 0.0
  3294. decay_mult: 0.0
  3295. }
  3296. param {
  3297. lr_mult: 0.0
  3298. decay_mult: 0.0
  3299. }
  3300. }
  3301.  
  3302. layer {
  3303. bottom: "res5c_branch2c_semi_scratch"
  3304. top: "res5c_branch2c_semi_scratch"
  3305. name: "scale5c_branch2c_semi_scratch"
  3306. type: "Scale"
  3307. scale_param {
  3308. bias_term: true
  3309. }
  3310. }
  3311.  
  3312. layer {
  3313. bottom: "res5b_semi_scratch"
  3314. bottom: "res5c_branch2c_semi_scratch"
  3315. top: "res5c_semi_scratch"
  3316. name: "res5c_semi_scratch"
  3317. type: "Eltwise"
  3318. }
  3319.  
  3320. layer {
  3321. bottom: "res5c_semi_scratch"
  3322. top: "res5c_semi_scratch"
  3323. name: "res5c_relu_semi_scratch"
  3324. type: "ReLU"
  3325. }
  3326.  
  3327. #========= RPN ============
  3328.  
  3329. layer {
  3330. name: "rpn_conv/3x3"
  3331. type: "Convolution"
  3332. bottom: "res4f_semi_scratch"
  3333. top: "rpn/output"
  3334. param { lr_mult: 1.0 decay_mult: 1.0 }
  3335. param { lr_mult: 2.0 decay_mult: 0 }
  3336. convolution_param {
  3337. num_output: 512
  3338. kernel_size: 3 pad: 1 stride: 1
  3339. weight_filler { type: "gaussian" std: 0.01 }
  3340. bias_filler { type: "constant" value: 0 }
  3341. }
  3342. }
  3343. layer {
  3344. name: "rpn_relu/3x3"
  3345. type: "ReLU"
  3346. bottom: "rpn/output"
  3347. top: "rpn/output"
  3348. }
  3349.  
  3350. layer {
  3351. name: "rpn_cls_score"
  3352. type: "Convolution"
  3353. bottom: "rpn/output"
  3354. top: "rpn_cls_score"
  3355. param { lr_mult: 1.0 decay_mult: 1.0 }
  3356. param { lr_mult: 2.0 decay_mult: 0 }
  3357. convolution_param {
  3358. num_output: 18 # 2(bg/fg) * 9(anchors)
  3359. kernel_size: 1 pad: 0 stride: 1
  3360. weight_filler { type: "gaussian" std: 0.01 }
  3361. bias_filler { type: "constant" value: 0 }
  3362. }
  3363. }
  3364. layer {
  3365. name: "rpn_bbox_pred"
  3366. type: "Convolution"
  3367. bottom: "rpn/output"
  3368. top: "rpn_bbox_pred"
  3369. param { lr_mult: 1.0 decay_mult: 1.0 }
  3370. param { lr_mult: 2.0 decay_mult: 0 }
  3371. convolution_param {
  3372. num_output: 36 # 4 * 9(anchors)
  3373. kernel_size: 1 pad: 0 stride: 1
  3374. weight_filler { type: "gaussian" std: 0.01 }
  3375. bias_filler { type: "constant" value: 0 }
  3376. }
  3377. }
  3378. layer {
  3379. bottom: "rpn_cls_score"
  3380. top: "rpn_cls_score_reshape"
  3381. name: "rpn_cls_score_reshape"
  3382. type: "Reshape"
  3383. reshape_param { shape { dim: 0 dim: 2 dim: -1 dim: 0 } }
  3384. }
  3385.  
  3386. #========= RoI Proposal ============
  3387.  
  3388. layer {
  3389. name: "rpn_cls_prob"
  3390. type: "Softmax"
  3391. bottom: "rpn_cls_score_reshape"
  3392. top: "rpn_cls_prob"
  3393. }
  3394. layer {
  3395. name: 'rpn_cls_prob_reshape'
  3396. type: 'Reshape'
  3397. bottom: 'rpn_cls_prob'
  3398. top: 'rpn_cls_prob_reshape'
  3399. reshape_param { shape { dim: 0 dim: 18 dim: -1 dim: 0 } }
  3400. }
  3401. layer {
  3402. name: 'proposal'
  3403. type: 'Python'
  3404. bottom: 'rpn_cls_prob_reshape'
  3405. bottom: 'rpn_bbox_pred'
  3406. bottom: 'im_info'
  3407. top: 'rois'
  3408. python_param {
  3409. module: 'rpn.proposal_layer'
  3410. layer: 'ProposalLayer'
  3411. param_str: "'feat_stride': 16"
  3412. }
  3413. }
  3414.  
  3415. #----------------------new conv layer------------------
  3416. layer {
  3417. bottom: "res5c_semi_scratch"
  3418. top: "conv_new_1"
  3419. name: "conv_new_1"
  3420. type: "Convolution"
  3421. convolution_param {
  3422. num_output: 1024
  3423. kernel_size: 1
  3424. pad: 0
  3425. weight_filler {
  3426. type: "gaussian"
  3427. std: 0.01
  3428. }
  3429. bias_filler {
  3430. type: "constant"
  3431. value: 0
  3432. }
  3433. }
  3434. param {
  3435. lr_mult: 1.0
  3436. }
  3437. param {
  3438. lr_mult: 2.0
  3439. }
  3440. }
  3441.  
  3442. layer {
  3443. bottom: "conv_new_1"
  3444. top: "conv_new_1"
  3445. name: "conv_new_1_relu"
  3446. type: "ReLU"
  3447. }
  3448.  
  3449. layer {
  3450. bottom: "conv_new_1"
  3451. top: "rfcn_cls"
  3452. name: "rfcn_cls"
  3453. type: "Convolution"
  3454. convolution_param {
  3455. num_output: 98 #2*(7^2) cls_num*(score_maps_size^2)
  3456. kernel_size: 1
  3457. pad: 0
  3458. weight_filler {
  3459. type: "gaussian"
  3460. std: 0.01
  3461. }
  3462. bias_filler {
  3463. type: "constant"
  3464. value: 0
  3465. }
  3466. }
  3467. param {
  3468. lr_mult: 1.0
  3469. }
  3470. param {
  3471. lr_mult: 2.0
  3472. }
  3473. }
  3474. layer {
  3475. bottom: "conv_new_1"
  3476. top: "rfcn_bbox"
  3477. name: "rfcn_bbox"
  3478. type: "Convolution"
  3479. convolution_param {
  3480. num_output: 392 #8*(7^2) cls_num*(score_maps_size^2)
  3481. kernel_size: 1
  3482. pad: 0
  3483. weight_filler {
  3484. type: "gaussian"
  3485. std: 0.01
  3486. }
  3487. bias_filler {
  3488. type: "constant"
  3489. value: 0
  3490. }
  3491. }
  3492. param {
  3493. lr_mult: 1.0
  3494. }
  3495. param {
  3496. lr_mult: 2.0
  3497. }
  3498. }
  3499.  
  3500. #--------------position sensitive RoI pooling--------------
  3501. layer {
  3502. bottom: "rfcn_cls"
  3503. bottom: "rois"
  3504. top: "psroipooled_cls_rois"
  3505. name: "psroipooled_cls_rois"
  3506. type: "PSROIPooling"
  3507. psroi_pooling_param {
  3508. spatial_scale: 0.0625
  3509. output_dim: 2
  3510. group_size: 7
  3511. }
  3512. }
  3513.  
  3514. layer {
  3515. bottom: "psroipooled_cls_rois"
  3516. top: "cls_score"
  3517. name: "ave_cls_score_rois"
  3518. type: "Pooling"
  3519. pooling_param {
  3520. pool: AVE
  3521. kernel_size: 7
  3522. stride: 7
  3523. }
  3524. }
  3525.  
  3526.  
  3527. layer {
  3528. bottom: "rfcn_bbox"
  3529. bottom: "rois"
  3530. top: "psroipooled_loc_rois"
  3531. name: "psroipooled_loc_rois"
  3532. type: "PSROIPooling"
  3533. psroi_pooling_param {
  3534. spatial_scale: 0.0625
  3535. output_dim: 8
  3536. group_size: 7
  3537. }
  3538. }
  3539.  
  3540. layer {
  3541. bottom: "psroipooled_loc_rois"
  3542. top: "bbox_pred_pre"
  3543. name: "ave_bbox_pred_rois"
  3544. type: "Pooling"
  3545. pooling_param {
  3546. pool: AVE
  3547. kernel_size: 7
  3548. stride: 7
  3549. }
  3550. }
  3551.  
  3552.  
  3553. #-----------------------output------------------------
  3554. layer {
  3555. name: "cls_prob"
  3556. type: "Softmax"
  3557. bottom: "cls_score"
  3558. top: "cls_prob_pre"
  3559. }
  3560.  
  3561. layer {
  3562. name: "cls_prob_reshape"
  3563. type: "Reshape"
  3564. bottom: "cls_prob_pre"
  3565. top: "cls_prob"
  3566. reshape_param {
  3567. shape {
  3568. dim: -1
  3569. dim: 2
  3570. }
  3571. }
  3572. }
  3573.  
  3574. layer {
  3575. name: "bbox_pred_reshape"
  3576. type: "Reshape"
  3577. bottom: "bbox_pred_pre"
  3578. top: "bbox_pred"
  3579. reshape_param {
  3580. shape {
  3581. dim: -1
  3582. dim: 8
  3583. }
  3584. }
  3585. }
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