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ResNet-50-deploy.prototxt 32 kB

4 years ago
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  1. name: "ResNet-50"
  2. input: "data"
  3. input_dim: 1
  4. input_dim: 3
  5. input_dim: 224
  6. input_dim: 224
  7. layer {
  8. bottom: "data"
  9. top: "conv1"
  10. name: "conv1"
  11. type: "Convolution"
  12. convolution_param {
  13. num_output: 64
  14. kernel_size: 7
  15. pad: 3
  16. stride: 2
  17. }
  18. }
  19. layer {
  20. bottom: "conv1"
  21. top: "conv1"
  22. name: "bn_conv1"
  23. type: "BatchNorm"
  24. batch_norm_param {
  25. use_global_stats: true
  26. }
  27. }
  28. layer {
  29. bottom: "conv1"
  30. top: "conv1"
  31. name: "scale_conv1"
  32. type: "Scale"
  33. scale_param {
  34. bias_term: true
  35. }
  36. }
  37. layer {
  38. bottom: "conv1"
  39. top: "conv1"
  40. name: "conv1_relu"
  41. type: "ReLU"
  42. }
  43. layer {
  44. bottom: "conv1"
  45. top: "pool1"
  46. name: "pool1"
  47. type: "Pooling"
  48. pooling_param {
  49. kernel_size: 3
  50. stride: 2
  51. pool: MAX
  52. }
  53. }
  54. layer {
  55. bottom: "pool1"
  56. top: "res2a_branch1"
  57. name: "res2a_branch1"
  58. type: "Convolution"
  59. convolution_param {
  60. num_output: 256
  61. kernel_size: 1
  62. pad: 0
  63. stride: 1
  64. bias_term: false
  65. }
  66. }
  67. layer {
  68. bottom: "res2a_branch1"
  69. top: "res2a_branch1"
  70. name: "bn2a_branch1"
  71. type: "BatchNorm"
  72. batch_norm_param {
  73. use_global_stats: true
  74. }
  75. }
  76. layer {
  77. bottom: "res2a_branch1"
  78. top: "res2a_branch1"
  79. name: "scale2a_branch1"
  80. type: "Scale"
  81. scale_param {
  82. bias_term: true
  83. }
  84. }
  85. layer {
  86. bottom: "pool1"
  87. top: "res2a_branch2a"
  88. name: "res2a_branch2a"
  89. type: "Convolution"
  90. convolution_param {
  91. num_output: 64
  92. kernel_size: 1
  93. pad: 0
  94. stride: 1
  95. bias_term: false
  96. }
  97. }
  98. layer {
  99. bottom: "res2a_branch2a"
  100. top: "res2a_branch2a"
  101. name: "bn2a_branch2a"
  102. type: "BatchNorm"
  103. batch_norm_param {
  104. use_global_stats: true
  105. }
  106. }
  107. layer {
  108. bottom: "res2a_branch2a"
  109. top: "res2a_branch2a"
  110. name: "scale2a_branch2a"
  111. type: "Scale"
  112. scale_param {
  113. bias_term: true
  114. }
  115. }
  116. layer {
  117. bottom: "res2a_branch2a"
  118. top: "res2a_branch2a"
  119. name: "res2a_branch2a_relu"
  120. type: "ReLU"
  121. }
  122. layer {
  123. bottom: "res2a_branch2a"
  124. top: "res2a_branch2b"
  125. name: "res2a_branch2b"
  126. type: "Convolution"
  127. convolution_param {
  128. num_output: 64
  129. kernel_size: 3
  130. pad: 1
  131. stride: 1
  132. bias_term: false
  133. }
  134. }
  135. layer {
  136. bottom: "res2a_branch2b"
  137. top: "res2a_branch2b"
  138. name: "bn2a_branch2b"
  139. type: "BatchNorm"
  140. batch_norm_param {
  141. use_global_stats: true
  142. }
  143. }
  144. layer {
  145. bottom: "res2a_branch2b"
  146. top: "res2a_branch2b"
  147. name: "scale2a_branch2b"
  148. type: "Scale"
  149. scale_param {
  150. bias_term: true
  151. }
  152. }
  153. layer {
  154. bottom: "res2a_branch2b"
  155. top: "res2a_branch2b"
  156. name: "res2a_branch2b_relu"
  157. type: "ReLU"
  158. }
  159. layer {
  160. bottom: "res2a_branch2b"
  161. top: "res2a_branch2c"
  162. name: "res2a_branch2c"
  163. type: "Convolution"
  164. convolution_param {
  165. num_output: 256
  166. kernel_size: 1
  167. pad: 0
  168. stride: 1
  169. bias_term: false
  170. }
  171. }
  172. layer {
  173. bottom: "res2a_branch2c"
  174. top: "res2a_branch2c"
  175. name: "bn2a_branch2c"
  176. type: "BatchNorm"
  177. batch_norm_param {
  178. use_global_stats: true
  179. }
  180. }
  181. layer {
  182. bottom: "res2a_branch2c"
  183. top: "res2a_branch2c"
  184. name: "scale2a_branch2c"
  185. type: "Scale"
  186. scale_param {
  187. bias_term: true
  188. }
  189. }
  190. layer {
  191. bottom: "res2a_branch1"
  192. bottom: "res2a_branch2c"
  193. top: "res2a"
  194. name: "res2a"
  195. type: "Eltwise"
  196. }
  197. layer {
  198. bottom: "res2a"
  199. top: "res2a"
  200. name: "res2a_relu"
  201. type: "ReLU"
  202. }
  203. layer {
  204. bottom: "res2a"
  205. top: "res2b_branch2a"
  206. name: "res2b_branch2a"
  207. type: "Convolution"
  208. convolution_param {
  209. num_output: 64
  210. kernel_size: 1
  211. pad: 0
  212. stride: 1
  213. bias_term: false
  214. }
  215. }
  216. layer {
  217. bottom: "res2b_branch2a"
  218. top: "res2b_branch2a"
  219. name: "bn2b_branch2a"
  220. type: "BatchNorm"
  221. batch_norm_param {
  222. use_global_stats: true
  223. }
  224. }
  225. layer {
  226. bottom: "res2b_branch2a"
  227. top: "res2b_branch2a"
  228. name: "scale2b_branch2a"
  229. type: "Scale"
  230. scale_param {
  231. bias_term: true
  232. }
  233. }
  234. layer {
  235. bottom: "res2b_branch2a"
  236. top: "res2b_branch2a"
  237. name: "res2b_branch2a_relu"
  238. type: "ReLU"
  239. }
  240. layer {
  241. bottom: "res2b_branch2a"
  242. top: "res2b_branch2b"
  243. name: "res2b_branch2b"
  244. type: "Convolution"
  245. convolution_param {
  246. num_output: 64
  247. kernel_size: 3
  248. pad: 1
  249. stride: 1
  250. bias_term: false
  251. }
  252. }
  253. layer {
  254. bottom: "res2b_branch2b"
  255. top: "res2b_branch2b"
  256. name: "bn2b_branch2b"
  257. type: "BatchNorm"
  258. batch_norm_param {
  259. use_global_stats: true
  260. }
  261. }
  262. layer {
  263. bottom: "res2b_branch2b"
  264. top: "res2b_branch2b"
  265. name: "scale2b_branch2b"
  266. type: "Scale"
  267. scale_param {
  268. bias_term: true
  269. }
  270. }
  271. layer {
  272. bottom: "res2b_branch2b"
  273. top: "res2b_branch2b"
  274. name: "res2b_branch2b_relu"
  275. type: "ReLU"
  276. }
  277. layer {
  278. bottom: "res2b_branch2b"
  279. top: "res2b_branch2c"
  280. name: "res2b_branch2c"
  281. type: "Convolution"
  282. convolution_param {
  283. num_output: 256
  284. kernel_size: 1
  285. pad: 0
  286. stride: 1
  287. bias_term: false
  288. }
  289. }
  290. layer {
  291. bottom: "res2b_branch2c"
  292. top: "res2b_branch2c"
  293. name: "bn2b_branch2c"
  294. type: "BatchNorm"
  295. batch_norm_param {
  296. use_global_stats: true
  297. }
  298. }
  299. layer {
  300. bottom: "res2b_branch2c"
  301. top: "res2b_branch2c"
  302. name: "scale2b_branch2c"
  303. type: "Scale"
  304. scale_param {
  305. bias_term: true
  306. }
  307. }
  308. layer {
  309. bottom: "res2a"
  310. bottom: "res2b_branch2c"
  311. top: "res2b"
  312. name: "res2b"
  313. type: "Eltwise"
  314. }
  315. layer {
  316. bottom: "res2b"
  317. top: "res2b"
  318. name: "res2b_relu"
  319. type: "ReLU"
  320. }
  321. layer {
  322. bottom: "res2b"
  323. top: "res2c_branch2a"
  324. name: "res2c_branch2a"
  325. type: "Convolution"
  326. convolution_param {
  327. num_output: 64
  328. kernel_size: 1
  329. pad: 0
  330. stride: 1
  331. bias_term: false
  332. }
  333. }
  334. layer {
  335. bottom: "res2c_branch2a"
  336. top: "res2c_branch2a"
  337. name: "bn2c_branch2a"
  338. type: "BatchNorm"
  339. batch_norm_param {
  340. use_global_stats: true
  341. }
  342. }
  343. layer {
  344. bottom: "res2c_branch2a"
  345. top: "res2c_branch2a"
  346. name: "scale2c_branch2a"
  347. type: "Scale"
  348. scale_param {
  349. bias_term: true
  350. }
  351. }
  352. layer {
  353. bottom: "res2c_branch2a"
  354. top: "res2c_branch2a"
  355. name: "res2c_branch2a_relu"
  356. type: "ReLU"
  357. }
  358. layer {
  359. bottom: "res2c_branch2a"
  360. top: "res2c_branch2b"
  361. name: "res2c_branch2b"
  362. type: "Convolution"
  363. convolution_param {
  364. num_output: 64
  365. kernel_size: 3
  366. pad: 1
  367. stride: 1
  368. bias_term: false
  369. }
  370. }
  371. layer {
  372. bottom: "res2c_branch2b"
  373. top: "res2c_branch2b"
  374. name: "bn2c_branch2b"
  375. type: "BatchNorm"
  376. batch_norm_param {
  377. use_global_stats: true
  378. }
  379. }
  380. layer {
  381. bottom: "res2c_branch2b"
  382. top: "res2c_branch2b"
  383. name: "scale2c_branch2b"
  384. type: "Scale"
  385. scale_param {
  386. bias_term: true
  387. }
  388. }
  389. layer {
  390. bottom: "res2c_branch2b"
  391. top: "res2c_branch2b"
  392. name: "res2c_branch2b_relu"
  393. type: "ReLU"
  394. }
  395. layer {
  396. bottom: "res2c_branch2b"
  397. top: "res2c_branch2c"
  398. name: "res2c_branch2c"
  399. type: "Convolution"
  400. convolution_param {
  401. num_output: 256
  402. kernel_size: 1
  403. pad: 0
  404. stride: 1
  405. bias_term: false
  406. }
  407. }
  408. layer {
  409. bottom: "res2c_branch2c"
  410. top: "res2c_branch2c"
  411. name: "bn2c_branch2c"
  412. type: "BatchNorm"
  413. batch_norm_param {
  414. use_global_stats: true
  415. }
  416. }
  417. layer {
  418. bottom: "res2c_branch2c"
  419. top: "res2c_branch2c"
  420. name: "scale2c_branch2c"
  421. type: "Scale"
  422. scale_param {
  423. bias_term: true
  424. }
  425. }
  426. layer {
  427. bottom: "res2b"
  428. bottom: "res2c_branch2c"
  429. top: "res2c"
  430. name: "res2c"
  431. type: "Eltwise"
  432. }
  433. layer {
  434. bottom: "res2c"
  435. top: "res2c"
  436. name: "res2c_relu"
  437. type: "ReLU"
  438. }
  439. layer {
  440. bottom: "res2c"
  441. top: "res3a_branch1"
  442. name: "res3a_branch1"
  443. type: "Convolution"
  444. convolution_param {
  445. num_output: 512
  446. kernel_size: 1
  447. pad: 0
  448. stride: 2
  449. bias_term: false
  450. }
  451. }
  452. layer {
  453. bottom: "res3a_branch1"
  454. top: "res3a_branch1"
  455. name: "bn3a_branch1"
  456. type: "BatchNorm"
  457. batch_norm_param {
  458. use_global_stats: true
  459. }
  460. }
  461. layer {
  462. bottom: "res3a_branch1"
  463. top: "res3a_branch1"
  464. name: "scale3a_branch1"
  465. type: "Scale"
  466. scale_param {
  467. bias_term: true
  468. }
  469. }
  470. layer {
  471. bottom: "res2c"
  472. top: "res3a_branch2a"
  473. name: "res3a_branch2a"
  474. type: "Convolution"
  475. convolution_param {
  476. num_output: 128
  477. kernel_size: 1
  478. pad: 0
  479. stride: 2
  480. bias_term: false
  481. }
  482. }
  483. layer {
  484. bottom: "res3a_branch2a"
  485. top: "res3a_branch2a"
  486. name: "bn3a_branch2a"
  487. type: "BatchNorm"
  488. batch_norm_param {
  489. use_global_stats: true
  490. }
  491. }
  492. layer {
  493. bottom: "res3a_branch2a"
  494. top: "res3a_branch2a"
  495. name: "scale3a_branch2a"
  496. type: "Scale"
  497. scale_param {
  498. bias_term: true
  499. }
  500. }
  501. layer {
  502. bottom: "res3a_branch2a"
  503. top: "res3a_branch2a"
  504. name: "res3a_branch2a_relu"
  505. type: "ReLU"
  506. }
  507. layer {
  508. bottom: "res3a_branch2a"
  509. top: "res3a_branch2b"
  510. name: "res3a_branch2b"
  511. type: "Convolution"
  512. convolution_param {
  513. num_output: 128
  514. kernel_size: 3
  515. pad: 1
  516. stride: 1
  517. bias_term: false
  518. }
  519. }
  520. layer {
  521. bottom: "res3a_branch2b"
  522. top: "res3a_branch2b"
  523. name: "bn3a_branch2b"
  524. type: "BatchNorm"
  525. batch_norm_param {
  526. use_global_stats: true
  527. }
  528. }
  529. layer {
  530. bottom: "res3a_branch2b"
  531. top: "res3a_branch2b"
  532. name: "scale3a_branch2b"
  533. type: "Scale"
  534. scale_param {
  535. bias_term: true
  536. }
  537. }
  538. layer {
  539. bottom: "res3a_branch2b"
  540. top: "res3a_branch2b"
  541. name: "res3a_branch2b_relu"
  542. type: "ReLU"
  543. }
  544. layer {
  545. bottom: "res3a_branch2b"
  546. top: "res3a_branch2c"
  547. name: "res3a_branch2c"
  548. type: "Convolution"
  549. convolution_param {
  550. num_output: 512
  551. kernel_size: 1
  552. pad: 0
  553. stride: 1
  554. bias_term: false
  555. }
  556. }
  557. layer {
  558. bottom: "res3a_branch2c"
  559. top: "res3a_branch2c"
  560. name: "bn3a_branch2c"
  561. type: "BatchNorm"
  562. batch_norm_param {
  563. use_global_stats: true
  564. }
  565. }
  566. layer {
  567. bottom: "res3a_branch2c"
  568. top: "res3a_branch2c"
  569. name: "scale3a_branch2c"
  570. type: "Scale"
  571. scale_param {
  572. bias_term: true
  573. }
  574. }
  575. layer {
  576. bottom: "res3a_branch1"
  577. bottom: "res3a_branch2c"
  578. top: "res3a"
  579. name: "res3a"
  580. type: "Eltwise"
  581. }
  582. layer {
  583. bottom: "res3a"
  584. top: "res3a"
  585. name: "res3a_relu"
  586. type: "ReLU"
  587. }
  588. layer {
  589. bottom: "res3a"
  590. top: "res3b_branch2a"
  591. name: "res3b_branch2a"
  592. type: "Convolution"
  593. convolution_param {
  594. num_output: 128
  595. kernel_size: 1
  596. pad: 0
  597. stride: 1
  598. bias_term: false
  599. }
  600. }
  601. layer {
  602. bottom: "res3b_branch2a"
  603. top: "res3b_branch2a"
  604. name: "bn3b_branch2a"
  605. type: "BatchNorm"
  606. batch_norm_param {
  607. use_global_stats: true
  608. }
  609. }
  610. layer {
  611. bottom: "res3b_branch2a"
  612. top: "res3b_branch2a"
  613. name: "scale3b_branch2a"
  614. type: "Scale"
  615. scale_param {
  616. bias_term: true
  617. }
  618. }
  619. layer {
  620. bottom: "res3b_branch2a"
  621. top: "res3b_branch2a"
  622. name: "res3b_branch2a_relu"
  623. type: "ReLU"
  624. }
  625. layer {
  626. bottom: "res3b_branch2a"
  627. top: "res3b_branch2b"
  628. name: "res3b_branch2b"
  629. type: "Convolution"
  630. convolution_param {
  631. num_output: 128
  632. kernel_size: 3
  633. pad: 1
  634. stride: 1
  635. bias_term: false
  636. }
  637. }
  638. layer {
  639. bottom: "res3b_branch2b"
  640. top: "res3b_branch2b"
  641. name: "bn3b_branch2b"
  642. type: "BatchNorm"
  643. batch_norm_param {
  644. use_global_stats: true
  645. }
  646. }
  647. layer {
  648. bottom: "res3b_branch2b"
  649. top: "res3b_branch2b"
  650. name: "scale3b_branch2b"
  651. type: "Scale"
  652. scale_param {
  653. bias_term: true
  654. }
  655. }
  656. layer {
  657. bottom: "res3b_branch2b"
  658. top: "res3b_branch2b"
  659. name: "res3b_branch2b_relu"
  660. type: "ReLU"
  661. }
  662. layer {
  663. bottom: "res3b_branch2b"
  664. top: "res3b_branch2c"
  665. name: "res3b_branch2c"
  666. type: "Convolution"
  667. convolution_param {
  668. num_output: 512
  669. kernel_size: 1
  670. pad: 0
  671. stride: 1
  672. bias_term: false
  673. }
  674. }
  675. layer {
  676. bottom: "res3b_branch2c"
  677. top: "res3b_branch2c"
  678. name: "bn3b_branch2c"
  679. type: "BatchNorm"
  680. batch_norm_param {
  681. use_global_stats: true
  682. }
  683. }
  684. layer {
  685. bottom: "res3b_branch2c"
  686. top: "res3b_branch2c"
  687. name: "scale3b_branch2c"
  688. type: "Scale"
  689. scale_param {
  690. bias_term: true
  691. }
  692. }
  693. layer {
  694. bottom: "res3a"
  695. bottom: "res3b_branch2c"
  696. top: "res3b"
  697. name: "res3b"
  698. type: "Eltwise"
  699. }
  700. layer {
  701. bottom: "res3b"
  702. top: "res3b"
  703. name: "res3b_relu"
  704. type: "ReLU"
  705. }
  706. layer {
  707. bottom: "res3b"
  708. top: "res3c_branch2a"
  709. name: "res3c_branch2a"
  710. type: "Convolution"
  711. convolution_param {
  712. num_output: 128
  713. kernel_size: 1
  714. pad: 0
  715. stride: 1
  716. bias_term: false
  717. }
  718. }
  719. layer {
  720. bottom: "res3c_branch2a"
  721. top: "res3c_branch2a"
  722. name: "bn3c_branch2a"
  723. type: "BatchNorm"
  724. batch_norm_param {
  725. use_global_stats: true
  726. }
  727. }
  728. layer {
  729. bottom: "res3c_branch2a"
  730. top: "res3c_branch2a"
  731. name: "scale3c_branch2a"
  732. type: "Scale"
  733. scale_param {
  734. bias_term: true
  735. }
  736. }
  737. layer {
  738. bottom: "res3c_branch2a"
  739. top: "res3c_branch2a"
  740. name: "res3c_branch2a_relu"
  741. type: "ReLU"
  742. }
  743. layer {
  744. bottom: "res3c_branch2a"
  745. top: "res3c_branch2b"
  746. name: "res3c_branch2b"
  747. type: "Convolution"
  748. convolution_param {
  749. num_output: 128
  750. kernel_size: 3
  751. pad: 1
  752. stride: 1
  753. bias_term: false
  754. }
  755. }
  756. layer {
  757. bottom: "res3c_branch2b"
  758. top: "res3c_branch2b"
  759. name: "bn3c_branch2b"
  760. type: "BatchNorm"
  761. batch_norm_param {
  762. use_global_stats: true
  763. }
  764. }
  765. layer {
  766. bottom: "res3c_branch2b"
  767. top: "res3c_branch2b"
  768. name: "scale3c_branch2b"
  769. type: "Scale"
  770. scale_param {
  771. bias_term: true
  772. }
  773. }
  774. layer {
  775. bottom: "res3c_branch2b"
  776. top: "res3c_branch2b"
  777. name: "res3c_branch2b_relu"
  778. type: "ReLU"
  779. }
  780. layer {
  781. bottom: "res3c_branch2b"
  782. top: "res3c_branch2c"
  783. name: "res3c_branch2c"
  784. type: "Convolution"
  785. convolution_param {
  786. num_output: 512
  787. kernel_size: 1
  788. pad: 0
  789. stride: 1
  790. bias_term: false
  791. }
  792. }
  793. layer {
  794. bottom: "res3c_branch2c"
  795. top: "res3c_branch2c"
  796. name: "bn3c_branch2c"
  797. type: "BatchNorm"
  798. batch_norm_param {
  799. use_global_stats: true
  800. }
  801. }
  802. layer {
  803. bottom: "res3c_branch2c"
  804. top: "res3c_branch2c"
  805. name: "scale3c_branch2c"
  806. type: "Scale"
  807. scale_param {
  808. bias_term: true
  809. }
  810. }
  811. layer {
  812. bottom: "res3b"
  813. bottom: "res3c_branch2c"
  814. top: "res3c"
  815. name: "res3c"
  816. type: "Eltwise"
  817. }
  818. layer {
  819. bottom: "res3c"
  820. top: "res3c"
  821. name: "res3c_relu"
  822. type: "ReLU"
  823. }
  824. layer {
  825. bottom: "res3c"
  826. top: "res3d_branch2a"
  827. name: "res3d_branch2a"
  828. type: "Convolution"
  829. convolution_param {
  830. num_output: 128
  831. kernel_size: 1
  832. pad: 0
  833. stride: 1
  834. bias_term: false
  835. }
  836. }
  837. layer {
  838. bottom: "res3d_branch2a"
  839. top: "res3d_branch2a"
  840. name: "bn3d_branch2a"
  841. type: "BatchNorm"
  842. batch_norm_param {
  843. use_global_stats: true
  844. }
  845. }
  846. layer {
  847. bottom: "res3d_branch2a"
  848. top: "res3d_branch2a"
  849. name: "scale3d_branch2a"
  850. type: "Scale"
  851. scale_param {
  852. bias_term: true
  853. }
  854. }
  855. layer {
  856. bottom: "res3d_branch2a"
  857. top: "res3d_branch2a"
  858. name: "res3d_branch2a_relu"
  859. type: "ReLU"
  860. }
  861. layer {
  862. bottom: "res3d_branch2a"
  863. top: "res3d_branch2b"
  864. name: "res3d_branch2b"
  865. type: "Convolution"
  866. convolution_param {
  867. num_output: 128
  868. kernel_size: 3
  869. pad: 1
  870. stride: 1
  871. bias_term: false
  872. }
  873. }
  874. layer {
  875. bottom: "res3d_branch2b"
  876. top: "res3d_branch2b"
  877. name: "bn3d_branch2b"
  878. type: "BatchNorm"
  879. batch_norm_param {
  880. use_global_stats: true
  881. }
  882. }
  883. layer {
  884. bottom: "res3d_branch2b"
  885. top: "res3d_branch2b"
  886. name: "scale3d_branch2b"
  887. type: "Scale"
  888. scale_param {
  889. bias_term: true
  890. }
  891. }
  892. layer {
  893. bottom: "res3d_branch2b"
  894. top: "res3d_branch2b"
  895. name: "res3d_branch2b_relu"
  896. type: "ReLU"
  897. }
  898. layer {
  899. bottom: "res3d_branch2b"
  900. top: "res3d_branch2c"
  901. name: "res3d_branch2c"
  902. type: "Convolution"
  903. convolution_param {
  904. num_output: 512
  905. kernel_size: 1
  906. pad: 0
  907. stride: 1
  908. bias_term: false
  909. }
  910. }
  911. layer {
  912. bottom: "res3d_branch2c"
  913. top: "res3d_branch2c"
  914. name: "bn3d_branch2c"
  915. type: "BatchNorm"
  916. batch_norm_param {
  917. use_global_stats: true
  918. }
  919. }
  920. layer {
  921. bottom: "res3d_branch2c"
  922. top: "res3d_branch2c"
  923. name: "scale3d_branch2c"
  924. type: "Scale"
  925. scale_param {
  926. bias_term: true
  927. }
  928. }
  929. layer {
  930. bottom: "res3c"
  931. bottom: "res3d_branch2c"
  932. top: "res3d"
  933. name: "res3d"
  934. type: "Eltwise"
  935. }
  936. layer {
  937. bottom: "res3d"
  938. top: "res3d"
  939. name: "res3d_relu"
  940. type: "ReLU"
  941. }
  942. layer {
  943. bottom: "res3d"
  944. top: "res4a_branch1"
  945. name: "res4a_branch1"
  946. type: "Convolution"
  947. convolution_param {
  948. num_output: 1024
  949. kernel_size: 1
  950. pad: 0
  951. stride: 2
  952. bias_term: false
  953. }
  954. }
  955. layer {
  956. bottom: "res4a_branch1"
  957. top: "res4a_branch1"
  958. name: "bn4a_branch1"
  959. type: "BatchNorm"
  960. batch_norm_param {
  961. use_global_stats: true
  962. }
  963. }
  964. layer {
  965. bottom: "res4a_branch1"
  966. top: "res4a_branch1"
  967. name: "scale4a_branch1"
  968. type: "Scale"
  969. scale_param {
  970. bias_term: true
  971. }
  972. }
  973. layer {
  974. bottom: "res3d"
  975. top: "res4a_branch2a"
  976. name: "res4a_branch2a"
  977. type: "Convolution"
  978. convolution_param {
  979. num_output: 256
  980. kernel_size: 1
  981. pad: 0
  982. stride: 2
  983. bias_term: false
  984. }
  985. }
  986. layer {
  987. bottom: "res4a_branch2a"
  988. top: "res4a_branch2a"
  989. name: "bn4a_branch2a"
  990. type: "BatchNorm"
  991. batch_norm_param {
  992. use_global_stats: true
  993. }
  994. }
  995. layer {
  996. bottom: "res4a_branch2a"
  997. top: "res4a_branch2a"
  998. name: "scale4a_branch2a"
  999. type: "Scale"
  1000. scale_param {
  1001. bias_term: true
  1002. }
  1003. }
  1004. layer {
  1005. bottom: "res4a_branch2a"
  1006. top: "res4a_branch2a"
  1007. name: "res4a_branch2a_relu"
  1008. type: "ReLU"
  1009. }
  1010. layer {
  1011. bottom: "res4a_branch2a"
  1012. top: "res4a_branch2b"
  1013. name: "res4a_branch2b"
  1014. type: "Convolution"
  1015. convolution_param {
  1016. num_output: 256
  1017. kernel_size: 3
  1018. pad: 1
  1019. stride: 1
  1020. bias_term: false
  1021. }
  1022. }
  1023. layer {
  1024. bottom: "res4a_branch2b"
  1025. top: "res4a_branch2b"
  1026. name: "bn4a_branch2b"
  1027. type: "BatchNorm"
  1028. batch_norm_param {
  1029. use_global_stats: true
  1030. }
  1031. }
  1032. layer {
  1033. bottom: "res4a_branch2b"
  1034. top: "res4a_branch2b"
  1035. name: "scale4a_branch2b"
  1036. type: "Scale"
  1037. scale_param {
  1038. bias_term: true
  1039. }
  1040. }
  1041. layer {
  1042. bottom: "res4a_branch2b"
  1043. top: "res4a_branch2b"
  1044. name: "res4a_branch2b_relu"
  1045. type: "ReLU"
  1046. }
  1047. layer {
  1048. bottom: "res4a_branch2b"
  1049. top: "res4a_branch2c"
  1050. name: "res4a_branch2c"
  1051. type: "Convolution"
  1052. convolution_param {
  1053. num_output: 1024
  1054. kernel_size: 1
  1055. pad: 0
  1056. stride: 1
  1057. bias_term: false
  1058. }
  1059. }
  1060. layer {
  1061. bottom: "res4a_branch2c"
  1062. top: "res4a_branch2c"
  1063. name: "bn4a_branch2c"
  1064. type: "BatchNorm"
  1065. batch_norm_param {
  1066. use_global_stats: true
  1067. }
  1068. }
  1069. layer {
  1070. bottom: "res4a_branch2c"
  1071. top: "res4a_branch2c"
  1072. name: "scale4a_branch2c"
  1073. type: "Scale"
  1074. scale_param {
  1075. bias_term: true
  1076. }
  1077. }
  1078. layer {
  1079. bottom: "res4a_branch1"
  1080. bottom: "res4a_branch2c"
  1081. top: "res4a"
  1082. name: "res4a"
  1083. type: "Eltwise"
  1084. }
  1085. layer {
  1086. bottom: "res4a"
  1087. top: "res4a"
  1088. name: "res4a_relu"
  1089. type: "ReLU"
  1090. }
  1091. layer {
  1092. bottom: "res4a"
  1093. top: "res4b_branch2a"
  1094. name: "res4b_branch2a"
  1095. type: "Convolution"
  1096. convolution_param {
  1097. num_output: 256
  1098. kernel_size: 1
  1099. pad: 0
  1100. stride: 1
  1101. bias_term: false
  1102. }
  1103. }
  1104. layer {
  1105. bottom: "res4b_branch2a"
  1106. top: "res4b_branch2a"
  1107. name: "bn4b_branch2a"
  1108. type: "BatchNorm"
  1109. batch_norm_param {
  1110. use_global_stats: true
  1111. }
  1112. }
  1113. layer {
  1114. bottom: "res4b_branch2a"
  1115. top: "res4b_branch2a"
  1116. name: "scale4b_branch2a"
  1117. type: "Scale"
  1118. scale_param {
  1119. bias_term: true
  1120. }
  1121. }
  1122. layer {
  1123. bottom: "res4b_branch2a"
  1124. top: "res4b_branch2a"
  1125. name: "res4b_branch2a_relu"
  1126. type: "ReLU"
  1127. }
  1128. layer {
  1129. bottom: "res4b_branch2a"
  1130. top: "res4b_branch2b"
  1131. name: "res4b_branch2b"
  1132. type: "Convolution"
  1133. convolution_param {
  1134. num_output: 256
  1135. kernel_size: 3
  1136. pad: 1
  1137. stride: 1
  1138. bias_term: false
  1139. }
  1140. }
  1141. layer {
  1142. bottom: "res4b_branch2b"
  1143. top: "res4b_branch2b"
  1144. name: "bn4b_branch2b"
  1145. type: "BatchNorm"
  1146. batch_norm_param {
  1147. use_global_stats: true
  1148. }
  1149. }
  1150. layer {
  1151. bottom: "res4b_branch2b"
  1152. top: "res4b_branch2b"
  1153. name: "scale4b_branch2b"
  1154. type: "Scale"
  1155. scale_param {
  1156. bias_term: true
  1157. }
  1158. }
  1159. layer {
  1160. bottom: "res4b_branch2b"
  1161. top: "res4b_branch2b"
  1162. name: "res4b_branch2b_relu"
  1163. type: "ReLU"
  1164. }
  1165. layer {
  1166. bottom: "res4b_branch2b"
  1167. top: "res4b_branch2c"
  1168. name: "res4b_branch2c"
  1169. type: "Convolution"
  1170. convolution_param {
  1171. num_output: 1024
  1172. kernel_size: 1
  1173. pad: 0
  1174. stride: 1
  1175. bias_term: false
  1176. }
  1177. }
  1178. layer {
  1179. bottom: "res4b_branch2c"
  1180. top: "res4b_branch2c"
  1181. name: "bn4b_branch2c"
  1182. type: "BatchNorm"
  1183. batch_norm_param {
  1184. use_global_stats: true
  1185. }
  1186. }
  1187. layer {
  1188. bottom: "res4b_branch2c"
  1189. top: "res4b_branch2c"
  1190. name: "scale4b_branch2c"
  1191. type: "Scale"
  1192. scale_param {
  1193. bias_term: true
  1194. }
  1195. }
  1196. layer {
  1197. bottom: "res4a"
  1198. bottom: "res4b_branch2c"
  1199. top: "res4b"
  1200. name: "res4b"
  1201. type: "Eltwise"
  1202. }
  1203. layer {
  1204. bottom: "res4b"
  1205. top: "res4b"
  1206. name: "res4b_relu"
  1207. type: "ReLU"
  1208. }
  1209. layer {
  1210. bottom: "res4b"
  1211. top: "res4c_branch2a"
  1212. name: "res4c_branch2a"
  1213. type: "Convolution"
  1214. convolution_param {
  1215. num_output: 256
  1216. kernel_size: 1
  1217. pad: 0
  1218. stride: 1
  1219. bias_term: false
  1220. }
  1221. }
  1222. layer {
  1223. bottom: "res4c_branch2a"
  1224. top: "res4c_branch2a"
  1225. name: "bn4c_branch2a"
  1226. type: "BatchNorm"
  1227. batch_norm_param {
  1228. use_global_stats: true
  1229. }
  1230. }
  1231. layer {
  1232. bottom: "res4c_branch2a"
  1233. top: "res4c_branch2a"
  1234. name: "scale4c_branch2a"
  1235. type: "Scale"
  1236. scale_param {
  1237. bias_term: true
  1238. }
  1239. }
  1240. layer {
  1241. bottom: "res4c_branch2a"
  1242. top: "res4c_branch2a"
  1243. name: "res4c_branch2a_relu"
  1244. type: "ReLU"
  1245. }
  1246. layer {
  1247. bottom: "res4c_branch2a"
  1248. top: "res4c_branch2b"
  1249. name: "res4c_branch2b"
  1250. type: "Convolution"
  1251. convolution_param {
  1252. num_output: 256
  1253. kernel_size: 3
  1254. pad: 1
  1255. stride: 1
  1256. bias_term: false
  1257. }
  1258. }
  1259. layer {
  1260. bottom: "res4c_branch2b"
  1261. top: "res4c_branch2b"
  1262. name: "bn4c_branch2b"
  1263. type: "BatchNorm"
  1264. batch_norm_param {
  1265. use_global_stats: true
  1266. }
  1267. }
  1268. layer {
  1269. bottom: "res4c_branch2b"
  1270. top: "res4c_branch2b"
  1271. name: "scale4c_branch2b"
  1272. type: "Scale"
  1273. scale_param {
  1274. bias_term: true
  1275. }
  1276. }
  1277. layer {
  1278. bottom: "res4c_branch2b"
  1279. top: "res4c_branch2b"
  1280. name: "res4c_branch2b_relu"
  1281. type: "ReLU"
  1282. }
  1283. layer {
  1284. bottom: "res4c_branch2b"
  1285. top: "res4c_branch2c"
  1286. name: "res4c_branch2c"
  1287. type: "Convolution"
  1288. convolution_param {
  1289. num_output: 1024
  1290. kernel_size: 1
  1291. pad: 0
  1292. stride: 1
  1293. bias_term: false
  1294. }
  1295. }
  1296. layer {
  1297. bottom: "res4c_branch2c"
  1298. top: "res4c_branch2c"
  1299. name: "bn4c_branch2c"
  1300. type: "BatchNorm"
  1301. batch_norm_param {
  1302. use_global_stats: true
  1303. }
  1304. }
  1305. layer {
  1306. bottom: "res4c_branch2c"
  1307. top: "res4c_branch2c"
  1308. name: "scale4c_branch2c"
  1309. type: "Scale"
  1310. scale_param {
  1311. bias_term: true
  1312. }
  1313. }
  1314. layer {
  1315. bottom: "res4b"
  1316. bottom: "res4c_branch2c"
  1317. top: "res4c"
  1318. name: "res4c"
  1319. type: "Eltwise"
  1320. }
  1321. layer {
  1322. bottom: "res4c"
  1323. top: "res4c"
  1324. name: "res4c_relu"
  1325. type: "ReLU"
  1326. }
  1327. layer {
  1328. bottom: "res4c"
  1329. top: "res4d_branch2a"
  1330. name: "res4d_branch2a"
  1331. type: "Convolution"
  1332. convolution_param {
  1333. num_output: 256
  1334. kernel_size: 1
  1335. pad: 0
  1336. stride: 1
  1337. bias_term: false
  1338. }
  1339. }
  1340. layer {
  1341. bottom: "res4d_branch2a"
  1342. top: "res4d_branch2a"
  1343. name: "bn4d_branch2a"
  1344. type: "BatchNorm"
  1345. batch_norm_param {
  1346. use_global_stats: true
  1347. }
  1348. }
  1349. layer {
  1350. bottom: "res4d_branch2a"
  1351. top: "res4d_branch2a"
  1352. name: "scale4d_branch2a"
  1353. type: "Scale"
  1354. scale_param {
  1355. bias_term: true
  1356. }
  1357. }
  1358. layer {
  1359. bottom: "res4d_branch2a"
  1360. top: "res4d_branch2a"
  1361. name: "res4d_branch2a_relu"
  1362. type: "ReLU"
  1363. }
  1364. layer {
  1365. bottom: "res4d_branch2a"
  1366. top: "res4d_branch2b"
  1367. name: "res4d_branch2b"
  1368. type: "Convolution"
  1369. convolution_param {
  1370. num_output: 256
  1371. kernel_size: 3
  1372. pad: 1
  1373. stride: 1
  1374. bias_term: false
  1375. }
  1376. }
  1377. layer {
  1378. bottom: "res4d_branch2b"
  1379. top: "res4d_branch2b"
  1380. name: "bn4d_branch2b"
  1381. type: "BatchNorm"
  1382. batch_norm_param {
  1383. use_global_stats: true
  1384. }
  1385. }
  1386. layer {
  1387. bottom: "res4d_branch2b"
  1388. top: "res4d_branch2b"
  1389. name: "scale4d_branch2b"
  1390. type: "Scale"
  1391. scale_param {
  1392. bias_term: true
  1393. }
  1394. }
  1395. layer {
  1396. bottom: "res4d_branch2b"
  1397. top: "res4d_branch2b"
  1398. name: "res4d_branch2b_relu"
  1399. type: "ReLU"
  1400. }
  1401. layer {
  1402. bottom: "res4d_branch2b"
  1403. top: "res4d_branch2c"
  1404. name: "res4d_branch2c"
  1405. type: "Convolution"
  1406. convolution_param {
  1407. num_output: 1024
  1408. kernel_size: 1
  1409. pad: 0
  1410. stride: 1
  1411. bias_term: false
  1412. }
  1413. }
  1414. layer {
  1415. bottom: "res4d_branch2c"
  1416. top: "res4d_branch2c"
  1417. name: "bn4d_branch2c"
  1418. type: "BatchNorm"
  1419. batch_norm_param {
  1420. use_global_stats: true
  1421. }
  1422. }
  1423. layer {
  1424. bottom: "res4d_branch2c"
  1425. top: "res4d_branch2c"
  1426. name: "scale4d_branch2c"
  1427. type: "Scale"
  1428. scale_param {
  1429. bias_term: true
  1430. }
  1431. }
  1432. layer {
  1433. bottom: "res4c"
  1434. bottom: "res4d_branch2c"
  1435. top: "res4d"
  1436. name: "res4d"
  1437. type: "Eltwise"
  1438. }
  1439. layer {
  1440. bottom: "res4d"
  1441. top: "res4d"
  1442. name: "res4d_relu"
  1443. type: "ReLU"
  1444. }
  1445. layer {
  1446. bottom: "res4d"
  1447. top: "res4e_branch2a"
  1448. name: "res4e_branch2a"
  1449. type: "Convolution"
  1450. convolution_param {
  1451. num_output: 256
  1452. kernel_size: 1
  1453. pad: 0
  1454. stride: 1
  1455. bias_term: false
  1456. }
  1457. }
  1458. layer {
  1459. bottom: "res4e_branch2a"
  1460. top: "res4e_branch2a"
  1461. name: "bn4e_branch2a"
  1462. type: "BatchNorm"
  1463. batch_norm_param {
  1464. use_global_stats: true
  1465. }
  1466. }
  1467. layer {
  1468. bottom: "res4e_branch2a"
  1469. top: "res4e_branch2a"
  1470. name: "scale4e_branch2a"
  1471. type: "Scale"
  1472. scale_param {
  1473. bias_term: true
  1474. }
  1475. }
  1476. layer {
  1477. bottom: "res4e_branch2a"
  1478. top: "res4e_branch2a"
  1479. name: "res4e_branch2a_relu"
  1480. type: "ReLU"
  1481. }
  1482. layer {
  1483. bottom: "res4e_branch2a"
  1484. top: "res4e_branch2b"
  1485. name: "res4e_branch2b"
  1486. type: "Convolution"
  1487. convolution_param {
  1488. num_output: 256
  1489. kernel_size: 3
  1490. pad: 1
  1491. stride: 1
  1492. bias_term: false
  1493. }
  1494. }
  1495. layer {
  1496. bottom: "res4e_branch2b"
  1497. top: "res4e_branch2b"
  1498. name: "bn4e_branch2b"
  1499. type: "BatchNorm"
  1500. batch_norm_param {
  1501. use_global_stats: true
  1502. }
  1503. }
  1504. layer {
  1505. bottom: "res4e_branch2b"
  1506. top: "res4e_branch2b"
  1507. name: "scale4e_branch2b"
  1508. type: "Scale"
  1509. scale_param {
  1510. bias_term: true
  1511. }
  1512. }
  1513. layer {
  1514. bottom: "res4e_branch2b"
  1515. top: "res4e_branch2b"
  1516. name: "res4e_branch2b_relu"
  1517. type: "ReLU"
  1518. }
  1519. layer {
  1520. bottom: "res4e_branch2b"
  1521. top: "res4e_branch2c"
  1522. name: "res4e_branch2c"
  1523. type: "Convolution"
  1524. convolution_param {
  1525. num_output: 1024
  1526. kernel_size: 1
  1527. pad: 0
  1528. stride: 1
  1529. bias_term: false
  1530. }
  1531. }
  1532. layer {
  1533. bottom: "res4e_branch2c"
  1534. top: "res4e_branch2c"
  1535. name: "bn4e_branch2c"
  1536. type: "BatchNorm"
  1537. batch_norm_param {
  1538. use_global_stats: true
  1539. }
  1540. }
  1541. layer {
  1542. bottom: "res4e_branch2c"
  1543. top: "res4e_branch2c"
  1544. name: "scale4e_branch2c"
  1545. type: "Scale"
  1546. scale_param {
  1547. bias_term: true
  1548. }
  1549. }
  1550. layer {
  1551. bottom: "res4d"
  1552. bottom: "res4e_branch2c"
  1553. top: "res4e"
  1554. name: "res4e"
  1555. type: "Eltwise"
  1556. }
  1557. layer {
  1558. bottom: "res4e"
  1559. top: "res4e"
  1560. name: "res4e_relu"
  1561. type: "ReLU"
  1562. }
  1563. layer {
  1564. bottom: "res4e"
  1565. top: "res4f_branch2a"
  1566. name: "res4f_branch2a"
  1567. type: "Convolution"
  1568. convolution_param {
  1569. num_output: 256
  1570. kernel_size: 1
  1571. pad: 0
  1572. stride: 1
  1573. bias_term: false
  1574. }
  1575. }
  1576. layer {
  1577. bottom: "res4f_branch2a"
  1578. top: "res4f_branch2a"
  1579. name: "bn4f_branch2a"
  1580. type: "BatchNorm"
  1581. batch_norm_param {
  1582. use_global_stats: true
  1583. }
  1584. }
  1585. layer {
  1586. bottom: "res4f_branch2a"
  1587. top: "res4f_branch2a"
  1588. name: "scale4f_branch2a"
  1589. type: "Scale"
  1590. scale_param {
  1591. bias_term: true
  1592. }
  1593. }
  1594. layer {
  1595. bottom: "res4f_branch2a"
  1596. top: "res4f_branch2a"
  1597. name: "res4f_branch2a_relu"
  1598. type: "ReLU"
  1599. }
  1600. layer {
  1601. bottom: "res4f_branch2a"
  1602. top: "res4f_branch2b"
  1603. name: "res4f_branch2b"
  1604. type: "Convolution"
  1605. convolution_param {
  1606. num_output: 256
  1607. kernel_size: 3
  1608. pad: 1
  1609. stride: 1
  1610. bias_term: false
  1611. }
  1612. }
  1613. layer {
  1614. bottom: "res4f_branch2b"
  1615. top: "res4f_branch2b"
  1616. name: "bn4f_branch2b"
  1617. type: "BatchNorm"
  1618. batch_norm_param {
  1619. use_global_stats: true
  1620. }
  1621. }
  1622. layer {
  1623. bottom: "res4f_branch2b"
  1624. top: "res4f_branch2b"
  1625. name: "scale4f_branch2b"
  1626. type: "Scale"
  1627. scale_param {
  1628. bias_term: true
  1629. }
  1630. }
  1631. layer {
  1632. bottom: "res4f_branch2b"
  1633. top: "res4f_branch2b"
  1634. name: "res4f_branch2b_relu"
  1635. type: "ReLU"
  1636. }
  1637. layer {
  1638. bottom: "res4f_branch2b"
  1639. top: "res4f_branch2c"
  1640. name: "res4f_branch2c"
  1641. type: "Convolution"
  1642. convolution_param {
  1643. num_output: 1024
  1644. kernel_size: 1
  1645. pad: 0
  1646. stride: 1
  1647. bias_term: false
  1648. }
  1649. }
  1650. layer {
  1651. bottom: "res4f_branch2c"
  1652. top: "res4f_branch2c"
  1653. name: "bn4f_branch2c"
  1654. type: "BatchNorm"
  1655. batch_norm_param {
  1656. use_global_stats: true
  1657. }
  1658. }
  1659. layer {
  1660. bottom: "res4f_branch2c"
  1661. top: "res4f_branch2c"
  1662. name: "scale4f_branch2c"
  1663. type: "Scale"
  1664. scale_param {
  1665. bias_term: true
  1666. }
  1667. }
  1668. layer {
  1669. bottom: "res4e"
  1670. bottom: "res4f_branch2c"
  1671. top: "res4f"
  1672. name: "res4f"
  1673. type: "Eltwise"
  1674. }
  1675. layer {
  1676. bottom: "res4f"
  1677. top: "res4f"
  1678. name: "res4f_relu"
  1679. type: "ReLU"
  1680. }
  1681. layer {
  1682. bottom: "res4f"
  1683. top: "res5a_branch1"
  1684. name: "res5a_branch1"
  1685. type: "Convolution"
  1686. convolution_param {
  1687. num_output: 2048
  1688. kernel_size: 1
  1689. pad: 0
  1690. stride: 2
  1691. bias_term: false
  1692. }
  1693. }
  1694. layer {
  1695. bottom: "res5a_branch1"
  1696. top: "res5a_branch1"
  1697. name: "bn5a_branch1"
  1698. type: "BatchNorm"
  1699. batch_norm_param {
  1700. use_global_stats: true
  1701. }
  1702. }
  1703. layer {
  1704. bottom: "res5a_branch1"
  1705. top: "res5a_branch1"
  1706. name: "scale5a_branch1"
  1707. type: "Scale"
  1708. scale_param {
  1709. bias_term: true
  1710. }
  1711. }
  1712. layer {
  1713. bottom: "res4f"
  1714. top: "res5a_branch2a"
  1715. name: "res5a_branch2a"
  1716. type: "Convolution"
  1717. convolution_param {
  1718. num_output: 512
  1719. kernel_size: 1
  1720. pad: 0
  1721. stride: 2
  1722. bias_term: false
  1723. }
  1724. }
  1725. layer {
  1726. bottom: "res5a_branch2a"
  1727. top: "res5a_branch2a"
  1728. name: "bn5a_branch2a"
  1729. type: "BatchNorm"
  1730. batch_norm_param {
  1731. use_global_stats: true
  1732. }
  1733. }
  1734. layer {
  1735. bottom: "res5a_branch2a"
  1736. top: "res5a_branch2a"
  1737. name: "scale5a_branch2a"
  1738. type: "Scale"
  1739. scale_param {
  1740. bias_term: true
  1741. }
  1742. }
  1743. layer {
  1744. bottom: "res5a_branch2a"
  1745. top: "res5a_branch2a"
  1746. name: "res5a_branch2a_relu"
  1747. type: "ReLU"
  1748. }
  1749. layer {
  1750. bottom: "res5a_branch2a"
  1751. top: "res5a_branch2b"
  1752. name: "res5a_branch2b"
  1753. type: "Convolution"
  1754. convolution_param {
  1755. num_output: 512
  1756. kernel_size: 3
  1757. pad: 1
  1758. stride: 1
  1759. bias_term: false
  1760. }
  1761. }
  1762. layer {
  1763. bottom: "res5a_branch2b"
  1764. top: "res5a_branch2b"
  1765. name: "bn5a_branch2b"
  1766. type: "BatchNorm"
  1767. batch_norm_param {
  1768. use_global_stats: true
  1769. }
  1770. }
  1771. layer {
  1772. bottom: "res5a_branch2b"
  1773. top: "res5a_branch2b"
  1774. name: "scale5a_branch2b"
  1775. type: "Scale"
  1776. scale_param {
  1777. bias_term: true
  1778. }
  1779. }
  1780. layer {
  1781. bottom: "res5a_branch2b"
  1782. top: "res5a_branch2b"
  1783. name: "res5a_branch2b_relu"
  1784. type: "ReLU"
  1785. }
  1786. layer {
  1787. bottom: "res5a_branch2b"
  1788. top: "res5a_branch2c"
  1789. name: "res5a_branch2c"
  1790. type: "Convolution"
  1791. convolution_param {
  1792. num_output: 2048
  1793. kernel_size: 1
  1794. pad: 0
  1795. stride: 1
  1796. bias_term: false
  1797. }
  1798. }
  1799. layer {
  1800. bottom: "res5a_branch2c"
  1801. top: "res5a_branch2c"
  1802. name: "bn5a_branch2c"
  1803. type: "BatchNorm"
  1804. batch_norm_param {
  1805. use_global_stats: true
  1806. }
  1807. }
  1808. layer {
  1809. bottom: "res5a_branch2c"
  1810. top: "res5a_branch2c"
  1811. name: "scale5a_branch2c"
  1812. type: "Scale"
  1813. scale_param {
  1814. bias_term: true
  1815. }
  1816. }
  1817. layer {
  1818. bottom: "res5a_branch1"
  1819. bottom: "res5a_branch2c"
  1820. top: "res5a"
  1821. name: "res5a"
  1822. type: "Eltwise"
  1823. }
  1824. layer {
  1825. bottom: "res5a"
  1826. top: "res5a"
  1827. name: "res5a_relu"
  1828. type: "ReLU"
  1829. }
  1830. layer {
  1831. bottom: "res5a"
  1832. top: "res5b_branch2a"
  1833. name: "res5b_branch2a"
  1834. type: "Convolution"
  1835. convolution_param {
  1836. num_output: 512
  1837. kernel_size: 1
  1838. pad: 0
  1839. stride: 1
  1840. bias_term: false
  1841. }
  1842. }
  1843. layer {
  1844. bottom: "res5b_branch2a"
  1845. top: "res5b_branch2a"
  1846. name: "bn5b_branch2a"
  1847. type: "BatchNorm"
  1848. batch_norm_param {
  1849. use_global_stats: true
  1850. }
  1851. }
  1852. layer {
  1853. bottom: "res5b_branch2a"
  1854. top: "res5b_branch2a"
  1855. name: "scale5b_branch2a"
  1856. type: "Scale"
  1857. scale_param {
  1858. bias_term: true
  1859. }
  1860. }
  1861. layer {
  1862. bottom: "res5b_branch2a"
  1863. top: "res5b_branch2a"
  1864. name: "res5b_branch2a_relu"
  1865. type: "ReLU"
  1866. }
  1867. layer {
  1868. bottom: "res5b_branch2a"
  1869. top: "res5b_branch2b"
  1870. name: "res5b_branch2b"
  1871. type: "Convolution"
  1872. convolution_param {
  1873. num_output: 512
  1874. kernel_size: 3
  1875. pad: 1
  1876. stride: 1
  1877. bias_term: false
  1878. }
  1879. }
  1880. layer {
  1881. bottom: "res5b_branch2b"
  1882. top: "res5b_branch2b"
  1883. name: "bn5b_branch2b"
  1884. type: "BatchNorm"
  1885. batch_norm_param {
  1886. use_global_stats: true
  1887. }
  1888. }
  1889. layer {
  1890. bottom: "res5b_branch2b"
  1891. top: "res5b_branch2b"
  1892. name: "scale5b_branch2b"
  1893. type: "Scale"
  1894. scale_param {
  1895. bias_term: true
  1896. }
  1897. }
  1898. layer {
  1899. bottom: "res5b_branch2b"
  1900. top: "res5b_branch2b"
  1901. name: "res5b_branch2b_relu"
  1902. type: "ReLU"
  1903. }
  1904. layer {
  1905. bottom: "res5b_branch2b"
  1906. top: "res5b_branch2c"
  1907. name: "res5b_branch2c"
  1908. type: "Convolution"
  1909. convolution_param {
  1910. num_output: 2048
  1911. kernel_size: 1
  1912. pad: 0
  1913. stride: 1
  1914. bias_term: false
  1915. }
  1916. }
  1917. layer {
  1918. bottom: "res5b_branch2c"
  1919. top: "res5b_branch2c"
  1920. name: "bn5b_branch2c"
  1921. type: "BatchNorm"
  1922. batch_norm_param {
  1923. use_global_stats: true
  1924. }
  1925. }
  1926. layer {
  1927. bottom: "res5b_branch2c"
  1928. top: "res5b_branch2c"
  1929. name: "scale5b_branch2c"
  1930. type: "Scale"
  1931. scale_param {
  1932. bias_term: true
  1933. }
  1934. }
  1935. layer {
  1936. bottom: "res5a"
  1937. bottom: "res5b_branch2c"
  1938. top: "res5b"
  1939. name: "res5b"
  1940. type: "Eltwise"
  1941. }
  1942. layer {
  1943. bottom: "res5b"
  1944. top: "res5b"
  1945. name: "res5b_relu"
  1946. type: "ReLU"
  1947. }
  1948. layer {
  1949. bottom: "res5b"
  1950. top: "res5c_branch2a"
  1951. name: "res5c_branch2a"
  1952. type: "Convolution"
  1953. convolution_param {
  1954. num_output: 512
  1955. kernel_size: 1
  1956. pad: 0
  1957. stride: 1
  1958. bias_term: false
  1959. }
  1960. }
  1961. layer {
  1962. bottom: "res5c_branch2a"
  1963. top: "res5c_branch2a"
  1964. name: "bn5c_branch2a"
  1965. type: "BatchNorm"
  1966. batch_norm_param {
  1967. use_global_stats: true
  1968. }
  1969. }
  1970. layer {
  1971. bottom: "res5c_branch2a"
  1972. top: "res5c_branch2a"
  1973. name: "scale5c_branch2a"
  1974. type: "Scale"
  1975. scale_param {
  1976. bias_term: true
  1977. }
  1978. }
  1979. layer {
  1980. bottom: "res5c_branch2a"
  1981. top: "res5c_branch2a"
  1982. name: "res5c_branch2a_relu"
  1983. type: "ReLU"
  1984. }
  1985. layer {
  1986. bottom: "res5c_branch2a"
  1987. top: "res5c_branch2b"
  1988. name: "res5c_branch2b"
  1989. type: "Convolution"
  1990. convolution_param {
  1991. num_output: 512
  1992. kernel_size: 3
  1993. pad: 1
  1994. stride: 1
  1995. bias_term: false
  1996. }
  1997. }
  1998. layer {
  1999. bottom: "res5c_branch2b"
  2000. top: "res5c_branch2b"
  2001. name: "bn5c_branch2b"
  2002. type: "BatchNorm"
  2003. batch_norm_param {
  2004. use_global_stats: true
  2005. }
  2006. }
  2007. layer {
  2008. bottom: "res5c_branch2b"
  2009. top: "res5c_branch2b"
  2010. name: "scale5c_branch2b"
  2011. type: "Scale"
  2012. scale_param {
  2013. bias_term: true
  2014. }
  2015. }
  2016. layer {
  2017. bottom: "res5c_branch2b"
  2018. top: "res5c_branch2b"
  2019. name: "res5c_branch2b_relu"
  2020. type: "ReLU"
  2021. }
  2022. layer {
  2023. bottom: "res5c_branch2b"
  2024. top: "res5c_branch2c"
  2025. name: "res5c_branch2c"
  2026. type: "Convolution"
  2027. convolution_param {
  2028. num_output: 2048
  2029. kernel_size: 1
  2030. pad: 0
  2031. stride: 1
  2032. bias_term: false
  2033. }
  2034. }
  2035. layer {
  2036. bottom: "res5c_branch2c"
  2037. top: "res5c_branch2c"
  2038. name: "bn5c_branch2c"
  2039. type: "BatchNorm"
  2040. batch_norm_param {
  2041. use_global_stats: true
  2042. }
  2043. }
  2044. layer {
  2045. bottom: "res5c_branch2c"
  2046. top: "res5c_branch2c"
  2047. name: "scale5c_branch2c"
  2048. type: "Scale"
  2049. scale_param {
  2050. bias_term: true
  2051. }
  2052. }
  2053. layer {
  2054. bottom: "res5b"
  2055. bottom: "res5c_branch2c"
  2056. top: "res5c"
  2057. name: "res5c"
  2058. type: "Eltwise"
  2059. }
  2060. layer {
  2061. bottom: "res5c"
  2062. top: "res5c"
  2063. name: "res5c_relu"
  2064. type: "ReLU"
  2065. }
  2066. layer {
  2067. bottom: "res5c"
  2068. top: "pool5"
  2069. name: "pool5"
  2070. type: "Pooling"
  2071. pooling_param {
  2072. kernel_size: 7
  2073. stride: 1
  2074. pool: AVE
  2075. }
  2076. }
  2077. layer {
  2078. bottom: "pool5"
  2079. top: "fc1000"
  2080. name: "fc1000"
  2081. type: "InnerProduct"
  2082. inner_product_param {
  2083. num_output: 1000
  2084. }
  2085. }
  2086. layer {
  2087. bottom: "fc1000"
  2088. top: "prob"
  2089. name: "prob"
  2090. type: "Softmax"
  2091. }