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  1. name: "DetectNet"
  2. layer {
  3. name: "train_data"
  4. type: "Data"
  5. top: "data"
  6. include {
  7. phase: TRAIN
  8. }
  9. data_param {
  10. batch_size: 2
  11. backend: LMDB
  12. }
  13. }
  14. layer {
  15. name: "train_label"
  16. type: "Data"
  17. top: "label"
  18. include {
  19. phase: TRAIN
  20. }
  21. data_param {
  22. batch_size: 2
  23. backend: LMDB
  24. }
  25. }
  26. layer {
  27. name: "val_data"
  28. type: "Data"
  29. top: "data"
  30. include {
  31. phase: TEST
  32. stage: "val"
  33. }
  34. data_param {
  35. batch_size: 2
  36. backend: LMDB
  37. }
  38. }
  39. layer {
  40. name: "val_label"
  41. type: "Data"
  42. top: "label"
  43. include {
  44. phase: TEST
  45. stage: "val"
  46. }
  47. data_param {
  48. batch_size: 2
  49. backend: LMDB
  50. }
  51. }
  52. layer {
  53. name: "deploy_data"
  54. type: "Input"
  55. top: "data"
  56. include {
  57. phase: TEST
  58. not_stage: "val"
  59. }
  60. input_param {
  61. shape {
  62. dim: 1
  63. dim: 3
  64. dim: 1280
  65. dim: 1280
  66. }
  67. }
  68. }
  69. layer {
  70. name: "train_transform"
  71. type: "DetectNetTransformation"
  72. bottom: "data"
  73. bottom: "label"
  74. top: "transformed_data"
  75. top: "transformed_label"
  76. include {
  77. phase: TRAIN
  78. }
  79. transform_param {
  80. mean_value: 127.0
  81. }
  82. detectnet_groundtruth_param {
  83. stride: 16
  84. scale_cvg: 0.4
  85. gridbox_type: GRIDBOX_MIN
  86. min_cvg_len: 20
  87. coverage_type: RECTANGULAR
  88. image_size_x: 512
  89. image_size_y: 512
  90. obj_norm: true
  91. crop_bboxes: false
  92. }
  93. detectnet_augmentation_param {
  94. crop_prob: 1.0
  95. shift_x: 32
  96. shift_y: 32
  97. scale_prob: 0.4
  98. scale_min: 0.8
  99. scale_max: 1.2
  100. flip_prob: 0.5
  101. rotation_prob: 0.0
  102. max_rotate_degree: 5.0
  103. hue_rotation_prob: 0.8
  104. hue_rotation: 30.0
  105. desaturation_prob: 0.8
  106. desaturation_max: 0.8
  107. }
  108. }
  109. layer {
  110. name: "val_transform"
  111. type: "DetectNetTransformation"
  112. bottom: "data"
  113. bottom: "label"
  114. top: "transformed_data"
  115. top: "transformed_label"
  116. include {
  117. phase: TEST
  118. stage: "val"
  119. }
  120. transform_param {
  121. mean_value: 127.0
  122. }
  123. detectnet_groundtruth_param {
  124. stride: 16
  125. scale_cvg: 0.4
  126. gridbox_type: GRIDBOX_MIN
  127. min_cvg_len: 20
  128. coverage_type: RECTANGULAR
  129. image_size_x: 1280
  130. image_size_y: 1280
  131. obj_norm: true
  132. crop_bboxes: false
  133. }
  134. }
  135. layer {
  136. name: "deploy_transform"
  137. type: "Power"
  138. bottom: "data"
  139. top: "transformed_data"
  140. include {
  141. phase: TEST
  142. not_stage: "val"
  143. }
  144. power_param {
  145. shift: -127.0
  146. }
  147. }
  148. layer {
  149. name: "slice-label"
  150. type: "Slice"
  151. bottom: "transformed_label"
  152. top: "foreground-label"
  153. top: "bbox-label"
  154. top: "size-label"
  155. top: "obj-label"
  156. top: "coverage-label"
  157. include {
  158. phase: TRAIN
  159. }
  160. include {
  161. phase: TEST
  162. stage: "val"
  163. }
  164. slice_param {
  165. slice_dim: 1
  166. slice_point: 1
  167. slice_point: 5
  168. slice_point: 7
  169. slice_point: 8
  170. }
  171. }
  172. layer {
  173. name: "coverage-block"
  174. type: "Concat"
  175. bottom: "foreground-label"
  176. bottom: "foreground-label"
  177. bottom: "foreground-label"
  178. bottom: "foreground-label"
  179. top: "coverage-block"
  180. include {
  181. phase: TRAIN
  182. }
  183. include {
  184. phase: TEST
  185. stage: "val"
  186. }
  187. concat_param {
  188. concat_dim: 1
  189. }
  190. }
  191. layer {
  192. name: "size-block"
  193. type: "Concat"
  194. bottom: "size-label"
  195. bottom: "size-label"
  196. top: "size-block"
  197. include {
  198. phase: TRAIN
  199. }
  200. include {
  201. phase: TEST
  202. stage: "val"
  203. }
  204. concat_param {
  205. concat_dim: 1
  206. }
  207. }
  208. layer {
  209. name: "obj-block"
  210. type: "Concat"
  211. bottom: "obj-label"
  212. bottom: "obj-label"
  213. bottom: "obj-label"
  214. bottom: "obj-label"
  215. top: "obj-block"
  216. include {
  217. phase: TRAIN
  218. }
  219. include {
  220. phase: TEST
  221. stage: "val"
  222. }
  223. concat_param {
  224. concat_dim: 1
  225. }
  226. }
  227. layer {
  228. name: "bb-label-norm"
  229. type: "Eltwise"
  230. bottom: "bbox-label"
  231. bottom: "size-block"
  232. top: "bbox-label-norm"
  233. include {
  234. phase: TRAIN
  235. }
  236. include {
  237. phase: TEST
  238. stage: "val"
  239. }
  240. eltwise_param {
  241. operation: PROD
  242. }
  243. }
  244. layer {
  245. name: "bb-obj-norm"
  246. type: "Eltwise"
  247. bottom: "bbox-label-norm"
  248. bottom: "obj-block"
  249. top: "bbox-obj-label-norm"
  250. include {
  251. phase: TRAIN
  252. }
  253. include {
  254. phase: TEST
  255. stage: "val"
  256. }
  257. eltwise_param {
  258. operation: PROD
  259. }
  260. }
  261. layer {
  262. name: "conv1/7x7_s2"
  263. type: "Convolution"
  264. bottom: "transformed_data"
  265. top: "conv1/7x7_s2"
  266. param {
  267. lr_mult: 1.0
  268. decay_mult: 1.0
  269. }
  270. param {
  271. lr_mult: 2.0
  272. decay_mult: 0.0
  273. }
  274. convolution_param {
  275. num_output: 64
  276. pad: 3
  277. kernel_size: 7
  278. stride: 2
  279. weight_filler {
  280. type: "xavier"
  281. std: 0.1
  282. }
  283. bias_filler {
  284. type: "constant"
  285. value: 0.2
  286. }
  287. }
  288. }
  289. layer {
  290. name: "conv1/relu_7x7"
  291. type: "ReLU"
  292. bottom: "conv1/7x7_s2"
  293. top: "conv1/7x7_s2"
  294. }
  295. layer {
  296. name: "pool1/3x3_s2"
  297. type: "Pooling"
  298. bottom: "conv1/7x7_s2"
  299. top: "pool1/3x3_s2"
  300. pooling_param {
  301. pool: MAX
  302. kernel_size: 3
  303. stride: 2
  304. }
  305. }
  306. layer {
  307. name: "pool1/norm1"
  308. type: "LRN"
  309. bottom: "pool1/3x3_s2"
  310. top: "pool1/norm1"
  311. lrn_param {
  312. local_size: 5
  313. alpha: 0.0001
  314. beta: 0.75
  315. }
  316. }
  317. layer {
  318. name: "conv2/3x3_reduce"
  319. type: "Convolution"
  320. bottom: "pool1/norm1"
  321. top: "conv2/3x3_reduce"
  322. param {
  323. lr_mult: 1.0
  324. decay_mult: 1.0
  325. }
  326. param {
  327. lr_mult: 2.0
  328. decay_mult: 0.0
  329. }
  330. convolution_param {
  331. num_output: 64
  332. kernel_size: 1
  333. weight_filler {
  334. type: "xavier"
  335. std: 0.1
  336. }
  337. bias_filler {
  338. type: "constant"
  339. value: 0.2
  340. }
  341. }
  342. }
  343. layer {
  344. name: "conv2/relu_3x3_reduce"
  345. type: "ReLU"
  346. bottom: "conv2/3x3_reduce"
  347. top: "conv2/3x3_reduce"
  348. }
  349. layer {
  350. name: "conv2/3x3"
  351. type: "Convolution"
  352. bottom: "conv2/3x3_reduce"
  353. top: "conv2/3x3"
  354. param {
  355. lr_mult: 1.0
  356. decay_mult: 1.0
  357. }
  358. param {
  359. lr_mult: 2.0
  360. decay_mult: 0.0
  361. }
  362. convolution_param {
  363. num_output: 192
  364. pad: 1
  365. kernel_size: 3
  366. weight_filler {
  367. type: "xavier"
  368. std: 0.03
  369. }
  370. bias_filler {
  371. type: "constant"
  372. value: 0.2
  373. }
  374. }
  375. }
  376. layer {
  377. name: "conv2/relu_3x3"
  378. type: "ReLU"
  379. bottom: "conv2/3x3"
  380. top: "conv2/3x3"
  381. }
  382. layer {
  383. name: "conv2/norm2"
  384. type: "LRN"
  385. bottom: "conv2/3x3"
  386. top: "conv2/norm2"
  387. lrn_param {
  388. local_size: 5
  389. alpha: 0.0001
  390. beta: 0.75
  391. }
  392. }
  393. layer {
  394. name: "pool2/3x3_s2"
  395. type: "Pooling"
  396. bottom: "conv2/norm2"
  397. top: "pool2/3x3_s2"
  398. pooling_param {
  399. pool: MAX
  400. kernel_size: 3
  401. stride: 2
  402. }
  403. }
  404. layer {
  405. name: "inception_3a/1x1"
  406. type: "Convolution"
  407. bottom: "pool2/3x3_s2"
  408. top: "inception_3a/1x1"
  409. param {
  410. lr_mult: 1.0
  411. decay_mult: 1.0
  412. }
  413. param {
  414. lr_mult: 2.0
  415. decay_mult: 0.0
  416. }
  417. convolution_param {
  418. num_output: 64
  419. kernel_size: 1
  420. weight_filler {
  421. type: "xavier"
  422. std: 0.03
  423. }
  424. bias_filler {
  425. type: "constant"
  426. value: 0.2
  427. }
  428. }
  429. }
  430. layer {
  431. name: "inception_3a/relu_1x1"
  432. type: "ReLU"
  433. bottom: "inception_3a/1x1"
  434. top: "inception_3a/1x1"
  435. }
  436. layer {
  437. name: "inception_3a/3x3_reduce"
  438. type: "Convolution"
  439. bottom: "pool2/3x3_s2"
  440. top: "inception_3a/3x3_reduce"
  441. param {
  442. lr_mult: 1.0
  443. decay_mult: 1.0
  444. }
  445. param {
  446. lr_mult: 2.0
  447. decay_mult: 0.0
  448. }
  449. convolution_param {
  450. num_output: 96
  451. kernel_size: 1
  452. weight_filler {
  453. type: "xavier"
  454. std: 0.09
  455. }
  456. bias_filler {
  457. type: "constant"
  458. value: 0.2
  459. }
  460. }
  461. }
  462. layer {
  463. name: "inception_3a/relu_3x3_reduce"
  464. type: "ReLU"
  465. bottom: "inception_3a/3x3_reduce"
  466. top: "inception_3a/3x3_reduce"
  467. }
  468. layer {
  469. name: "inception_3a/3x3"
  470. type: "Convolution"
  471. bottom: "inception_3a/3x3_reduce"
  472. top: "inception_3a/3x3"
  473. param {
  474. lr_mult: 1.0
  475. decay_mult: 1.0
  476. }
  477. param {
  478. lr_mult: 2.0
  479. decay_mult: 0.0
  480. }
  481. convolution_param {
  482. num_output: 128
  483. pad: 1
  484. kernel_size: 3
  485. weight_filler {
  486. type: "xavier"
  487. std: 0.03
  488. }
  489. bias_filler {
  490. type: "constant"
  491. value: 0.2
  492. }
  493. }
  494. }
  495. layer {
  496. name: "inception_3a/relu_3x3"
  497. type: "ReLU"
  498. bottom: "inception_3a/3x3"
  499. top: "inception_3a/3x3"
  500. }
  501. layer {
  502. name: "inception_3a/5x5_reduce"
  503. type: "Convolution"
  504. bottom: "pool2/3x3_s2"
  505. top: "inception_3a/5x5_reduce"
  506. param {
  507. lr_mult: 1.0
  508. decay_mult: 1.0
  509. }
  510. param {
  511. lr_mult: 2.0
  512. decay_mult: 0.0
  513. }
  514. convolution_param {
  515. num_output: 16
  516. kernel_size: 1
  517. weight_filler {
  518. type: "xavier"
  519. std: 0.2
  520. }
  521. bias_filler {
  522. type: "constant"
  523. value: 0.2
  524. }
  525. }
  526. }
  527. layer {
  528. name: "inception_3a/relu_5x5_reduce"
  529. type: "ReLU"
  530. bottom: "inception_3a/5x5_reduce"
  531. top: "inception_3a/5x5_reduce"
  532. }
  533. layer {
  534. name: "inception_3a/5x5"
  535. type: "Convolution"
  536. bottom: "inception_3a/5x5_reduce"
  537. top: "inception_3a/5x5"
  538. param {
  539. lr_mult: 1.0
  540. decay_mult: 1.0
  541. }
  542. param {
  543. lr_mult: 2.0
  544. decay_mult: 0.0
  545. }
  546. convolution_param {
  547. num_output: 32
  548. pad: 2
  549. kernel_size: 5
  550. weight_filler {
  551. type: "xavier"
  552. std: 0.03
  553. }
  554. bias_filler {
  555. type: "constant"
  556. value: 0.2
  557. }
  558. }
  559. }
  560. layer {
  561. name: "inception_3a/relu_5x5"
  562. type: "ReLU"
  563. bottom: "inception_3a/5x5"
  564. top: "inception_3a/5x5"
  565. }
  566. layer {
  567. name: "inception_3a/pool"
  568. type: "Pooling"
  569. bottom: "pool2/3x3_s2"
  570. top: "inception_3a/pool"
  571. pooling_param {
  572. pool: MAX
  573. kernel_size: 3
  574. stride: 1
  575. pad: 1
  576. }
  577. }
  578. layer {
  579. name: "inception_3a/pool_proj"
  580. type: "Convolution"
  581. bottom: "inception_3a/pool"
  582. top: "inception_3a/pool_proj"
  583. param {
  584. lr_mult: 1.0
  585. decay_mult: 1.0
  586. }
  587. param {
  588. lr_mult: 2.0
  589. decay_mult: 0.0
  590. }
  591. convolution_param {
  592. num_output: 32
  593. kernel_size: 1
  594. weight_filler {
  595. type: "xavier"
  596. std: 0.1
  597. }
  598. bias_filler {
  599. type: "constant"
  600. value: 0.2
  601. }
  602. }
  603. }
  604. layer {
  605. name: "inception_3a/relu_pool_proj"
  606. type: "ReLU"
  607. bottom: "inception_3a/pool_proj"
  608. top: "inception_3a/pool_proj"
  609. }
  610. layer {
  611. name: "inception_3a/output"
  612. type: "Concat"
  613. bottom: "inception_3a/1x1"
  614. bottom: "inception_3a/3x3"
  615. bottom: "inception_3a/5x5"
  616. bottom: "inception_3a/pool_proj"
  617. top: "inception_3a/output"
  618. }
  619. layer {
  620. name: "inception_3b/1x1"
  621. type: "Convolution"
  622. bottom: "inception_3a/output"
  623. top: "inception_3b/1x1"
  624. param {
  625. lr_mult: 1.0
  626. decay_mult: 1.0
  627. }
  628. param {
  629. lr_mult: 2.0
  630. decay_mult: 0.0
  631. }
  632. convolution_param {
  633. num_output: 128
  634. kernel_size: 1
  635. weight_filler {
  636. type: "xavier"
  637. std: 0.03
  638. }
  639. bias_filler {
  640. type: "constant"
  641. value: 0.2
  642. }
  643. }
  644. }
  645. layer {
  646. name: "inception_3b/relu_1x1"
  647. type: "ReLU"
  648. bottom: "inception_3b/1x1"
  649. top: "inception_3b/1x1"
  650. }
  651. layer {
  652. name: "inception_3b/3x3_reduce"
  653. type: "Convolution"
  654. bottom: "inception_3a/output"
  655. top: "inception_3b/3x3_reduce"
  656. param {
  657. lr_mult: 1.0
  658. decay_mult: 1.0
  659. }
  660. param {
  661. lr_mult: 2.0
  662. decay_mult: 0.0
  663. }
  664. convolution_param {
  665. num_output: 128
  666. kernel_size: 1
  667. weight_filler {
  668. type: "xavier"
  669. std: 0.09
  670. }
  671. bias_filler {
  672. type: "constant"
  673. value: 0.2
  674. }
  675. }
  676. }
  677. layer {
  678. name: "inception_3b/relu_3x3_reduce"
  679. type: "ReLU"
  680. bottom: "inception_3b/3x3_reduce"
  681. top: "inception_3b/3x3_reduce"
  682. }
  683. layer {
  684. name: "inception_3b/3x3"
  685. type: "Convolution"
  686. bottom: "inception_3b/3x3_reduce"
  687. top: "inception_3b/3x3"
  688. param {
  689. lr_mult: 1.0
  690. decay_mult: 1.0
  691. }
  692. param {
  693. lr_mult: 2.0
  694. decay_mult: 0.0
  695. }
  696. convolution_param {
  697. num_output: 192
  698. pad: 1
  699. kernel_size: 3
  700. weight_filler {
  701. type: "xavier"
  702. std: 0.03
  703. }
  704. bias_filler {
  705. type: "constant"
  706. value: 0.2
  707. }
  708. }
  709. }
  710. layer {
  711. name: "inception_3b/relu_3x3"
  712. type: "ReLU"
  713. bottom: "inception_3b/3x3"
  714. top: "inception_3b/3x3"
  715. }
  716. layer {
  717. name: "inception_3b/5x5_reduce"
  718. type: "Convolution"
  719. bottom: "inception_3a/output"
  720. top: "inception_3b/5x5_reduce"
  721. param {
  722. lr_mult: 1.0
  723. decay_mult: 1.0
  724. }
  725. param {
  726. lr_mult: 2.0
  727. decay_mult: 0.0
  728. }
  729. convolution_param {
  730. num_output: 32
  731. kernel_size: 1
  732. weight_filler {
  733. type: "xavier"
  734. std: 0.2
  735. }
  736. bias_filler {
  737. type: "constant"
  738. value: 0.2
  739. }
  740. }
  741. }
  742. layer {
  743. name: "inception_3b/relu_5x5_reduce"
  744. type: "ReLU"
  745. bottom: "inception_3b/5x5_reduce"
  746. top: "inception_3b/5x5_reduce"
  747. }
  748. layer {
  749. name: "inception_3b/5x5"
  750. type: "Convolution"
  751. bottom: "inception_3b/5x5_reduce"
  752. top: "inception_3b/5x5"
  753. param {
  754. lr_mult: 1.0
  755. decay_mult: 1.0
  756. }
  757. param {
  758. lr_mult: 2.0
  759. decay_mult: 0.0
  760. }
  761. convolution_param {
  762. num_output: 96
  763. pad: 2
  764. kernel_size: 5
  765. weight_filler {
  766. type: "xavier"
  767. std: 0.03
  768. }
  769. bias_filler {
  770. type: "constant"
  771. value: 0.2
  772. }
  773. }
  774. }
  775. layer {
  776. name: "inception_3b/relu_5x5"
  777. type: "ReLU"
  778. bottom: "inception_3b/5x5"
  779. top: "inception_3b/5x5"
  780. }
  781. layer {
  782. name: "inception_3b/pool"
  783. type: "Pooling"
  784. bottom: "inception_3a/output"
  785. top: "inception_3b/pool"
  786. pooling_param {
  787. pool: MAX
  788. kernel_size: 3
  789. stride: 1
  790. pad: 1
  791. }
  792. }
  793. layer {
  794. name: "inception_3b/pool_proj"
  795. type: "Convolution"
  796. bottom: "inception_3b/pool"
  797. top: "inception_3b/pool_proj"
  798. param {
  799. lr_mult: 1.0
  800. decay_mult: 1.0
  801. }
  802. param {
  803. lr_mult: 2.0
  804. decay_mult: 0.0
  805. }
  806. convolution_param {
  807. num_output: 64
  808. kernel_size: 1
  809. weight_filler {
  810. type: "xavier"
  811. std: 0.1
  812. }
  813. bias_filler {
  814. type: "constant"
  815. value: 0.2
  816. }
  817. }
  818. }
  819. layer {
  820. name: "inception_3b/relu_pool_proj"
  821. type: "ReLU"
  822. bottom: "inception_3b/pool_proj"
  823. top: "inception_3b/pool_proj"
  824. }
  825. layer {
  826. name: "inception_3b/output"
  827. type: "Concat"
  828. bottom: "inception_3b/1x1"
  829. bottom: "inception_3b/3x3"
  830. bottom: "inception_3b/5x5"
  831. bottom: "inception_3b/pool_proj"
  832. top: "inception_3b/output"
  833. }
  834. layer {
  835. name: "pool3/3x3_s2"
  836. type: "Pooling"
  837. bottom: "inception_3b/output"
  838. top: "pool3/3x3_s2"
  839. pooling_param {
  840. pool: MAX
  841. kernel_size: 3
  842. stride: 2
  843. }
  844. }
  845. layer {
  846. name: "inception_4a/1x1"
  847. type: "Convolution"
  848. bottom: "pool3/3x3_s2"
  849. top: "inception_4a/1x1"
  850. param {
  851. lr_mult: 1.0
  852. decay_mult: 1.0
  853. }
  854. param {
  855. lr_mult: 2.0
  856. decay_mult: 0.0
  857. }
  858. convolution_param {
  859. num_output: 192
  860. kernel_size: 1
  861. weight_filler {
  862. type: "xavier"
  863. std: 0.03
  864. }
  865. bias_filler {
  866. type: "constant"
  867. value: 0.2
  868. }
  869. }
  870. }
  871. layer {
  872. name: "inception_4a/relu_1x1"
  873. type: "ReLU"
  874. bottom: "inception_4a/1x1"
  875. top: "inception_4a/1x1"
  876. }
  877. layer {
  878. name: "inception_4a/3x3_reduce"
  879. type: "Convolution"
  880. bottom: "pool3/3x3_s2"
  881. top: "inception_4a/3x3_reduce"
  882. param {
  883. lr_mult: 1.0
  884. decay_mult: 1.0
  885. }
  886. param {
  887. lr_mult: 2.0
  888. decay_mult: 0.0
  889. }
  890. convolution_param {
  891. num_output: 96
  892. kernel_size: 1
  893. weight_filler {
  894. type: "xavier"
  895. std: 0.09
  896. }
  897. bias_filler {
  898. type: "constant"
  899. value: 0.2
  900. }
  901. }
  902. }
  903. layer {
  904. name: "inception_4a/relu_3x3_reduce"
  905. type: "ReLU"
  906. bottom: "inception_4a/3x3_reduce"
  907. top: "inception_4a/3x3_reduce"
  908. }
  909. layer {
  910. name: "inception_4a/3x3"
  911. type: "Convolution"
  912. bottom: "inception_4a/3x3_reduce"
  913. top: "inception_4a/3x3"
  914. param {
  915. lr_mult: 1.0
  916. decay_mult: 1.0
  917. }
  918. param {
  919. lr_mult: 2.0
  920. decay_mult: 0.0
  921. }
  922. convolution_param {
  923. num_output: 208
  924. pad: 1
  925. kernel_size: 3
  926. weight_filler {
  927. type: "xavier"
  928. std: 0.03
  929. }
  930. bias_filler {
  931. type: "constant"
  932. value: 0.2
  933. }
  934. }
  935. }
  936. layer {
  937. name: "inception_4a/relu_3x3"
  938. type: "ReLU"
  939. bottom: "inception_4a/3x3"
  940. top: "inception_4a/3x3"
  941. }
  942. layer {
  943. name: "inception_4a/5x5_reduce"
  944. type: "Convolution"
  945. bottom: "pool3/3x3_s2"
  946. top: "inception_4a/5x5_reduce"
  947. param {
  948. lr_mult: 1.0
  949. decay_mult: 1.0
  950. }
  951. param {
  952. lr_mult: 2.0
  953. decay_mult: 0.0
  954. }
  955. convolution_param {
  956. num_output: 16
  957. kernel_size: 1
  958. weight_filler {
  959. type: "xavier"
  960. std: 0.2
  961. }
  962. bias_filler {
  963. type: "constant"
  964. value: 0.2
  965. }
  966. }
  967. }
  968. layer {
  969. name: "inception_4a/relu_5x5_reduce"
  970. type: "ReLU"
  971. bottom: "inception_4a/5x5_reduce"
  972. top: "inception_4a/5x5_reduce"
  973. }
  974. layer {
  975. name: "inception_4a/5x5"
  976. type: "Convolution"
  977. bottom: "inception_4a/5x5_reduce"
  978. top: "inception_4a/5x5"
  979. param {
  980. lr_mult: 1.0
  981. decay_mult: 1.0
  982. }
  983. param {
  984. lr_mult: 2.0
  985. decay_mult: 0.0
  986. }
  987. convolution_param {
  988. num_output: 48
  989. pad: 2
  990. kernel_size: 5
  991. weight_filler {
  992. type: "xavier"
  993. std: 0.03
  994. }
  995. bias_filler {
  996. type: "constant"
  997. value: 0.2
  998. }
  999. }
  1000. }
  1001. layer {
  1002. name: "inception_4a/relu_5x5"
  1003. type: "ReLU"
  1004. bottom: "inception_4a/5x5"
  1005. top: "inception_4a/5x5"
  1006. }
  1007. layer {
  1008. name: "inception_4a/pool"
  1009. type: "Pooling"
  1010. bottom: "pool3/3x3_s2"
  1011. top: "inception_4a/pool"
  1012. pooling_param {
  1013. pool: MAX
  1014. kernel_size: 3
  1015. stride: 1
  1016. pad: 1
  1017. }
  1018. }
  1019. layer {
  1020. name: "inception_4a/pool_proj"
  1021. type: "Convolution"
  1022. bottom: "inception_4a/pool"
  1023. top: "inception_4a/pool_proj"
  1024. param {
  1025. lr_mult: 1.0
  1026. decay_mult: 1.0
  1027. }
  1028. param {
  1029. lr_mult: 2.0
  1030. decay_mult: 0.0
  1031. }
  1032. convolution_param {
  1033. num_output: 64
  1034. kernel_size: 1
  1035. weight_filler {
  1036. type: "xavier"
  1037. std: 0.1
  1038. }
  1039. bias_filler {
  1040. type: "constant"
  1041. value: 0.2
  1042. }
  1043. }
  1044. }
  1045. layer {
  1046. name: "inception_4a/relu_pool_proj"
  1047. type: "ReLU"
  1048. bottom: "inception_4a/pool_proj"
  1049. top: "inception_4a/pool_proj"
  1050. }
  1051. layer {
  1052. name: "inception_4a/output"
  1053. type: "Concat"
  1054. bottom: "inception_4a/1x1"
  1055. bottom: "inception_4a/3x3"
  1056. bottom: "inception_4a/5x5"
  1057. bottom: "inception_4a/pool_proj"
  1058. top: "inception_4a/output"
  1059. }
  1060. layer {
  1061. name: "inception_4b/1x1"
  1062. type: "Convolution"
  1063. bottom: "inception_4a/output"
  1064. top: "inception_4b/1x1"
  1065. param {
  1066. lr_mult: 1.0
  1067. decay_mult: 1.0
  1068. }
  1069. param {
  1070. lr_mult: 2.0
  1071. decay_mult: 0.0
  1072. }
  1073. convolution_param {
  1074. num_output: 160
  1075. kernel_size: 1
  1076. weight_filler {
  1077. type: "xavier"
  1078. std: 0.03
  1079. }
  1080. bias_filler {
  1081. type: "constant"
  1082. value: 0.2
  1083. }
  1084. }
  1085. }
  1086. layer {
  1087. name: "inception_4b/relu_1x1"
  1088. type: "ReLU"
  1089. bottom: "inception_4b/1x1"
  1090. top: "inception_4b/1x1"
  1091. }
  1092. layer {
  1093. name: "inception_4b/3x3_reduce"
  1094. type: "Convolution"
  1095. bottom: "inception_4a/output"
  1096. top: "inception_4b/3x3_reduce"
  1097. param {
  1098. lr_mult: 1.0
  1099. decay_mult: 1.0
  1100. }
  1101. param {
  1102. lr_mult: 2.0
  1103. decay_mult: 0.0
  1104. }
  1105. convolution_param {
  1106. num_output: 112
  1107. kernel_size: 1
  1108. weight_filler {
  1109. type: "xavier"
  1110. std: 0.09
  1111. }
  1112. bias_filler {
  1113. type: "constant"
  1114. value: 0.2
  1115. }
  1116. }
  1117. }
  1118. layer {
  1119. name: "inception_4b/relu_3x3_reduce"
  1120. type: "ReLU"
  1121. bottom: "inception_4b/3x3_reduce"
  1122. top: "inception_4b/3x3_reduce"
  1123. }
  1124. layer {
  1125. name: "inception_4b/3x3"
  1126. type: "Convolution"
  1127. bottom: "inception_4b/3x3_reduce"
  1128. top: "inception_4b/3x3"
  1129. param {
  1130. lr_mult: 1.0
  1131. decay_mult: 1.0
  1132. }
  1133. param {
  1134. lr_mult: 2.0
  1135. decay_mult: 0.0
  1136. }
  1137. convolution_param {
  1138. num_output: 224
  1139. pad: 1
  1140. kernel_size: 3
  1141. weight_filler {
  1142. type: "xavier"
  1143. std: 0.03
  1144. }
  1145. bias_filler {
  1146. type: "constant"
  1147. value: 0.2
  1148. }
  1149. }
  1150. }
  1151. layer {
  1152. name: "inception_4b/relu_3x3"
  1153. type: "ReLU"
  1154. bottom: "inception_4b/3x3"
  1155. top: "inception_4b/3x3"
  1156. }
  1157. layer {
  1158. name: "inception_4b/5x5_reduce"
  1159. type: "Convolution"
  1160. bottom: "inception_4a/output"
  1161. top: "inception_4b/5x5_reduce"
  1162. param {
  1163. lr_mult: 1.0
  1164. decay_mult: 1.0
  1165. }
  1166. param {
  1167. lr_mult: 2.0
  1168. decay_mult: 0.0
  1169. }
  1170. convolution_param {
  1171. num_output: 24
  1172. kernel_size: 1
  1173. weight_filler {
  1174. type: "xavier"
  1175. std: 0.2
  1176. }
  1177. bias_filler {
  1178. type: "constant"
  1179. value: 0.2
  1180. }
  1181. }
  1182. }
  1183. layer {
  1184. name: "inception_4b/relu_5x5_reduce"
  1185. type: "ReLU"
  1186. bottom: "inception_4b/5x5_reduce"
  1187. top: "inception_4b/5x5_reduce"
  1188. }
  1189. layer {
  1190. name: "inception_4b/5x5"
  1191. type: "Convolution"
  1192. bottom: "inception_4b/5x5_reduce"
  1193. top: "inception_4b/5x5"
  1194. param {
  1195. lr_mult: 1.0
  1196. decay_mult: 1.0
  1197. }
  1198. param {
  1199. lr_mult: 2.0
  1200. decay_mult: 0.0
  1201. }
  1202. convolution_param {
  1203. num_output: 64
  1204. pad: 2
  1205. kernel_size: 5
  1206. weight_filler {
  1207. type: "xavier"
  1208. std: 0.03
  1209. }
  1210. bias_filler {
  1211. type: "constant"
  1212. value: 0.2
  1213. }
  1214. }
  1215. }
  1216. layer {
  1217. name: "inception_4b/relu_5x5"
  1218. type: "ReLU"
  1219. bottom: "inception_4b/5x5"
  1220. top: "inception_4b/5x5"
  1221. }
  1222. layer {
  1223. name: "inception_4b/pool"
  1224. type: "Pooling"
  1225. bottom: "inception_4a/output"
  1226. top: "inception_4b/pool"
  1227. pooling_param {
  1228. pool: MAX
  1229. kernel_size: 3
  1230. stride: 1
  1231. pad: 1
  1232. }
  1233. }
  1234. layer {
  1235. name: "inception_4b/pool_proj"
  1236. type: "Convolution"
  1237. bottom: "inception_4b/pool"
  1238. top: "inception_4b/pool_proj"
  1239. param {
  1240. lr_mult: 1.0
  1241. decay_mult: 1.0
  1242. }
  1243. param {
  1244. lr_mult: 2.0
  1245. decay_mult: 0.0
  1246. }
  1247. convolution_param {
  1248. num_output: 64
  1249. kernel_size: 1
  1250. weight_filler {
  1251. type: "xavier"
  1252. std: 0.1
  1253. }
  1254. bias_filler {
  1255. type: "constant"
  1256. value: 0.2
  1257. }
  1258. }
  1259. }
  1260. layer {
  1261. name: "inception_4b/relu_pool_proj"
  1262. type: "ReLU"
  1263. bottom: "inception_4b/pool_proj"
  1264. top: "inception_4b/pool_proj"
  1265. }
  1266. layer {
  1267. name: "inception_4b/output"
  1268. type: "Concat"
  1269. bottom: "inception_4b/1x1"
  1270. bottom: "inception_4b/3x3"
  1271. bottom: "inception_4b/5x5"
  1272. bottom: "inception_4b/pool_proj"
  1273. top: "inception_4b/output"
  1274. }
  1275. layer {
  1276. name: "inception_4c/1x1"
  1277. type: "Convolution"
  1278. bottom: "inception_4b/output"
  1279. top: "inception_4c/1x1"
  1280. param {
  1281. lr_mult: 1.0
  1282. decay_mult: 1.0
  1283. }
  1284. param {
  1285. lr_mult: 2.0
  1286. decay_mult: 0.0
  1287. }
  1288. convolution_param {
  1289. num_output: 128
  1290. kernel_size: 1
  1291. weight_filler {
  1292. type: "xavier"
  1293. std: 0.03
  1294. }
  1295. bias_filler {
  1296. type: "constant"
  1297. value: 0.2
  1298. }
  1299. }
  1300. }
  1301. layer {
  1302. name: "inception_4c/relu_1x1"
  1303. type: "ReLU"
  1304. bottom: "inception_4c/1x1"
  1305. top: "inception_4c/1x1"
  1306. }
  1307. layer {
  1308. name: "inception_4c/3x3_reduce"
  1309. type: "Convolution"
  1310. bottom: "inception_4b/output"
  1311. top: "inception_4c/3x3_reduce"
  1312. param {
  1313. lr_mult: 1.0
  1314. decay_mult: 1.0
  1315. }
  1316. param {
  1317. lr_mult: 2.0
  1318. decay_mult: 0.0
  1319. }
  1320. convolution_param {
  1321. num_output: 128
  1322. kernel_size: 1
  1323. weight_filler {
  1324. type: "xavier"
  1325. std: 0.09
  1326. }
  1327. bias_filler {
  1328. type: "constant"
  1329. value: 0.2
  1330. }
  1331. }
  1332. }
  1333. layer {
  1334. name: "inception_4c/relu_3x3_reduce"
  1335. type: "ReLU"
  1336. bottom: "inception_4c/3x3_reduce"
  1337. top: "inception_4c/3x3_reduce"
  1338. }
  1339. layer {
  1340. name: "inception_4c/3x3"
  1341. type: "Convolution"
  1342. bottom: "inception_4c/3x3_reduce"
  1343. top: "inception_4c/3x3"
  1344. param {
  1345. lr_mult: 1.0
  1346. decay_mult: 1.0
  1347. }
  1348. param {
  1349. lr_mult: 2.0
  1350. decay_mult: 0.0
  1351. }
  1352. convolution_param {
  1353. num_output: 256
  1354. pad: 1
  1355. kernel_size: 3
  1356. weight_filler {
  1357. type: "xavier"
  1358. std: 0.03
  1359. }
  1360. bias_filler {
  1361. type: "constant"
  1362. value: 0.2
  1363. }
  1364. }
  1365. }
  1366. layer {
  1367. name: "inception_4c/relu_3x3"
  1368. type: "ReLU"
  1369. bottom: "inception_4c/3x3"
  1370. top: "inception_4c/3x3"
  1371. }
  1372. layer {
  1373. name: "inception_4c/5x5_reduce"
  1374. type: "Convolution"
  1375. bottom: "inception_4b/output"
  1376. top: "inception_4c/5x5_reduce"
  1377. param {
  1378. lr_mult: 1.0
  1379. decay_mult: 1.0
  1380. }
  1381. param {
  1382. lr_mult: 2.0
  1383. decay_mult: 0.0
  1384. }
  1385. convolution_param {
  1386. num_output: 24
  1387. kernel_size: 1
  1388. weight_filler {
  1389. type: "xavier"
  1390. std: 0.2
  1391. }
  1392. bias_filler {
  1393. type: "constant"
  1394. value: 0.2
  1395. }
  1396. }
  1397. }
  1398. layer {
  1399. name: "inception_4c/relu_5x5_reduce"
  1400. type: "ReLU"
  1401. bottom: "inception_4c/5x5_reduce"
  1402. top: "inception_4c/5x5_reduce"
  1403. }
  1404. layer {
  1405. name: "inception_4c/5x5"
  1406. type: "Convolution"
  1407. bottom: "inception_4c/5x5_reduce"
  1408. top: "inception_4c/5x5"
  1409. param {
  1410. lr_mult: 1.0
  1411. decay_mult: 1.0
  1412. }
  1413. param {
  1414. lr_mult: 2.0
  1415. decay_mult: 0.0
  1416. }
  1417. convolution_param {
  1418. num_output: 64
  1419. pad: 2
  1420. kernel_size: 5
  1421. weight_filler {
  1422. type: "xavier"
  1423. std: 0.03
  1424. }
  1425. bias_filler {
  1426. type: "constant"
  1427. value: 0.2
  1428. }
  1429. }
  1430. }
  1431. layer {
  1432. name: "inception_4c/relu_5x5"
  1433. type: "ReLU"
  1434. bottom: "inception_4c/5x5"
  1435. top: "inception_4c/5x5"
  1436. }
  1437. layer {
  1438. name: "inception_4c/pool"
  1439. type: "Pooling"
  1440. bottom: "inception_4b/output"
  1441. top: "inception_4c/pool"
  1442. pooling_param {
  1443. pool: MAX
  1444. kernel_size: 3
  1445. stride: 1
  1446. pad: 1
  1447. }
  1448. }
  1449. layer {
  1450. name: "inception_4c/pool_proj"
  1451. type: "Convolution"
  1452. bottom: "inception_4c/pool"
  1453. top: "inception_4c/pool_proj"
  1454. param {
  1455. lr_mult: 1.0
  1456. decay_mult: 1.0
  1457. }
  1458. param {
  1459. lr_mult: 2.0
  1460. decay_mult: 0.0
  1461. }
  1462. convolution_param {
  1463. num_output: 64
  1464. kernel_size: 1
  1465. weight_filler {
  1466. type: "xavier"
  1467. std: 0.1
  1468. }
  1469. bias_filler {
  1470. type: "constant"
  1471. value: 0.2
  1472. }
  1473. }
  1474. }
  1475. layer {
  1476. name: "inception_4c/relu_pool_proj"
  1477. type: "ReLU"
  1478. bottom: "inception_4c/pool_proj"
  1479. top: "inception_4c/pool_proj"
  1480. }
  1481. layer {
  1482. name: "inception_4c/output"
  1483. type: "Concat"
  1484. bottom: "inception_4c/1x1"
  1485. bottom: "inception_4c/3x3"
  1486. bottom: "inception_4c/5x5"
  1487. bottom: "inception_4c/pool_proj"
  1488. top: "inception_4c/output"
  1489. }
  1490. layer {
  1491. name: "inception_4d/1x1"
  1492. type: "Convolution"
  1493. bottom: "inception_4c/output"
  1494. top: "inception_4d/1x1"
  1495. param {
  1496. lr_mult: 1.0
  1497. decay_mult: 1.0
  1498. }
  1499. param {
  1500. lr_mult: 2.0
  1501. decay_mult: 0.0
  1502. }
  1503. convolution_param {
  1504. num_output: 112
  1505. kernel_size: 1
  1506. weight_filler {
  1507. type: "xavier"
  1508. std: 0.1
  1509. }
  1510. bias_filler {
  1511. type: "constant"
  1512. value: 0.2
  1513. }
  1514. }
  1515. }
  1516. layer {
  1517. name: "inception_4d/relu_1x1"
  1518. type: "ReLU"
  1519. bottom: "inception_4d/1x1"
  1520. top: "inception_4d/1x1"
  1521. }
  1522. layer {
  1523. name: "inception_4d/3x3_reduce"
  1524. type: "Convolution"
  1525. bottom: "inception_4c/output"
  1526. top: "inception_4d/3x3_reduce"
  1527. param {
  1528. lr_mult: 1.0
  1529. decay_mult: 1.0
  1530. }
  1531. param {
  1532. lr_mult: 2.0
  1533. decay_mult: 0.0
  1534. }
  1535. convolution_param {
  1536. num_output: 144
  1537. kernel_size: 1
  1538. weight_filler {
  1539. type: "xavier"
  1540. std: 0.1
  1541. }
  1542. bias_filler {
  1543. type: "constant"
  1544. value: 0.2
  1545. }
  1546. }
  1547. }
  1548. layer {
  1549. name: "inception_4d/relu_3x3_reduce"
  1550. type: "ReLU"
  1551. bottom: "inception_4d/3x3_reduce"
  1552. top: "inception_4d/3x3_reduce"
  1553. }
  1554. layer {
  1555. name: "inception_4d/3x3"
  1556. type: "Convolution"
  1557. bottom: "inception_4d/3x3_reduce"
  1558. top: "inception_4d/3x3"
  1559. param {
  1560. lr_mult: 1.0
  1561. decay_mult: 1.0
  1562. }
  1563. param {
  1564. lr_mult: 2.0
  1565. decay_mult: 0.0
  1566. }
  1567. convolution_param {
  1568. num_output: 288
  1569. pad: 1
  1570. kernel_size: 3
  1571. weight_filler {
  1572. type: "xavier"
  1573. std: 0.1
  1574. }
  1575. bias_filler {
  1576. type: "constant"
  1577. value: 0.2
  1578. }
  1579. }
  1580. }
  1581. layer {
  1582. name: "inception_4d/relu_3x3"
  1583. type: "ReLU"
  1584. bottom: "inception_4d/3x3"
  1585. top: "inception_4d/3x3"
  1586. }
  1587. layer {
  1588. name: "inception_4d/5x5_reduce"
  1589. type: "Convolution"
  1590. bottom: "inception_4c/output"
  1591. top: "inception_4d/5x5_reduce"
  1592. param {
  1593. lr_mult: 1.0
  1594. decay_mult: 1.0
  1595. }
  1596. param {
  1597. lr_mult: 2.0
  1598. decay_mult: 0.0
  1599. }
  1600. convolution_param {
  1601. num_output: 32
  1602. kernel_size: 1
  1603. weight_filler {
  1604. type: "xavier"
  1605. std: 0.1
  1606. }
  1607. bias_filler {
  1608. type: "constant"
  1609. value: 0.2
  1610. }
  1611. }
  1612. }
  1613. layer {
  1614. name: "inception_4d/relu_5x5_reduce"
  1615. type: "ReLU"
  1616. bottom: "inception_4d/5x5_reduce"
  1617. top: "inception_4d/5x5_reduce"
  1618. }
  1619. layer {
  1620. name: "inception_4d/5x5"
  1621. type: "Convolution"
  1622. bottom: "inception_4d/5x5_reduce"
  1623. top: "inception_4d/5x5"
  1624. param {
  1625. lr_mult: 1.0
  1626. decay_mult: 1.0
  1627. }
  1628. param {
  1629. lr_mult: 2.0
  1630. decay_mult: 0.0
  1631. }
  1632. convolution_param {
  1633. num_output: 64
  1634. pad: 2
  1635. kernel_size: 5
  1636. weight_filler {
  1637. type: "xavier"
  1638. std: 0.1
  1639. }
  1640. bias_filler {
  1641. type: "constant"
  1642. value: 0.2
  1643. }
  1644. }
  1645. }
  1646. layer {
  1647. name: "inception_4d/relu_5x5"
  1648. type: "ReLU"
  1649. bottom: "inception_4d/5x5"
  1650. top: "inception_4d/5x5"
  1651. }
  1652. layer {
  1653. name: "inception_4d/pool"
  1654. type: "Pooling"
  1655. bottom: "inception_4c/output"
  1656. top: "inception_4d/pool"
  1657. pooling_param {
  1658. pool: MAX
  1659. kernel_size: 3
  1660. stride: 1
  1661. pad: 1
  1662. }
  1663. }
  1664. layer {
  1665. name: "inception_4d/pool_proj"
  1666. type: "Convolution"
  1667. bottom: "inception_4d/pool"
  1668. top: "inception_4d/pool_proj"
  1669. param {
  1670. lr_mult: 1.0
  1671. decay_mult: 1.0
  1672. }
  1673. param {
  1674. lr_mult: 2.0
  1675. decay_mult: 0.0
  1676. }
  1677. convolution_param {
  1678. num_output: 64
  1679. kernel_size: 1
  1680. weight_filler {
  1681. type: "xavier"
  1682. std: 0.1
  1683. }
  1684. bias_filler {
  1685. type: "constant"
  1686. value: 0.2
  1687. }
  1688. }
  1689. }
  1690. layer {
  1691. name: "inception_4d/relu_pool_proj"
  1692. type: "ReLU"
  1693. bottom: "inception_4d/pool_proj"
  1694. top: "inception_4d/pool_proj"
  1695. }
  1696. layer {
  1697. name: "inception_4d/output"
  1698. type: "Concat"
  1699. bottom: "inception_4d/1x1"
  1700. bottom: "inception_4d/3x3"
  1701. bottom: "inception_4d/5x5"
  1702. bottom: "inception_4d/pool_proj"
  1703. top: "inception_4d/output"
  1704. }
  1705. layer {
  1706. name: "inception_4e/1x1"
  1707. type: "Convolution"
  1708. bottom: "inception_4d/output"
  1709. top: "inception_4e/1x1"
  1710. param {
  1711. lr_mult: 1.0
  1712. decay_mult: 1.0
  1713. }
  1714. param {
  1715. lr_mult: 2.0
  1716. decay_mult: 0.0
  1717. }
  1718. convolution_param {
  1719. num_output: 256
  1720. kernel_size: 1
  1721. weight_filler {
  1722. type: "xavier"
  1723. std: 0.03
  1724. }
  1725. bias_filler {
  1726. type: "constant"
  1727. value: 0.2
  1728. }
  1729. }
  1730. }
  1731. layer {
  1732. name: "inception_4e/relu_1x1"
  1733. type: "ReLU"
  1734. bottom: "inception_4e/1x1"
  1735. top: "inception_4e/1x1"
  1736. }
  1737. layer {
  1738. name: "inception_4e/3x3_reduce"
  1739. type: "Convolution"
  1740. bottom: "inception_4d/output"
  1741. top: "inception_4e/3x3_reduce"
  1742. param {
  1743. lr_mult: 1.0
  1744. decay_mult: 1.0
  1745. }
  1746. param {
  1747. lr_mult: 2.0
  1748. decay_mult: 0.0
  1749. }
  1750. convolution_param {
  1751. num_output: 160
  1752. kernel_size: 1
  1753. weight_filler {
  1754. type: "xavier"
  1755. std: 0.09
  1756. }
  1757. bias_filler {
  1758. type: "constant"
  1759. value: 0.2
  1760. }
  1761. }
  1762. }
  1763. layer {
  1764. name: "inception_4e/relu_3x3_reduce"
  1765. type: "ReLU"
  1766. bottom: "inception_4e/3x3_reduce"
  1767. top: "inception_4e/3x3_reduce"
  1768. }
  1769. layer {
  1770. name: "inception_4e/3x3"
  1771. type: "Convolution"
  1772. bottom: "inception_4e/3x3_reduce"
  1773. top: "inception_4e/3x3"
  1774. param {
  1775. lr_mult: 1.0
  1776. decay_mult: 1.0
  1777. }
  1778. param {
  1779. lr_mult: 2.0
  1780. decay_mult: 0.0
  1781. }
  1782. convolution_param {
  1783. num_output: 320
  1784. pad: 1
  1785. kernel_size: 3
  1786. weight_filler {
  1787. type: "xavier"
  1788. std: 0.03
  1789. }
  1790. bias_filler {
  1791. type: "constant"
  1792. value: 0.2
  1793. }
  1794. }
  1795. }
  1796. layer {
  1797. name: "inception_4e/relu_3x3"
  1798. type: "ReLU"
  1799. bottom: "inception_4e/3x3"
  1800. top: "inception_4e/3x3"
  1801. }
  1802. layer {
  1803. name: "inception_4e/5x5_reduce"
  1804. type: "Convolution"
  1805. bottom: "inception_4d/output"
  1806. top: "inception_4e/5x5_reduce"
  1807. param {
  1808. lr_mult: 1.0
  1809. decay_mult: 1.0
  1810. }
  1811. param {
  1812. lr_mult: 2.0
  1813. decay_mult: 0.0
  1814. }
  1815. convolution_param {
  1816. num_output: 32
  1817. kernel_size: 1
  1818. weight_filler {
  1819. type: "xavier"
  1820. std: 0.2
  1821. }
  1822. bias_filler {
  1823. type: "constant"
  1824. value: 0.2
  1825. }
  1826. }
  1827. }
  1828. layer {
  1829. name: "inception_4e/relu_5x5_reduce"
  1830. type: "ReLU"
  1831. bottom: "inception_4e/5x5_reduce"
  1832. top: "inception_4e/5x5_reduce"
  1833. }
  1834. layer {
  1835. name: "inception_4e/5x5"
  1836. type: "Convolution"
  1837. bottom: "inception_4e/5x5_reduce"
  1838. top: "inception_4e/5x5"
  1839. param {
  1840. lr_mult: 1.0
  1841. decay_mult: 1.0
  1842. }
  1843. param {
  1844. lr_mult: 2.0
  1845. decay_mult: 0.0
  1846. }
  1847. convolution_param {
  1848. num_output: 128
  1849. pad: 2
  1850. kernel_size: 5
  1851. weight_filler {
  1852. type: "xavier"
  1853. std: 0.03
  1854. }
  1855. bias_filler {
  1856. type: "constant"
  1857. value: 0.2
  1858. }
  1859. }
  1860. }
  1861. layer {
  1862. name: "inception_4e/relu_5x5"
  1863. type: "ReLU"
  1864. bottom: "inception_4e/5x5"
  1865. top: "inception_4e/5x5"
  1866. }
  1867. layer {
  1868. name: "inception_4e/pool"
  1869. type: "Pooling"
  1870. bottom: "inception_4d/output"
  1871. top: "inception_4e/pool"
  1872. pooling_param {
  1873. pool: MAX
  1874. kernel_size: 3
  1875. stride: 1
  1876. pad: 1
  1877. }
  1878. }
  1879. layer {
  1880. name: "inception_4e/pool_proj"
  1881. type: "Convolution"
  1882. bottom: "inception_4e/pool"
  1883. top: "inception_4e/pool_proj"
  1884. param {
  1885. lr_mult: 1.0
  1886. decay_mult: 1.0
  1887. }
  1888. param {
  1889. lr_mult: 2.0
  1890. decay_mult: 0.0
  1891. }
  1892. convolution_param {
  1893. num_output: 128
  1894. kernel_size: 1
  1895. weight_filler {
  1896. type: "xavier"
  1897. std: 0.1
  1898. }
  1899. bias_filler {
  1900. type: "constant"
  1901. value: 0.2
  1902. }
  1903. }
  1904. }
  1905. layer {
  1906. name: "inception_4e/relu_pool_proj"
  1907. type: "ReLU"
  1908. bottom: "inception_4e/pool_proj"
  1909. top: "inception_4e/pool_proj"
  1910. }
  1911. layer {
  1912. name: "inception_4e/output"
  1913. type: "Concat"
  1914. bottom: "inception_4e/1x1"
  1915. bottom: "inception_4e/3x3"
  1916. bottom: "inception_4e/5x5"
  1917. bottom: "inception_4e/pool_proj"
  1918. top: "inception_4e/output"
  1919. }
  1920. layer {
  1921. name: "inception_5a/1x1"
  1922. type: "Convolution"
  1923. bottom: "inception_4e/output"
  1924. top: "inception_5a/1x1"
  1925. param {
  1926. lr_mult: 1.0
  1927. decay_mult: 1.0
  1928. }
  1929. param {
  1930. lr_mult: 2.0
  1931. decay_mult: 0.0
  1932. }
  1933. convolution_param {
  1934. num_output: 256
  1935. kernel_size: 1
  1936. weight_filler {
  1937. type: "xavier"
  1938. std: 0.03
  1939. }
  1940. bias_filler {
  1941. type: "constant"
  1942. value: 0.2
  1943. }
  1944. }
  1945. }
  1946. layer {
  1947. name: "inception_5a/relu_1x1"
  1948. type: "ReLU"
  1949. bottom: "inception_5a/1x1"
  1950. top: "inception_5a/1x1"
  1951. }
  1952. layer {
  1953. name: "inception_5a/3x3_reduce"
  1954. type: "Convolution"
  1955. bottom: "inception_4e/output"
  1956. top: "inception_5a/3x3_reduce"
  1957. param {
  1958. lr_mult: 1.0
  1959. decay_mult: 1.0
  1960. }
  1961. param {
  1962. lr_mult: 2.0
  1963. decay_mult: 0.0
  1964. }
  1965. convolution_param {
  1966. num_output: 160
  1967. kernel_size: 1
  1968. weight_filler {
  1969. type: "xavier"
  1970. std: 0.09
  1971. }
  1972. bias_filler {
  1973. type: "constant"
  1974. value: 0.2
  1975. }
  1976. }
  1977. }
  1978. layer {
  1979. name: "inception_5a/relu_3x3_reduce"
  1980. type: "ReLU"
  1981. bottom: "inception_5a/3x3_reduce"
  1982. top: "inception_5a/3x3_reduce"
  1983. }
  1984. layer {
  1985. name: "inception_5a/3x3"
  1986. type: "Convolution"
  1987. bottom: "inception_5a/3x3_reduce"
  1988. top: "inception_5a/3x3"
  1989. param {
  1990. lr_mult: 1.0
  1991. decay_mult: 1.0
  1992. }
  1993. param {
  1994. lr_mult: 2.0
  1995. decay_mult: 0.0
  1996. }
  1997. convolution_param {
  1998. num_output: 320
  1999. pad: 1
  2000. kernel_size: 3
  2001. weight_filler {
  2002. type: "xavier"
  2003. std: 0.03
  2004. }
  2005. bias_filler {
  2006. type: "constant"
  2007. value: 0.2
  2008. }
  2009. }
  2010. }
  2011. layer {
  2012. name: "inception_5a/relu_3x3"
  2013. type: "ReLU"
  2014. bottom: "inception_5a/3x3"
  2015. top: "inception_5a/3x3"
  2016. }
  2017. layer {
  2018. name: "inception_5a/5x5_reduce"
  2019. type: "Convolution"
  2020. bottom: "inception_4e/output"
  2021. top: "inception_5a/5x5_reduce"
  2022. param {
  2023. lr_mult: 1.0
  2024. decay_mult: 1.0
  2025. }
  2026. param {
  2027. lr_mult: 2.0
  2028. decay_mult: 0.0
  2029. }
  2030. convolution_param {
  2031. num_output: 32
  2032. kernel_size: 1
  2033. weight_filler {
  2034. type: "xavier"
  2035. std: 0.2
  2036. }
  2037. bias_filler {
  2038. type: "constant"
  2039. value: 0.2
  2040. }
  2041. }
  2042. }
  2043. layer {
  2044. name: "inception_5a/relu_5x5_reduce"
  2045. type: "ReLU"
  2046. bottom: "inception_5a/5x5_reduce"
  2047. top: "inception_5a/5x5_reduce"
  2048. }
  2049. layer {
  2050. name: "inception_5a/5x5"
  2051. type: "Convolution"
  2052. bottom: "inception_5a/5x5_reduce"
  2053. top: "inception_5a/5x5"
  2054. param {
  2055. lr_mult: 1.0
  2056. decay_mult: 1.0
  2057. }
  2058. param {
  2059. lr_mult: 2.0
  2060. decay_mult: 0.0
  2061. }
  2062. convolution_param {
  2063. num_output: 128
  2064. pad: 2
  2065. kernel_size: 5
  2066. weight_filler {
  2067. type: "xavier"
  2068. std: 0.03
  2069. }
  2070. bias_filler {
  2071. type: "constant"
  2072. value: 0.2
  2073. }
  2074. }
  2075. }
  2076. layer {
  2077. name: "inception_5a/relu_5x5"
  2078. type: "ReLU"
  2079. bottom: "inception_5a/5x5"
  2080. top: "inception_5a/5x5"
  2081. }
  2082. layer {
  2083. name: "inception_5a/pool"
  2084. type: "Pooling"
  2085. bottom: "inception_4e/output"
  2086. top: "inception_5a/pool"
  2087. pooling_param {
  2088. pool: MAX
  2089. kernel_size: 3
  2090. stride: 1
  2091. pad: 1
  2092. }
  2093. }
  2094. layer {
  2095. name: "inception_5a/pool_proj"
  2096. type: "Convolution"
  2097. bottom: "inception_5a/pool"
  2098. top: "inception_5a/pool_proj"
  2099. param {
  2100. lr_mult: 1.0
  2101. decay_mult: 1.0
  2102. }
  2103. param {
  2104. lr_mult: 2.0
  2105. decay_mult: 0.0
  2106. }
  2107. convolution_param {
  2108. num_output: 128
  2109. kernel_size: 1
  2110. weight_filler {
  2111. type: "xavier"
  2112. std: 0.1
  2113. }
  2114. bias_filler {
  2115. type: "constant"
  2116. value: 0.2
  2117. }
  2118. }
  2119. }
  2120. layer {
  2121. name: "inception_5a/relu_pool_proj"
  2122. type: "ReLU"
  2123. bottom: "inception_5a/pool_proj"
  2124. top: "inception_5a/pool_proj"
  2125. }
  2126. layer {
  2127. name: "inception_5a/output"
  2128. type: "Concat"
  2129. bottom: "inception_5a/1x1"
  2130. bottom: "inception_5a/3x3"
  2131. bottom: "inception_5a/5x5"
  2132. bottom: "inception_5a/pool_proj"
  2133. top: "inception_5a/output"
  2134. }
  2135. layer {
  2136. name: "inception_5b/1x1"
  2137. type: "Convolution"
  2138. bottom: "inception_5a/output"
  2139. top: "inception_5b/1x1"
  2140. param {
  2141. lr_mult: 1.0
  2142. decay_mult: 1.0
  2143. }
  2144. param {
  2145. lr_mult: 2.0
  2146. decay_mult: 0.0
  2147. }
  2148. convolution_param {
  2149. num_output: 384
  2150. kernel_size: 1
  2151. weight_filler {
  2152. type: "xavier"
  2153. std: 0.1
  2154. }
  2155. bias_filler {
  2156. type: "constant"
  2157. value: 0.2
  2158. }
  2159. }
  2160. }
  2161. layer {
  2162. name: "inception_5b/relu_1x1"
  2163. type: "ReLU"
  2164. bottom: "inception_5b/1x1"
  2165. top: "inception_5b/1x1"
  2166. }
  2167. layer {
  2168. name: "inception_5b/3x3_reduce"
  2169. type: "Convolution"
  2170. bottom: "inception_5a/output"
  2171. top: "inception_5b/3x3_reduce"
  2172. param {
  2173. lr_mult: 1.0
  2174. decay_mult: 1.0
  2175. }
  2176. param {
  2177. lr_mult: 1.0
  2178. decay_mult: 0.0
  2179. }
  2180. convolution_param {
  2181. num_output: 192
  2182. kernel_size: 1
  2183. weight_filler {
  2184. type: "xavier"
  2185. std: 0.1
  2186. }
  2187. bias_filler {
  2188. type: "constant"
  2189. value: 0.2
  2190. }
  2191. }
  2192. }
  2193. layer {
  2194. name: "inception_5b/relu_3x3_reduce"
  2195. type: "ReLU"
  2196. bottom: "inception_5b/3x3_reduce"
  2197. top: "inception_5b/3x3_reduce"
  2198. }
  2199. layer {
  2200. name: "inception_5b/3x3"
  2201. type: "Convolution"
  2202. bottom: "inception_5b/3x3_reduce"
  2203. top: "inception_5b/3x3"
  2204. param {
  2205. lr_mult: 1.0
  2206. decay_mult: 1.0
  2207. }
  2208. param {
  2209. lr_mult: 2.0
  2210. decay_mult: 0.0
  2211. }
  2212. convolution_param {
  2213. num_output: 384
  2214. pad: 1
  2215. kernel_size: 3
  2216. weight_filler {
  2217. type: "xavier"
  2218. std: 0.1
  2219. }
  2220. bias_filler {
  2221. type: "constant"
  2222. value: 0.2
  2223. }
  2224. }
  2225. }
  2226. layer {
  2227. name: "inception_5b/relu_3x3"
  2228. type: "ReLU"
  2229. bottom: "inception_5b/3x3"
  2230. top: "inception_5b/3x3"
  2231. }
  2232. layer {
  2233. name: "inception_5b/5x5_reduce"
  2234. type: "Convolution"
  2235. bottom: "inception_5a/output"
  2236. top: "inception_5b/5x5_reduce"
  2237. param {
  2238. lr_mult: 1.0
  2239. decay_mult: 1.0
  2240. }
  2241. param {
  2242. lr_mult: 2.0
  2243. decay_mult: 0.0
  2244. }
  2245. convolution_param {
  2246. num_output: 48
  2247. kernel_size: 1
  2248. weight_filler {
  2249. type: "xavier"
  2250. std: 0.1
  2251. }
  2252. bias_filler {
  2253. type: "constant"
  2254. value: 0.2
  2255. }
  2256. }
  2257. }
  2258. layer {
  2259. name: "inception_5b/relu_5x5_reduce"
  2260. type: "ReLU"
  2261. bottom: "inception_5b/5x5_reduce"
  2262. top: "inception_5b/5x5_reduce"
  2263. }
  2264. layer {
  2265. name: "inception_5b/5x5"
  2266. type: "Convolution"
  2267. bottom: "inception_5b/5x5_reduce"
  2268. top: "inception_5b/5x5"
  2269. param {
  2270. lr_mult: 1.0
  2271. decay_mult: 1.0
  2272. }
  2273. param {
  2274. lr_mult: 2.0
  2275. decay_mult: 0.0
  2276. }
  2277. convolution_param {
  2278. num_output: 128
  2279. pad: 2
  2280. kernel_size: 5
  2281. weight_filler {
  2282. type: "xavier"
  2283. std: 0.1
  2284. }
  2285. bias_filler {
  2286. type: "constant"
  2287. value: 0.2
  2288. }
  2289. }
  2290. }
  2291. layer {
  2292. name: "inception_5b/relu_5x5"
  2293. type: "ReLU"
  2294. bottom: "inception_5b/5x5"
  2295. top: "inception_5b/5x5"
  2296. }
  2297. layer {
  2298. name: "inception_5b/pool"
  2299. type: "Pooling"
  2300. bottom: "inception_5a/output"
  2301. top: "inception_5b/pool"
  2302. pooling_param {
  2303. pool: MAX
  2304. kernel_size: 3
  2305. stride: 1
  2306. pad: 1
  2307. }
  2308. }
  2309. layer {
  2310. name: "inception_5b/pool_proj"
  2311. type: "Convolution"
  2312. bottom: "inception_5b/pool"
  2313. top: "inception_5b/pool_proj"
  2314. param {
  2315. lr_mult: 1.0
  2316. decay_mult: 1.0
  2317. }
  2318. param {
  2319. lr_mult: 2.0
  2320. decay_mult: 0.0
  2321. }
  2322. convolution_param {
  2323. num_output: 128
  2324. kernel_size: 1
  2325. weight_filler {
  2326. type: "xavier"
  2327. std: 0.1
  2328. }
  2329. bias_filler {
  2330. type: "constant"
  2331. value: 0.2
  2332. }
  2333. }
  2334. }
  2335. layer {
  2336. name: "inception_5b/relu_pool_proj"
  2337. type: "ReLU"
  2338. bottom: "inception_5b/pool_proj"
  2339. top: "inception_5b/pool_proj"
  2340. }
  2341. layer {
  2342. name: "inception_5b/output"
  2343. type: "Concat"
  2344. bottom: "inception_5b/1x1"
  2345. bottom: "inception_5b/3x3"
  2346. bottom: "inception_5b/5x5"
  2347. bottom: "inception_5b/pool_proj"
  2348. top: "inception_5b/output"
  2349. }
  2350. layer {
  2351. name: "pool5/drop_s1"
  2352. type: "Dropout"
  2353. bottom: "inception_5b/output"
  2354. top: "pool5/drop_s1"
  2355. dropout_param {
  2356. dropout_ratio: 0.4
  2357. }
  2358. }
  2359. layer {
  2360. name: "cvg/classifier"
  2361. type: "Convolution"
  2362. bottom: "pool5/drop_s1"
  2363. top: "cvg/classifier"
  2364. param {
  2365. lr_mult: 1.0
  2366. decay_mult: 1.0
  2367. }
  2368. param {
  2369. lr_mult: 2.0
  2370. decay_mult: 0.0
  2371. }
  2372. convolution_param {
  2373. num_output: 1
  2374. kernel_size: 1
  2375. weight_filler {
  2376. type: "xavier"
  2377. std: 0.03
  2378. }
  2379. bias_filler {
  2380. type: "constant"
  2381. value: 0.0
  2382. }
  2383. }
  2384. }
  2385. layer {
  2386. name: "coverage/sig"
  2387. type: "Sigmoid"
  2388. bottom: "cvg/classifier"
  2389. top: "coverage"
  2390. }
  2391. layer {
  2392. name: "bbox/regressor"
  2393. type: "Convolution"
  2394. bottom: "pool5/drop_s1"
  2395. top: "bboxes"
  2396. param {
  2397. lr_mult: 1.0
  2398. decay_mult: 1.0
  2399. }
  2400. param {
  2401. lr_mult: 2.0
  2402. decay_mult: 0.0
  2403. }
  2404. convolution_param {
  2405. num_output: 4
  2406. kernel_size: 1
  2407. weight_filler {
  2408. type: "xavier"
  2409. std: 0.03
  2410. }
  2411. bias_filler {
  2412. type: "constant"
  2413. value: 0.0
  2414. }
  2415. }
  2416. }
  2417. layer {
  2418. name: "bbox_mask"
  2419. type: "Eltwise"
  2420. bottom: "bboxes"
  2421. bottom: "coverage-block"
  2422. top: "bboxes-masked"
  2423. include {
  2424. phase: TRAIN
  2425. }
  2426. include {
  2427. phase: TEST
  2428. stage: "val"
  2429. }
  2430. eltwise_param {
  2431. operation: PROD
  2432. }
  2433. }
  2434. layer {
  2435. name: "bbox-norm"
  2436. type: "Eltwise"
  2437. bottom: "bboxes-masked"
  2438. bottom: "size-block"
  2439. top: "bboxes-masked-norm"
  2440. include {
  2441. phase: TRAIN
  2442. }
  2443. include {
  2444. phase: TEST
  2445. stage: "val"
  2446. }
  2447. eltwise_param {
  2448. operation: PROD
  2449. }
  2450. }
  2451. layer {
  2452. name: "bbox-obj-norm"
  2453. type: "Eltwise"
  2454. bottom: "bboxes-masked-norm"
  2455. bottom: "obj-block"
  2456. top: "bboxes-obj-masked-norm"
  2457. include {
  2458. phase: TRAIN
  2459. }
  2460. include {
  2461. phase: TEST
  2462. stage: "val"
  2463. }
  2464. eltwise_param {
  2465. operation: PROD
  2466. }
  2467. }
  2468. layer {
  2469. name: "bbox_loss"
  2470. type: "L1Loss"
  2471. bottom: "bboxes-obj-masked-norm"
  2472. bottom: "bbox-obj-label-norm"
  2473. top: "loss_bbox"
  2474. loss_weight: 2.0
  2475. include {
  2476. phase: TRAIN
  2477. }
  2478. include {
  2479. phase: TEST
  2480. stage: "val"
  2481. }
  2482. }
  2483. layer {
  2484. name: "coverage_loss"
  2485. type: "EuclideanLoss"
  2486. bottom: "coverage"
  2487. bottom: "coverage-label"
  2488. top: "loss_coverage"
  2489. include {
  2490. phase: TRAIN
  2491. }
  2492. include {
  2493. phase: TEST
  2494. stage: "val"
  2495. }
  2496. }
  2497. layer {
  2498. name: "cluster"
  2499. type: "Python"
  2500. bottom: "coverage"
  2501. bottom: "bboxes"
  2502. top: "bbox-list"
  2503. include {
  2504. phase: TEST
  2505. }
  2506. python_param {
  2507. module: "caffe.layers.detectnet.clustering"
  2508. layer: "ClusterDetections"
  2509. param_str: "1280, 1280, 16, 0.06, 3, 0.02, 10,1"
  2510. }
  2511. }
  2512. layer {
  2513. name: "cluster_gt"
  2514. type: "Python"
  2515. bottom: "coverage-label"
  2516. bottom: "bbox-label"
  2517. top: "bbox-list-label"
  2518. include {
  2519. phase: TEST
  2520. stage: "val"
  2521. }
  2522. python_param {
  2523. module: "caffe.layers.detectnet.clustering"
  2524. layer: "ClusterGroundtruth"
  2525. param_str: "1280, 1280, 16"
  2526. }
  2527. }
  2528. layer {
  2529. name: "score"
  2530. type: "Python"
  2531. bottom: "bbox-list-label"
  2532. bottom: "bbox-list"
  2533. top: "bbox-list-scored"
  2534. include {
  2535. phase: TEST
  2536. stage: "val"
  2537. }
  2538. python_param {
  2539. module: "caffe.layers.detectnet.mean_ap"
  2540. layer: "ScoreDetections"
  2541. }
  2542. }
  2543. layer {
  2544. name: "mAP"
  2545. type: "Python"
  2546. bottom: "bbox-list-scored"
  2547. top: "mAP"
  2548. top: "precision"
  2549. top: "recall"
  2550. include {
  2551. phase: TEST
  2552. stage: "val"
  2553. }
  2554. python_param {
  2555. module: "caffe.layers.detectnet.mean_ap"
  2556. layer: "mAP"
  2557. param_str: "1280, 1280, 16"
  2558. }
  2559. }
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