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  1. python tools/train.py configs/faster_rcnn/custom_faster_rcnn_r50_fpn_1x_coco.py --gpus 1
  2. 2020-08-26 19:27:53,187 - mmdet - INFO - Environment info:
  3. ------------------------------------------------------------
  4. sys.platform: linux
  5. Python: 3.7.7 (default, May 7 2020, 21:25:33) [GCC 7.3.0]
  6. CUDA available: True
  7. CUDA_HOME: /usr/local/cuda
  8. NVCC: Cuda compilation tools, release 10.0, V10.0.130
  9. GPU 0: GeForce GTX 1080
  10. GCC: gcc (Ubuntu 9.3.0-10ubuntu2) 9.3.0
  11. PyTorch: 1.6.0
  12. PyTorch compiling details: PyTorch built with:
  13. - GCC 7.3
  14. - C++ Version: 201402
  15. - Intel(R) Math Kernel Library Version 2020.0.1 Product Build 20200208 for Intel(R) 64 architecture applications
  16. - Intel(R) MKL-DNN v1.5.0 (Git Hash e2ac1fac44c5078ca927cb9b90e1b3066a0b2ed0)
  17. - OpenMP 201511 (a.k.a. OpenMP 4.5)
  18. - NNPACK is enabled
  19. - CPU capability usage: AVX
  20. - CUDA Runtime 10.2
  21. - NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_61,code=sm_61;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_37,code=compute_37
  22. - CuDNN 7.6.5
  23. - Magma 2.5.2
  24. - Build settings: BLAS=MKL, BUILD_TYPE=Release, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DUSE_VULKAN_WRAPPER -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-variable -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-stringop-overflow, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, USE_CUDA=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, USE_STATIC_DISPATCH=OFF,
  25.  
  26. TorchVision: 0.7.0
  27. OpenCV: 4.4.0
  28. MMCV: 1.0.5
  29. MMDetection: 2.3.0+68d860d
  30. MMDetection Compiler: GCC 7.3
  31. MMDetection CUDA Compiler: 10.2
  32. ------------------------------------------------------------
  33.  
  34. 2020-08-26 19:27:53,188 - mmdet - INFO - Distributed training: False
  35. 2020-08-26 19:27:53,528 - mmdet - INFO - Config:
  36. model = dict(
  37. type='FasterRCNN',
  38. pretrained='torchvision://resnet50',
  39. backbone=dict(
  40. type='ResNet',
  41. depth=50,
  42. num_stages=4,
  43. out_indices=(0, 1, 2, 3),
  44. frozen_stages=1,
  45. norm_cfg=dict(type='BN', requires_grad=True),
  46. norm_eval=True,
  47. style='pytorch'),
  48. neck=dict(
  49. type='FPN',
  50. in_channels=[256, 512, 1024, 2048],
  51. out_channels=256,
  52. num_outs=5),
  53. rpn_head=dict(
  54. type='RPNHead',
  55. in_channels=256,
  56. feat_channels=256,
  57. anchor_generator=dict(
  58. type='AnchorGenerator',
  59. scales=[8],
  60. ratios=[0.5, 1.0, 2.0],
  61. strides=[4, 8, 16, 32, 64]),
  62. bbox_coder=dict(
  63. type='DeltaXYWHBBoxCoder',
  64. target_means=[0.0, 0.0, 0.0, 0.0],
  65. target_stds=[1.0, 1.0, 1.0, 1.0]),
  66. loss_cls=dict(
  67. type='CrossEntropyLoss', use_sigmoid=True, loss_weight=1.0),
  68. loss_bbox=dict(type='L1Loss', loss_weight=1.0)),
  69. roi_head=dict(
  70. type='StandardRoIHead',
  71. bbox_roi_extractor=dict(
  72. type='SingleRoIExtractor',
  73. roi_layer=dict(type='RoIAlign', output_size=7, sampling_ratio=0),
  74. out_channels=256,
  75. featmap_strides=[4, 8, 16, 32]),
  76. bbox_head=dict(
  77. type='Shared2FCBBoxHead',
  78. in_channels=256,
  79. fc_out_channels=1024,
  80. roi_feat_size=7,
  81. num_classes=80,
  82. bbox_coder=dict(
  83. type='DeltaXYWHBBoxCoder',
  84. target_means=[0.0, 0.0, 0.0, 0.0],
  85. target_stds=[0.1, 0.1, 0.2, 0.2]),
  86. reg_class_agnostic=False,
  87. loss_cls=dict(
  88. type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0),
  89. loss_bbox=dict(type='L1Loss', loss_weight=1.0))))
  90. train_cfg = dict(
  91. rpn=dict(
  92. assigner=dict(
  93. type='MaxIoUAssigner',
  94. pos_iou_thr=0.7,
  95. neg_iou_thr=0.3,
  96. min_pos_iou=0.3,
  97. match_low_quality=True,
  98. ignore_iof_thr=-1),
  99. sampler=dict(
  100. type='RandomSampler',
  101. num=256,
  102. pos_fraction=0.5,
  103. neg_pos_ub=-1,
  104. add_gt_as_proposals=False),
  105. allowed_border=-1,
  106. pos_weight=-1,
  107. debug=False),
  108. rpn_proposal=dict(
  109. nms_across_levels=False,
  110. nms_pre=2000,
  111. nms_post=1000,
  112. max_num=1000,
  113. nms_thr=0.7,
  114. min_bbox_size=0),
  115. rcnn=dict(
  116. assigner=dict(
  117. type='MaxIoUAssigner',
  118. pos_iou_thr=0.5,
  119. neg_iou_thr=0.5,
  120. min_pos_iou=0.5,
  121. match_low_quality=False,
  122. ignore_iof_thr=-1),
  123. sampler=dict(
  124. type='RandomSampler',
  125. num=512,
  126. pos_fraction=0.25,
  127. neg_pos_ub=-1,
  128. add_gt_as_proposals=True),
  129. pos_weight=-1,
  130. debug=False))
  131. test_cfg = dict(
  132. rpn=dict(
  133. nms_across_levels=False,
  134. nms_pre=1000,
  135. nms_post=1000,
  136. max_num=1000,
  137. nms_thr=0.7,
  138. min_bbox_size=0),
  139. rcnn=dict(
  140. score_thr=0.05,
  141. nms=dict(type='nms', iou_threshold=0.5),
  142. max_per_img=100))
  143. dataset_type = 'CocoDataset'
  144. data_root = 'data/synth_rocks/'
  145. classes = ['large_rock']
  146. img_norm_cfg = dict(
  147. mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
  148. train_pipeline = [
  149. dict(type='LoadImageFromFile'),
  150. dict(type='LoadAnnotations', with_bbox=True),
  151. dict(type='Resize', img_scale=(1333, 800), keep_ratio=True),
  152. dict(type='RandomFlip', flip_ratio=0.5),
  153. dict(
  154. type='Normalize',
  155. mean=[123.675, 116.28, 103.53],
  156. std=[58.395, 57.12, 57.375],
  157. to_rgb=True),
  158. dict(type='Pad', size_divisor=32),
  159. dict(type='DefaultFormatBundle'),
  160. dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels'])
  161. ]
  162. test_pipeline = [
  163. dict(type='LoadImageFromFile'),
  164. dict(
  165. type='MultiScaleFlipAug',
  166. img_scale=(1333, 800),
  167. flip=False,
  168. transforms=[
  169. dict(type='Resize', keep_ratio=True),
  170. dict(type='RandomFlip'),
  171. dict(
  172. type='Normalize',
  173. mean=[123.675, 116.28, 103.53],
  174. std=[58.395, 57.12, 57.375],
  175. to_rgb=True),
  176. dict(type='Pad', size_divisor=32),
  177. dict(type='ImageToTensor', keys=['img']),
  178. dict(type='Collect', keys=['img'])
  179. ])
  180. ]
  181. data = dict(
  182. samples_per_gpu=2,
  183. workers_per_gpu=2,
  184. train=dict(
  185. type='CocoDataset',
  186. classes=['large_rock'],
  187. ann_file='data/synth_rocks/annotations/train.json',
  188. img_prefix='data/synth_rocks/train/',
  189. pipeline=[
  190. dict(type='LoadImageFromFile'),
  191. dict(type='LoadAnnotations', with_bbox=True),
  192. dict(type='Resize', img_scale=(1333, 800), keep_ratio=True),
  193. dict(type='RandomFlip', flip_ratio=0.5),
  194. dict(
  195. type='Normalize',
  196. mean=[123.675, 116.28, 103.53],
  197. std=[58.395, 57.12, 57.375],
  198. to_rgb=True),
  199. dict(type='Pad', size_divisor=32),
  200. dict(type='DefaultFormatBundle'),
  201. dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels'])
  202. ]),
  203. val=dict(
  204. type='CocoDataset',
  205. classes=['large_rock'],
  206. ann_file='data/synth_rocks/annotations/val.json',
  207. img_prefix='data/synth_rocks/val/',
  208. pipeline=[
  209. dict(type='LoadImageFromFile'),
  210. dict(
  211. type='MultiScaleFlipAug',
  212. img_scale=(1333, 800),
  213. flip=False,
  214. transforms=[
  215. dict(type='Resize', keep_ratio=True),
  216. dict(type='RandomFlip'),
  217. dict(
  218. type='Normalize',
  219. mean=[123.675, 116.28, 103.53],
  220. std=[58.395, 57.12, 57.375],
  221. to_rgb=True),
  222. dict(type='Pad', size_divisor=32),
  223. dict(type='ImageToTensor', keys=['img']),
  224. dict(type='Collect', keys=['img'])
  225. ])
  226. ]),
  227. test=dict(
  228. type='CocoDataset',
  229. classes=['large_rock'],
  230. ann_file='data/synth_rocks/annotations/val.json',
  231. img_prefix='data/synth_rocks/val/',
  232. pipeline=[
  233. dict(type='LoadImageFromFile'),
  234. dict(
  235. type='MultiScaleFlipAug',
  236. img_scale=(1333, 800),
  237. flip=False,
  238. transforms=[
  239. dict(type='Resize', keep_ratio=True),
  240. dict(type='RandomFlip'),
  241. dict(
  242. type='Normalize',
  243. mean=[123.675, 116.28, 103.53],
  244. std=[58.395, 57.12, 57.375],
  245. to_rgb=True),
  246. dict(type='Pad', size_divisor=32),
  247. dict(type='ImageToTensor', keys=['img']),
  248. dict(type='Collect', keys=['img'])
  249. ])
  250. ]))
  251. evaluation = dict(interval=1, metric='bbox')
  252. optimizer = dict(type='SGD', lr=0.02, momentum=0.9, weight_decay=0.0001)
  253. optimizer_config = dict(grad_clip=None)
  254. lr_config = dict(
  255. policy='step',
  256. warmup='linear',
  257. warmup_iters=500,
  258. warmup_ratio=0.001,
  259. step=[8, 11])
  260. total_epochs = 12
  261. checkpoint_config = dict(interval=50, by_epoch=False)
  262. log_config = dict(interval=50, hooks=[dict(type='TextLoggerHook')])
  263. dist_params = dict(backend='nccl')
  264. log_level = 'INFO'
  265. load_from = None
  266. resume_from = None
  267. workflow = [('train', 1)]
  268. work_dir = './work_dirs/custom_faster_rcnn_r50_fpn_1x_coco'
  269. gpu_ids = range(0, 1)
  270.  
  271. 2020-08-26 19:27:53,984 - mmdet - INFO - load model from: torchvision://resnet50
  272. 2020-08-26 19:27:54,458 - mmdet - WARNING - The model and loaded state dict do not match exactly
  273.  
  274. unexpected key in source state_dict: fc.weight, fc.bias
  275.  
  276. loading annotations into memory...
  277. Done (t=0.89s)
  278. creating index...
  279. index created!
  280. loading annotations into memory...
  281. Done (t=0.21s)
  282. creating index...
  283. index created!
  284. 2020-08-26 19:27:59,188 - mmdet - INFO - Start running, host: u42@u42, work_dir: /home/u42/Documents/mmdetection/work_dirs/custom_faster_rcnn_r50_fpn_1x_coco
  285. 2020-08-26 19:27:59,188 - mmdet - INFO - workflow: [('train', 1)], max: 12 epochs
  286. 2020-08-26 19:28:27,204 - mmdet - INFO - Saving checkpoint at 50 iterations
  287. 2020-08-26 19:28:29,196 - mmdet - INFO - Epoch [1][50/3907] lr: 1.978e-03, eta: 7:48:24, time: 0.600, data_time: 0.051, memory: 3482, loss_rpn_cls: 0.2715, loss_rpn_bbox: 0.0325, loss_cls: 0.7673, acc: 89.1113, loss_bbox: 0.0209, loss: 1.0923
  288. 2020-08-26 19:28:54,916 - mmdet - INFO - Saving checkpoint at 100 iterations
  289. 2020-08-26 19:28:56,918 - mmdet - INFO - Epoch [1][100/3907] lr: 3.976e-03, eta: 7:30:06, time: 0.554, data_time: 0.005, memory: 3482, loss_rpn_cls: 0.0380, loss_rpn_bbox: 0.0410, loss_cls: 0.0617, acc: 99.0371, loss_bbox: 0.0361, loss: 0.1768
  290. 2020-08-26 19:29:22,669 - mmdet - INFO - Saving checkpoint at 150 iterations
  291. 2020-08-26 19:29:24,660 - mmdet - INFO - Epoch [1][150/3907] lr: 5.974e-03, eta: 7:23:48, time: 0.555, data_time: 0.005, memory: 3482, loss_rpn_cls: 0.0398, loss_rpn_bbox: 0.0290, loss_cls: 0.0593, acc: 98.7227, loss_bbox: 0.0499, loss: 0.1780
  292. 2020-08-26 19:29:50,502 - mmdet - INFO - Saving checkpoint at 200 iterations
  293. 2020-08-26 19:29:52,502 - mmdet - INFO - Epoch [1][200/3907] lr: 7.972e-03, eta: 7:20:48, time: 0.557, data_time: 0.005, memory: 3482, loss_rpn_cls: 0.0344, loss_rpn_bbox: 0.0313, loss_cls: 0.0625, acc: 98.9512, loss_bbox: 0.0402, loss: 0.1683
  294. 2020-08-26 19:30:18,907 - mmdet - INFO - Saving checkpoint at 250 iterations
  295. 2020-08-26 19:30:20,899 - mmdet - INFO - Epoch [1][250/3907] lr: 9.970e-03, eta: 7:20:31, time: 0.568, data_time: 0.005, memory: 3482, loss_rpn_cls: 0.0283, loss_rpn_bbox: 0.0242, loss_cls: 0.0466, acc: 98.8867, loss_bbox: 0.0430, loss: 0.1422
  296. 2020-08-26 19:30:46,801 - mmdet - INFO - Saving checkpoint at 300 iterations
  297. 2020-08-26 19:30:48,789 - mmdet - INFO - Epoch [1][300/3907] lr: 1.197e-02, eta: 7:18:54, time: 0.558, data_time: 0.005, memory: 3482, loss_rpn_cls: 0.0367, loss_rpn_bbox: 0.0255, loss_cls: 0.0512, acc: 98.8633, loss_bbox: 0.0450, loss: 0.1585
  298. 2020-08-26 19:31:14,377 - mmdet - INFO - Saving checkpoint at 350 iterations
  299. 2020-08-26 19:31:16,376 - mmdet - INFO - Epoch [1][350/3907] lr: 1.397e-02, eta: 7:16:56, time: 0.552, data_time: 0.005, memory: 3482, loss_rpn_cls: 0.0298, loss_rpn_bbox: 0.0401, loss_cls: 0.0642, acc: 98.5762, loss_bbox: 0.0587, loss: 0.1929
  300. 2020-08-26 19:31:42,010 - mmdet - INFO - Saving checkpoint at 400 iterations
  301. 2020-08-26 19:31:44,051 - mmdet - INFO - Epoch [1][400/3907] lr: 1.596e-02, eta: 7:15:30, time: 0.554, data_time: 0.005, memory: 3482, loss_rpn_cls: 0.0474, loss_rpn_bbox: 0.0507, loss_cls: 0.0605, acc: 98.9258, loss_bbox: 0.0424, loss: 0.2009
  302. 2020-08-26 19:32:09,704 - mmdet - INFO - Saving checkpoint at 450 iterations
  303. 2020-08-26 19:32:11,729 - mmdet - INFO - Epoch [1][450/3907] lr: 1.796e-02, eta: 7:14:18, time: 0.554, data_time: 0.005, memory: 3482, loss_rpn_cls: 0.0288, loss_rpn_bbox: 0.0342, loss_cls: 0.0698, acc: 98.7734, loss_bbox: 0.0495, loss: 0.1823
  304. 2020-08-26 19:32:37,683 - mmdet - INFO - Saving checkpoint at 500 iterations
  305. 2020-08-26 19:32:39,671 - mmdet - INFO - Epoch [1][500/3907] lr: 1.996e-02, eta: 7:13:39, time: 0.559, data_time: 0.005, memory: 3482, loss_rpn_cls: 0.0395, loss_rpn_bbox: 0.0446, loss_cls: 0.1208, acc: 98.3965, loss_bbox: 0.0597, loss: 0.2645
  306. 2020-08-26 19:33:05,797 - mmdet - INFO - Saving checkpoint at 550 iterations
  307. 2020-08-26 19:33:07,823 - mmdet - INFO - Epoch [1][550/3907] lr: 2.000e-02, eta: 7:13:19, time: 0.563, data_time: 0.005, memory: 3482, loss_rpn_cls: 0.0420, loss_rpn_bbox: 0.0401, loss_cls: 0.0984, acc: 98.8262, loss_bbox: 0.0474, loss: 0.2279
  308. 2020-08-26 19:33:33,309 - mmdet - INFO - Saving checkpoint at 600 iterations
  309. 2020-08-26 19:33:35,317 - mmdet - INFO - Epoch [1][600/3907] lr: 2.000e-02, eta: 7:12:08, time: 0.550, data_time: 0.005, memory: 3482, loss_rpn_cls: 0.0501, loss_rpn_bbox: 0.0469, loss_cls: 0.0905, acc: 98.8379, loss_bbox: 0.0454, loss: 0.2329
  310. 2020-08-26 19:34:00,467 - mmdet - INFO - Saving checkpoint at 650 iterations
  311. 2020-08-26 19:34:02,487 - mmdet - INFO - Epoch [1][650/3907] lr: 2.000e-02, eta: 7:10:40, time: 0.543, data_time: 0.005, memory: 3482, loss_rpn_cls: 0.0250, loss_rpn_bbox: 0.0379, loss_cls: 0.2915, acc: 98.9121, loss_bbox: 0.0425, loss: 0.3969
  312. 2020-08-26 19:34:28,406 - mmdet - INFO - Saving checkpoint at 700 iterations
  313. 2020-08-26 19:34:30,423 - mmdet - INFO - Epoch [1][700/3907] lr: 2.000e-02, eta: 7:10:11, time: 0.559, data_time: 0.005, memory: 3482, loss_rpn_cls: 0.0358, loss_rpn_bbox: 0.0400, loss_cls: 0.0589, acc: 98.6133, loss_bbox: 0.0543, loss: 0.1891
  314. 2020-08-26 19:34:56,054 - mmdet - INFO - Saving checkpoint at 750 iterations
  315. 2020-08-26 19:34:58,040 - mmdet - INFO - Epoch [1][750/3907] lr: 2.000e-02, eta: 7:09:23, time: 0.552, data_time: 0.005, memory: 3482, loss_rpn_cls: 0.0468, loss_rpn_bbox: 0.0361, loss_cls: 0.0637, acc: 98.5059, loss_bbox: 0.0574, loss: 0.2039
  316. 2020-08-26 19:35:23,959 - mmdet - INFO - Saving checkpoint at 800 iterations
  317. 2020-08-26 19:35:25,964 - mmdet - INFO - Epoch [1][800/3907] lr: 2.000e-02, eta: 7:08:55, time: 0.558, data_time: 0.005, memory: 3482, loss_rpn_cls: 0.0438, loss_rpn_bbox: 0.0395, loss_cls: 0.0526, acc: 98.8770, loss_bbox: 0.0435, loss: 0.1794
  318. 2020-08-26 19:35:51,695 - mmdet - INFO - Saving checkpoint at 850 iterations
  319. 2020-08-26 19:35:53,712 - mmdet - INFO - Epoch [1][850/3907] lr: 2.000e-02, eta: 7:08:18, time: 0.555, data_time: 0.005, memory: 3482, loss_rpn_cls: 0.0428, loss_rpn_bbox: 0.0380, loss_cls: 0.0634, acc: 98.6309, loss_bbox: 0.0537, loss: 0.1979
  320. 2020-08-26 19:36:18,825 - mmdet - INFO - Saving checkpoint at 900 iterations
  321. 2020-08-26 19:36:20,843 - mmdet - INFO - Epoch [1][900/3907] lr: 2.000e-02, eta: 7:07:10, time: 0.543, data_time: 0.005, memory: 3482, loss_rpn_cls: 0.0400, loss_rpn_bbox: 0.0421, loss_cls: 0.0542, acc: 98.9355, loss_bbox: 0.0399, loss: 0.1761
  322. 2020-08-26 19:36:46,272 - mmdet - INFO - Saving checkpoint at 950 iterations
  323. 2020-08-26 19:36:48,270 - mmdet - INFO - Epoch [1][950/3907] lr: 2.000e-02, eta: 7:06:21, time: 0.549, data_time: 0.005, memory: 3482, loss_rpn_cls: 0.0261, loss_rpn_bbox: 0.0247, loss_cls: 0.0560, acc: 98.7480, loss_bbox: 0.0495, loss: 0.1563
  324. 2020-08-26 19:37:14,323 - mmdet - INFO - Saving checkpoint at 1000 iterations
  325. 2020-08-26 19:37:16,322 - mmdet - INFO - Epoch [1][1000/3907] lr: 2.000e-02, eta: 7:06:03, time: 0.561, data_time: 0.005, memory: 3482, loss_rpn_cls: 0.0399, loss_rpn_bbox: 0.0386, loss_cls: 0.0554, acc: 98.6875, loss_bbox: 0.0509, loss: 0.1848
  326. 2020-08-26 19:37:42,277 - mmdet - INFO - Saving checkpoint at 1050 iterations
  327. 2020-08-26 19:37:44,294 - mmdet - INFO - Epoch [1][1050/3907] lr: 2.000e-02, eta: 7:05:40, time: 0.559, data_time: 0.005, memory: 3482, loss_rpn_cls: 0.0385, loss_rpn_bbox: 0.0296, loss_cls: 0.0575, acc: 98.6426, loss_bbox: 0.0544, loss: 0.1799
  328. 2020-08-26 19:38:09,950 - mmdet - INFO - Saving checkpoint at 1100 iterations
  329. 2020-08-26 19:38:11,962 - mmdet - INFO - Epoch [1][1100/3907] lr: 2.000e-02, eta: 7:05:04, time: 0.553, data_time: 0.005, memory: 3482, loss_rpn_cls: 0.0454, loss_rpn_bbox: 0.0349, loss_cls: 0.0556, acc: 98.7168, loss_bbox: 0.0504, loss: 0.1864
  330. 2020-08-26 19:38:36,478 - mmdet - INFO - Saving checkpoint at 1150 iterations
  331. 2020-08-26 19:38:38,517 - mmdet - INFO - Epoch [1][1150/3907] lr: 2.000e-02, eta: 7:03:44, time: 0.531, data_time: 0.005, memory: 3482, loss_rpn_cls: 0.0421, loss_rpn_bbox: 0.0494, loss_cls: 0.0566, acc: 98.7051, loss_bbox: 0.0497, loss: 0.1978
  332. 2020-08-26 19:39:03,147 - mmdet - INFO - Saving checkpoint at 1200 iterations
  333. 2020-08-26 19:39:05,176 - mmdet - INFO - Epoch [1][1200/3907] lr: 2.000e-02, eta: 7:02:33, time: 0.533, data_time: 0.005, memory: 3482, loss_rpn_cls: 0.0397, loss_rpn_bbox: 0.0324, loss_cls: 0.0562, acc: 98.6035, loss_bbox: 0.0552, loss: 0.1835
  334. 2020-08-26 19:39:29,997 - mmdet - INFO - Saving checkpoint at 1250 iterations
  335. 2020-08-26 19:39:32,000 - mmdet - INFO - Epoch [1][1250/3907] lr: 2.000e-02, eta: 7:01:32, time: 0.536, data_time: 0.006, memory: 3482, loss_rpn_cls: 0.0386, loss_rpn_bbox: 0.0439, loss_cls: 0.0569, acc: 98.5977, loss_bbox: 0.0536, loss: 0.1929
  336. 2020-08-26 19:39:56,881 - mmdet - INFO - Saving checkpoint at 1300 iterations
  337. 2020-08-26 19:39:58,863 - mmdet - INFO - Epoch [1][1300/3907] lr: 2.000e-02, eta: 7:00:34, time: 0.537, data_time: 0.005, memory: 3482, loss_rpn_cls: 0.0251, loss_rpn_bbox: 0.0267, loss_cls: 0.0548, acc: 98.6055, loss_bbox: 0.0516, loss: 0.1581
  338. 2020-08-26 19:40:23,810 - mmdet - INFO - Saving checkpoint at 1350 iterations
  339. 2020-08-26 19:40:25,799 - mmdet - INFO - Epoch [1][1350/3907] lr: 2.000e-02, eta: 6:59:41, time: 0.539, data_time: 0.005, memory: 3482, loss_rpn_cls: 0.0279, loss_rpn_bbox: 0.0303, loss_cls: 0.0537, acc: 98.5469, loss_bbox: 0.0553, loss: 0.1673
  340. 2020-08-26 19:40:50,615 - mmdet - INFO - Saving checkpoint at 1400 iterations
  341. 2020-08-26 19:40:52,591 - mmdet - INFO - Epoch [1][1400/3907] lr: 2.000e-02, eta: 6:58:46, time: 0.536, data_time: 0.005, memory: 3482, loss_rpn_cls: 0.0323, loss_rpn_bbox: 0.0346, loss_cls: 0.0418, acc: 98.9531, loss_bbox: 0.0379, loss: 0.1467
  342. 2020-08-26 19:41:17,471 - mmdet - INFO - Saving checkpoint at 1450 iterations
  343. 2020-08-26 19:41:19,446 - mmdet - INFO - Epoch [1][1450/3907] lr: 2.000e-02, eta: 6:57:54, time: 0.537, data_time: 0.005, memory: 3482, loss_rpn_cls: 0.0319, loss_rpn_bbox: 0.0299, loss_cls: 0.0526, acc: 98.6582, loss_bbox: 0.0514, loss: 0.1659
  344. 2020-08-26 19:41:44,146 - mmdet - INFO - Saving checkpoint at 1500 iterations
  345. 2020-08-26 19:41:46,159 - mmdet - INFO - Epoch [1][1500/3907] lr: 2.000e-02, eta: 6:57:00, time: 0.534, data_time: 0.005, memory: 3482, loss_rpn_cls: 0.0178, loss_rpn_bbox: 0.0207, loss_cls: 0.0572, acc: 98.5195, loss_bbox: 0.0573, loss: 0.1530
  346. 2020-08-26 19:42:11,132 - mmdet - INFO - Saving checkpoint at 1550 iterations
  347. 2020-08-26 19:42:13,138 - mmdet - INFO - Epoch [1][1550/3907] lr: 2.000e-02, eta: 6:56:15, time: 0.540, data_time: 0.005, memory: 3482, loss_rpn_cls: 0.0209, loss_rpn_bbox: 0.0222, loss_cls: 0.0537, acc: 98.5469, loss_bbox: 0.0544, loss: 0.1513
  348. 2020-08-26 19:42:37,484 - mmdet - INFO - Saving checkpoint at 1600 iterations
  349. 2020-08-26 19:42:39,497 - mmdet - INFO - Epoch [1][1600/3907] lr: 2.000e-02, eta: 6:55:14, time: 0.527, data_time: 0.005, memory: 3482, loss_rpn_cls: 0.0189, loss_rpn_bbox: 0.0258, loss_cls: 0.0546, acc: 98.3789, loss_bbox: 0.0570, loss: 0.1563
  350. 2020-08-26 19:43:04,171 - mmdet - INFO - Saving checkpoint at 1650 iterations
  351. 2020-08-26 19:43:06,179 - mmdet - INFO - Epoch [1][1650/3907] lr: 2.000e-02, eta: 6:54:24, time: 0.534, data_time: 0.005, memory: 3482, loss_rpn_cls: 0.0300, loss_rpn_bbox: 0.0329, loss_cls: 0.0622, acc: 98.2988, loss_bbox: 0.0676, loss: 0.1926
  352. 2020-08-26 19:43:31,068 - mmdet - INFO - Saving checkpoint at 1700 iterations
  353. 2020-08-26 19:43:33,059 - mmdet - INFO - Epoch [1][1700/3907] lr: 2.000e-02, eta: 6:53:40, time: 0.538, data_time: 0.005, memory: 3482, loss_rpn_cls: 0.0366, loss_rpn_bbox: 0.0354, loss_cls: 0.0551, acc: 98.4844, loss_bbox: 0.0570, loss: 0.1841
  354. 2020-08-26 19:43:58,601 - mmdet - INFO - Saving checkpoint at 1750 iterations
  355. 2020-08-26 19:44:00,605 - mmdet - INFO - Epoch [1][1750/3907] lr: 2.000e-02, eta: 6:53:15, time: 0.551, data_time: 0.005, memory: 3482, loss_rpn_cls: 0.0310, loss_rpn_bbox: 0.0309, loss_cls: 0.0553, acc: 98.4473, loss_bbox: 0.0575, loss: 0.1747
  356. 2020-08-26 19:44:25,324 - mmdet - INFO - Saving checkpoint at 1800 iterations
  357. 2020-08-26 19:44:27,318 - mmdet - INFO - Epoch [1][1800/3907] lr: 2.000e-02, eta: 6:52:28, time: 0.534, data_time: 0.005, memory: 3482, loss_rpn_cls: 0.0241, loss_rpn_bbox: 0.0247, loss_cls: 0.0515, acc: 98.5879, loss_bbox: 0.0518, loss: 0.1521
  358. 2020-08-26 19:44:51,993 - mmdet - INFO - Saving checkpoint at 1850 iterations
  359. 2020-08-26 19:44:53,996 - mmdet - INFO - Epoch [1][1850/3907] lr: 2.000e-02, eta: 6:51:42, time: 0.534, data_time: 0.006, memory: 3482, loss_rpn_cls: 0.0311, loss_rpn_bbox: 0.0226, loss_cls: 0.0517, acc: 98.6289, loss_bbox: 0.0487, loss: 0.1542
  360. 2020-08-26 19:45:19,420 - mmdet - INFO - Saving checkpoint at 1900 iterations
  361. 2020-08-26 19:45:21,429 - mmdet - INFO - Epoch [1][1900/3907] lr: 2.000e-02, eta: 6:51:15, time: 0.549, data_time: 0.005, memory: 3482, loss_rpn_cls: 0.0362, loss_rpn_bbox: 0.0296, loss_cls: 0.0588, acc: 98.4062, loss_bbox: 0.0586, loss: 0.1831
  362. 2020-08-26 19:45:47,785 - mmdet - INFO - Saving checkpoint at 1950 iterations
  363. 2020-08-26 19:45:49,834 - mmdet - INFO - Epoch [1][1950/3907] lr: 2.000e-02, eta: 6:51:10, time: 0.568, data_time: 0.006, memory: 3482, loss_rpn_cls: 0.0237, loss_rpn_bbox: 0.0301, loss_cls: 0.0600, acc: 98.3633, loss_bbox: 0.0608, loss: 0.1747
  364. 2020-08-26 19:46:16,472 - mmdet - INFO - Saving checkpoint at 2000 iterations
  365. 2020-08-26 19:46:18,533 - mmdet - INFO - Epoch [1][2000/3907] lr: 2.000e-02, eta: 6:51:11, time: 0.574, data_time: 0.005, memory: 3482, loss_rpn_cls: 0.0236, loss_rpn_bbox: 0.0350, loss_cls: 0.0617, acc: 98.1738, loss_bbox: 0.0683, loss: 0.1886
  366. 2020-08-26 19:46:44,215 - mmdet - INFO - Saving checkpoint at 2050 iterations
  367. 2020-08-26 19:46:46,235 - mmdet - INFO - Epoch [1][2050/3907] lr: 2.000e-02, eta: 6:50:48, time: 0.554, data_time: 0.006, memory: 3482, loss_rpn_cls: 0.0250, loss_rpn_bbox: 0.0256, loss_cls: 0.0543, acc: 98.4336, loss_bbox: 0.0568, loss: 0.1617
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