(flappbird) luo@luo-ThinkPad-W540:tf-faster-rcnn$ ./experiments/scripts/train_faster_rcnn.sh 0 pascal_voc_0712 res101
+ set -e
+ export PYTHONUNBUFFERED=True
+ PYTHONUNBUFFERED=True
+ GPU_ID=0
+ DATASET=pascal_voc_0712
+ NET=res101
+ array=($@)
+ len=3
+ EXTRA_ARGS=
+ EXTRA_ARGS_SLUG=
+ case ${DATASET} in
+ TRAIN_IMDB=voc_2007_trainval+voc_2012_trainval
+ TEST_IMDB=voc_2007_test
+ STEPSIZE='[80000]'
+ ITERS=110000
+ ANCHORS='[8,16,32]'
+ RATIOS='[0.5,1,2]'
++ date +%Y-%m-%d_%H-%M-%S
+ LOG=experiments/logs/res101_voc_2007_trainval+voc_2012_trainval__res101.txt.2019-04-04_16-16-38
+ exec
++ tee -a experiments/logs/res101_voc_2007_trainval+voc_2012_trainval__res101.txt.2019-04-04_16-16-38
+ echo Logging output to experiments/logs/res101_voc_2007_trainval+voc_2012_trainval__res101.txt.2019-04-04_16-16-38
Logging output to experiments/logs/res101_voc_2007_trainval+voc_2012_trainval__res101.txt.2019-04-04_16-16-38
+ set +x
+ '[' '!' -f output/res101/voc_2007_trainval+voc_2012_trainval/default/res101_faster_rcnn_iter_110000.ckpt.index ']'
+ [[ ! -z '' ]]
+ CUDA_VISIBLE_DEVICES=0
+ time python ./tools/trainval_net.py --weight data/imagenet_weights/res101.ckpt --imdb voc_2007_trainval+voc_2012_trainval --imdbval voc_2007_test --iters 110000 --cfg experiments/cfgs/res101.yml --net res101 --set ANCHOR_SCALES '[8,16,32]' ANCHOR_RATIOS '[0.5,1,2]' TRAIN.STEPSIZE '[80000]'
Called with args:
Namespace(cfg_file='experiments/cfgs/res101.yml', imdb_name='voc_2007_trainval+voc_2012_trainval', imdbval_name='voc_2007_test', max_iters=110000, net='res101', set_cfgs=['ANCHOR_SCALES', '[8,16,32]', 'ANCHOR_RATIOS', '[0.5,1,2]', 'TRAIN.STEPSIZE', '[80000]'], tag='../output_model_2019/2019_04_04/', weight='data/imagenet_weights/res101.ckpt')
Using config:
{'ANCHOR_RATIOS': [0.5, 1, 2],
'ANCHOR_SCALES': [8, 16, 32],
'DATA_DIR': '/home/luo/TensorflowProject/tf-faster-rcnn/data',
'EXP_DIR': 'res101',
'MATLAB': 'matlab',
'MOBILENET': {'DEPTH_MULTIPLIER': 1.0,
'FIXED_LAYERS': 5,
'REGU_DEPTH': False,
'WEIGHT_DECAY': 4e-05},
'PIXEL_MEANS': array([[[102.9801, 115.9465, 122.7717]]]),
'POOLING_MODE': 'crop',
'POOLING_SIZE': 7,
'RESNET': {'FIXED_BLOCKS': 1, 'MAX_POOL': False},
'RNG_SEED': 3,
'ROOT_DIR': '/home/luo/TensorflowProject/tf-faster-rcnn',
'RPN_CHANNELS': 512,
'TEST': {'BBOX_REG': True,
'HAS_RPN': True,
'MAX_SIZE': 1000,
'MODE': 'nms',
'NMS': 0.3,
'PROPOSAL_METHOD': 'gt',
'RPN_NMS_THRESH': 0.7,
'RPN_POST_NMS_TOP_N': 300,
'RPN_PRE_NMS_TOP_N': 6000,
'RPN_TOP_N': 5000,
'SCALES': [600],
'SVM': False},
'TRAIN': {'ASPECT_GROUPING': False,
'BATCH_SIZE': 256,
'BBOX_INSIDE_WEIGHTS': [1.0, 1.0, 1.0, 1.0],
'BBOX_NORMALIZE_MEANS': [0.0, 0.0, 0.0, 0.0],
'BBOX_NORMALIZE_STDS': [0.1, 0.1, 0.2, 0.2],
'BBOX_NORMALIZE_TARGETS': True,
'BBOX_NORMALIZE_TARGETS_PRECOMPUTED': True,
'BBOX_REG': True,
'BBOX_THRESH': 0.5,
'BG_THRESH_HI': 0.5,
'BG_THRESH_LO': 0.0,
'BIAS_DECAY': False,
'DISPLAY': 20,
'DOUBLE_BIAS': False,
'FG_FRACTION': 0.25,
'FG_THRESH': 0.5,
'GAMMA': 0.1,
'HAS_RPN': True,
'IMS_PER_BATCH': 1,
'LEARNING_RATE': 0.001,
'MAX_SIZE': 1000,
'MOMENTUM': 0.9,
'PROPOSAL_METHOD': 'gt',
'RPN_BATCHSIZE': 256,
'RPN_BBOX_INSIDE_WEIGHTS': [1.0, 1.0, 1.0, 1.0],
'RPN_CLOBBER_POSITIVES': False,
'RPN_FG_FRACTION': 0.5,
'RPN_NEGATIVE_OVERLAP': 0.3,
'RPN_NMS_THRESH': 0.7,
'RPN_POSITIVE_OVERLAP': 0.7,
'RPN_POSITIVE_WEIGHT': -1.0,
'RPN_POST_NMS_TOP_N': 2000,
'RPN_PRE_NMS_TOP_N': 12000,
'SCALES': [600],
'SNAPSHOT_ITERS': 5000,
'SNAPSHOT_KEPT': 3,
'SNAPSHOT_PREFIX': 'res101_faster_rcnn',
'STEPSIZE': [80000],
'SUMMARY_INTERVAL': 180,
'TRUNCATED': False,
'USE_ALL_GT': True,
'USE_FLIPPED': True,
'USE_GT': False,
'WEIGHT_DECAY': 0.0001},
'USE_E2E_TF': True,
'USE_GPU_NMS': False}
Loaded dataset `voc_2007_trainval` for training
Set proposal method: gt
Appending horizontally-flipped training examples...
voc_2007_trainval gt roidb loaded from /home/luo/TensorflowProject/tf-faster-rcnn/data/cache/voc_2007_trainval_gt_roidb.pkl
done
Preparing training data...
done
Loaded dataset `voc_2012_trainval` for training
Set proposal method: gt
Appending horizontally-flipped training examples...
wrote gt roidb to /home/luo/TensorflowProject/tf-faster-rcnn/data/cache/voc_2012_trainval_gt_roidb.pkl
done
Preparing training data...
done
3100 roidb entries
Output will be saved to `/home/luo/TensorflowProject/tf-faster-rcnn/output/res101/voc_2007_trainval+voc_2012_trainval/../output_model_2019/2019_04_04/`
TensorFlow summaries will be saved to `/home/luo/TensorflowProject/tf-faster-rcnn/tensorboard/res101/voc_2007_trainval+voc_2012_trainval/../output_model_2019/2019_04_04/`
Loaded dataset `voc_2007_test` for training
Set proposal method: gt
Preparing training data...
wrote gt roidb to /home/luo/TensorflowProject/tf-faster-rcnn/data/cache/voc_2007_test_gt_roidb.pkl
done
400 validation roidb entries
Filtered 0 roidb entries: 3100 -> 3100
Filtered 0 roidb entries: 400 -> 400
2019-04-04 16:16:42.984263: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
Solving...
/home/luo/anaconda3/envs/flappbird/lib/python3.6/site-packages/tensorflow/python/ops/gradients_impl.py:100: UserWarning: Converting sparse IndexedSlices to a dense Tensor of unknown shape. This may consume a large amount of memory.
"Converting sparse IndexedSlices to a dense Tensor of unknown shape. "
Loading initial model weights from data/imagenet_weights/res101.ckpt
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Loaded.
Fix Resnet V1 layers..
Fixed.
2019-04-04 16:17:03.078635: W tensorflow/core/framework/allocator.cc:108] Allocation of 71442432 exceeds 10% of system memory.
2019-04-04 16:17:03.078653: W tensorflow/core/framework/allocator.cc:108] Allocation of 71442432 exceeds 10% of system memory.
2019-04-04 16:17:03.157909: W tensorflow/core/framework/allocator.cc:108] Allocation of 102760448 exceeds 10% of system memory.
2019-04-04 16:17:04.281898: W tensorflow/core/framework/allocator.cc:108] Allocation of 102760448 exceeds 10% of system memory.
2019-04-04 16:17:05.142933: W tensorflow/core/framework/allocator.cc:108] Allocation of 102760448 exceeds 10% of system memory.
iter: 20 / 110000, total loss: 1.226864
>>> rpn_loss_cls: 0.124033
>>> rpn_loss_box: 0.083634
>>> loss_cls: 0.329475
>>> loss_box: 0.307215
>>> lr: 0.001000
speed: 38.009s / iter
iter: 40 / 110000, total loss: 1.041049
>>> rpn_loss_cls: 0.121411
>>> rpn_loss_box: 0.247878
>>> loss_cls: 0.139931
>>> loss_box: 0.149327
>>> lr: 0.001000
speed: 37.712s / iter
iter: 60 / 110000, total loss: 1.060756
>>> rpn_loss_cls: 0.135637
>>> rpn_loss_box: 0.022396
>>> loss_cls: 0.147341
>>> loss_box: 0.372890
>>> lr: 0.001000
speed: 37.601s / iter
iter: 80 / 110000, total loss: 0.826487
>>> rpn_loss_cls: 0.055820
>>> rpn_loss_box: 0.079405
>>> loss_cls: 0.114159
>>> loss_box: 0.194618
>>> lr: 0.001000
speed: 37.545s / iter

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