~/py-faster-rcnn$ ./experiments/scripts/faster_rcnn_alt_opt.sh 0 ZF pascal_voc
+ set -e
+ export PYTHONUNBUFFERED=True
+ PYTHONUNBUFFERED=True
+ GPU_ID=0
+ NET=ZF
+ NET_lc=zf
+ DATASET=pascal_voc
+ array=($@)
+ len=3
+ EXTRA_ARGS=
+ EXTRA_ARGS_SLUG=
+ case $DATASET in
+ TRAIN_IMDB=voc_2007_trainval
+ TEST_IMDB=voc_2007_test
+ PT_DIR=pascal_voc
+ ITERS=40000
++ date +%Y-%m-%d_%H-%M-%S
+ LOG=experiments/logs/faster_rcnn_alt_opt_ZF_.txt.2017-09-30_13-10-33
+ exec
++ tee -a experiments/logs/faster_rcnn_alt_opt_ZF_.txt.2017-09-30_13-10-33
+ echo Logging output to experiments/logs/faster_rcnn_alt_opt_ZF_.txt.2017-09-30_13-10-33
Logging output to experiments/logs/faster_rcnn_alt_opt_ZF_.txt.2017-09-30_13-10-33
+ ./tools/train_faster_rcnn_alt_opt.py --gpu 0 --net_name ZF --weights data/imagenet_models/ZF.v2.caffemodel --imdb voc_2007_trainval --cfg experiments/cfgs/faster_rcnn_alt_opt.yml
Called with args:
Namespace(cfg_file='experiments/cfgs/faster_rcnn_alt_opt.yml', gpu_id=0, imdb_name='voc_2007_trainval', net_name='ZF', pretrained_model='data/imagenet_models/ZF.v2.caffemodel', set_cfgs=None)
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Stage 1 RPN, init from ImageNet model
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Init model: data/imagenet_models/ZF.v2.caffemodel
Using config:
{'DATA_DIR': '/home/py-faster-rcnn/data',
'DEDUP_BOXES': 0.0625,
'EPS': 1e-14,
'EXP_DIR': 'faster_rcnn_alt_opt',
'GPU_ID': 0,
'MATLAB': 'matlab',
'MODELS_DIR': '/home/py-faster-rcnn/models/pascal_voc',
'PIXEL_MEANS': array([[[ 102.9801, 115.9465, 122.7717]]]),
'RNG_SEED': 3,
'ROOT_DIR': '/home/icalc/py-faster-rcnn',
'TEST': {'BBOX_REG': True,
'HAS_RPN': True,
'MAX_SIZE': 1000,
'NMS': 0.3,
'PROPOSAL_METHOD': 'selective_search',
'RPN_MIN_SIZE': 16,
'RPN_NMS_THRESH': 0.7,
'RPN_POST_NMS_TOP_N': 300,
'RPN_PRE_NMS_TOP_N': 6000,
'SCALES': [600],
'SVM': False},
'TRAIN': {'ASPECT_GROUPING': True,
'BATCH_SIZE': 128,
'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': False,
'BBOX_REG': False,
'BBOX_THRESH': 0.5,
'BG_THRESH_HI': 0.5,
'BG_THRESH_LO': 0.0,
'FG_FRACTION': 0.25,
'FG_THRESH': 0.5,
'HAS_RPN': True,
'IMS_PER_BATCH': 1,
'MAX_SIZE': 1000,
'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_MIN_SIZE': 16,
'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_INFIX': 'stage1',
'SNAPSHOT_ITERS': 10000,
'USE_FLIPPED': True,
'USE_PREFETCH': False},
'USE_GPU_NMS': True}
Loaded dataset `voc_2007_trainval` for training
Set proposal method: gt
Appending horizontally-flipped training examples...
Process Process-1:
Traceback (most recent call last):
File "/usr/lib/python2.7/multiprocessing/process.py", line 258, in _bootstrap
self.run()
File "/usr/lib/python2.7/multiprocessing/process.py", line 114, in run
self._target(*self._args, **self._kwargs)
File "./tools/train_faster_rcnn_alt_opt.py", line 122, in train_rpn
roidb, imdb = get_roidb(imdb_name)
File "./tools/train_faster_rcnn_alt_opt.py", line 67, in get_roidb
roidb = get_training_roidb(imdb)
File "/home/py-faster-rcnn/tools/../lib/fast_rcnn/train.py", line 118, in get_training_roidb
imdb.append_flipped_images()
File "/home/py-faster-rcnn/tools/../lib/datasets/imdb.py", line 106, in append_flipped_images
boxes = self.roidb[i]['boxes'].copy()
File "/home/py-faster-rcnn/tools/../lib/datasets/imdb.py", line 67, in roidb
self._roidb = self.roidb_handler()
File "/home/py-faster-rcnn/tools/../lib/datasets/pascal_voc.py", line 107, in gt_roidb
for index in self.image_index]
File "/home/py-faster-rcnn/tools/../lib/datasets/pascal_voc.py", line 212, in _load_pascal_annotation
cls = self._class_to_ind[obj.find('name').text.lower().strip()]
KeyError: 'obj'
