Exemple #1
0
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals
from edict import AttrDict
import six
import numpy as np

_C = AttrDict()
cfg = _C
"""
Training options
"""
_C.TRAIN = AttrDict()

# scales an image's shortest side
_C.TRAIN.scales = [800]

# max size of longest side
_C.TRAIN.max_size = 1333

# images per GPU in minibatch
_C.TRAIN.im_per_batch = 1

# stopgrad at a spcified stage
_C.TRAIN.freeze_at = 2

# number of RPN proposals to keep before NMS
_C.TRAIN.rpn_pre_nms_top_n = 12000

# number of RPN proposals to keep after NMS
Exemple #2
0
#    http://www.apache.org/licenses/LICENSE-2.0
#Unless required by applicable law or agreed to in writing, software
#distributed under the License is distributed on an "AS IS" BASIS,
#WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
#See the License for the specific language governing permissions and
#limitations under the License. 

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals
from edict import AttrDict
import six
import numpy as np

_C = AttrDict()
cfg = _C

#
# Training options
#

# Snapshot period
_C.snapshot_iter = 2000

# min valid area for gt boxes
_C.gt_min_area = -1

# max target box number in an image
_C.max_box_num = 50
Exemple #3
0
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals
import sys
import distutils.util
import numpy as np
import six
from collections import deque
import argparse
import functools
from edict import AttrDict
import pdb

_C = AttrDict()
cfg = _C

#
# Training options
#

_C.data_dir = './veri'
# Snapshot period
_C.snapshot_iter = 2000

_C.num_instances = 1

_C.batch_size = 64

# pixel mean values
Exemple #4
0
#    http://www.apache.org/licenses/LICENSE-2.0
#Unless required by applicable law or agreed to in writing, software
#distributed under the License is distributed on an "AS IS" BASIS,
#WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
#See the License for the specific language governing permissions and
#limitations under the License. 

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals
from edict import AttrDict
import six
import numpy as np

_C = AttrDict()
cfg = _C

#
# Training options
#
_C.TRAIN = AttrDict()

# scales an image's shortest side
_C.TRAIN.scales = [800]

# max size of longest side
_C.TRAIN.max_size = 1333

# images per GPU in minibatch
_C.TRAIN.im_per_batch = 1
Exemple #5
0
#    http://www.apache.org/licenses/LICENSE-2.0
#Unless required by applicable law or agreed to in writing, software
#distributed under the License is distributed on an "AS IS" BASIS,
#WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
#See the License for the specific language governing permissions and
#limitations under the License.

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals
from edict import AttrDict
import six
import numpy as np

_C = AttrDict()
cfg = _C

#
# Training options
#
_C.TRAIN = AttrDict()

# scales an image's shortest side
_C.TRAIN.scales = [800]

# max size of longest side
_C.TRAIN.max_size = 1333

# images per GPU in minibatch
_C.TRAIN.im_per_batch = 1