本文整理汇总了Python中fast_rcnn.train.get_training_roidb方法的典型用法代码示例。如果您正苦于以下问题：Python train.get_training_roidb方法的具体用法？Python train.get_training_roidb怎么用？Python train.get_training_roidb使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类fast_rcnn.train的用法示例。
在下文中一共展示了train.get_training_roidb方法的3个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: combined_roidb
# 需要导入模块: from fast_rcnn import train [as 别名]
# 或者: from fast_rcnn.train import get_training_roidb [as 别名]
def combined_roidb(imdb_names):
def get_roidb(imdb_name):
imdb = get_imdb(imdb_name)
print 'Loaded dataset `{:s}` for training'.format(imdb.name)
imdb.set_proposal_method(cfg.TRAIN.PROPOSAL_METHOD)
print 'Set proposal method: {:s}'.format(cfg.TRAIN.PROPOSAL_METHOD)
roidb = get_training_roidb(imdb)
return roidb
roidbs = [get_roidb(s) for s in imdb_names.split('+')]
roidb = roidbs[0]
if len(roidbs) > 1:
for r in roidbs[1:]:
roidb.extend(r)
imdb = datasets.imdb.imdb(imdb_names)
else:
imdb = get_imdb(imdb_names)
return imdb, roidb 示例2: get_roidb
# 需要导入模块: from fast_rcnn import train [as 别名]
# 或者: from fast_rcnn.train import get_training_roidb [as 别名]
def get_roidb(imdb_name, rpn_file=None):
imdb = get_imdb(imdb_name)
print 'Loaded dataset `{:s}` for training'.format(imdb.name)
imdb.set_proposal_method(cfg.TRAIN.PROPOSAL_METHOD)
print 'Set proposal method: {:s}'.format(cfg.TRAIN.PROPOSAL_METHOD)
if rpn_file is not None:
imdb.config['rpn_file'] = rpn_file
roidb = get_training_roidb(imdb)
return roidb, imdb 示例3: get_roidb
# 需要导入模块: from fast_rcnn import train [as 别名]
# 或者: from fast_rcnn.train import get_training_roidb [as 别名]
def get_roidb(imdb_name, rpn_file=None):
imdb = get_imdb(imdb_name)
print 'Loaded dataset `{:s}` for training'.format(imdb.name)
imdb.set_proposal_method(cfg.TRAIN.PROPOSAL_METHOD)
print 'Set proposal method: {:s}'.format(cfg.TRAIN.PROPOSAL_METHOD)
if rpn_file is not None:
imdb.config['rpn_file'] = rpn_file
roidb = get_training_roidb(imdb)
return roidb, imdb
# ------------------------------------------------------------------------------
# Pycaffe doesn't reliably free GPU memory when instantiated nets are discarded
# (e.g. "del net" in Python code) . To work around this issue, each training
# stage is executed in a separate process using multiprocessing.Process.
# ------------------------------------------------------------------------------