本文整理汇总了Python中utils.create_logger.create_logger方法的典型用法代码示例。如果您正苦于以下问题:Python create_logger.create_logger方法的具体用法?Python create_logger.create_logger怎么用?Python create_logger.create_logger使用的例子?那么, 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utils.create_logger
的用法示例。
在下文中一共展示了create_logger.create_logger方法的13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: main
# 需要导入模块: from utils import create_logger [as 别名]
# 或者: from utils.create_logger import create_logger [as 别名]
def main():
ctx = [mx.gpu(int(i)) for i in config.gpus.split(',')]
print args
logger, final_output_path = create_logger(config.output_path, args.cfg, config.dataset.test_image_set)
test_rcnn(config, config.dataset.dataset, config.dataset.test_image_set, config.dataset.root_path, config.dataset.dataset_path,
ctx, os.path.join(final_output_path, '..', '_'.join([iset for iset in config.dataset.image_set.split('+')]), config.TRAIN.model_prefix), config.TEST.test_epoch,
args.vis, args.ignore_cache, args.shuffle, config.TEST.HAS_RPN, config.dataset.proposal, args.thresh, logger=logger, output_path=final_output_path)
示例2: main
# 需要导入模块: from utils import create_logger [as 别名]
# 或者: from utils.create_logger import create_logger [as 别名]
def main():
print ('Called with argument:', args)
ctx = [mx.gpu(int(i)) for i in config.gpus.split(',')]
logger, output_path = create_logger(config.output_path, args.cfg, config.dataset.image_set)
shutil.copy2(os.path.join(curr_path, 'symbols', config.symbol + '.py'), output_path)
prefix = os.path.join(output_path, 'rcnn')
logging.info('########## TRAIN rcnn WITH IMAGENET INIT AND RPN DETECTION')
train_rcnn(config, config.dataset.dataset, config.dataset.image_set, config.dataset.root_path, config.dataset.dataset_path,
args.frequent, config.default.kvstore, config.TRAIN.FLIP, config.TRAIN.SHUFFLE, config.TRAIN.RESUME,
ctx, config.network.pretrained, config.network.pretrained_epoch, prefix, config.TRAIN.begin_epoch,
config.TRAIN.end_epoch, train_shared=False, lr=config.TRAIN.lr, lr_step=config.TRAIN.lr_step,
proposal=config.dataset.proposal, logger=logger)
示例3: main
# 需要导入模块: from utils import create_logger [as 别名]
# 或者: from utils.create_logger import create_logger [as 别名]
def main():
print ('Called with argument:', args)
ctx = [mx.gpu(int(i)) for i in config.gpus.split(',')]
logger, output_path = create_logger(config.output_path, args.cfg, config.dataset.image_set)
shutil.copy2(os.path.join(curr_path, 'symbols', config.symbol + '.py'), output_path)
prefix = os.path.join(output_path, 'rfcn')
logging.info('########## TRAIN rfcn WITH IMAGENET INIT AND RPN DETECTION')
train_rcnn(config, config.dataset.dataset, config.dataset.image_set, config.dataset.root_path, config.dataset.dataset_path,
args.frequent, config.default.kvstore, config.TRAIN.FLIP, config.TRAIN.SHUFFLE, config.TRAIN.RESUME,
ctx, config.network.pretrained, config.network.pretrained_epoch, prefix, config.TRAIN.begin_epoch,
config.TRAIN.end_epoch, train_shared=False, lr=config.TRAIN.lr, lr_step=config.TRAIN.lr_step,
proposal=config.dataset.proposal, logger=logger)
示例4: main
# 需要导入模块: from utils import create_logger [as 别名]
# 或者: from utils.create_logger import create_logger [as 别名]
def main():
ctx = [mx.gpu(int(i)) for i in config.gpus.split(',')]
print args
np.random.seed(0)
mx.random.seed(0)
logger, final_output_path = create_logger(config.output_path, args.cfg, config.dataset.test_image_set)
test_rcnn(config, config.dataset.dataset, config.dataset.test_image_set, config.dataset.root_path, config.dataset.dataset_path,
ctx, os.path.join(final_output_path, '..', '_'.join([iset for iset in config.dataset.image_set.split('+')]), config.TRAIN.model_prefix), config.TEST.test_epoch,
args.vis, args.ignore_cache, args.shuffle, config.TEST.HAS_RPN, config.dataset.proposal, args.thresh, logger=logger, output_path=final_output_path)
示例5: main
# 需要导入模块: from utils import create_logger [as 别名]
# 或者: from utils.create_logger import create_logger [as 别名]
def main():
print ('Called with argument:', args)
ctx = [mx.gpu(int(i)) for i in config.gpus.split(',')]
logger, output_path = create_logger(config.output_path, args.cfg, config.dataset.image_set)
shutil.copy2(os.path.join(curr_path, 'symbols', config.symbol + '.py'), output_path)
assert config.TRAIN.END2END == False
prefix = os.path.join(output_path, config.TRAIN.model_prefix)
logging.info('########## TRAIN rcnn WITH IMAGENET INIT AND RPN DETECTION')
train_rcnn(config, config.dataset.dataset, config.dataset.image_set, config.dataset.root_path, config.dataset.dataset_path,
args.frequent, config.default.kvstore, config.TRAIN.FLIP, config.TRAIN.SHUFFLE, config.TRAIN.RESUME,
ctx, config.network.pretrained, config.network.pretrained_epoch, prefix, config.TRAIN.begin_epoch,
config.TRAIN.end_epoch, train_shared=False, lr=config.TRAIN.lr, lr_step=config.TRAIN.lr_step,
proposal=config.dataset.proposal, logger=logger, output_path=output_path)
示例6: main
# 需要导入模块: from utils import create_logger [as 别名]
# 或者: from utils.create_logger import create_logger [as 别名]
def main():
ctx = [mx.gpu(int(i)) for i in config.gpus.split(',')]
print args
logger, final_output_path = create_logger(config.output_path, args.cfg, config.dataset.test_image_set)
test_rcnn(config, config.dataset.dataset, config.dataset.test_image_set, config.dataset.root_path, config.dataset.dataset_path, config.dataset.motion_iou_path,
ctx, os.path.join(final_output_path, '..', '_'.join([iset for iset in config.dataset.image_set.split('+')]), config.TRAIN.model_prefix), config.TEST.test_epoch,
args.vis, args.ignore_cache, args.shuffle, config.TEST.HAS_RPN, config.dataset.proposal, args.thresh, logger=logger, output_path=final_output_path,
enable_detailed_eval=config.dataset.enable_detailed_eval)
示例7: main
# 需要导入模块: from utils import create_logger [as 别名]
# 或者: from utils.create_logger import create_logger [as 别名]
def main():
ctx = [mx.gpu(int(i)) for i in config.gpus.split(',')]
print args
logger, final_output_path = create_logger(config.output_path, args.cfg, config.dataset.test_image_set)
test_rcnn_poly(config, config.dataset.dataset, config.dataset.test_image_set, config.dataset.root_path,
config.dataset.dataset_path,
ctx,
os.path.join(final_output_path, '..', '_'.join([iset for iset in config.dataset.image_set.split('+')]),
config.TRAIN.model_prefix), config.TEST.test_epoch,
args.vis, args.draw, args.ignore_cache, args.shuffle, config.TEST.HAS_RPN, config.dataset.proposal, args.thresh,
logger=logger, output_path=final_output_path)
示例8: main
# 需要导入模块: from utils import create_logger [as 别名]
# 或者: from utils.create_logger import create_logger [as 别名]
def main():
ctx = [mx.gpu(int(i)) for i in config.gpus.split(',')]
print args
logger, final_output_path = create_logger(config.output_path, args.cfg, config.dataset.test_image_set)
# test_rcnn(config, config.dataset.dataset, config.dataset.test_image_set, config.dataset.root_path, config.dataset.dataset_path,
# ctx, os.path.join(final_output_path, '..', '_'.join([iset for iset in config.dataset.image_set.split('+')]), config.TRAIN.model_prefix), config.TEST.test_epoch,
# args.vis, args.ignore_cache, args.shuffle, config.TEST.HAS_RPN, config.dataset.proposal, args.thresh, logger=logger, output_path=final_output_path)
test_rcnn_poly(config, config.dataset.dataset, config.dataset.test_image_set, config.dataset.root_path, config.dataset.dataset_path,
ctx, os.path.join(final_output_path, '..', '_'.join([iset for iset in config.dataset.image_set.split('+')]), config.TRAIN.model_prefix), config.TEST.test_epoch,
args.vis, args.ignore_cache, args.shuffle, config.TEST.HAS_RPN, config.dataset.proposal, args.thresh, logger=logger, output_path=final_output_path)
示例9: main
# 需要导入模块: from utils import create_logger [as 别名]
# 或者: from utils.create_logger import create_logger [as 别名]
def main():
ctx = [mx.gpu(int(i)) for i in config.gpus.split(',')]
print args
logger, final_output_path = create_logger(config.output_path, args.cfg, config.dataset.test_image_set)
# test_rcnn(config, config.dataset.dataset, config.dataset.test_image_set, config.dataset.root_path, config.dataset.dataset_path,
# ctx, os.path.join(final_output_path, '..', '_'.join([iset for iset in config.dataset.image_set.split('+')]), config.TRAIN.model_prefix), config.TEST.test_epoch,
# args.vis, args.ignore_cache, args.shuffle, config.TEST.HAS_RPN, config.dataset.proposal, args.thresh, logger=logger, output_path=final_output_path)
test_rcnn(config, config.dataset.dataset, config.dataset.test_image_set, config.dataset.root_path, config.dataset.dataset_path,
ctx, os.path.join(final_output_path, '..', '_'.join([iset for iset in config.dataset.image_set.split('+')]), config.TRAIN.model_prefix), config.TEST.test_epoch,
args.vis, True, args.shuffle, config.TEST.HAS_RPN, config.dataset.proposal, args.thresh, logger=logger, output_path=final_output_path)
示例10: main
# 需要导入模块: from utils import create_logger [as 别名]
# 或者: from utils.create_logger import create_logger [as 别名]
def main():
ctx = [mx.gpu(int(i)) for i in config.gpus.split(',')]
print args
logger, final_output_path = create_logger(config.output_path, args.cfg, config.dataset.test_image_set)
test_rcnn(config, config.dataset.dataset, config.dataset.test_image_set, config.dataset.root_path,
config.dataset.dataset_path,
ctx, os.path.join(final_output_path, '..',
'_'.join([iset for iset in config.dataset.image_set.split('+')]),
config.TRAIN.model_prefix), config.TEST.test_epoch,
args.vis, args.ignore_cache, args.shuffle, config.TEST.HAS_RPN, config.dataset.proposal,
args.thresh, logger=logger, output_path=final_output_path)
示例11: main
# 需要导入模块: from utils import create_logger [as 别名]
# 或者: from utils.create_logger import create_logger [as 别名]
def main():
ctx = [mx.gpu(int(i)) for i in config.gpus.split(',')]
print args
logger, final_output_path = create_logger(config.output_path, args.cfg, config.dataset.test_image_set)
test_rcnn_dota(config, config.dataset.dataset, config.dataset.test_image_set, config.dataset.root_path,
config.dataset.dataset_path,
ctx, os.path.join(final_output_path, '..',
'_'.join([iset for iset in config.dataset.image_set.split('+')]),
config.TRAIN.model_prefix), config.TEST.test_epoch,
args.vis, args.ignore_cache, args.shuffle, config.TEST.HAS_RPN, config.dataset.proposal,
args.thresh, logger=logger, output_path=final_output_path)
示例12: main
# 需要导入模块: from utils import create_logger [as 别名]
# 或者: from utils.create_logger import create_logger [as 别名]
def main():
ctx = [mx.gpu(int(i)) for i in config.gpus.split(',')]
print args
logger, final_output_path = create_logger(config.output_path, args.cfg, config.dataset.test_image_set)
test_rcnn_dota_quadrangle(config, config.dataset.dataset, config.dataset.test_image_set, config.dataset.root_path, config.dataset.dataset_path,
ctx, os.path.join(final_output_path, '..', '_'.join([iset for iset in config.dataset.image_set.split('+')]), config.TRAIN.model_prefix), config.TEST.test_epoch,
args.vis, args.ignore_cache, args.shuffle, config.TEST.HAS_RPN, config.dataset.proposal, args.thresh, logger=logger, output_path=final_output_path)
示例13: main
# 需要导入模块: from utils import create_logger [as 别名]
# 或者: from utils.create_logger import create_logger [as 别名]
def main():
ctx = [mx.gpu(int(i)) for i in config.gpus.split(',')]
print(args)
if args.sample_stride != -1:
config.TEST.sample_stride = args.sample_stride
if args.key_frame_interval != -1:
config.TEST.KEY_FRAME_INTERVAL = args.key_frame_interval
if args.video_shuffle:
config.TEST.video_shuffle = args.video_shuffle
logger, final_output_path, tb_log_path = create_logger(config.output_path, config.log_path, args.cfg,
config.dataset.test_image_set)
trained_model = os.path.join(final_output_path, '..', '_'.join(
[iset for iset in config.dataset.image_set.split('+')]),
config.TRAIN.model_prefix)
test_epoch = config.TEST.test_epoch
if args.test_pretrained:
trained_model = args.test_pretrained
test_epoch = 0
test_rcnn(config, config.dataset.dataset, config.dataset.test_image_set, config.dataset.root_path,
config.dataset.dataset_path, config.dataset.motion_iou_path,
ctx,
trained_model,
test_epoch,
args.vis, args.ignore_cache, args.shuffle, config.TEST.HAS_RPN, config.dataset.proposal, args.thresh,
logger=logger, output_path=final_output_path,
enable_detailed_eval=config.dataset.enable_detailed_eval)