本文整理汇总了Python中data.base_data_loader.BaseDataLoader.initialize方法的典型用法代码示例。如果您正苦于以下问题：Python BaseDataLoader.initialize方法的具体用法？Python BaseDataLoader.initialize怎么用？Python BaseDataLoader.initialize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data.base_data_loader.BaseDataLoader的用法示例。
在下文中一共展示了BaseDataLoader.initialize方法的15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: CreateDataset
# 需要导入模块: from data.base_data_loader import BaseDataLoader [as 别名]
# 或者: from data.base_data_loader.BaseDataLoader import initialize [as 别名]
def CreateDataset(opt):
dataset = None
if opt.dataset_mode == 'aligned':
from data.aligned_dataset import AlignedDataset
dataset = AlignedDataset()
elif opt.dataset_mode == 'unaligned':
from data.unaligned_dataset import UnalignedDataset
dataset = UnalignedDataset()
elif opt.dataset_mode == 'labeled':
from data.labeled_dataset import LabeledDataset
dataset = LabeledDataset()
elif opt.dataset_mode == 'single':
from data.single_dataset import SingleDataset
dataset = SingleDataset()
else:
raise ValueError("Dataset [%s] not recognized." % opt.dataset_mode)
print("dataset [%s] was created" % (dataset.name()))
dataset.initialize(opt)
return dataset 示例2: CreateDataset
# 需要导入模块: from data.base_data_loader import BaseDataLoader [as 别名]
# 或者: from data.base_data_loader.BaseDataLoader import initialize [as 别名]
def CreateDataset(opt):
dataset = None
if opt.dataset_mode == 'aligned':
from data.aligned_dataset import AlignedDataset
dataset = AlignedDataset()
elif opt.dataset_mode == 'unaligned':
from data.unaligned_dataset import UnalignedDataset
dataset = UnalignedDataset()
elif opt.dataset_mode == 'single':
from data.single_dataset import SingleDataset
dataset = SingleDataset()
elif opt.dataset_mode == 'half_crop':
from data.half_dataset import HalfDataset
dataset = HalfDataset()
else:
raise ValueError("Dataset [%s] not recognized." % opt.dataset_mode)
print("dataset [%s] was created" % (dataset.name()))
dataset.initialize(opt)
return dataset 示例3: CreateDataset
# 需要导入模块: from data.base_data_loader import BaseDataLoader [as 别名]
# 或者: from data.base_data_loader.BaseDataLoader import initialize [as 别名]
def CreateDataset(opt):
dataset = None
if 'face' in opt.name:
from data.aligned_dataset_GAN import AlignedDataset
dataset = AlignedDataset()
elif opt.is_temporal:
from data.aligned_dataset_temporal import AlignedDataset
dataset = AlignedDataset()
else:
from data.aligned_dataset import AlignedDataset
dataset = AlignedDataset()
print("dataset [%s] was created" % (dataset.name()))
dataset.initialize(opt)
return dataset 示例4: CreateDataset
# 需要导入模块: from data.base_data_loader import BaseDataLoader [as 别名]
# 或者: from data.base_data_loader.BaseDataLoader import initialize [as 别名]
def CreateDataset(opt):
dataset = None
if opt.dataset_mode == 'synthia_cityscapes':
from data.synthia_cityscapes import SynthiaCityscapesDataset
dataset = SynthiaCityscapesDataset()
elif opt.dataset_mode == 'gta5_cityscapes':
from data.gta5_cityscapes import GTAVCityscapesDataset
dataset = GTAVCityscapesDataset()
elif opt.dataset_mode == 'gta_synthia_cityscapes':
from data.gta_synthia_cityscapes import GTASynthiaCityscapesDataset
dataset = GTASynthiaCityscapesDataset()
elif opt.dataset_mode == 'merged_gta_synthia_cityscapes':
from data.merged_gta_synthia_cityscapes import MergedGTASynthiaCityscapesDataset
dataset = MergedGTASynthiaCityscapesDataset()
else:
raise ValueError("Dataset [%s] not recognized." % opt.dataset_mode)
print("dataset [%s] was created" % (dataset.name()))
dataset.initialize(opt)
return dataset 示例5: __init__
# 需要导入模块: from data.base_data_loader import BaseDataLoader [as 别名]
# 或者: from data.base_data_loader.BaseDataLoader import initialize [as 别名]
def __init__(self,_root, _list_dir, mode):
# BaseDataLoader.initialize(self)
# self.fineSize = opt.fineSize
# transformations = [
# TODO: Scale
#transforms.CenterCrop((600,800)),
# transforms.Scale(256, Image.BICUBIC),
# transforms.ToTensor() ]
transform = None
# transform = transforms.Compose(transformations)
# Dataset A
# dataset = ImageFolder(root='/phoenix/S6/zl548/AMOS/test/', \
# list_dir = '/phoenix/S6/zl548/AMOS/test/list/',transform=transform)
# testset
dataset = IIW_ImageFolder(root=_root, \
list_dir =_list_dir, mode = mode, is_flip = True, transform=transform)
data_loader = torch.utils.data.DataLoader(dataset, batch_size= 16, shuffle= True, num_workers=int(2))
self.dataset = dataset
flip = False
self.iiw_data = IIWData(data_loader, flip) 示例6: CreateDataset
# 需要导入模块: from data.base_data_loader import BaseDataLoader [as 别名]
# 或者: from data.base_data_loader.BaseDataLoader import initialize [as 别名]
def CreateDataset(opt):
dataset = None
if opt.dataset_mode == 'aligned':
from data.aligned_dataset import AlignedDataset
dataset = AlignedDataset()
elif opt.dataset_mode == 'aligned_resized':
from data.aligned_dataset_resized import AlignedDatasetResized
dataset = AlignedDatasetResized()
elif opt.dataset_mode == 'single':
from data.single_dataset import SingleDataset
dataset = SingleDataset()
else:
raise ValueError("Dataset [%s] not recognized." % opt.dataset_mode)
print("dataset [%s] was created" % (dataset.name()))
dataset.initialize(opt)
return dataset 示例7: CreateDataset
# 需要导入模块: from data.base_data_loader import BaseDataLoader [as 别名]
# 或者: from data.base_data_loader.BaseDataLoader import initialize [as 别名]
def CreateDataset(opt):
dataset = None
if opt.dataset_mode == 'unaligned':
from data.unaligned_dataset import UnalignedDataset
dataset = UnalignedDataset()
elif opt.dataset_mode == 'unaligned_triplet':
from data.unaligned_triplet_dataset import UnalignedTripletDataset
dataset = UnalignedTripletDataset()
else:
raise ValueError("Dataset [%s] not recognized." % opt.dataset_mode)
print("dataset [%s] was created" % (dataset.name()))
dataset.initialize(opt)
return dataset 示例8: initialize
# 需要导入模块: from data.base_data_loader import BaseDataLoader [as 别名]
# 或者: from data.base_data_loader.BaseDataLoader import initialize [as 别名]
def initialize(self, opt):
BaseDataLoader.initialize(self, opt)
self.dataset = CreateDataset(opt)
self.dataloader = torch.utils.data.DataLoader(
self.dataset,
batch_size=opt.batchSize,
shuffle=not opt.serial_batches,
num_workers=int(opt.nThreads)) 示例9: CreateDataset
# 需要导入模块: from data.base_data_loader import BaseDataLoader [as 别名]
# 或者: from data.base_data_loader.BaseDataLoader import initialize [as 别名]
def CreateDataset(opt):
dataset = None
from data.aligned_pair_dataset import AlignedPairDataset
dataset = AlignedPairDataset()
print("dataset [%s] was created" % (dataset.name()))
dataset.initialize(opt)
return dataset 示例10: CreateDataset
# 需要导入模块: from data.base_data_loader import BaseDataLoader [as 别名]
# 或者: from data.base_data_loader.BaseDataLoader import initialize [as 别名]
def CreateDataset(opt):
dataset = None
from data.aligned_dataset import AlignedDataset
dataset = AlignedDataset()
print("dataset [%s] was created" % (dataset.name()))
dataset.initialize(opt)
return dataset 开发者ID:CUHKSZ-TQL，项目名称:EverybodyDanceNow_reproduce_pytorch，代码行数:10，代码来源:custom_dataset_data_loader.py
示例11: CreateDataset
# 需要导入模块: from data.base_data_loader import BaseDataLoader [as 别名]
# 或者: from data.base_data_loader.BaseDataLoader import initialize [as 别名]
def CreateDataset(opt):
dataset = None
if opt.model == 'audioVisual':
from data.audioVisual_dataset import AudioVisualDataset
dataset = AudioVisualDataset()
else:
raise ValueError("Dataset [%s] not recognized." % opt.model)
print("dataset [%s] was created" % (dataset.name()))
dataset.initialize(opt)
return dataset 示例12: initialize
# 需要导入模块: from data.base_data_loader import BaseDataLoader [as 别名]
# 或者: from data.base_data_loader.BaseDataLoader import initialize [as 别名]
def initialize(self, opt):
BaseDataLoader.initialize(self, opt)
self.dataset = CreateDataset(opt)
self.dataloader = torch.utils.data.DataLoader(
self.dataset,
batch_size=opt.batchSize,
shuffle=True,
num_workers=int(opt.nThreads)) 示例13: CreateDataLoader
# 需要导入模块: from data.base_data_loader import BaseDataLoader [as 别名]
# 或者: from data.base_data_loader.BaseDataLoader import initialize [as 别名]
def CreateDataLoader(opt):
data_loader = CustomDatasetDataLoader()
print(data_loader.name())
data_loader.initialize(opt)
return data_loader 示例14: initialize
# 需要导入模块: from data.base_data_loader import BaseDataLoader [as 别名]
# 或者: from data.base_data_loader.BaseDataLoader import initialize [as 别名]
def initialize(self, opt):
BaseDataLoader.initialize(self, opt)
self.dataset = CreateDataset(opt)
self.dataloader = torch.utils.data.DataLoader(
self.dataset,
batch_size=opt.batchSize,
shuffle=not opt.serial_batches,
num_workers=int(opt.nThreads)) 示例15: CreateDataLoader
# 需要导入模块: from data.base_data_loader import BaseDataLoader [as 别名]
# 或者: from data.base_data_loader.BaseDataLoader import initialize [as 别名]
def CreateDataLoader(args):
data_loader = CustomDatasetDataLoader()
data_loader.initialize(args)
return data_loader