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
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 == 'unaligned_A_labeled':
from data.unaligned_A_labeled_dataset import UnalignedALabeledDataset
dataset = UnalignedALabeledDataset()
elif opt.dataset_mode == 'mnist_svhn':
from data.mnist_svhn_dataset import MnistSvhnDataset
dataset = MnistSvhnDataset()
elif opt.dataset_mode == 'svhn_mnist':
from data.svhn_mnist_dataset import SvhnMnistDataset
dataset = SvhnMnistDataset()
else:
raise ValueError("Dataset [%s] not recognized." % opt.dataset_mode)
print("dataset [%s] was created" % (dataset.name()))
dataset.initialize(opt)
return dataset
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 == 'yh':
from data.yh_dataset import yhDataset
dataset = yhDataset()
elif opt.dataset_mode == 'yh_seg':
from data.yh_seg_dataset import yhSegDataset
dataset = yhSegDataset()
elif opt.dataset_mode == 'yh_seg_spleen':
from data.yh_seg_spleenonly_dataset import yhSegDatasetSpleenOnly
dataset = yhSegDatasetSpleenOnly()
elif opt.dataset_mode == 'yh_test_seg':
from data.yh_test_seg_dataset import yhTestSegDataset
dataset = yhTestSegDataset()
else:
raise ValueError("Dataset [%s] not recognized." % opt.dataset_mode)
print("dataset [%s] was created" % (dataset.name()))
dataset.initialize(opt)
return dataset
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 == 'unaligned_A_labeled':
from data.unaligned_A_labeled_dataset import UnalignedALabeledDataset
dataset = UnalignedALabeledDataset()
elif opt.dataset_mode == 'EEG':
from data.eeg_dataset import EEGDataset
dataset = EEGDataset()
elif opt.dataset_mode == 'EEGsingle':
from data.eeg_single_dataset import EEGDataset
dataset = EEGDataset()
elif opt.dataset_mode == 'TestEEG':
from data.eeg_dataset_test import EEGDataset
dataset = EEGDataset()
else:
raise ValueError("Dataset [%s] not recognized." % opt.dataset_mode)
print("dataset [%s] was created" % (dataset.name()))
dataset.initialize(opt)
return dataset
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 == 'mat':
from data.mat_dataset import MatDataset
dataset = MatDataset()
elif opt.dataset_mode == 'singlemat':
from data.single_mat_dataset import SingleMatDataset
dataset = SingleMatDataset()
elif opt.dataset_mode == 'superpix':
from data.superpix_dataset import SuperPixDataset
dataset = SuperPixDataset()
else:
raise ValueError("Dataset [%s] not recognized." % opt.dataset_mode)
print("dataset [%s] was created" % (dataset.name()))
dataset.initialize(opt)
return dataset
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 == 'unaligned_random_crop':
from data.unaligned_random_crop import UnalignedDataset
dataset = UnalignedDataset()
elif opt.dataset_mode == 'pair':
from data.pair_dataset import PairDataset
dataset = PairDataset()
elif opt.dataset_mode == 'syn':
from data.syn_dataset import PairDataset
dataset = PairDataset()
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
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 == 'thermal':
from data.thermal_dataset import ThermalDataset
dataset = ThermalDataset()
elif opt.dataset_mode == 'thermal_rel':
from data.thermal_rel_dataset import ThermalRelDataset
dataset = ThermalRelDataset()
elif opt.dataset_mode == 'fruxel':
from data.fruxel_dataset import FruxelDataset
dataset = FruxelDataset()
else:
raise ValueError("Dataset [%s] not recognized." % opt.dataset_mode)
print("dataset [%s] was created" % (dataset.name()))
dataset.initialize(opt)
return dataset
def CreateDataset(opt):
''' Gets called by CustomDatasetDataLoader.initialize(). dataset_mode is
by default unaligned. Dataset has generic structure, inputs are coming
from opts. Aligned, Unaligned are for A->B (i.e., image-to-image transfer
type problems, whereas Single is for z->A problems (and testing).
'''
dataset = None
if opt.dataset_mode == 'aligned':
from data.aligned_dataset import AlignedDataset
dataset = AlignedDataset()
# I've commented out these dataset modes as we do not use them. They may be
# useful in a later version.
# 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 == 'slice':
from data.slice_dataset import SliceDataset
dataset = SliceDataset()
elif opt.dataset_mode == 'voxel':
from data.voxel_dataset import VoxelDataset
dataset = VoxelDataset()
else:
raise ValueError("Dataset [%s] not recognized." % opt.dataset_mode)
print("dataset [%s] was created" % (dataset.name()))
dataset.initialize(opt)
return dataset
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 == 'alignedrandom':
from data.aligned_random_dataset import AlignedRandomDataset
dataset = AlignedRandomDataset()
elif opt.dataset_mode == 'Coco':
from data.coco_dataset import UnalignedCocoDataset
dataset = UnalignedCocoDataset()
elif opt.dataset_mode == 'CocoSeg':
from data.cocoseg_dataset import CocoSegDataset
dataset = CocoSegDataset()
else:
raise ValueError("Dataset [%s] not recognized." % opt.dataset_mode)
print("dataset [%s] was created" % (dataset.name()))
dataset.initialize(opt)
return dataset
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 == 'tif':
from data.tif_dataset import TifDataset
dataset = TifDataset(opt)
elif opt.dataset_mode == 'mb':
from data.mb_dataset import MBDataset
dataset = MBDataset(opt)
elif opt.dataset_mode == 'png_withlist':
from data.png_dataset_withlist import PngDataset
dataset = PngDataset(opt)
elif opt.dataset_mode == 'png':
from data.png_dataset import PngDataset
dataset = PngDataset(opt)
else:
raise ValueError("Dataset [%s] not recognized." % opt.dataset_mode)
print("dataset [%s] was created" % (dataset.name()))
dataset.initialize(opt)
return dataset
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 == 'unaligned_attr':
from data.unaligned_attr_dataset import UnalignedAttrDataset
dataset = UnalignedAttrDataset()
elif opt.dataset_mode == 'unaligned_prog':
from data.unaligned_prog_dataset import UnalignedProgDataset
dataset = UnalignedProgDataset()
elif opt.dataset_mode == 'single':
from data.single_dataset import SingleDataset
dataset = SingleDataset()
elif opt.dataset_mode == 'triple':
from data.triple_dataset import TripleDataset
dataset = TripleDataset()
else:
raise ValueError("Dataset [%s] not recognized." % opt.dataset_mode)
print("dataset [%s] was created" % (dataset.name()))
dataset.initialize(opt)
return dataset
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 == 'imagelist':
from data.imagelist_dataset import ImageList
if opt.isTrain:
dataset = ImageList(root=opt.image_root, fileList=opt.train_list)
else:
dataset = ImageList(root=opt.image_root,
fileList=opt.train_list,
testPahse=True)
elif opt.dataset_mode == 'imagelist_cross_view':
from data.imagelist_dataset import ImageList_cross_view
dataset = ImageList_cross_view()
elif opt.dataset_mode == 'imglist_pts':
from data.imagelist_pts_dataset import Imglist_Pts_Dataset
dataset = Imglist_Pts_Dataset()
else:
raise ValueError("Dataset [%s] not recognized." % opt.dataset_mode)
print("dataset [%s] was created" % (dataset.name()))
dataset.initialize(opt)
return dataset
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
def CreateDataset(opt):
dataset = None
from data.aligned_dataset import AlignedDataset
dataset = AlignedDataset()
print(
"dataset [%s] was created" %
(dataset.name())) # The name of the print dataset is ‘AlignedDataset’
dataset.initialize(opt) # Initialize data set parameter
return dataset # Return the created dataset
def CreateDataset(opt):
dataset = None
if not opt.temporal_smoothing:
from data.aligned_dataset import AlignedDataset
dataset = AlignedDataset()
else:
from data.aligned_dataset import TemporalSmoothingDataset
dataset = TemporalSmoothingDataset()
print("dataset [%s] was created" % (dataset.name()))
dataset.initialize(opt)
return dataset
def CreateDataset(opt):
from data.aligned_dataset import AlignedDataset
train_dataset = AlignedDataset()
train_dataset.initialize(opt)
print("dataset [%s] was created" % (train_dataset.name()))
test_dataset = AlignedDataset()
opt_test = copy.deepcopy(opt)
opt_test.shuffle = False
opt_test.phase = "test"
opt_test.no_flip = True
opt_test.num_input_views = 9
test_dataset.initialize(opt_test)
print("dataset [%s] was created" % (test_dataset.name()))
validation_dataset = AlignedDataset()
opt_val = copy.deepcopy(opt)
opt_val.phase = "validation"
opt_val.no_flip = True
opt_val.shuffle = False
opt_val.num_input_views = 9
validation_dataset.initialize(opt_val)
print("dataset [%s] was created" % (validation_dataset.name()))
return train_dataset, test_dataset, validation_dataset
def CreateDataset(opt):
dataset = None
if opt.dataset_mode == 'aligned':
from data.aligned_dataset import AlignedDataset
dataset = AlignedDataset()
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
def CreateDataset(opt):
dataset = None
if opt.dataset == 'aligned':
from data.aligned_dataset import AlignedDataset
dataset = AlignedDataset()
elif opt.dataset == 'simple_grid':
from data.simple_grid_dataset import SimpleGridDataset
dataset = SimpleGridDataset()
elif opt.dataset == 'seamless_grid':
from data.seamless_grid_dataset import SeamlessGridDataset
dataset = SeamlessGridDataset()
print("dataset [%s] was created" % (dataset.name()))
dataset.initialize(opt)
return dataset
def CreateDataset(opt):
dataset = None
if opt.model == 'pix2pixHD':
from data.aligned_dataset import AlignedDataset
dataset = AlignedDataset()
elif opt.model == 'pix2pixHDts':
if opt.face:
from .aligned_paired_dataset import AlignedPairedFaceDataset
dataset = AlignedPairedFaceDataset()
else:
from .aligned_paired_dataset import AlignedPairedDataset
dataset = AlignedPairedDataset()
print("dataset [%s] was created" % (dataset.name()))
dataset.initialize(opt)
return dataset
def CreateDataset(opt):
dataset = None
if opt.dataset_mode == 'aligned':
from data.aligned_dataset import AlignedDataset
dataset = AlignedDataset()
elif opt.dataset_mode == 'aligned_time':
from data.aligned_dataset_time import AlignedDatasetTime
dataset = AlignedDatasetTime()
elif opt.dataset_mode == 'aligned_TPN':
from data.aligned_dataset_TPN import AlignedDatasetTPN
dataset = AlignedDatasetTPN()
elif opt.dataset_mode == 'aligned_DM':
from data.aligned_dataset_DM import AlignedDatasetDM
dataset = AlignedDatasetDM()
print("dataset [%s] was created" % (dataset.name()))
dataset.initialize(opt)
return dataset
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()
else:
raise ValueError("Dataset [%s] not recognized." % opt.dataset_mode)
print("dataset [%s] was created" % (dataset.name()))
dataset.initialize(opt)
return dataset
def CreateDataset(opt):
dataset = None
if opt.dataset_mode == 'aligned':
from data.aligned_dataset import AlignedDataset
dataset = AlignedDataset()
elif opt.dataset_mode == 'aligned_with_C':
from data.aligned_dataset_with_C import AlignedDatasetWithC
dataset = AlignedDatasetWithC()
elif opt.dataset_mode == 'aligned_multi_view':
from data.aligned_dataset_multi_view import AlignedDatasetMultiView
dataset = AlignedDatasetMultiView()
elif opt.dataset_mode == 'aligned_multi_view_random':
from data.aligned_dataset_multi_view_random import AlignedDatasetMultiView
dataset = AlignedDatasetMultiView()
elif opt.dataset_mode == 'aligned_depth':
from data.aligned_dataset_depth import AlignedDatasetDepth
dataset = AlignedDatasetDepth()
elif opt.dataset_mode == 'appearance_flow':
from data.appearance_flow_dataloader import AppearanceFlowDataloader
dataset = AppearanceFlowDataloader()
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 == 'unaligned_with_guidance':
from data.unaligned_dataset_with_guidance import UnalignedDatasetWithGuidance
dataset = UnalignedDatasetWithGuidance()
elif opt.dataset_mode == 'unaligned_with_label':
from data.unaligned_dataset_with_label import UnalignedDatasetWithLabel
dataset = UnalignedDatasetWithLabel()
elif opt.dataset_mode == 'unaligned_tensor_with_label':
from data.unaligned_tensor_dataset_with_label import UnalignedTensorDatasetWithLabel
dataset = UnalignedTensorDatasetWithLabel()
else:
raise ValueError("Dataset [%s] not recognized." % opt.dataset_mode)
print("dataset [%s] was created" % (dataset.name()))
dataset.initialize(opt)
return dataset
def CreateDataset(opt):
dataset = None
# Data stored as one image concatenated along horizontal axis
if opt.dataset_mode == 'aligned':
from data.aligned_dataset import AlignedDataset
dataset = AlignedDataset()
# Data stored in different directories
elif opt.dataset_mode == 'unaligned':
from data.unaligned_dataset import UnalignedDataset
dataset = UnalignedDataset()
elif opt.dataset_mode == 'geo':
from data.geo_dataset import GeoDataset
dataset = GeoDataset()
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
def CreateDataset(opt):
dataset = None
#print("================="+str(opt.dataset_mode))
if opt.dataset_mode == 'aligned':
from data.aligned_dataset import AlignedDataset
dataset = AlignedDataset()
## add 3D videodataset loader
elif opt.dataset_mode == 'v':
from data.video_data import VideoDataset
dataset = VideoDataset()
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()
else:
raise ValueError("Dataset [%s] not recognized." % opt.dataset_mode)
print("dataset [%s] was created" % (dataset.name()))
dataset.initialize(opt)
return dataset
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 == 'unaligned_landmark':
from data.unaligned_landmark_dataset import UnalignedLandmarkDataset
dataset = UnalignedLandmarkDataset()
elif opt.dataset_mode == 'aligned_heatmap2face':
from data.aligned_dataset import AlignedDatasetHeatmap2Face
dataset = AlignedDatasetHeatmap2Face()
elif opt.dataset_mode == 'aligned_boundary_detection':
from data.aligned_dataset import AlignedBoundaryDetection
dataset = AlignedBoundaryDetection()
elif opt.dataset_mode == 'aligned_boundary_detection_landmarks':
from data.aligned_dataset import AlignedBoundaryDetectionLandmark
dataset = AlignedBoundaryDetectionLandmark()
elif opt.dataset_mode == 'aligned_face2boundary2face':
from data.aligned_dataset import AlignedFace2Boudnary2Face
dataset = AlignedFace2Boudnary2Face()
elif opt.dataset_mode == 'aligned_face2face':
from data.aligned_dataset import AlignedFace2Face
dataset = AlignedFace2Face()
elif opt.dataset_mode == 'aligned_faceDataset':
from data.aligned_dataset import AlignedFaceDataset
dataset = AlignedFaceDataset()
else:
raise ValueError("Dataset [%s] not recognized." % opt.dataset_mode)
print("dataset [%s] was created" % (dataset.name()))
dataset.initialize(opt)
return dataset
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 == 'aligned_rand':
from data.aligned_dataset_rand import AlignedDataset_Rand
dataset = AlignedDataset_Rand()
elif opt.dataset_mode == 'aligned_test':
from data.aligned_dataset_test import AlignedDataset_Test
dataset = AlignedDataset_Test()
elif opt.dataset_mode == 'unaligned_seg':
from data.unaligned_dataset_seg import UnalignedDataset_Seg
dataset = UnalignedDataset_Seg()
elif opt.dataset_mode == 'aligned_seg':
from data.aligned_dataset_seg import AlignedDataset_Seg
dataset = AlignedDataset_Seg()
elif opt.dataset_mode == 'aligned_seg_rand':
from data.aligned_dataset_seg_rand import AlignedDataset_Seg_Rand
dataset = AlignedDataset_Seg_Rand()
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
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 == 'aligned_rand':
from data.aligned_dataset_rand import AlignedDataset_Rand
dataset = AlignedDataset_Rand()
elif opt.dataset_mode == 'aligned_test':
from data.aligned_dataset_test import AlignedDataset_Test
dataset = AlignedDataset_Test()
elif opt.dataset_mode == 'unaligned_seg':
from data.unaligned_dataset_seg import UnalignedDataset_Seg
dataset = UnalignedDataset_Seg()
elif opt.dataset_mode == 'aligned_seg':
from data.aligned_dataset_seg import AlignedDataset_Seg
dataset = AlignedDataset_Seg()
elif opt.dataset_mode == 'aligned_seg_rand':
from data.aligned_dataset_seg_rand import AlignedDataset_Seg_Rand
dataset = AlignedDataset_Seg_Rand()
elif opt.dataset_mode == 'single':
from data.single_dataset import SingleDataset
dataset = SingleDataset()
elif opt.dataset_mode == 'fivek':
from data.fivek_dataset import FiveKDataset
dataset = FiveKDataset()
elif opt.dataset_mode == 'fivek2':
from data.fivek_dataset2 import FiveKDataset2
dataset = FiveKDataset2()
elif opt.dataset_mode == 'fivek3':
from data.fivek_dataset3 import FiveKDataset3
dataset = FiveKDataset3()
elif opt.dataset_mode == 'fivek4':
from data.fivek_dataset4 import FiveKDataset4
dataset = FiveKDataset4()
elif opt.dataset_mode == 'fivek4_syn':
from data.fivek_dataset4_syn import FiveKDataset4_syn
dataset = FiveKDataset4_syn()
elif opt.dataset_mode == 'fivek_single':
from data.fivek_single import FiveKDataset_single
dataset = FiveKDataset_single()
elif opt.dataset_mode == 'ava':
from data.ava_dataset import AVADataset
dataset = AVADataset()
elif opt.dataset_mode == 'aadb':
from data.aadb_dataset import AADBDataset
dataset = AADBDataset()
else:
raise ValueError("Dataset [%s] not recognized." % opt.dataset_mode)
print("dataset [%s] was created" % (dataset.name()))
dataset.initialize(opt)
return dataset
