def CreateSingleDataset(opt): dataset = None from data.single_dataset import SingleDataset dataset = SingleDataset() print("dataset [%s] was created" % (dataset.name())) dataset.initialize(opt) return dataset
def CreateDataset(opt): dataset = None if opt.dataset_mode == 'single': from data.single_dataset import SingleDataset dataset = SingleDataset() elif opt.dataset_mode == 'aligned': from data.aligned_dataset import AlignedDataset dataset = AlignedDataset() 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() 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 == '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 == '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 == '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 == '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): 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 == '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 == '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 == '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 == '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 ISTD_test(self): opt = self.opt opt.mask_test = '/home/balin/exper/shadow_removal/Dataset/ISTD_Dataset/test/test_B' dataset = SingleDataset( '/home/balin/exper/shadow_removal/Dataset/ISTD_Dataset/test/test_A', opt) opt.results_dir = './ISTD_b/' self.eval_backend_output_only(dataset, opt)
def create_dataset(args): if args.phase == 'train': rgb_transforms, torchvision_transforms, gt_transforms = get_transform( args) return AlignedDataset(args.data_root, rgb_transforms, torchvision_transforms, gt_transforms) elif args.phase == 'test': rgb_transforms = get_transform(args) return SingleDataset(args.data_root, rgb_transforms)
def CreateDataset(opt): dataset = None if opt.dataset_mode == 'aligned_2': from data.aligned_dataset import Aligned_2_Dataset dataset = Aligned_2_Dataset() elif opt.dataset_mode == 'aligned_3': from data.aligned_dataset import Aligned_3_Dataset dataset = Aligned_3_Dataset() elif opt.dataset_mode == 'aligned_4': from data.aligned_dataset import Aligned_4_Dataset dataset = Aligned_4_Dataset() 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 == 'single': from data.single_dataset import SingleDataset dataset = SingleDataset() elif opt.dataset_mode == 'star' or opt.dataset_mode == 'n2': from data.half_dataset import N2Dataset dataset = N2Dataset() elif opt.dataset_mode == 'star1' or opt.dataset_mode == 'n2t': from data.half_dataset import N2TestDataset dataset = N2TestDataset() elif opt.dataset_mode == 'star2' or opt.dataset_mode == '2n': from data.half_dataset import _2NDataset dataset = _2NDataset() elif opt.dataset_mode == 'single_star' or opt.dataset_mode == 'sn2t': from data.single_dataset import SingleN2Dataset dataset = SingleN2Dataset() elif opt.dataset_mode == 'single_star1' or opt.dataset_mode == 'snt': from data.single_dataset import SingleNDataset dataset = SingleNDataset() 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 == 'patch': from data.patch_dataset import PatchDataset dataset = PatchDataset() 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): 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 modify_commandline_options(parser, is_train): parser = SingleDataset.modify_commandline_options(parser, is_train) parser.set_defaults(preprocess_mode='resize_and_crop') load_size = 36 if is_train else 32 parser.set_defaults(load_size=load_size) parser.set_defaults(crop_size=32) parser.set_defaults(display_winsize=32) parser.set_defaults(label_nc=1) parser.set_defaults(contain_dontcare_label=False) parser.add_argument( '--image_dir', type=str, required=True, help='path to the directory that contains photo images') return parser
def CreateDataset(opt): dataset = None if opt.dataset_mode == 'aligned': from data.aligned_dataset import AlignedDataset dataset = AlignedDataset() elif opt.dataset_mode == 'blur': from data.blur_dataset import BlurDataset dataset = BlurDataset() elif opt.dataset_mode == 'single': from data.single_dataset import SingleDataset dataset = SingleDataset() elif opt.dataset_mode == 'multi': from data.multi_dataset import MultiDataset dataset = MultiDataset() 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 == 'single': from data.single_dataset import SingleDataset dataset = SingleDataset() elif opt.dataset_mode == 'reid': from data.reid_dataset import ReidDataset dataset = ReidDataset() elif opt.dataset_mode == 'chokepoint': from data.chokepoint import ChokePoint dataset = ChokePoint() 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 == 'gopro': from data.gopro_dataset import GoProDataset dataset = GoProDataset() elif opt.dataset_mode == 'gopro_multi_scale': from data.gopro_dataset import GoProMultiScaleDataset dataset = GoProMultiScaleDataset() 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 == 'sequential': from data.sequential_dataset import SequentialDataset dataset = SequentialDataset() elif opt.dataset_mode == 'feedback': from data.feedback_dataset import FeedbackDataset dataset = FeedbackDataset() 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 == 'aligned_resized': from data.aligned_dataset_resized import AlignedDatasetResized dataset = AlignedDatasetResized() elif opt.dataset_mode == 'single': from data.single_dataset import SingleDataset dataset = SingleDataset() elif opt.dataset_mode == 'seismic': from data.seismic_dataset import SeismicDataset dataset = SeismicDataset() 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