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datasets.py
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datasets.py
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from pathlib import Path
import hydra.utils
import torch
import torch.utils.data
import torchvision
from hydra.utils import to_absolute_path
def load_stl10_enc_train_data(cfg):
color_transfer = hydra.utils.instantiate(cfg.colorspace.translator)
normalize = torchvision.transforms.Normalize(mean=cfg.colorspace.im_norm_mean, std=cfg.colorspace.im_norm_std)
transform = torchvision.transforms.Compose([
torchvision.transforms.RandomResizedCrop(cfg.image_size, scale=(cfg.low_crop, 1.0)),
torchvision.transforms.RandomHorizontalFlip(),
color_transfer,
torchvision.transforms.ToTensor(),
normalize
])
train_dataset = torchvision.datasets.ImageFolder(
to_absolute_path((Path(cfg.stl10_dataset_path) / 'unlabeled')),
transform=transform
)
train_dataloader = torch.utils.data.dataloader.DataLoader(
train_dataset, shuffle=True, batch_size=cfg.batch_size)
return train_dataset, train_dataloader
def load_stl10_class_train_data(cfg):
color_transfer = hydra.utils.instantiate(cfg.colorspace.translator)
normalize = torchvision.transforms.Normalize(mean=cfg.colorspace.im_norm_mean, std=cfg.colorspace.im_norm_std)
transform = torchvision.transforms.Compose([
torchvision.transforms.Resize(cfg.image_size),
torchvision.transforms.RandomHorizontalFlip(),
color_transfer,
torchvision.transforms.ToTensor(),
normalize
])
train_dataset = torchvision.datasets.ImageFolder(
to_absolute_path((Path(cfg.stl10_dataset_path) / 'train')),
transform=transform
)
train_dataloader = torch.utils.data.dataloader.DataLoader(
train_dataset, shuffle=True, batch_size=cfg.batch_size)
return train_dataset, train_dataloader
def load_stl10_test_data(cfg):
color_transfer = hydra.utils.instantiate(cfg.colorspace.translator)
normalize = torchvision.transforms.Normalize(mean=cfg.colorspace.im_norm_mean, std=cfg.colorspace.im_norm_std)
transform = torchvision.transforms.Compose([
torchvision.transforms.Resize(cfg.image_size),
color_transfer,
torchvision.transforms.ToTensor(),
normalize
])
test_dataset = torchvision.datasets.ImageFolder(
to_absolute_path((Path(cfg.stl10_dataset_path) / 'test')),
transform=transform
)
test_dataloader = torch.utils.data.dataloader.DataLoader(
test_dataset, batch_size=cfg.batch_size)
return test_dataset, test_dataloader