def get_data(name,
data_dir,
height,
width,
batch_size,
workers,
trainset=False,
flip=False):
dataset = datasets.create(name, data_dir)
normalizer = T.Normalize(mean=[0.485, 0.456, 0.406],
std=[0.229, 0.224, 0.225])
test_transformer = T.Compose(
[T.Resize((height, width), interpolation=3),
T.ToTensor(), normalizer])
test_set = sorted(dataset.train) if trainset else list(
set(dataset.query) | set(dataset.gallery))
test_loader = DataLoader(Preprocessor(test_set,
root=dataset.images_dir,
transform=test_transformer,
flip=flip),
batch_size=batch_size,
num_workers=workers,
shuffle=False,
pin_memory=True)
return dataset, test_loader
def get_data(name, data_dir):
dataset = datasets.create(name, data_dir)
return dataset