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import copy
import itertools
import functools
import numpy as np
import torch
import torch.utils.data
import torchvision.transforms as torch_transforms
import encoding.datasets as enc_ds
encoding_datasets = {
x: functools.partial(enc_ds.get_dataset, x)
for x in ["coco", "ade20k", "pascal_voc", "pascal_aug", "pcontext", "citys"]
}
def get_dataset(name, **kwargs):
if name in encoding_datasets:
return encoding_datasets[name.lower()](**kwargs)
assert False, f"dataset {name} not found"
def get_available_datasets():
return list(encoding_datasets.keys())
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