preprocessing/dataset_creation_utils.py

import os
import torch
import random
import numpy as np
from SR_Inference.inference_hat import HAT
from SR_Inference.inference_gfpgan import GFPGAN
from SR_Inference.inference_realesr import RealEsr
from SR_Inference.inference_srresnet import SRResNet
from SR_Inference.inference_codeformer import CodeFormer


def seed_everything(seed=42):
    random.seed(seed)
    os.environ["PYTHONHASHSEED"] = str(seed)
    np.random.seed(seed)
    torch.manual_seed(seed)
    torch.cuda.manual_seed(seed)
    torch.backends.cudnn.benchmark = True
    torch.backends.cudnn.deterministic = True


def get_sr_method(self, sr_configs):
    sr_method_class = globals().get(self.sr_method_name)
    if sr_method_class is not None:
        return sr_method_class(**sr_configs["params"])
    else:
        raise Exception(
            f"No such SR method called '{self.sr_method_name}' implemented!"
        )