detector_codes/C2P-CLIP-DeepfakeDetection-main/utils/util.py

import os
import sys

import torch


def mkdirs(paths):
    if isinstance(paths, list) and not isinstance(paths, str):
        for path in paths:
            mkdir(path)
    else:
        mkdir(paths)


def mkdir(path):
    if not os.path.exists(path):
        os.makedirs(path)


def unnormalize(tens, mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]):
    # assume tensor of shape NxCxHxW
    return (
        tens * torch.Tensor(std)[None, :, None, None]
        + torch.Tensor(mean)[None, :, None, None]
    )


class Logger(object):
    """Log stdout messages."""

    def __init__(self, outfile):
        self.terminal = sys.stdout
        self.log = open(outfile, 'a')
        sys.stdout = self

    def write(self, message):
        self.terminal.write(message)
        self.log.write(message)

    def flush(self):
        self.terminal.flush()

    def isatty(self):
        return self.terminal.isatty()


def printSet(set_str):
    set_str = str(set_str)
    num = len(set_str)
    print('=' * num * 3)
    print(' ' * num + set_str)
    print('=' * num * 3)