

'''simple docstring'''

import numpy as np
import PIL
import torch
import torchvision.transforms as T
import torchvision.transforms.functional as TF
from PIL import Image

def     lowerCamelCase__       ( A					,   A=2_5_6							)			->		Dict:
	snake_case							 =				min(img.size							)

	if s < target_image_size:
		raise ValueError(F'''min dim for image {s} < {target_image_size}'''							)

	snake_case							 =				target_image_size / s
	snake_case							 =				(round(r * img.size[1]							), round(r * img.size[0]							))
	snake_case							 =				TF.resize(_UpperCAmelCase					,   _UpperCAmelCase					,   interpolation=PIL.Image.LANCZOS							)
	snake_case							 =				TF.center_crop(_UpperCAmelCase					,   output_size=2 * [target_image_size]							)
	snake_case							 =				torch.unsqueeze(T.ToTensor()(_UpperCAmelCase							)					,   0							)
	return img

def     lowerCamelCase__       ( A							)			->		List[Any]:
	snake_case							 =				2.0 * x - 1.0
	return x

def     lowerCamelCase__       ( A					,   A=True					,   A="RGB"							)			->		Optional[Any]:
	snake_case							 =				x.detach().cpu()
	if process:
		snake_case							 =				post_process_tensor(_UpperCAmelCase							)
	snake_case							 =				x.numpy()
	if process:
		snake_case							 =				(2_5_5 * x).astype(np.uinta							)
	snake_case							 =				Image.fromarray(_UpperCAmelCase							)
	if not x.mode == mode:
		snake_case							 =				x.convert(_UpperCAmelCase							)
	return x

def     lowerCamelCase__       ( A							)			->		Optional[Any]:
	snake_case							 =				torch.clamp(_UpperCAmelCase					,   -1.0					,   1.0							)
	snake_case							 =				(x + 1.0) / 2.0
	snake_case							 =				x.permute(1					,   2					,   0							)
	return x


def     lowerCamelCase__       ( A							)			->		str:
	snake_case							 =				post_process_tensor(x.squeeze()							)
	return x.permute(2					,   0					,   1							).unsqueeze(0							)








'''simple docstring'''

import os

import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent

lowerCAmelCase_						   =			{"UserAgent": UserAgent().random}
lowerCAmelCase_						   =			"https://www.mywaifulist.moe/random"

def     __magic_name__       ( A					,   A							)			->		None:
	snake_case							 =				requests.get(A					,   headers=A							)
	with open(A					,   'wb'							) as file:
		file.write(image.content							)

def     __magic_name__       ( )			->		tuple[str, str, str]:
	snake_case							 =				BeautifulSoup(requests.get(A					,   headers=A							).text					,   'html.parser'							)
	snake_case							 =				soup.find('meta'					,   attrs={'property': 'og:title'}							).attrs['content']
	snake_case							 =				soup.find('meta'					,   attrs={'property': 'og:image'}							).attrs['content']
	snake_case							 =				soup.find('p'					,   id='description'							).get_text()
	snake_case , snake_case							 =				os.path.splitext(os.path.basename(A							)							)
	snake_case							 =				title.strip().replace(' '					,   '_'							)
	snake_case							 =				F'''{image_title}{image_extension}'''
	save_image(A					,   A							)
	return (title, description, image_title)


if __name__ == "__main__":
						lowerCAmelCase_   ,	lowerCAmelCase_   ,	lowerCAmelCase_						   =			random_anime_character()
						print(f"{title}\n\n{desc}\n\nImage saved : {image_title}")





