app.py

from diffusers import DiffusionPipeline
from diffusers import StableDiffusionImg2ImgPipeline
import torch


pipeline = StableDiffusionImg2ImgPipeline.from_pretrained("Lykon/DreamShaper",torch_dtype=torch.float32)


import requests
from PIL import Image
from io import BytesIO

response = requests.get("https://www.indivstock.com/static51/preview2/stock-photo-everyday-life-of-an-indian-young-adult-woman-20s-elegant-summer-dress-indoor-in-a-shopping-center-or-university-as-a-student-or-at-the-airport-or-train-station-slim-figure-tanned-skin-color-long-1030011.jpg")
init_image = Image.open(BytesIO(response.content)).convert("RGB")
image_size = init_image.size
print("Image Size:", image_size)
while init_image.size[0]>5000 or init_image.size[1]>500:
  print('iii')
  init_image = init_image.resize((init_image.size[0] // 2, init_image.size[1] // 2))
print("Image Size:", init_image.size)
init_image



pipeline(f"Mirror the features of the provided image into a cartoon avatar, accurately capturing all visible characteristics including gender, skin tone, hair color, facial features, clothing, and any other distinctive elements. Ensure a faithful recreation with a plain white background.",
         image=init_image,
         guidance_scale=10,
         num_inference_steps=75,
         negative_prompt='sad,angry,more than one people,different from input image,teeth,2d,low quality,blurry,2 difference faces merge into one face,object in background').images[0]