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# -*- coding: utf-8 -*-
# file: protogen.py
# time: 14:27 2023/1/9
# author: yangheng <hy345@exeter.ac.uk>
# github: https://github.com/yangheng95
# huggingface: https://huggingface.co/yangheng
# google scholar: https://scholar.google.com/citations?user=NPq5a_0AAAAJ&hl=en
# Copyright (C) 2021. All Rights Reserved.
from diffusers import StableDiffusionPipeline, DPMSolverMultistepScheduler
import torch
import random
prompt_keys = [
"naked",
"loli",
"teen",
"squat",
"big nipples",
"hairy pussy",
"pee",
"beautiful eyes",
# 'dress', 'wind', 'fingers', 'hands',
# random.choice(['Sinon', 'saber', ]),
# random.choice(['white dress', 'red dress', 'blonde dress', 'black dress', 'green dress', ]),
# random.choice(['white bra', 'red bra', 'black bra',]),
"lovely",
"details",
# random.choice(['white hair', 'red hair', 'blonde hair', 'black hair', 'green hair', ]),
random.choice(["white hair"]),
random.choice(["blue eyes", "red eyes", "black eyes"]),
random.choice(["flower meadow", "garden"]),
]
prompt = ",".join(prompt_keys)
model_id = "darkstorm2150/Protogen_x3.4_Official_Release"
pipe = StableDiffusionPipeline.from_pretrained(
model_id, torch_dtype=torch.float16, safety_checker=None
)
pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)
pipe = pipe.to("cuda")
guidance = 7.5
width = 768
height = 512
image = pipe(
prompt,
num_inference_steps=25,
guidance_scale=guidance,
width=width,
height=height,
).images[0]
image.save("./result.jpg")
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