protogen.py

# -*- coding: utf-8 -*-
# file: protogen.py
# time: 14:27 2023/1/9
# author: yangheng <[email protected]>
# 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")