junnyu/webui_ppdiffusers

AUTOMATIC1111 WebUI Stable Diffusion

WebUIStableDiffusionPipeline 是与 AUTOMATIC1111/stable-diffusion-webui 基本对齐的一个pipeline。

该自定义Pipeline支持如下的功能：

• 输入的 token 没有长度限制，可以超过77；
• 支持clip_skip，即可以使用不同层text_encoder的输出；
• 支持直接加载webui中的textual_inversion权重；

import paddle
from ppdiffusers.utils import image_grid
from ppdiffusers import DiffusionPipeline
from pathlib import Path

pipe = DiffusionPipeline.from_pretrained("TASUKU2023/Chilloutmix", paddle_dtype=paddle.float16, custom_pipeline="junnyu/webui_ppdiffusers")

# 自动下载civitai的lora及ti文件（请注意自己的网络。）
# 介绍网页，程序将自动搜索介绍网页的下载链接
pipe.download_civitai_lora_file('https://civitai.com/models/15365/hanfu')
pipe.download_civitai_lora_file('https://civitai.com/models/12597/moxin')
pipe.download_civitai_ti_file('https://civitai.com/models/1998/autumn-style')
pipe.download_civitai_ti_file('https://civitai.com/models/21131/daisy-ridley-embedding')
# 纯下载链接
pipe.download_civitai_lora_file('https://civitai.com/api/download/models/21656')

print("Supported Lora: " + "、 ".join([p.stem for p in Path(pipe.LORA_DIR).glob("*.safetensors")]))

# 我们需要安装develop版的paddle才可以使用xformers
# pipe.enable_xformers_memory_efficient_attention()
scheduler_name = ["ddim", "pndm", "euler", "dpm-multi"]
for enable_lora in [True, False]:
    images = []
    for sc in scheduler_name:
        # 切换scheduler
        pipe.switch_scheduler(sc)
        # 指定clip_skip
        clip_skip = 1
        # 指定seed
        generator = paddle.Generator().manual_seed(0)
        # guidance_scale
        guidance_scale = 3.5
        prompt = "# shukezouma, negative space, , shuimobysim , portrait of a woman standing , willow branches, (masterpiece, best quality:1.2), traditional chinese ink painting, <lora:Moxin_10:1.0>, modelshoot style, peaceful, (smile), looking at viewer, wearing long hanfu, hanfu, song, willow tree in background, wuchangshuo,"
        negative_prompt = "(worst quality:2), (low quality:2), (normal quality:2), lowres, normal quality, skin spots, acnes, skin blemishes, age spot, glans, (watermark:2),"
        img = pipe(prompt, negative_prompt=negative_prompt, num_inference_steps=50, height=768, width=512, clip_skip=clip_skip, guidance_scale=guidance_scale, generator=generator, enable_lora=enable_lora).images[0]
        images.append(img)
    if enable_lora:
        image_grid(images, 2, 2).save(f"lora_enable.png")
    else:
        image_grid(images, 2, 2).save(f"lora_disable.png")

生成的图片如下所示：

lora_disable.png	lora_enable.png