stable-diffusion-webui [Centos]安装记录

yum install git-lfs
git lfs install

# pip install huggingface_hub
from huggingface_hub import snapshot_download, hf_hub_download
snapshot_download(repo_id="stabilityai/stable-diffusion-2-1", cache_dir='/your_path/')
hf_hub_download(repo_id="stabilityai/stable-diffusion-2-1", filename="v2-1_768-ema-pruned.safetensors", cache_dir='/your_path/')
hf_hub_download(repo_id="runwayml/stable-diffusion-v1-5", filename="v1-5-pruned-emaonly.safetensors", cache_dir='/your_path/')

from pytorch_lightning.utilities.rank_zero import rank_zero_only 

# basicsr\utils\misc.py
import torch
def get_device():
    if torch.cuda.is_available():
        return torch.device("cuda")
    else:
        return torch.device("cpu")

def gpu_is_available():
        return torch.cuda.is_available()

ssh-keygen -R ip
ssh -L 7860:localhost:7860 user@ip

$ python launch.py 
Python 3.10.12 (main, Jul  5 2023, 18:54:27) [GCC 11.2.0]
Version: v1.5.1
Commit hash: 68f336bd994bed5442ad95bad6b6ad5564a5409a
Launching Web UI with arguments: 
No module 'xformers'. Proceeding without it.
Loading weights [dcd690123c] from /opt/bdp/stable-diffusion-webui/models/Stable-diffusion/models--stabilityai--stable-diffusion-2-1/snapshots/5cae40e6a2745ae2b01ad92ae5043f95f23644d6/v2-1_768-ema-pruned.safetensors
Running on local URL:  http://127.0.0.1:7860

To create a public link, set `share=True` in `launch()`.
Startup time: 10.9s (launcher: 2.2s, import torch: 2.7s, import gradio: 0.9s, setup paths: 1.2s, other imports: 2.3s, load scripts: 0.7s, create ui: 0.6s, gradio launch: 0.2s).

(sd) [web@bdp-measure3 stable-diffusion-webui]$ sh webui.sh --nowebui --xformers

################################################################
Install script for stable-diffusion + Web UI
Tested on Debian 11 (Bullseye)
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Running on web user
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Repo already cloned, using it as install directory
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Create and activate python venv
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Launching launch.py...
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Cannot locate TCMalloc (improves CPU memory usage)
Python 3.8.16 (default, Mar  2 2023, 03:21:46) 
[GCC 11.2.0]
Version: v1.5.1
Commit hash: 68f336bd994bed5442ad95bad6b6ad5564a5409a
Installing xformers
Launching API server with arguments: --nowebui --xformers
Loading weights [6ce0161689] from /opt/bdp/stable-diffusion-webui/models/Stable-diffusion/models--runwayml--stable-diffusion-v1-5/snapshots/c9ab35ff5f2c362e9e22fbafe278077e196057f0/v1-5-pruned-emaonly.safetensors
Startup time: 176.5s (launcher: 151.6s, import torch: 9.7s, import gradio: 2.4s, setup paths: 5.3s, other imports: 3.1s, setup codeformer: 0.2s, load scripts: 2.5s, reload hypernetworks: 0.1s, lora_script.py: 1.7s).
INFO:     Started server process [26450]
INFO:     Waiting for application startup.
INFO:     Application startup complete.
INFO:     Uvicorn running on http://127.0.0.1:7861 (Press CTRL+C to quit)
Creating model from config: /opt/bdp/stable-diffusion-webui/configs/v1-inference.yaml
LatentDiffusion: Running in eps-prediction mode
DiffusionWrapper has 859.52 M params.
Applying attention optimization: xformers... done.
Model loaded in 158.2s (load weights from disk: 1.9s, create model: 19.9s, apply weights to model: 119.6s, apply half(): 15.2s, move model to device: 1.3s, calculate empty prompt: 0.3s).
INFO:     127.0.0.1:64184 - "GET /docs HTTP/1.1" 200 OK
INFO:     127.0.0.1:64184 - "GET /openapi.json HTTP/1.1" 200 OK

import json
import base64
import requests


def submit_post(url: str, data: dict):
    return requests.post(url, data=json.dumps(data))


def save_encoded_image(b64_image: str, output_path: str):
    with open(output_path, 'wb') as image_file:
        image_file.write(base64.b64decode(b64_image))


if __name__ == '__main__':
    txt2img_url = r'http://127.0.0.1:7861/sdapi/v1/txt2img'

    data = {'prompt': 'an old chinese building near by the mountain, and sunset in the sky.',
            'negative_prompt': '',
            'sampler_index': 'DPM++ SDE',
            'seed': 1234,
            'steps': 20,
            'width': 512,
            'height': 512,
            'cfg_scale': 8}

    response = submit_post(txt2img_url, data)
    save_image_path = r'sd-test.png'
    save_encoded_image(response.json()['images'][0], save_image_path)