설치
GitHub - cmdr2/stable-diffusion-ui: A simple 1-click way to install and use Stable Diffusion on your own computer. Provides a br
A simple 1-click way to install and use Stable Diffusion on your own computer. Provides a browser UI for generating images from text prompts and images. Just enter your text prompt, and see the gen...
github.com
Download 에서 저는 Windows를 클릭해서 설치 파일을 다운 받습니다.

다운된 설치 파일 입니다.

C드라이브 등에 압축을 풀면 아래와 같이 폴더에 풀립니다.
설치 실행 : Start Dttable Diffusion UI.cmd 를 더블 클릭해서 설치를 실행 합니다.

cmd 창에서 설치가 진행 됩니다.
done
Retrieving notices: ...working... done
"Downloading data files (weights) for Stable Diffusion.."
% Total % Received % Xferd Average Speed Time Time Time Current
Dload Upload Total Spent Left Speed
0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0
100 4067M 100 4067M 0 0 10.4M 0 0:06:27 0:06:27 --:--:-- 10.8M
"Downloading data files (weights) for GFPGAN (Face Correction).."
% Total % Received % Xferd Average Speed Time Time Time Current
Dload Upload Total Spent Left Speed
0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0
100 332M 100 332M 0 0 8041k 0 0:00:42 0:00:42 --:--:-- 8815k
"Downloading data files (weights) for ESRGAN (Resolution Upscaling) x4plus.."
% Total % Received % Xferd Average Speed Time Time Time Current
Dload Upload Total Spent Left Speed
0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0
100 63.9M 100 63.9M 0 0 6645k 0 0:00:09 0:00:09 --:--:-- 9378k
"Downloading data files (weights) for ESRGAN (Resolution Upscaling) x4plus_anime.."
% Total % Received % Xferd Average Speed Time Time Time Current
Dload Upload Total Spent Left Speed
0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0
100 17.1M 100 17.1M 0 0 4388k 0 0:00:03 0:00:03 --:--:-- 6093k
"Stable Diffusion is ready!"
PYTHONPATH=E:\stable-diffusion-ui\stable-diffusion;E:\stable-diffusion-ui\stable-diffusion\env\Lib\site-packages
Python 3.8.5
started in E:\stable-diffusion-ui\stable-diffusion
[32mINFO[0m: Started server process [[36m22908[0m]
[32mINFO[0m: Waiting for application startup.
[32mINFO[0m: Application startup complete.
[32mINFO[0m: Uvicorn running on [1mhttp://0.0.0.0:9000[0m (Press CTRL+C to quit)
[32mINFO[0m: 127.0.0.1:57680 - "[1mGET / HTTP/1.1[0m" [32m200 OK[0m
[32mINFO[0m: 127.0.0.1:57687 - "[1mGET /drawingboard.min.css HTTP/1.1[0m" [32m200 OK[0m
[32mINFO[0m: 127.0.0.1:57680 - "[1mGET /main.css?v=10 HTTP/1.1[0m" [32m200 OK[0m
[32mINFO[0m: 127.0.0.1:57681 - "[1mGET /jquery-3.6.1.min.js HTTP/1.1[0m" [32m200 OK[0m
[32mINFO[0m: 127.0.0.1:57687 - "[1mGET /drawingboard.min.js HTTP/1.1[0m" [32m200 OK[0m
[32mINFO[0m: 127.0.0.1:57681 - "[1mGET /main.js?v=15 HTTP/1.1[0m" [32m200 OK[0m
[32mINFO[0m: 127.0.0.1:57687 - "[1mGET /kofi.png HTTP/1.1[0m" [32m200 OK[0m
[32mINFO[0m: 127.0.0.1:57681 - "[1mGET /modifiers.json?v=2 HTTP/1.1[0m" [32m200 OK[0m
[32mINFO[0m: 127.0.0.1:57681 - "[1mGET /output_dir HTTP/1.1[0m" [32m200 OK[0m
[32mINFO[0m: 127.0.0.1:57680 - "[1mGET /app_config HTTP/1.1[0m" [32m200 OK[0m
GPU detected: GeForce GTX 1080
Loading model from sd-v1-4.ckpt
Global Step: 470000
UNet: Running in eps-prediction mode
CondStage: Running in eps-prediction mode
Downloading: "https://github.com/DagnyT/hardnet/raw/master/pretrained/train_liberty_with_aug/checkpoint_liberty_with_aug.pth" to C:\Users\admin/.cache\torch\hub\checkpoints\checkpoint_liberty_with_aug.pth
100%|█████████████████████████████████████████████████████████████████████████████| 5.10M/5.10M [00:01<00:00, 3.34MB/s]
Downloading: 100%|███████████████████████████████████████████████████████████████████| 939k/939k [00:01<00:00, 825kB/s]
Downloading: 100%|███████████████████████████████████████████████████████████████████| 512k/512k [00:00<00:00, 540kB/s]
Downloading: 100%|█████████████████████████████████████████████████████████████████████| 389/389 [00:00<00:00, 194kB/s]
Downloading: 100%|█████████████████████████████████████████████████████████████████████| 905/905 [00:00<00:00, 906kB/s]
Downloading: 100%|████████████████████████████████████████████████████████████████| 4.41k/4.41k [00:00<00:00, 1.50MB/s]
Downloading: 100%|████████████████████████████████████████████████████████████████| 1.59G/1.59G [02:40<00:00, 10.7MB/s]
FirstStage: Running in eps-prediction mode
making attention of type 'vanilla' with 512 in_channels
Working with z of shape (1, 4, 32, 32) = 4096 dimensions.
making attention of type 'vanilla' with 512 in_channels
loaded sd-v1-4 to cuda precision autocast
INFO: 127.0.0.1:57704 - "GET /ding.mp3 HTTP/1.1" 200 OK
INFO: 127.0.0.1:57680 - "GET /favicon-32x32.png HTTP/1.1" 200 OK
설치가 끝나면 브라우저에 다음과 같은 창이 열립니다.

이미지 만들기
- 문장 : a photograph of an astronaut riding a horse
(Default로 위 문장이 있습니다)
- 'Make Image' 버튼을 클릭합니다.

cmd창에 이미지를 만들기 위해 진행 합니다.
session_id: 1664843574184
prompt: a photograph of an astronaut riding a horse
negative_prompt:
seed: 7889137
num_inference_steps: 50
sampler: plms
guidance_scale: 7.5
w: 512
h: 512
precision: autocast
save_to_disk_path: None
turbo: True
use_cpu: False
use_full_precision: False
use_face_correction: None
use_upscale: None
show_only_filtered_image: True
stream_progress_updates: True
stream_image_progress: False
device cuda
Using precision: autocast
Global seed set to 7889137
Sampling: 0%| | 0/1 [00:00<?, ?it/s]seeds used = [7889137] | 0/1 [00:00<?, ?it/s]
Data shape for PLMS sampling is [1, 4, 64, 64]
Running PLMS Sampling with 50 timesteps
PLMS Sampler: 100%|████████████████████████████████████████████████████████████████████| 50/50 [00:38<00:00, 1.29it/s]
saving images
memory_final = 0.544256███████████████████████████████████████████████████████████████| 50/50 [00:38<00:00, 1.58it/s]
data: 100%|██████████████████████████████████████████████████████████████████████████████| 1/1 [00:54<00:00, 54.03s/it]
Sampling: 100%|██████████████████████████████████████████████████████████████████████████| 1/1 [00:54<00:00, 54.03s/it]
Task completed
INFO: 127.0.0.1:59314 - "GET /ding.mp3 HTTP/1.1" 304 Not Modified
1분 정도 걸려서 아래의 이미지가 만들어 집니다.

추가 실험
구글 번역기에서 번역해서 문장을 넣고 실행해 봤습니다.
문장 : photo of a whale flying in the sky (고래가 하늘을 나르는 사진)

문장 : Photo of a whale flying through a sky with crushed clouds (고래가 뭉개 구름이 있는 하늘을 날고 있는 사진)

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