Stable Diffusion WebUI: 159K+ Stars — Hướng Dẫn Cài Đặt Đầy Đủ 2026

:: Tải sd.webui.zip từ trang releases
:: Giải nén tại C:\stable-diffusion-webui
:: Chạy updater trước
cd C:\stable-diffusion-webui
update.bat

:: KhởI chạy WebUI
run.bat

@echo off

set PYTHON=python
set GIT=git
set VENV_DIR=venv
set COMMANDLINE_ARGS=--xformers --autolaunch --update-check

:: Tùy chọn tối ưu VRAM (chọn MỘT):
:: set COMMANDLINE_ARGS=--medvram    &:: GPU 8GB
:: set COMMANDLINE_ARGS=--lowvram    &:: GPU 4GB  
:: set COMMANDLINE_ARGS=--normalvram &:: GPU 12GB+

:: RTX 40-series thêm --xformers để tăng 20-30% tốc độ

call webui.bat

# Cài dependencies (Ubuntu/Debian)
sudo apt update && sudo apt install -y wget git python3 python3-venv libgl1 libglib2.0-0

# Clone repository
git clone https://github.com/AUTOMATIC1111/stable-diffusion-webui.git
cd stable-diffusion-webui

# Tạo môi trường ảo và cài đặt
python3 -m venv venv
source venv/bin/activate
pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121
pip install -r requirements.txt

# KhởI chạy
./webui.sh --xformers --listen

# Dockerfile.stable-diffusion-webui
FROM nvidia/cuda:12.1.1-devel-ubuntu22.04

ENV DEBIAN_FRONTEND=noninteractive

RUN apt-get update && apt-get install -y \
    python3 python3-pip python3-venv git wget \
    libgl1 libglib2.0-0 libsm6 libxext6 \
    && rm -rf /var/lib/apt/lists/*

RUN useradd -m -s /bin/bash sduser
WORKDIR /home/sduser

RUN git clone https://github.com/AUTOMATIC1111/stable-diffusion-webui.git
WORKDIR /home/sduser/stable-diffusion-webui

RUN python3 -m venv venv && \
    . venv/bin/activate && \
    pip install --no-cache-dir torch torchvision torchaudio \
    --index-url https://download.pytorch.org/whl/cu121 && \
    pip install -r requirements.txt

RUN chown -R sduser:sduser /home/sduser
USER sduser

EXPOSE 7860

ENTRYPOINT ["bash", "-c", \". venv/bin/activate && python3 launch.py --listen --api --xformers"]

# Build image
docker build -f Dockerfile.stable-diffusion-webui -t sd-webui:latest .

# Chạy với GPU và persistent model
docker run -d \
  --name stable-diffusion-webui \
  --gpus all \
  -p 7860:7860 \
  -v $(pwd)/models:/home/sduser/stable-diffusion-webui/models/Stable-diffusion \
  -v $(pwd)/outputs:/home/sduser/stable-diffusion-webui/outputs \
  -v $(pwd)/extensions:/home/sduser/stable-diffusion-webui/extensions \
  -e NVIDIA_VISIBLE_DEVICES=all \
  sd-webui:latest

# docker-compose.yml
version: '3.8'

services:
  stable-diffusion-webui:
    build:
      context: .
      dockerfile: Dockerfile.stable-diffusion-webui
    container_name: sd-webui
    runtime: nvidia
    ports:
      - "7860:7860"
    volumes:
      - ./models:/home/sduser/stable-diffusion-webui/models/Stable-diffusion
      - ./outputs:/home/sduser/stable-diffusion-webui/outputs
      - ./extensions:/home/sduser/stable-diffusion-webui/extensions
      - ./vae:/home/sduser/stable-diffusion-webui/models/VAE
    environment:
      - NVIDIA_VISIBLE_DEVICES=all
    deploy:
      resources:
        reservations:
          devices:
            - driver: nvidia
              count: all
              capabilities: [gpu]
    restart: unless-stopped

docker-compose up -d

# Trên Hostinger VPS (Ubuntu 22.04)
sudo apt update && sudo apt install -y git wget

# Clone và cấu hình
git clone https://github.com/AUTOMATIC1111/stable-diffusion-webui.git
cd stable-diffusion-webui

# Cài đặt với CUDA 12
python3 -m venv venv
source venv/bin/activate
pip install torch torchvision --index-url https://download.pytorch.org/whl/cu121
pip install -r requirements.txt

# KhởI chạy
python3 launch.py --listen --port 7860 --xformers --gradio-auth admin:matkhau123

# Cài qua tab Extensions (khuyến nghị)
# 1. Mở WebUI → Extensions → Available
# 2. Click "Load from"
# 3. Tìm "ControlNet"
# 4. Click Install
# 5. Restart UI

# Hoặc cài thủ công:
cd extensions
git clone https://github.com/Mikubill/sd-webui-controlnet.git

# Models ControlNet cơ bản (SD 1.5)
wget -P models/ControlNet/ https://huggingface.co/lllyasviel/ControlNet-v1-1/resolve/main/control_v11p_sd15_openpose.pth
wget -P models/ControlNet/ https://huggingface.co/lllyasviel/ControlNet-v1-1/resolve/main/control_v11f1p_sd15_depth.pth
wget -P models/ControlNet/ https://huggingface.co/lllyasviel/ControlNet-v1-1/resolve/main/control_v11p_sd15_canny.pth

# Models ControlNet SDXL
wget -P models/ControlNet/ https://huggingface.co/lllyasviel/sd_control_collection/resolve/main/diffusers_xl_canny_mid.safetensors

# Tải LoRA vào thư mục models/Lora/
wget -P models/Lora/ "https://civitai.com/api/download/models/12345"

git clone https://github.com/comfyanonymous/ComfyUI.git
cd ComfyUI
pip install -r requirements.txt

# Chia sẻ thư mục models
ln -s /path/to/stable-diffusion-webui/models/Stable-diffusion models/checkpoints
ln -s /path/to/stable-diffusion-webui/models/Lora models/loras

python main.py --port 8188

cd extensions

# Adetailer - sửa mặt/tay tự động
git clone https://github.com/Bing-su/adetailer.git

# Ultimate SD Upscale
git clone https://github.com/Coyote-A/ultimate-upscale-for-automatic1111.git

# Tiled VAE - giảm VRAM
git clone https://github.com/pkuliyi2015/multidiffusion-upscaler-for-automatic1111.git

# Tag Autocomplete
git clone https://github.com/DominikDoom/a1111-sd-webui-tagcomplete.git

# System Info + Benchmark
git clone https://github.com/vladmandic/sd-extension-system-info.git

# GPU 4GB:
python3 launch.py --lowvram --precision full --no-half --xformers

# GPU 6-8GB:
python3 launch.py --medvram --xformers --opt-split-attention

# GPU 12GB+:
python3 launch.py --xformers --opt-sdp-attention

# GPU 24GB:
python3 launch.py --xformers --opt-sdp-attention --no-half-vae

import requests
import base64

url = "http://localhost:7860/sdapi/v1/txt2img"

payload = {
    "prompt": "masterpiece, best quality, portrait of a cyberpunk samurai",
    "negative_prompt": "blurry, low quality, deformed",
    "steps": 25,
    "cfg_scale": 7.0,
    "width": 1024,
    "height": 1024,
    "sampler_name": "DPM++ 2M Karras",
    "batch_size": 1,
    "seed": -1
}

response = requests.post(url, json=payload)
result = response.json()

for i, img_data in enumerate(result['images']):
    with open(f"output_{i}.png", "wb") as f:
        f.write(base64.b64decode(img_data))

import requests
import csv
import base64

API_URL = "http://localhost:7860/sdapi/v1/txt2img"

def generate_image(prompt, filename, width=1024, height=1024):
    payload = {
        "prompt": prompt,
        "negative_prompt": "blurry, low quality",
        "steps": 25,
        "cfg_scale": 7.0,
        "width": width,
        "height": height,
        "sampler_name": "DPM++ 2M Karras"
    }
    response = requests.post(API_URL, json=payload)
    result = response.json()
    with open(filename, "wb") as f:
        f.write(base64.b64decode(result['images'][0]))
    return filename

with open("prompts.csv", "r") as f:
    reader = csv.DictReader(f)
    for i, row in enumerate(reader):
        generate_image(row['prompt'], f"output_{i:04d}.png")

# 1. Bật xác thực
python3 launch.py --listen --gradio-auth admin:matkhau_manh

# 2. Nginx reverse proxy + HTTPS
server {
    listen 443 ssl http2;
    server_name sd.example.com;
    ssl_certificate /etc/letsencrypt/live/sd.example.com/fullchain.pem;
    ssl_certificate_key /etc/letsencrypt/live/sd.example.com/privkey.pem;

    location / {
        proxy_pass http://127.0.0.1:7860;
        proxy_http_version 1.1;
        proxy_set_header Host $host;
        proxy_set_header Upgrade $http_upgrade;
        proxy_set_header Connection "upgrade";
    }
}

# 3. Firewall
sudo ufw default deny incoming
sudo ufw allow ssh
sudo ufw allow 443/tcp
sudo ufw enable