name: auto-ad-generator description: Generate professional advertisement posters for multiple industries including automotive, cultural tourism, fragrance, tea, and more. Create commercial layouts with AI-generated backgrounds using PIL (local/free) or Dreamina/即夢 (high-quality AI), composite product images with typography, and export to multiple platform formats (WeChat, Xiaohongshu, airport displays). Use when the user wants to create ads, marketing posters, commercial photography layouts, brand promotional materials, or replicate advertisement styles with product replacement. Trigger on phrases like "generate ad", "make poster", "create advertisement", "like Li Auto style", "product poster", "marketing material", or when the user uploads product images and asks for marketing layouts. metadata: openclaw: requires: bins: - python3 - dreamina env: - DREAMINA_API_KEY - REMOVE_BG_API_KEY

Auto Ad Generator

Generate professional advertisement posters with AI-powered backgrounds and product compositing.

依賴宣告 (Dependencies)

本 Skill 需要以下外部服務和工具：

必需的二進位制檔案

• python3 - Python 3.8+
• dreamina - Dreamina CLI (通過 curl -s https://jimeng.jianying.com/cli | bash 安裝)

必需的環境變數

• DREAMINA_API_KEY - Dreamina API 金鑰
• REMOVE_BG_API_KEY - remove.bg API 金鑰（可選，用於背景移除）

可選 API 服務

• DALL-E / Midjourney / Stability AI - 用於 AI 影像生成
• Dreamina/即夢 - 主要 AI 生成後端
• remove.bg - 產品圖背景移除

Overview

This skill supports multiple industries and platforms: - Industries: Automotive, cultural tourism, fragrance/beauty, tea, recruitment, public welfare - Platforms: WeChat official accounts (21:9), Xiaohongshu (3:4), airport displays (16:9/9:16), lightboxes - Backends: PIL (local/free) or Dreamina/即夢 CLI (AI-powered, high quality)

Quick Start

Generate an Ad

# Using Dreamina AI backend
python main.py --backend dreamina \
  --car ./product.jpg \
  --brand "Brand Name" \
  --subtitle "Product Tagline" \
  --slogan "Marketing Slogan" \
  --platform xiaohongshu \
  --style premium \
  --output ./output

# Using PIL (local, free)
python main.py --backend pil \
  --car ./product.jpg \
  --brand "Brand Name" \
  --output ad.jpg

Interactive Mode

python main.py
# Follow prompts to select backend, platform, and style

Core Workflow

1. Analyze Input

When user provides car images and requests: - Identify car type: sedan, SUV, MPV, etc. - Extract key features: color, design highlights, target audience - Determine ad style: luxury, sporty, family-friendly, tech-focused

2. Gather Requirements

Ask the user (unless provided):

1. Brand name and model?
2. Main headline/slogan?
3. Subtitle/description?
4. Target audience? (young professionals, families, etc.)
5. Celebrity endorser image? (optional)
6. Preferred color scheme? (or auto-detect from brand)

3. Generate Ad Components

Background Generation

Use image generation to create gradient background:

Prompt template:
"Premium gradient background for car advertisement, 
{primary_color} to {secondary_color} smooth gradient, 
subtle light rays, luxury automotive aesthetic, 
minimalist, high-end commercial photography style, 
no text, no car, clean background only"

Car Subject Enhancement

• Clean up the car image (remove background if needed)
• Enhance lighting and reflections
• Position car at 3/4 front angle or side profile

Typography Layout

Layout Structure (1080x1920 vertical):
┌─────────────────┐
│   HEADLINE      │ ← 40-60px, bold, white or contrast color
│   subtitle      │ ← 20-28px, lighter weight
│                 │
│   [CAR IMAGE]   │ ← Main visual, 60% of frame
│   [Celebrity]   │ ← Optional, overlapping or beside
│                 │
│   Slogan        │ ← Bottom area
│   Logo          │ ← Corner placement
└─────────────────┘

4. Style Reference: Li Auto Aesthetic

Color Palettes: - Premium: Deep blue → Purple gradient (#1a237e → #7c4dff) - Warm: Orange → Pink gradient (#ff6b35 → #f7931e) - Cool: Teal → Cyan gradient (#00897b → #00bcd4) - Dark: Black → Deep gray with subtle blue tint

Typography: - Headline: Bold, condensed sans-serif - Subtitle: Light weight, generous letter-spacing - Slogan: Italic or script for emotional touch

Lighting: - Soft, diffused key light - Subtle rim light on car edges - Gradient background with light source from top

5. Execution Steps

# Pseudo-code for skill execution
def generate_car_ad(car_image, params):
    # Step 1: Analyze car
    car_analysis = analyze_image(car_image)

    # Step 2: Generate background
    background = generate_image(
        prompt=build_background_prompt(params['style']),
        size="1024x1536"
    )

    # Step 3: Process car image
    car_processed = remove_background(car_image)
    car_enhanced = enhance_lighting(car_processed)

    # Step 4: Composite
    composite = overlay_car_on_background(
        background, 
        car_enhanced,
        position="center-bottom",
        scale=0.7
    )

    # Step 5: Add text
    final = add_typography(
        composite,
        headline=params['headline'],
        subtitle=params['subtitle'],
        slogan=params['slogan'],
        font_style=params['style']
    )

    # Step 6: Add logo
    if params.get('logo'):
        final = overlay_logo(final, params['logo'])

    return final

6. Quality Checklist

Before presenting to user: - [ ] Car is the clear focal point - [ ] Text is readable against background - [ ] Color harmony between car and background - [ ] Professional lighting on car - [ ] Brand/logo placement is subtle but visible - [ ] Overall composition follows rule of thirds

Example Outputs

Example 1: Li Auto Style SUV Ad

Input: SUV image, "理想i6", "新形態純電五座SUV"
Output: Purple-blue gradient, car at 3/4 angle, large white text, celebrity placement

Example 2: Sporty Sedan Ad

Input: Sports sedan, "P7", "純粹駕駛樂趣"
Output: Dark background with orange accent lighting, dynamic angle, bold typography

Example 3: Family MPV Ad

Input: Minivan, "MEGA", "全家人的幸福空間"
Output: Warm gradient, spacious composition, friendly tone, emphasis on interior space

Tools & Scripts

Required Tools

• Image generation (DALL-E, Midjourney, or local SD)
• Image editing (remove.bg API or local model)
• Text overlay (PIL/Pillow or similar)
• Image composition (layer blending)

Bundled Scripts

• scripts/generate_background.py - Generate gradient backgrounds
• scripts/composite_ad.py - Layer car, background, text
• scripts/typography.py - Add professional text layout

Guidelines

Do

• Match background color to car's personality (sporty=warm, luxury=cool)
• Keep text minimal - one headline, one subtitle max
• Ensure car lighting matches background light source
• Use high-resolution source images (min 1024px width)

  7w4.net小蔥技能站，你的AI助手技能庫。

Don't

• Overcrowd with too much text
• Use clashing colors (unless intentional for contrast)
• Place car too small in frame (should be 50-70% of composition)
• Ignore the brand's existing visual identity

Edge Cases

• No car image provided: Ask user to upload, or generate concept car
• Low resolution input: Upscale first, or use as thumbnail/concept only
• Multiple cars: Focus on hero car, use others as supporting elements
• Specific brand requirements: Follow brand guidelines over Li Auto style

Reference Materials

See references/ directory for: - li_auto_examples.md - Analysis of Li Auto ad patterns - color_palettes.json - Pre-defined gradient combinations - typography_guide.md - Font pairing recommendations - composition_templates/ - Layout reference images

Dreamina (即夢) Integration

This skill supports Dreamina CLI for AI-powered background generation with higher quality results.

Prerequisites

# Install Dreamina CLI
curl -s https://jimeng.jianying.com/cli | bash

# Login (required before use)
dreamina login --headless

Two Backend Modes

Mode 1: PIL (Local, Free)

Uses Python PIL to generate simple gradient backgrounds. - Pros: No API cost, instant, offline - Cons: Basic quality, limited styles

python main.py --backend pil --car image.jpg --brand 理想 --model i6

Mode 2: Dreamina (AI-powered)

Uses Dreamina's text2image for professional AI backgrounds. - Pros: High quality, diverse styles, professional aesthetics - Cons: Consumes credits (~10-50 per image)

python main.py --backend dreamina --car image.jpg --brand 理想 --model i6 \
  --platform xiaohongshu --style premium

Platform Presets

Style Presets

Complete Workflow with Dreamina

# Step 1: Generate AI background
python main.py --backend dreamina \
  --car ./assets/suv.png \
  --brand 理想 \
  --model i6 \
  --subtitle "新形態純電五座SUV" \
  --slogan "理想，就是活成自己喜歡的樣子" \
  --platform xiaohongshu \
  --style premium \
  --output ./output

# Step 2: Check generation status
dreamina query_result --submit_id=<id_from_step1>

# Step 3: Download result and composite (manual or scripted)
# Step 4: Add typography using composite_ad.py

Credit Management

# Check remaining credits
dreamina user_credit

# Typical consumption:
# - text2image (2k): ~10-20 credits
# - text2image (4k): ~30-50 credits
# - image_upscale: ~20-40 credits

Advanced: Image-to-Image

Use existing image as base for style transfer:

from scripts.dreamina_backend import image_to_image

result = image_to_image(
    prompt="luxury car advertisement style, premium gradient background",
    image_path="existing_car_shot.jpg",
    ratio="16:9"
)