product-analysis-styling（product analysis styling 命令行）

Product Analysis and Styling

When to Use This Skill

Use this skill when you need to:

• Analyze product images before creating photography
• Extract product attributes for accurate representation
• Generate styling recommendations for product shoots
• Determine appropriate complementary items
• Understand product positioning and target audience
• Create cohesive styled product compositions

Core Concepts

Three-Level Material Specificity

Always analyze materials with three levels:

1. Base Material: Cotton, leather, polyester, metal, ceramic
2. Construction: Weave type, grain pattern, metal type
3. Surface Finish: Texture, treatment, appearance

Example: "cotton denim with right-hand twill weave and stone-washed matte finish"

Analysis Categories

Product Classification:

• Category (top, bottom, fullbody, accessory, home goods)
• Specific type (silk blouse, leather boots, ceramic vase)
• Gender/target demographic
• Age category (infant, child, teen, adult)

Style Assessment:

• Style classification (casual, formal, sporty, elegant, minimalist)
• Occasion suitability
• Brand positioning (budget, mid-market, premium, luxury)

Material Analysis:

• Base materials
• Construction methods
• Surface treatments and finishes

Design Details:

• Silhouette and fit
• Key design elements
• Construction details
• Brand indicators

Step-by-Step Instructions

Step 1: Visual Product Analysis

Examine product images to identify:

• Product category and specific type
• Gender/target demographic
• Age category
• Style classification
• Occasion suitability

Step 2: Material and Construction Analysis

Apply three-level specificity:

• Identify base materials
• Determine construction methods
• Assess surface finishes and treatments

Step 3: Color and Pattern Analysis

Extract:

• Primary colors (specific names: "navy blue" not "blue")
• Secondary/accent colors
• Pattern type (solid, striped, floral, geometric)
• Color temperature (warm, cool, neutral)
• Finish (matte, glossy, metallic)

Step 4: Design Details Extraction

Document:

• Silhouette and fit characteristics
• Key design elements (buttons, zippers, pockets)
• Construction details (stitching, seams, hardware)
• Brand indicators and distinctive features

Step 5: Generate Styling Recommendations

Based on analysis, recommend:

For Garments:

• Complementary topwear (if bottom analyzed)
• Complementary bottomwear (if top analyzed)
• Appropriate footwear (specific style and color)
• Accessories (minimal, statement, or none)
• Overall styling approach

For Accessories:

• Outfit context (what to pair with)
• Styling placement (how to wear/display)
• Complementary pieces
• Occasion suitability

For Products:

• Display context (environment, props)
• Complementary items
• Lifestyle integration

Step 6: Create Structured Output

Format as JSON:

{
  "product_category": "top|bottom|fullbody|accessory",
  "product_type": "specific item name",
  "gender": "male|female|unisex",
  "age_category": "infant|child|teen|adult",
  "style_classification": "casual|formal|sporty|elegant",
  "materials": {
    "base": "primary material",
    "construction": "weave/grain/type",
    "finish": "surface treatment"
  },
  "colors": {
    "primary": "specific color name",
    "secondary": ["color1", "color2"],
    "temperature": "warm|cool|neutral"
  },
  "design_details": ["feature1", "feature2"],
  "styling_recommendations": {
    "topwear": "recommendation or N/A",
    "bottomwear": "recommendation or N/A",
    "footwear": "specific style and color",
    "accessories": "minimal|statement|none",
    "overall_approach": "styling philosophy"
  }
}

Examples

Example 1: Denim Jacket Analysis

Input: Image of blue denim jacket

Analysis Output:

{
  "product_category": "top",
  "product_type": "denim trucker jacket",
  "gender": "unisex",
  "age_category": "adult",
  "style_classification": "casual",
  "materials": {
    "base": "cotton denim",
    "construction": "right-hand twill weave",
    "finish": "stone-washed with slight fading, matte surface"
  },
  "colors": {
    "primary": "medium indigo blue",
    "secondary": ["brass hardware", "white contrast stitching"],
    "temperature": "cool"
  },
  "design_details": [
    "Classic trucker silhouette with pointed collar",
    "Brass button closure and rivets",
    "Two chest pockets with button flaps",
    "Adjustable side tabs at waist"
  ],
  "styling_recommendations": {
    "topwear": "N/A (this is the top)",
    "bottomwear": "Black or dark grey slim-fit chinos, or light wash jeans for contrast",
    "footwear": "White leather sneakers or tan suede desert boots",
    "accessories": "Minimal - simple watch, no competing denim",
    "overall_approach": "Classic casual Americana - keep styling clean and unfussy, let the jacket be the statement piece"
  }
}

Example 2: Statement Earrings Analysis

Input: Image of gold chandelier earrings

Analysis Output:

{
  "product_category": "accessory",
  "product_type": "chandelier drop earrings",
  "gender": "female",
  "age_category": "adult",
  "style_classification": "elegant",
  "materials": {
    "base": "gold-plated brass",
    "construction": "multi-tier chandelier structure",
    "finish": "polished with high shine"
  },
  "colors": {
    "primary": "warm gold",
    "secondary": ["clear crystal accents"],
    "temperature": "warm"
  },
  "design_details": [
    "Three-tier cascading design with crystal embellishments",
    "Approximately 3 inches in length",
    "Post back closure",
    "Intricate filigree metalwork"
  ],
  "styling_recommendations": {
    "topwear": "N/A",
    "bottomwear": "N/A",
    "footwear": "N/A",
    "accessories": "Keep other jewelry minimal - these are statement pieces",
    "overall_approach": "Pair with updo or swept-back hair to showcase earrings. Wear with elegant neckline (off-shoulder, V-neck, or strapless) in solid colors. Avoid competing patterns or necklaces. Suitable for formal events, weddings, or evening occasions."
  }
}

Example 3: Ceramic Vase Analysis

Input: Image of white ceramic vase

Analysis Output:

{
  "product_category": "home_decor",
  "product_type": "minimalist ceramic vase",
  "gender": "unisex",
  "age_category": "adult",
  "style_classification": "minimalist",
  "materials": {
    "base": "ceramic stoneware",
    "construction": "wheel-thrown with hand-finished rim",
    "finish": "matte white glaze with subtle texture"
  },
  "colors": {
    "primary": "warm off-white",
    "secondary": [],
    "temperature": "warm neutral"
  },
  "design_details": [
    "Organic asymmetrical form",
    "Narrow neck opening to wide body",
    "Approximately 10 inches tall",
    "Visible throwing lines add handcrafted character"
  ],
  "styling_recommendations": {
    "topwear": "N/A",
    "bottomwear": "N/A",
    "footwear": "N/A",
    "accessories": "N/A",
    "overall_approach": "Display on natural wood surface or light-colored shelf. Pair with single stem or small dried arrangement - avoid overcrowding. Complement with other neutral tones and natural materials. Suitable for Scandinavian, minimalist, or modern organic interiors. Photograph with soft natural light and clean background."
  }
}

Key Principles

1. Precision Over Generalization: "Navy blue cotton twill" not "blue pants"
2. Three-Level Material Specificity: Always base + construction + finish
3. Actionable Recommendations: Specific items, not vague suggestions
4. Style Consistency: Recommendations match product's aesthetic level
5. Avoid Redundancy: Don't recommend competing items
6. Context Awareness: Consider occasion, season, target audience

Common Mistakes to Avoid

• ❌ Generic descriptions: "nice fabric" instead of specific material
• ❌ Vague colors: "blue" instead of "navy blue" or "cobalt blue"
• ❌ Missing construction details: "leather" instead of "full-grain leather with pebbled finish"
• ❌ Inconsistent styling: Recommending formal shoes with casual garment
• ❌ Over-styling: Too many competing elements
• ❌ Ignoring target audience: Adult styling for children's products

Integration Pattern

# Analyze product
analysis = await analyze_product(
    product_images=["url1", "url2"],
    model_category="default"  # or "male", "female", "child"
)

# Use analysis for prompt generation
prompt = f"""
Professional fashion photography of {analysis['product_type']}.

PRODUCT DETAILS:
- Material: {analysis['materials']['base']} with {analysis['materials']['finish']}
- Color: {analysis['colors']['primary']}
- Style: {analysis['style_classification']}

STYLING:
- {analysis['styling_recommendations']['bottomwear']}
- {analysis['styling_recommendations']['footwear']}
- Accessories: {analysis['styling_recommendations']['accessories']}

{analysis['styling_recommendations']['overall_approach']}

Shot on professional camera, editorial quality, 8K resolution.
"""

# Generate image
result = await image_gen(
    prompt=prompt,
    images=[{"url": product_image, "name": "Product"}],
    aspect_ratio="2:3"
)

Output Schema

from pydantic import BaseModel, Field
from typing import List, Optional
from enum import Enum

class GarmentCategory(str, Enum):
    TOP = "top"
    BOTTOM = "bottom"
    FULLBODY = "fullbody"
    ACCESSORY = "accessory"

class Gender(str, Enum):
    MALE = "male"
    FEMALE = "female"
    UNISEX = "unisex"

class StyleCategory(str, Enum):
    CASUAL = "casual"
    FORMAL = "formal"
    SPORTY = "sporty"
    ELEGANT = "elegant"
    MINIMALIST = "minimalist"

class StylingRecommendations(BaseModel):
    topwear: str
    bottomwear: str
    footwear: str
    accessories: str
    overall_approach: str

class ProductAnalysis(BaseModel):
    product_category: GarmentCategory
    product_type: str
    gender: Gender
    age_category: str
    style_classification: StyleCategory
    materials: dict
    colors: dict
    design_details: List[str]
    styling_recommendations: StylingRecommendations

References

• Source: workflow_garments_v2/implementation/utils/garment_analysis.py
• Related Skills: product-background-generation, fashion-model-photography
• Material Terminology Guide: See references/materials.md