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:

• Base Material: Cotton, leather, polyester, metal, ceramic

• Construction: Weave type, grain pattern, metal type

• 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

• Precision Over Generalization: "Navy blue cotton twill" not "blue pants"

• Three-Level Material Specificity: Always base + construction + finish

• Actionable Recommendations: Specific items, not vague suggestions

• Style Consistency: Recommendations match product's aesthetic level

• Avoid Redundancy: Don't recommend competing items

• 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