276 lines
3.2 KiB
Plaintext
276 lines
3.2 KiB
Plaintext
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Material Analyzer Design Specification
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Version: 1.0
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Status: Draft
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1. Objective
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Purpose
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The Material Analyzer is an offline preprocessing pipeline responsible for converting every flooring SKU into a standardized Material Asset.
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The generated Material Asset serves as the Ground Truth for all downstream AI image generation tasks.
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Its objectives are:
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Eliminate repeated analysis during generation
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Standardize all flooring materials into a unified representation
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Improve material consistency across AI-generated images
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Provide reusable visual features for similarity search and quality assurance
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2. Scope
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Supported categories:
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Hardwood
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Engineered Wood
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Laminate
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SPC
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LVP
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WPC
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Ceramic Tile
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Porcelain Tile
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Stone
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Marble
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Vinyl
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Every SKU is processed only once.
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3. Pipeline
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SKU
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↓
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Load Texture Image
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↓
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Universal Feature Extraction
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↓
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Texture Feature Extraction
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↓
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Semantic Analysis
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↓
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Material Adapter
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↓
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Visual Embedding
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↓
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Asset Generation
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↓
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Material Asset
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4. Input
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Example
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{
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"sku":"67907_847",
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"category":"SPC-LVP",
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"material":"Luxury Vinyl",
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"main_image_url":"texture.jpg",
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"room_image_url":"room.jpg"
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}
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5. Output
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MaterialAssets/
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67907_847/
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preview.jpg
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material.json
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histogram.json
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embedding.bin
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thumbnail.jpg
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tileable.png (future)
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6. Universal Visual Features
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These features are extracted for every flooring material.
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Examples:
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Dominant RGB
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Secondary RGB
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LAB Color
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HSV
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Brightness
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Contrast
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Saturation
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Color Histogram
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Recommended implementation:
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OpenCV
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KMeans
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LAB
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HSV
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7. Texture Features
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Extract low-level texture statistics.
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Examples:
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Texture Entropy
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Texture Frequency
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Edge Density
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Orientation Variance
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Recommended algorithms:
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GLCM
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LBP
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FFT
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Gabor Filter
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Structure Tensor
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8. Semantic Features
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Generated by a Vision LLM.
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Examples:
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{
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"description":"...",
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"surface_finish":"Matte",
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"visual_style":"Natural",
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"grain":"Straight Oak",
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"variation":"Medium"
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}
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Recommended models:
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Gemini
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GPT-4o
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Claude
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9. Material Adapter
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Extract category-specific features.
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Wood:
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Species
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Grain Direction
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Knot Density
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Cathedral Density
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Tile:
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Stone Type
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Vein Density
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Vein Orientation
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Grout Color
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SPC / LVP:
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Printed Pattern
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Emboss Depth
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Surface Finish
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10. Visual Embeddings
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Generate two independent embeddings.
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DINOv2
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Purpose:
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Texture similarity
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Material similarity
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Drift detection
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CLIP
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Purpose:
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Semantic similarity
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Product recommendation
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11. Material Asset Schema
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{
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"sku":"",
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"category":"",
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"material":"",
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"visual":{
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},
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"texture":{
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},
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"semantic":{
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},
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"material_specific":{
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},
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"embeddings":{
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}
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}
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12. Future Modules
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Planned but not implemented.
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Canonical Texture Generator
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Tile Detection
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Image Quilting
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Seamless Texture Generation
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Pattern Detector
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13. Future Material QA
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The Material Analyzer will later be reused by the Material QA module.
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Workflow:
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Generated Image
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↓
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Floor Segmentation
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↓
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Crop Floor
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↓
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Analyzer
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↓
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Compare with Ground Truth
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↓
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Similarity Score
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14. Development Priority
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Phase 1
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Universal Features
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Texture Features
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Semantic Features
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Embeddings
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Material JSON
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Phase 2
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Tileable Texture
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Pattern Detection
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Phase 3
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Material QA
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