Deploy to Hugging Face Space: product-image-update-port-1

.gitattributes

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+# Standard LFS patterns
+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tar filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.wasm filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zst filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text
+
+# Model-specific patterns
+models/**/*.bin filter=lfs diff=lfs merge=lfs -text
+models/**/*.safetensors filter=lfs diff=lfs merge=lfs -text
+models/**/*.onnx filter=lfs diff=lfs merge=lfs -text
+models/**/*.pt filter=lfs diff=lfs merge=lfs -text
+models/**/*.pth filter=lfs diff=lfs merge=lfs -text
+
+# Cache patterns
+.cache/**/*.bin filter=lfs diff=lfs merge=lfs -text
+.cache/**/*.safetensors filter=lfs diff=lfs merge=lfs -text
+.cache/**/*.json filter=lfs diff=lfs merge=lfs -text
+
+# Image patterns (for sample images)
+*.jpg filter=lfs diff=lfs merge=lfs -text
+*.jpeg filter=lfs diff=lfs merge=lfs -text
+*.png filter=lfs diff=lfs merge=lfs -text
+*.webp filter=lfs diff=lfs merge=lfs -text
+*.gif filter=lfs diff=lfs merge=lfs -text
+*.bmp filter=lfs diff=lfs merge=lfs -text
+
+# Video patterns (if needed)
+*.mp4 filter=lfs diff=lfs merge=lfs -text
+*.avi filter=lfs diff=lfs merge=lfs -text
+*.mov filter=lfs diff=lfs merge=lfs -text
+*.webm filter=lfs diff=lfs merge=lfs -text
+
+# Text files (not LFS)
+*.txt -filter=lfs -diff=lfs -merge=lfs text
+*.md -filter=lfs -diff=lfs -merge=lfs text
+*.json -filter=lfs -diff=lfs -merge=lfs text
+*.py -filter=lfs -diff=lfs -merge=lfs text
+*.yml -filter=lfs -diff=lfs -merge=lfs text
+*.yaml -filter=lfs -diff=lfs -merge=lfs text
+requirements.txt -filter=lfs -diff=lfs -merge=lfs text
+README.md -filter=lfs -diff=lfs -merge=lfs text

Dockerfile

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+version: '3.8'
+
+services:
+  product-image-update:
+    build:
+      context: .
+      dockerfile: Dockerfile
+    ports:
+      - "7860:7860"
+    environment:
+      # Copy from .env file or set directly
+      - HF_TOKEN=${HF_TOKEN}
+      - CUDA_VISIBLE_DEVICES=${CUDA_VISIBLE_DEVICES:-0}
+      - PYTORCH_CUDA_ALLOC_CONF=max_split_size_mb:512
+      - TRANSFORMERS_CACHE=/app/.cache/huggingface
+      - HF_HOME=/app/.cache/huggingface
+      - GRADIO_SERVER_NAME=0.0.0.0
+      - GRADIO_SERVER_PORT=7860
+      - DEBUG=${DEBUG:-false}
+    volumes:
+      # Mount cache directories for faster restarts
+      - huggingface-cache:/app/.cache/huggingface
+      - torch-cache:/app/.cache/torch
+      - models-cache:/app/models
+      # Mount processed images directory
+      - ./processed_imgs:/app/processed_imgs
+      # For development - mount source code
+      - ./app.py:/app/app.py:ro
+      - ./utils.py:/app/utils.py:ro
+      - ./image-download:/app/image-download:ro
+      - ./remove-background:/app/remove-background:ro
+      - ./bounding-box:/app/bounding-box:ro
+      - ./cropping-padding:/app/cropping-padding:ro
+      - ./return-images:/app/return-images:ro
+    deploy:
+      resources:
+        limits:
+          memory: 16G
+        reservations:
+          devices:
+            - driver: nvidia
+              count: 1
+              capabilities: [gpu]
+    healthcheck:
+      test: ["CMD", "curl", "-f", "http://localhost:7860/health"]
+      interval: 30s
+      timeout: 10s
+      retries: 3
+      start_period: 60s
+    restart: unless-stopped
+    networks:
+      - app-network
+
+  # Optional: Nginx reverse proxy for production
+  nginx:
+    image: nginx:alpine
+    ports:
+      - "80:80"
+      - "443:443"
+    volumes:
+      - ./nginx.conf:/etc/nginx/nginx.conf:ro
+      - ./ssl:/etc/nginx/ssl:ro
+    depends_on:
+      - product-image-update
+    networks:
+      - app-network
+    profiles:
+      - production
+
+  # Optional: Monitoring with Prometheus
+  prometheus:
+    image: prom/prometheus:latest
+    ports:
+      - "9090:9090"
+    volumes:
+      - ./prometheus.yml:/etc/prometheus/prometheus.yml:ro
+      - prometheus-data:/prometheus
+    command:
+      - '--config.file=/etc/prometheus/prometheus.yml'
+      - '--storage.tsdb.path=/prometheus'
+    networks:
+      - app-network
+    profiles:
+      - monitoring
+
+  # Optional: Grafana for visualization
+  grafana:
+    image: grafana/grafana:latest
+    ports:
+      - "3000:3000"
+    environment:
+      - GF_SECURITY_ADMIN_PASSWORD=admin
+    volumes:
+      - grafana-data:/var/lib/grafana
+    depends_on:
+      - prometheus
+    networks:
+      - app-network
+    profiles:
+      - monitoring
+
+volumes:
+  huggingface-cache:
+    driver: local
+  torch-cache:
+    driver: local
+  models-cache:
+    driver: local
+  prometheus-data:
+    driver: local
+  grafana-data:
+    driver: local
+
+networks:
+  app-network:
+    driver: bridge

src/processing/bounding_box/flow_diagram.mermaid

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+flowchart TD
+    classDef blueBox fill:#0000ff33,stroke:#0000ff,color:#000
+    classDef greenBox fill:#00ff0033,stroke:#00ff00,color:#000
+    classDef violetBox fill:#ee82ee33,stroke:#ee82ee,color:#000
+    classDef orangeBox fill:#ffa50033,stroke:#ffa500,color:#000
+    classDef redBox fill:#ff000033,stroke:#ff0000,color:#000
+    classDef multiBox fill:lightyellow,stroke:#333,color:#000
+    classDef processNode fill:#dae8fc,stroke:#6c8ebf,color:#000
+    classDef dataNode fill:#d5e8d4,stroke:#82b366,color:#000
+
+    Input[/"Input Image"/] --> Step1
+    
+    subgraph Models["Detection Models"]
+        direction TB
+        RTDETR["RT-DETR Model
+🟦 Main Product Detection:
+person, coat, dress, jacket,
+shirt, skirt, pants, shorts
+
+🟧 Some Features:
+tie → collar"]:::multiBox
+        
+        RTDETR_A["RT-DETR Artifact Detection
+🟥 Artifacts:
+backpack, handbag → bag,
+bottle, cup → cup,
+book, cell phone, camera,
+umbrella"]:::redBox
+        
+        YOLO["YOLOv11 Model
+🟦 Main Products:
+jacket, coat, shirt, dress,
+vest, pants, jeans, shorts
+
+🟪 Shoes:
+footwear, shoes, boots,
+high heels, sandals
+
+🟧 Some Features:
+tie → collar"]:::multiBox
+        
+        HEAD["Head Detection Model
+🟩 Head:
+face, head"]:::greenBox
+    end
+    
+    Step1["Step 1: Define Largest Box
+Use RT-DETR to identify 
+the main product region"]:::processNode
+    RTDETR --> Step1
+    Step1 --> Step2
+    
+    Step2["Step 2: Multi-model Detection
+Run all models on 
+largest box region"]:::processNode
+    RTDETR --> Step2
+    RTDETR_A --> Step2
+    YOLO --> Step2
+    HEAD --> Step2
+    Step2 --> Step3
+    
+    Step3["Step 3: Color Assignment
+& Keyword Mapping"]:::processNode --> Categories
+    
+    subgraph Categories["Map objects to categories"]
+        direction TB
+        Product["🟦 BLUE: Product Type (0.4)
+jacket, shirt, vest,
+jeans, shorts, skirt, 
+overall, dress"]:::blueBox
+        
+        Head["🟩 GREEN: Head (0.5)
+head"]:::greenBox
+        
+        Shoes["🟪 VIOLET: Shoes (0.5)
+shoes"]:::violetBox
+        
+        Features["🟧 ORANGE: Features (0.4)
+neckline, collar, sleeve,
+closure, pocket"]:::orangeBox
+        
+        Artifacts["🟥 RED: Artifacts (0.7)
+bag, cup, hanger, book,
+phone, camera, umbrella"]:::redBox
+    end
+    
+    Categories --> Step4
+    
+    Step4["Step 4: Adjust Blue Box
+Refine product box based on 
+head and shoe positions"]:::processNode --> Step5
+    
+    Step5["Step 5: Draw Boxes
+Add colored bbox
+to image"]:::processNode --> Output
+    
+    Output["Processed Image
+With Boxes"]:::dataNode

src/processing/cropping_padding/flow_diagram.mermaid

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+flowchart TD
+    classDef processNode fill:#dae8fc,stroke:#6c8ebf,color:#000
+    classDef imageNode fill:#d5e8d4,stroke:#82b366,color:#000
+    classDef decisionNode fill:#fff2cc,stroke:#d6b656,color:#000
+    classDef squareNode fill:#e3f2fd,stroke:#1976d2,color:#000
+    classDef landscapeNode fill:#e8f5e8,stroke:#388e3c,color:#000
+    classDef portraitNode fill:#fce4ec,stroke:#c2185b,color:#000
+    classDef transformNode fill:#f3e5f5,stroke:#7b1fa2,color:#000
+    classDef borderNode fill:#fff3e0,stroke:#f57c00,color:#000
+
+    Input[/"Input RGBA Image
+with transparent background"/]:::imageNode
+    Input --> InitialCrop
+    
+    InitialCrop["Initial Cropping
+• Use blue box coordinates from detection
+• Remove excess vertical space
+• Preserve product boundaries"]:::processNode
+    InitialCrop --> ShrinkBox
+    
+    ShrinkBox["Shrink Primary Box
+• Analyze alpha channel transparency
+• Remove white-only regions
+• Create tight bounding box"]:::processNode
+    ShrinkBox --> BorderDetect
+    
+    BorderDetect["Border Detection Analysis
+• Measure edge coverage ratios
+• Calculate feathering smoothness
+• Classify border types as straight lines"]:::processNode
+    BorderDetect --> OrientCheck
+    
+    OrientCheck{"Determine Image Orientation
+Width vs Height Analysis"}:::decisionNode
+    OrientCheck -->|"Width ≈ Height"| SquareFlow
+    OrientCheck -->|"Width > Height"| LandscapeFlow
+    OrientCheck -->|"Height > Width"| PortraitFlow
+    
+    subgraph SquareFlow["Square Image Transformation Pipeline □"]
+        SqInput["Square Input □
+Width ≈ Height"]:::squareNode
+        SqInput --> SqCheck{"Detect Special Cases"}:::decisionNode
+        
+        SqCheck -->|"Shoes Detected"| SqShoes["Shoes Transformation:
+□ → Pad bottom only
+□ → Ignore lower border flags
+□ → Result: Slightly taller square"]:::squareNode
+        
+        SqCheck -->|"Head + Borders"| SqHeadBorder["Head with Borders:
+□ → No padding changes
+□ → Preserve existing borders
+□ → Result: Original square maintained"]:::squareNode
+        
+        SqCheck -->|"Border Lines"| SqBorders["Border Lines Present:
+□ → No additional padding
+□ → Maintain current dimensions
+□ → Result: Original square preserved"]:::squareNode
+        
+        SqCheck -->|"Default Case"| SqDefault["Universal Padding:
+□ → UNIVERSAL_PAD_RATIO on all sides
+□ → Equal padding: top, bottom, left, right
+□ → Result: Larger square with even spacing"]:::squareNode
+        
+        SqShoes --> SqOutput["□ Final Square Output"]:::squareNode
+        SqHeadBorder --> SqOutput
+        SqBorders --> SqOutput
+        SqDefault --> SqOutput
+    end
+    
+    subgraph LandscapeFlow["Landscape Image Transformation Pipeline ▭"]
+        LsInput["Landscape Input ▭
+Width > Height"]:::landscapeNode
+        LsInput --> LsCheck{"Detect Special Cases"}:::decisionNode
+        
+        LsCheck -->|"Shoes Detected"| LsShoes["Shoes Transformation:
+▭ → Add bottom padding
+▭ → Crop to square format
+▭ → Result: Square with shoes at bottom"]:::transformNode
+        
+        LsCheck -->|"Head Detected"| LsHead["Head Transformation:
+▭ → Remove top padding
+▭ → Keep landscape shape square
+▭ → Result: Square with head positioned well"]:::transformNode
+        
+        LsCheck -->|"Border Lines"| LsBorders["Border Lines Transformation:
+▭ → Coverage-based cropping
+▭ → Analyze content distribution
+▭ → Result: Square from content analysis"]:::transformNode
+        
+        LsCheck -->|"Default Case"| LsDefault["Two-Step Transformation:
+▭ → Step 1: Pad height to approach square
+▭ → Step 2: Equalize to perfect square
+▭ → Result: Centered square with even padding"]:::transformNode
+        
+        LsShoes --> LsOutput["□ Final Square Output"]:::landscapeNode
+        LsHead --> LsOutput
+        LsBorders --> LsOutput
+        LsDefault --> LsOutput
+    end
+    
+    subgraph PortraitFlow["Portrait Image Transformation Pipeline ▯"]
+        PtInput["Portrait Input ▯
+Height > Width"]:::portraitNode
+        PtInput --> PtCheck{"Detect Special Cases"}:::decisionNode
+        
+        PtCheck -->|"Shoes Detected"| PtShoes["Shoes Transformation:
+▯ → Never pad top
+▯ → Always pad bottom
+▯ → Pad sides to square
+▯ → Result: Square with shoes at bottom"]:::transformNode
+        
+        PtCheck -->|"Head Detected"| PtHead["Head Transformation:
+▯ → Pad left and right only
+▯ → Maintain head position
+▯ → Result: Square with head positioned"]:::transformNode
+        
+        PtCheck -->|"L/R Borders"| PtLR["L/R Borders Transformation:
+▯ → Coverage-based cropping
+▯ → Remove excess based on content density
+▯ → Result: Square from intelligent cropping"]:::transformNode
+        
+        PtCheck -->|"U+L Borders"| PtUL["U+L Borders Transformation:
+▯ → Pad left and right only
+▯ → Maintain vertical borders
+▯ → Result: Square with preserved content"]:::transformNode
+        
+        PtCheck -->|"One Border"| PtOne["Single Border Transformation:
+▯ → Two-step padding process
+▯ → Step 1: Pad width toward square
+▯ → Result: Balanced square output"]:::transformNode
+        
+        PtCheck -->|"Default Case"| PtDefault["Default Transformation:
+▯ → Two-step padding process
+▯ → Step 1: Add horizontal padding
+▯ → Result: Centered square with side padding"]:::transformNode
+        
+        PtShoes --> PtOutput["□ Final Square Output"]:::portraitNode
+        PtHead --> PtOutput
+        PtLR --> PtOutput
+        PtUL --> PtOutput
+        PtOne --> PtOutput
+        PtDefault --> PtOutput
+    end
+    
+    SqOutput --> Centering
+    LsOutput --> Centering
+    PtOutput --> Centering
+    
+    Centering["Final Object Centering
+• Analyze alpha channel boundaries
+• Calculate product midpoint
+• Shift horizontally to center
+• Maintain padding relationships"]:::processNode
+    Centering --> FinalOutput
+    
+    FinalOutput[/"□ Final Processed Square Image
+Consistently sized and centered"/]:::imageNode
+    
+    subgraph BorderDetectionDetails["Border Detection Algorithm Details"]
+        BorderParams["Detection Parameters:
+COVERAGE_THRESHOLD = 0.25
+FEATHER_THRESHOLD_MIN = 0.3
+FEATHER_THRESHOLD_MAX = 0.7"]:::borderNode
+        
+        CoverageAnalysis["Coverage Analysis:
+• Left Border: Vertical edge pattern
+• Right Border: Opposite vertical edge
+• Upper Border: Top horizontal edge
+• Lower Border: Bottom horizontal edge"]:::borderNode
+        
+        FeatheringAnalysis["Feathering Analysis:
+• Hard Edges: Sharp transitions
+• Soft Edges: Gradual transitions
+• Feathering Ratio: Transition zone proportion"]:::borderNode
+        
+        Classification["Classification Criteria:
+Border = Straight Line when:
+• Coverage > COVERAGE_THRESHOLD
+• Feathering outside MIN-MAX range"]:::borderNode
+        
+        BorderParams --> CoverageAnalysis --> FeatheringAnalysis --> Classification
+    end
+    
+    BorderDetect -.-> BorderDetectionDetails
+    
+    subgraph TransformationExamples["Visual Transformation Examples"]
+        ExampleSquare["Square Examples:
+□ 1000×1000 → □ 1150×1150 (universal pad)
+□ 1000×1000 → □ 1000×1000 (preserved)"]:::squareNode
+        
+        ExampleLandscape["Landscape Examples:
+▭ 1200×800 → ▭ 1200×1200 (height pad) → □ 1200×1200
+▭ 1400×900 → Analysis → □ 1200×1200 (coverage crop)"]:::landscapeNode
+        
+        ExamplePortrait["Portrait Examples:
+▯ 800×1200 → ▯ 1200×1200 (width pad) → □ 1200×1200
+▯ 600×1000 → ▯ 1000×1000 (side pad) → □ 1000×1000"]:::portraitNode
+    end
+    
+    FinalOutput -.-> TransformationExamples
+    
+    subgraph PaddingStrategies["Padding Strategy Implementation"]
+        UniversalPadding["Universal Padding:
+UNIVERSAL_PAD_RATIO = 0.075
+Applied as 7.5% of image dimension
+1000px image = 75px padding per side"]:::borderNode
+        
+        TwoStepPadding["Two-Step Padding:
+Step 1: Pad longer dimension toward square
+Step 2: Equalize shorter dimension
+Step 3: Complete perfect square formation"]:::borderNode
+        
+        CoverageCropping["Coverage-Based Cropping:
+Step 1: Analyze content distribution
+Step 2: Remove excess based on density
+Step 3: Apply minimal padding
+Step 4: Achieve square format"]:::borderNode
+        
+        UniversalPadding --> TwoStepPadding --> CoverageCropping
+    end
+    
+    SquareFlow -.-> PaddingStrategies
+    LandscapeFlow -.-> PaddingStrategies
+    PortraitFlow -.-> PaddingStrategies

src/processing/return_images/flow_diagram.mermaid

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+flowchart TD
+    classDef processNode fill:#dae8fc,stroke:#6c8ebf,color:#000
+    classDef dataNode fill:#d5e8d4,stroke:#82b366,color:#000
+    classDef colorNode fill:#ffe6cc,stroke:#d79b00,color:#000
+    classDef typeNode fill:#e1d5e7,stroke:#9673a6,color:#000
+    classDef outputNode fill:#f8cecc,stroke:#b85450,color:#000
+
+    Input[/"Processed Image"/]:::dataNode --> Step1
+    
+    Step1["Step 1: Color Extraction & Mapping
+Sample non-transparent pixels, 
+quantize colors, determine dominant color"]:::processNode --> Step2
+    
+    Step2["Step 2: Image Type Detection
+Analyze padding information 
+and detection keywords"]:::processNode --> Step3
+    
+    Step3["Step 3: WebP Conversion & Base64 Encoding
+Check for artifacts, convert format,
+encode for API response"]:::processNode --> Output
+    
+    Output[/"Final Response Data"/]:::dataNode
+    
+    subgraph ColorAnalysis["Color Classification Logic"]
+        RGBToHSL["RGB → HSL conversion"]:::processNode
+        
+        MonochromeCheck{"Is monochrome?
+(low saturation)"}:::colorNode
+        RGBToHSL --> MonochromeCheck
+        
+        MonochromeCheck -->|"Yes"| GreyscaleGrouping{"Lightness values"}:::colorNode
+        GreyscaleGrouping -->|"< 0.28"| Black["Black"]:::colorNode
+        GreyscaleGrouping -->|"0.28-0.88"| Grey["Grey"]:::colorNode
+        GreyscaleGrouping -->|"> 0.88"| White["White"]:::colorNode
+        
+        MonochromeCheck -->|"No"| BlueRangeCheck{"Is blue range?
+(160° ≤ H < 260°)"}:::colorNode
+        BlueRangeCheck -->|"Yes"| BlueShades{"Lightness values"}:::colorNode
+        BlueShades -->|"< 0.40"| DarkBlue["Dark Blue"]:::colorNode
+        BlueShades -->|"0.40-0.65"| Blue["Blue"]:::colorNode
+        BlueShades -->|"> 0.65"| LightBlue["Light Blue"]:::colorNode
+        
+        BlueRangeCheck -->|"No"| PrimaryColors{"Primary color groups
+based on hue angle"}:::colorNode
+        PrimaryColors -->|"0°-70°"| YellowGroup["Yellow Group"]:::colorNode
+        PrimaryColors -->|"70°-160°"| GreenGroup["Green Group"]:::colorNode
+        PrimaryColors -->|"260°-360°"| RedGroup["Red Group"]:::colorNode
+    end
+    
+    Step1 -.-> ColorAnalysis
+    
+    subgraph TypeAssignment["Image Type Assignment"]
+        PaddingCheck{"All sides padded?"}:::typeNode
+        PaddingCheck -->|"Yes"| PaddedProduct["padded_product"]:::typeNode
+        PaddingCheck -->|"No"| HeadShoesCheck{"Head or shoes
+detected?"}:::typeNode
+        HeadShoesCheck -->|"No"| DetailType["detail"]:::typeNode
+        HeadShoesCheck -->|"Yes"| DefaultType["none"]:::typeNode
+    end
+    
+    Step2 -.-> TypeAssignment