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Image Annotation

Classification, bounding boxes, और region labeling के साथ images को annotate करें।

Image Annotation

Potato classification, object detection, और region labeling tasks के लिए image annotation का समर्थन करता है।

Image Display सक्षम करना

yaml
image:
  enabled: true
  max_width: 800
  max_height: 600

Data Format

अपने data में images reference करें:

json
{
  "id": "img_1",
  "image_path": "images/photo_001.jpg",
  "description": "Optional description"
}

Image field configure करें:

yaml
data_files:
  - path: data/image_tasks.json
    image_field: image_path

Image Classification

पूरी images classify करें:

yaml
annotation_schemes:
  - annotation_type: radio
    name: category
    description: "What is shown in this image?"
    labels:
      - Cat
      - Dog
      - Bird
      - Other
 
  - annotation_type: multiselect
    name: attributes
    description: "Select all that apply"
    labels:
      - Indoor
      - Outdoor
      - Multiple animals
      - Human present

Multi-Label Classification

yaml
annotation_schemes:
  - annotation_type: multiselect
    name: objects
    description: "What objects are visible?"
    labels:
      - Person
      - Car
      - Building
      - Tree
      - Animal
      - Furniture
      - Food
      - Electronic device

Image Quality Assessment

yaml
annotation_schemes:
  - annotation_type: likert
    name: quality
    description: "Overall image quality"
    size: 5
    min_label: "Very poor"
    max_label: "Excellent"
 
  - annotation_type: multiselect
    name: issues
    description: "Select any quality issues"
    labels:
      - Blurry
      - Overexposed
      - Underexposed
      - Noisy
      - Low resolution
      - Watermark visible

Bounding Box Annotation

Objects के चारों ओर boxes खींचें:

yaml
annotation_schemes:
  - annotation_type: bbox
    name: objects
    description: "Draw boxes around objects"
    labels:
      - Person
      - Car
      - Bicycle
      - Traffic sign
    label_colors:
      Person: "#3b82f6"
      Car: "#10b981"
      Bicycle: "#f59e0b"
      "Traffic sign": "#ef4444"

Bounding Box Output

json
{
  "id": "img_1",
  "objects": [
    {
      "label": "Person",
      "x": 100,
      "y": 50,
      "width": 80,
      "height": 200
    },
    {
      "label": "Car",
      "x": 300,
      "y": 150,
      "width": 150,
      "height": 100
    }
  ]
}

Pre-Loaded Bounding Boxes

समीक्षा के लिए मौजूदा annotations लोड करें:

json
{
  "id": "img_1",
  "image_path": "images/photo_001.jpg",
  "predictions": [
    {"label": "Person", "x": 100, "y": 50, "width": 80, "height": 200, "confidence": 0.95}
  ]
}
yaml
annotation_schemes:
  - annotation_type: bbox
    name: objects
    load_predictions: true
    prediction_field: predictions

Region/Polygon Annotation

गैर-आयताकार regions के लिए:

yaml
annotation_schemes:
  - annotation_type: polygon
    name: regions
    description: "Outline regions of interest"
    labels:
      - Building
      - Road
      - Vegetation
      - Water

Image Comparison

दो images की तुलना करें:

yaml
data_files:
  - path: data/image_pairs.json
    item_a_field: image_original
    item_b_field: image_edited
 
annotation_schemes:
  - annotation_type: pairwise
    name: preference
    description: "Which image looks better?"
    options:
      - label: "Original"
        value: "A"
      - label: "Edited"
        value: "B"
      - label: "Same"
        value: "tie"

Image Captioning

yaml
annotation_schemes:
  - annotation_type: text
    name: caption
    description: "Write a caption for this image"
    textarea: true
    placeholder: "Describe what you see..."
    min_length: 10
    max_length: 300

Caption Quality Review

yaml
data_files:
  - path: data/captions.json
    image_field: image_path
    text_field: generated_caption
 
annotation_schemes:
  - annotation_type: likert
    name: accuracy
    description: "How accurate is this caption?"
    size: 5
    min_label: "Very inaccurate"
    max_label: "Very accurate"
 
  - annotation_type: likert
    name: fluency
    description: "How natural is the language?"
    size: 5
    min_label: "Very awkward"
    max_label: "Very natural"
 
  - annotation_type: text
    name: improved_caption
    description: "Suggest a better caption (optional)"
    textarea: true

Display Options

Image Sizing

yaml
image:
  max_width: 800
  max_height: 600
  preserve_aspect_ratio: true

Zoom Controls

yaml
image:
  zoom_enabled: true
  initial_zoom: fit  # 'fit', 'actual', or percentage

Full-Screen Mode

yaml
image:
  fullscreen_enabled: true

Content Moderation

yaml
annotation_schemes:
  - annotation_type: radio
    name: safe_for_work
    description: "Is this image safe for work?"
    labels:
      - Safe
      - Questionable
      - Not Safe
 
  - annotation_type: multiselect
    name: violation_types
    description: "Select all violations (if any)"
    labels:
      - Violence
      - Adult content
      - Hate symbols
      - Graphic content
      - Spam/advertisement
    show_if:
      scheme: safe_for_work
      value: ["Questionable", "Not Safe"]

समर्थित Formats

सामान्य image formats समर्थित हैं:

  • JPEG/JPG
  • PNG
  • GIF
  • WebP
  • BMP
yaml
image:
  allowed_formats: ["jpg", "jpeg", "png", "webp"]

पूर्ण उदाहरण: Object Detection Review

yaml
task_name: "Object Detection Verification"
 
image:
  enabled: true
  max_width: 1000
  zoom_enabled: true
 
data_files:
  - path: data/detections.json
    image_field: image_path
 
annotation_schemes:
  # Review pre-loaded predictions
  - annotation_type: bbox
    name: objects
    description: "Verify and correct object boxes"
    labels:
      - Person
      - Vehicle
      - Animal
      - Object
    load_predictions: true
    prediction_field: model_predictions
    label_colors:
      Person: "#3b82f6"
      Vehicle: "#10b981"
      Animal: "#f59e0b"
      Object: "#6b7280"
 
  # Overall assessment
  - annotation_type: radio
    name: prediction_quality
    description: "How accurate were the predictions?"
    labels:
      - All correct
      - Minor corrections needed
      - Major corrections needed
      - Mostly incorrect
 
  - annotation_type: number
    name: missed_objects
    description: "How many objects were missed?"
    min: 0
    max: 50
 
  - annotation_type: text
    name: notes
    description: "Any issues or comments?"
    textarea: true
    required: false

प्रदर्शन सुझाव

  1. Image size अनुकूलित करें - Annotation से पहले बड़ी images resize करें
  2. Photos के लिए JPEG का उपयोग करें - छोटे file sizes, तेज़ loading
  3. Graphics के लिए PNG का उपयोग करें - Diagrams/screenshots के लिए बेहतर गुणवत्ता
  4. Lazy loading सक्षम करें - बड़े datasets के लिए
  5. Thumbnails पर विचार करें - List views में previews दिखाएँ
  6. Pre-process consistently - Sizes और formats normalize करें