docs/annotation_guide.md

Annotation Guide — IndoLepAtlas

1. Class Definitions

Each species is its own class. Classes are defined at the species level (~1,094 total):

• Butterflies: ~967 species (class IDs 0–966)
• Plants: ~127 species (class IDs 967–1093)

See annotations/classes.txt for the full mapping.

Edge Cases

Scenario	Rule
Multiple subjects in one image	Annotate all visible subjects with separate bounding boxes
Subject partially visible	Annotate if >30% of the subject is visible
Very small subject	Annotate if clearly identifiable as the target species
Subject occluded by vegetation	Annotate the visible portion
Image contains both butterfly and plant	Each gets its own bbox with respective species class

2. Annotation Format

YOLO (per image .txt)

<class_id> <x_center> <y_center> <width> <height>

All coordinates are normalized (0.0 to 1.0) relative to image dimensions.

COCO (annotations.json)

Standard COCO format with bbox in [x, y, width, height] pixel coordinates (top-left origin).

3. Annotation Protocol

Automated (v1)

• Grounding DINO zero-shot detection with text prompts
• Butterfly prompts: "butterfly . moth . caterpillar . pupa . chrysalis"
• Plant prompts: "plant . flower . leaf . tree . shrub"
• Fallback: full image as bounding box if detection fails
• Species class assigned from directory structure (not model output)

Quality Verification (recommended)

• Spot-check 100 random images per dataset
• Verify bbox covers the subject adequately
• Flag images where detection clearly failed
• Re-annotate flagged images manually if needed

4. Metadata Annotation

Per-image metadata is extracted automatically via OCR:

• Scientific name, common name, family
• Media code (cross-validated against existing records)
• Location, date, photographer credit
• Sex/life stage (butterflies only)

Missing fields are stored as empty strings, not dropped.

5. Tools Used

Tool	Purpose
Grounding DINO	Zero-shot object detection for bounding boxes
pytesseract	OCR for overlay text extraction
Pillow	Image cropping and processing
CVAT (optional)	Manual annotation refinement