Cauliflower Disease Detection: <1,000 YOLO-Formatted Leaf Images

Encompassing under 1,000 images of cauliflower leaves for disease detection and classification, published by indra17 and updated in January 2026. It provides visual data in YOLO-compatible format specifically for agricultural plant pathology and computer vision applications.

Use Cases

• Training object detection models to identify disease lesions on cauliflower leaves using YOLO bounding boxes
• Classifying cauliflower leaf health into specific disease categories
• Transfer learning for agricultural diagnostic tools using the leaf image set

Strengths

• YOLO-compatible format for immediate object detection training
• MIT license allows for commercial and research use
• Specialized focus on cauliflower-specific leaf pathology

Limitations

• Small sample size of fewer than 1,000 images
• Geographic bias toward the United States as indicated by metadata tags

Provenance

Source

indra17 via Hugging Face

Freshness

Last updated January 2026.

Geography

United States