A dataset of annotated images for detecting plant diseases across 29 crop classes. The dataset is formatted for use with the YOLOv8 object detection model. Its origin, size, and specific collection details are unknown.
Use Cases
- Train object detection models for plant disease identification based on annotated images.
- Benchmark multi-label classification performance across 29 crop classes.
- Develop agricultural monitoring tools based on computer vision techniques.
Strengths
- Dataset is specifically formatted for the YOLOv8 object detection framework.
- Covers 29 distinct crop classes, suggesting a broad scope.
Limitations
- Row count, file size, and column structure are unknown, limiting suitability assessment.
- Column-level documentation is absent; field semantics must be inferred after download.
- Last update date is unknown; freshness unverified.
Provenance
- Geography
- India (inferred from platform tags)