Tomato Leaf Disease Images for YOLOv8 Object Detection

A dataset of tomato leaf images annotated for object detection tasks. The description indicates it is intended for training YOLOv8 models and includes background noise. The dataset's author, organization, and specific size are unknown.

Use Cases

• Train object detection models to identify tomato leaf diseases based on annotated images.
• Benchmark YOLOv8 model performance on agricultural imagery.
• Study the impact of background noise on model robustness for plant disease detection.

Strengths

• The dataset is explicitly formatted for the YOLOv8 object detection framework.
• The description mentions inclusion of background noise, which may aid in training more robust models.

Limitations

• Row count and dataset size are unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Last update date is unknown; freshness unverified.

Provenance

Source

The dataset title references 'PlantVillage', which is a known repository for plant disease images.

Collection Method

The description suggests images were merged and annotated for YOLOv8, but the exact gathering method is unspecified.