Tomato Disease Images with 11 Classes, ~400 Images per Class

An augmented image dataset for tomato disease classification contains approximately 400 images for each of 11 disease classes. The dataset is hosted on Kaggle and is intended for computer vision applications in agriculture. Its specific creation details, such as author and collection timeframe, are not provided.

Use Cases

• Train image classification models to identify tomato diseases based on the 11 labeled classes.
• Develop automated plant health monitoring systems based on visual symptom analysis.
• Benchmark computer vision algorithms for agricultural pathology using the provided image splits.
• Augment existing plant disease datasets with the provided ~400 images per class.

Strengths

• Dataset is augmented, which may increase model robustness.
• Contains approximately 400 images for each of the 11 classes, suggesting balanced representation per category.
• Data is pre-split for training and evaluation, facilitating immediate use.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Data may reflect geographic, temporal, or source bias inherent to its collection on Kaggle.

Provenance

Source

Kaggle