Ghana Crop Disease Detection Dataset

The training set includes annotated images with bounding boxes that mark the location and type of crop diseases, allowing for the detection of multiple diseases in a single image. Each disease is carefully annotated to provide precise training data for machine learning models.

The test set contains images that may feature new, previously unseen diseases, with bounding boxes removed, making it perfect for testing model robustness and generalization to novel conditions.

Key Features:

• Corn, Pepper, and Tomato Crops: Focused on three major Ghanaian crops.
• Disease Annotations: Precise bounding boxes indicating disease presence and type.
• Multi-Disease Detection: Training images may contain multiple diseases, annotated separately.
• Test Set for Generalization: Test images may include new diseases not seen in training data.