Tomato Disease Dataset

This dataset comprises 1,026 images of tomato plants affected by viral diseases, gray mold, and bacterial wilt, with a total data volume of approximately 3.14 GB. The images were captured from multiple angles and distances to comprehensively reflect the multi-scale phenotypic characteristics of the diseases. Under the guidance of plant pathology experts, all images were manually annotated using the LabelImg tool, with labeled regions including leaves, fruits, and stems. Each image is accompanied by a corresponding XML-format annotation file. The dataset is well-suited for tasks such as disease classification, object detection, and plant phenotyping. It can support the training of deep learning models and holds promise for applications in cross-crop transfer learning.