Tomato Target Detection Dataset

In the current agricultural field, tomato cultivation faces challenges such as frequent pests and low production efficiency. Existing solutions often rely on manual inspection, which is inefficient and prone to missed detections. Therefore, the tomato target detection dataset is created to help farmers promptly discover and address pests, improving crop yield and quality through efficient target detection technology. The dataset is constructed by capturing tomato images in various growth environments using high-resolution cameras, followed by multiple rounds of annotation and expert review to ensure accuracy and consistency. Data storage employs JPEG format, organized such that each image file corresponds to an annotation file, facilitating subsequent processing and model training. This dataset not only includes images of tomatoes in various growth states but also undergoes strict quality control to ensure data usability.