Tomato Maturity Detection Dataset

The current agricultural industry faces issues such as low crop management efficiency and high cost of manual inspection, particularly in determining the maturity of tomatoes, affecting yield and market sales. Existing solutions rely heavily on manual observation, which is subjective and inefficient. This dataset aims to help develop accurate automated detection models by providing high-quality images of tomato maturity, thereby enhancing agricultural production efficiency. The dataset includes 5000 high-resolution images of tomatoes collected from various growing environments, taken with professional cameras, and standardized under multiple conditions such as lighting and angle. In terms of quality control, the data has gone through multiple rounds of labeling and consistency checks to ensure labeling accuracy. The data is stored in JPEG format, organized by folders for ease of subsequent processing and analysis.