High-Resolution Litchi Fruit Image Dataset for Maturity Detection
Description
1) The demand for high-quality, fresh fruits is universal. In today’s health-conscious society, people are increasingly selective about their food choices, believing that consuming spoiled fruits can negatively impact their health. As a result, the fruit market often suffers, leading to significant economic losses. A major contributor to fruit spoilage in Bangladesh is the manual method used to assess fruit maturity. If fruits aren’t harvested at the right time, they can deteriorate quickly. Therefore, accurately distinguishing between ripe and unripe fruits is crucial for determining the optimal harvest period. Litchi, a highly nutritious fruit and a key crop in Bangladesh, faces substantial daily financial losses due to spoilage. This highlights the urgent need for an automated system to categorize litchi fruits as mature, and immature which would be invaluable to farmers, vendors, and the fruit processing industry. (2) In the modern era, computer vision techniques have shown great potential in handling tasks like classification and detection. (3) To support the development of computer vision-based algorithms, we introduce a comprehensive dataset for litchi fruit that includes Maturity Detection datasets. The Maturity Detection Dataset classifies fruits as either immature or mature, This classifications were made in consultation with an agricultural expert from a specialized institute. (4) The dataset includes 3,400 images of mature, immature litchi fruits collected from demonstration areas across three locations in Bangladesh. Additionally, 20,000 augmented images were generated using flipping, width, height shifting, brightening, rotation, shearing, and zooming to expand the dataset.