Guava Dataset

Recent advances in artificial intelligence methods and computer vision algorithms have emerged as a
bridge between machines and humans, helping to solve complex real-world problems. Images play a crucial role
in extracting valuable information, and in agriculture, they serve as a powerful tool for crop yield estimation, weed
detection, plant disease classification, nutrient deficiency assessment, and fruit and flower counting, among other
applications. In this manuscript, we introduce a comprehensive database of the well-known fruit plant, Guava.
The fruit has diverse applications in both the food and medical domains. Estimating guava yield using image
processing and computational intelligence algorithms can be highly beneficial for assessing actual crop
productivity. This study presents a real-time collection of guava fruit images and videos using mobile and digital
cameras. A total of 320 original images were captured. The raw dataset will be publicly available on Mendeley, providing researchers and
academicians with a valuable resource for exploring fruit counting methodologies and predicting field
productivity. We believe that this dataset will contribute significantly to the advancement of AI-driven agricultural
research and precision farming. Video data will be made available on request. The images acquired with the help of camera are named as IMG_ABCD.JPG and the images captured with the help of mobile phone camera are named as IMG2024AAAAAAAAAA_00.jpg