Fruit Classification is a fruit classification image dataset designed to train machine learning and deep learning models for fruit recognition and classification. The dataset covers 101 fruit species, such as apples, bananas, oranges, grapes, strawberries, etc. Each category contains about 400 images for training, 50 images for validation, and 50 images for testing. The dataset has high image resolution, covers fruits under different viewing angles and lighting, and has good diversity.