Mango Fruit Image Classification - Uganda

This dataset contains 37,957 high-resolution images of mango fruits collected in Eastern Uganda (Soroti District: Aloet and Madera areas) using smartphone cameras under natural daylight conditions. It includes both healthy and defective mangoes, representing a wide range of post-harvest conditions encountered during harvesting, handling, and marketing.

Dataset Organization:
Original: 4,699 raw images captured in the field.
Preprocessed: 5,064 images resized and center-cropped for consistent framing.
Augmented: 28,194 images generated via flipping, brightness adjustment, cropping, and controlled 90°/270° rotations to simulate natural orientation changes.

File Format & Access:
Images are stored in JPEG format.
The dataset is provided in .zpaq format for maximum compression and can be extracted using PeaZip (Windows).

A .zip version of the dataset is also available on Kaggle: https://www.kaggle.com/datasets/joanitanamuyiga/mango-fruit-image-classification-uganda

Potential Applications:
Computer vision and image processing research
Fruit quality assessment and post-harvest defect studies
Machine learning applications for classification, defect detection, and infection segmentation