AllerNuts: Dataset for Identifying Allergenic Nuts via Image Classification

This Nuts Classification Dataset is developed to support health-related research, particularly for identifying allergenic nuts through computer vision techniques. Given the health benefits of nuts, there is also a need to detect varieties that may cause allergic reactions. Based on online research, four types of nuts commonly associated with allergies were selected: Almonds, Cashews, Peanuts, and Pistachios. Nuts Samples were collected from local markets in Kaliakoir, Gazipur, Bangladesh, between November 16 and November 18, 2023. Images of these nuts were captured using a Xiaomi Redmi Note 9S smartphone. Originally in high dimensions (300x300 px), images were resized to 800x600 px to optimize file size while preserving quality. The dataset contains 4,390 images: 1,039 Almonds, 1,070 Cashews, 1,153 Peanuts, and 1,128 Pistachios. Backgrounds were removed to improve model learning efficiency; mages were taken with a white paper background and flash lighting for clarity and consistency. This balanced dataset, with backgrounds removed, is useful for computer vision projects to identify allergenic nuts using machine learning and deep learning models. It will also support health-related research by helping to classify nuts that may cause allergies.

Original Data:
Total: 4390 Images
Data Type: JPG
Dimension: 800 X 600

Without Background Data:
Total: 4390 Images
Data Type: JPG
Dimension: 800 X 600