emma7991/Fruits-30

Fruits30 Dataset

Description:

The Fruits30 dataset is a collection of images featuring 30 different types of fruits. Each image has been preprocessed and standardized to a size of 224x224 pixels, ensuring uniformity in the dataset.

Dataset Composition:

• —Number of Classes: 30
• —Image Resolution: 224x224 pixels
• —Total Images: 826

Classes:

0 : acerolas 1 : apples 2 : apricots 3 : avocados 4 : bananas 5 : blackberries 6 : blueberries 7 : cantaloupes 8 : cherries 9 : coconuts 10 : figs 11 : grapefruits 12 : grapes 13 : guava 14 : kiwifruit 15 : lemons 16 : limes 17 : mangos 18 : olives 19 : oranges 20 : passionfruit 21 : peaches 22 : pears 23 : pineapples 24 : plums 25 : pomegranates 26 : raspberries 27 : strawberries 28 : tomatoes 29 : watermelons

Preprocessing:

Images have undergone preprocessing to maintain consistency and facilitate model training. Preprocessing steps may include resizing, normalization, and other enhancements.

Intended Use:

The Fruits30 dataset is suitable for tasks such as image classification, object recognition, and machine learning model training within the domain of fruit identification.

Sources:

Croudsource.

Note:

Ensure proper attribution and compliance with the dataset's licensing terms when using it for research or development purposes.