VinayHajare/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.