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license: apache-2.0 |
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task_categories: |
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- image-classification |
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language: |
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- en |
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tags: |
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- multiclass-image-classification |
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- vision |
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size_categories: |
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- n<1K |
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--- |
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# Fruits30 Dataset |
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## Description: |
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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. |
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## Dataset Composition: |
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- **Number of Classes:** 30 |
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- **Image Resolution:** 224x224 pixels |
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- **Total Images:** 826 |
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## Classes: |
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0 : acerolas |
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1 : apples |
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2 : apricots |
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3 : avocados |
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4 : bananas |
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5 : blackberries |
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6 : blueberries |
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7 : cantaloupes |
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8 : cherries |
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9 : coconuts |
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10 : figs |
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11 : grapefruits |
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12 : grapes |
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13 : guava |
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14 : kiwifruit |
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15 : lemons |
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16 : limes |
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17 : mangos |
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18 : olives |
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19 : oranges |
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20 : passionfruit |
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21 : peaches |
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22 : pears |
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23 : pineapples |
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24 : plums |
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25 : pomegranates |
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26 : raspberries |
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27 : strawberries |
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28 : tomatoes |
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29 : watermelons |
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## Preprocessing: |
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Images have undergone preprocessing to maintain consistency and facilitate model training. Preprocessing steps may include resizing, normalization, and other enhancements. |
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## Intended Use: |
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The Fruits30 dataset is suitable for tasks such as image classification, object recognition, and machine learning model training within the domain of fruit identification. |
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## Sources: |
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Croudsource. |
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## Note: |
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Ensure proper attribution and compliance with the dataset's licensing terms when using it for research or development purposes. |
