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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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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:** 856 |
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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. |
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