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--- |
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task_categories: |
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- image-classification |
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--- |
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# Dataset for project: food-classification |
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## Dataset Description |
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This dataset has been processed for project food-classification. |
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### Languages |
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The BCP-47 code for the dataset's language is unk. |
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## Dataset Structure |
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### Data Instances |
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A sample from this dataset looks as follows: |
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```json |
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[ |
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{ |
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"image": "<308x512 RGB PIL image>", |
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"target": 0 |
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}, |
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{ |
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"image": "<512x512 RGB PIL image>", |
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"target": 0 |
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} |
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] |
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``` |
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### Dataset Fields |
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The dataset has the following fields (also called "features"): |
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```json |
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{ |
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"image": "Image(decode=True, id=None)", |
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"target": "ClassLabel(names=['apple_pie', 'falafel', 'french_toast', 'ice_cream', 'ramen', 'sushi', 'tiramisu'], id=None)" |
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} |
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``` |
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### Dataset Splits |
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This dataset is split into a train and validation split. The split sizes are as follow: |
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| Split name | Num samples | |
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| ------------ | ------------------- | |
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| train | 1050 | |
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| valid | 350 | |
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