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