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