Datasets:

bazudde
/

Sweetpotato_images

Tasks:

Modalities:

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AutoTrain Dataset for project: sweet-potato-classification

This dataset has been automatically processed by AutoTrain for project sweet-potato-classification.

The BCP-47 code for the dataset's language is unk.

A sample from this dataset looks as follows:

[
  {
    "image": "<256x192 RGB PIL image>",
    "target": 0
  },
  {
    "image": "<256x192 RGB PIL image>",
    "target": 0
  }
]

The dataset has the following fields (also called "features"):

{
  "image": "Image(decode=True, id=None)",
  "target": "ClassLabel(names=['Leaf rust', 'Root rot', 'alternaria_sweet_potato_leaf_spot'], id=None)"
}

This dataset is split into a train and validation split. The split sizes are as follow:

Split name	Num samples
train	46
valid	13