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---
task_categories:
- image-classification
---
# AutoTrain Dataset for project: rice_diagnosis
## Dataset Description
This dataset has been automatically processed by AutoTrain for project rice_diagnosis.
Originally from Kaggle, this shows rice leaves (leaf) up close pictures labeled with the disease of which they show symptoms.
### Languages
The BCP-47 code for the dataset's language is unk.
## Dataset Structure
### Data Instances
A sample from this dataset looks as follows:
```json
[
{
"image": "<3081x897 RGB PIL image>",
"target": 0
},
{
"image": "<3081x897 RGB PIL image>",
"target": 0
}
]
```
### Dataset Fields
The dataset has the following fields (also called "features"):
```json
{
"image": "Image(decode=True, id=None)",
"target": "ClassLabel(names=['Bacterial leaf blight', 'Brown spot', 'Leaf smut'], id=None)"
}
```
### Dataset Splits
This dataset is split into a train and validation split. The split sizes are as follow:
| Split name | Num samples |
| ------------ | ------------------- |
| train | 96 |
| valid | 24 |
|