Datasets:
Tasks:
Image Classification
Modalities:
Image
task_categories: | |
- image-classification | |
# AutoTrain Dataset for project: swin-muppet | |
## Dataset Description | |
This dataset has been automatically processed by AutoTrain for project swin-muppet. | |
### 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": "<286x286 RGB PIL image>", | |
"target": 7 | |
}, | |
{ | |
"image": "<169x170 RGB PIL image>", | |
"target": 13 | |
} | |
] | |
``` | |
### Dataset Fields | |
The dataset has the following fields (also called "features"): | |
```json | |
{ | |
"image": "Image(decode=True, id=None)", | |
"target": "ClassLabel(num_classes=24, names=['Animal', 'Beaker', 'Bert', 'BigBird', 'Bunsen', 'Camilla', 'CookieMonster', 'Elmo', 'Ernie', 'Floyd', 'Fozzie', 'Gonzo', 'Grover', 'Kermit', 'Oscar', 'Pepe', 'Piggy', 'Rowlf', 'Scooter', 'Statler', 'SwedishChef', 'TheCount', 'Waldorf', 'Zoot'], 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 | 599 | | |
| valid | 162 | | |