license:mit region:us
The Stanford Dogs dataset contains images of 120 breeds of dogs from around the world. This dataset has been built using images and annotation from ImageNet for the task of fine-grained image categorization.
---
pretty_name: "Stanford Dogs"
license: "mit"
task_category: "Classification"
---

# Dataset

This dataset is extracted from [Stanford Dogs Dataset](http://vision.stanford.edu/aditya86/ImageNetDogs/)

# Load

```python
import datasets

dataset = datasets.load_dataset("Alanox/stanford-dogs", split="full")

print(dataset)
"""
Dataset({
    features: ['name', 'annotations', 'target', 'image'],
    num_rows: 20580
})
"""

print(dataset.features)
"""
{
    'name':         Value(dtype='string', id=None),
    'annotations':  Array2D(shape=(None, 4), dtype='int32', id=None),
    # ["xmin", "ymin", "xmax", "ymax"]
    'target':       Value(dtype='string', id=None),
    'image':        Image(decode=True, id=None)
}
"""
```

This dataset was created by the scripts from [this github repo](https://github.com/AlanBlanchet/ClassezDesImagesAvecDesAlgorithmesDeDeeplearning)

# Fixes

- `n02105855_2933.jpg` was not a `.jpg`. Converted all images to `.jpg`
