---
language:
- en
task_categories:
- image-classification
- object-detection
- visual-question-answering
- text-to-image
- image-to-text
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
dataset_info:
features:
- name: image_id
dtype: string
- name: image
dtype: image
- name: label_cat_dog
dtype: string
- name: label_breed
dtype: string
- name: caption_enriched
dtype: string
- name: label_bbox_enriched
list:
- name: bbox
sequence: int64
- name: label
dtype: string
- name: issues
list:
- name: confidence
dtype: float64
- name: duplicate_group_id
dtype: string
- name: issue_type
dtype: string
splits:
- name: train
num_bytes: 148789851.0
num_examples: 3680
- name: test
num_bytes: 133008511.375
num_examples: 3669
download_size: 281276926
dataset_size: 281798362.375
---
[](https://app.visual-layer.com/dataset/3972b3fc-1809-11ef-bb76-064432e0d220/data?p=1&page=1)
# Oxford-IIIT-Pets-VL-Enriched
An enriched version of the Oxford IIIT Pets Dataset with image caption, bounding boxes, and label issues!
With this additional information, the Oxford IIIT Pet dataset can be extended to various tasks such as image retrieval or visual question answering.
The label issues help to curate a cleaner and leaner dataset.
## Description
The dataset consists of 6 columns:
+ `image_id`: Unique identifier for each image. `image_id` is the original filename of the image from the [Oxford IIIT Pet dataset](https://www.robots.ox.ac.uk/~vgg/data/pets/).
+ `image`: Image data in the form of PIL Image.
+ `label_cat_dog`: Label for the image, whether it is a cat or a dog. Provided by the authors of the original dataset.
+ `label_breed`: Label for the breed of the cat or dog in the image. Consists of 37 pet breeds of cats and dogs. Provided by the authors of the original dataset.
+ `label_bbox_enriched`: Enriched labels for the image. Consists of bounding box coordinates, confidence score, and label for the bounding box. Generated by in-house and customized YOLOv8 model.
+ `caption_enriched`: Enriched captions for the image. Generated by BLIP2 captioning model.
+ `issues`: Quality issues found such as duplicate, mislabeled, dark, blurry, bright, and outlier image.
## Usage
This dataset can be used with the Hugging Face Datasets library.:
```python
import datasets
ds = datasets.load_dataset("visual-layer/oxford-iiit-pet-vl-enriched")
```
More in this [notebook](usage.ipynb).
## Interactive Visualization
Visual Layer provides a platform to interactively visualize the dataset.
Check it out [here](https://app.visual-layer.com/dataset/3972b3fc-1809-11ef-bb76-064432e0d220/data?p=1&page=1). No sign-up required.
## License & Disclaimer
We provide no warranty on the dataset, and the user takes full responsibility for the usage of the dataset. By using the dataset, you agree to the terms of the Oxford IIIT Pets dataset license.
## About Visual Layer
