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Add captions to images.
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---
language:
- en
task_categories:
- image-classification
- object-detection
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: label_bbox_enriched
list:
- name: bbox
sequence: float64
- name: confidence
dtype: float64
- name: label
dtype: string
- name: caption_enriched
dtype: string
splits:
- name: train
num_bytes: 149043965.64
num_examples: 3680
- name: test
num_bytes: 133273793.037
num_examples: 3669
download_size: 281624839
dataset_size: 282317758.677
---
[![Visualize Dataset on Visual Layer](https://img.shields.io/badge/Visualize%20on-%20Visual%20Layer-purple?style=for-the-badge&logo=numpy)](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 and bounding boxes.
With this additional information, the Oxford IIIT Pet dataset can be extended to a variety of tasks such as image retrieval or visual question answering.
## Description
The dataset consists of 6 columns:
+ `image_id`: Unique identifier for each image. `image_id` is the original filename of the image from Oxford IIIT Pets dataset.
+ `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.
## 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.
<video controls autoplay src="https://cdn-uploads.huggingface.co/production/uploads/6195f404c07573b03c61702c/_RZTBZ6zNGz8f7g0sxow4.mp4"></video>
<div style="text-align: center;">
<a href="https://app.visual-layer.com/dataset/3972b3fc-1809-11ef-bb76-064432e0d220/data?p=1&page=1">
<img src="https://img.shields.io/badge/Visualize%20on-%20Visual%20Layer-purple?style=for-the-badge&logo=numpy" alt="Visualize Dataset on Visual Layer">
</a>
</div>
## License & Disclaimer
We provide no warranty of 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
<div style="text-align: center; margin-top:50px;">
<a href="https://visual-layer.com/" style="padding:10px; display: inline-block;">
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</div>
<div style="text-align: center;">
<img style="width:200px; display: block; margin: 0 auto;" alt="logo" src="https://d2iycffepdu1yp.cloudfront.net/design-assets/VL_horizontal_logo.png">
<div style="margin-top:20px;">Copyright © 2024 Visual Layer. All rights reserved.</div>
</div>