The Oxford-IIIT Pet Dataset

  Description

A 37 category pet dataset with roughly 200 images for each class. The images have a large variations in scale, pose and lighting. This instance of the dataset uses standard label ordering and includes the standard train/test splits. Trimaps and bbox are not included, but there is an image_id field that can be used to reference those annotations from official metadata. Website: https://www.robots.ox.ac.uk/~vgg/data/pets/… See the full description on the dataset page: https://huggingface.co/datasets/timm/oxford-iiit-pet.

The Oxford-IIIT pet dataset is a 37 category pet image dataset with roughly 200 images for each class. The images have large variations in scale, pose and lighting. All images have an associated ground truth annotation of breed and species. Additionally, head bounding boxes are provided for the training split, allowing using this dataset for simple object detection tasks. In the test split, the bounding boxes are empty.

To use this dataset:

import tensorflow_datasets as tfds

ds = tfds.load('oxford_iiit_pet', split='train')
for ex in ds.take(4):
 print(ex)

See the guide for more informations on tensorflow_datasets.

Visualize on Visual Layer

  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… See the full description on the dataset page: https://huggingface.co/datasets/visual-layer/oxford-iiit-pet-vl-enriched.

Oxford IIIT Pet Dataset

## Overview

Oxford IIIT Pet Dataset is a dataset for instance segmentation tasks - it contains Pets annotations for 2,690 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

https://www.robots.ox.ac.uk/%7Evgg/data/pets/pet_annotations.jpg" alt="Example Annotations">

About this Dataset

The Oxford Pets dataset (also known as the "dogs vs cats" dataset) is a collection of images and annotations labeling various breeds of dogs and cats. There are approximately 100 examples of each of the 37 breeds. This dataset contains the object detection portion of the original dataset with bounding boxes around the animals' heads.

Origin

This dataset was collected by the Visual Geometry Group (VGG) at the University of Oxford.

Oxford Pets

## Overview

Oxford Pets is a dataset for object detection tasks - it contains Animals annotations for 3,580 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

Oxford-IIT Pets dataset generated using Stable Diffusion 1.5. Original image is used to perform Img2Img to generate a new image.

This dataset can be used to perform image classification on its own or used as additional training data for Oxford-IIT Pets dataset.

The approach to generating this dataset can be found in the notebook: https://www.kaggle.com/code/chekhui/generation-of-images-via-stable-diffusion

Omkar M Parkhi and Andrea Vedaldi have created a 37 category pet dataset with roughly 200 images for each class. The images have a large variations in scale, pose and lighting. All images have an associated ground truth annotation of breed, head ROI, and pixel level trimap segmentation.The details of the categories and the number of images for each class can be found at:https://www.robots.ox.ac.uk/~vgg/data/pets/.

jonathancui/oxford-pets dataset hosted on Hugging Face and contributed by the HF Datasets community

Oxford Pets Dataset

## Overview

Oxford Pets Dataset is a dataset for object detection tasks - it contains Pets annotations for 3,680 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [Public Domain license](https://creativecommons.org/licenses/Public Domain).

The Oxford IIIT Pet dataset is one of the most frequently used datasets for people who are new to image segmentation. This is an augmented version of the same dataset. Transformations like rotations, flips and crops have been performed on the dataset to make models trained with this dataset more robust.

Both training and test datasets are in tfrecord format for better optimizing read during training.

The dataset consists of the image and its segmented counterpart in the same record, each being 256x256x3 images. The original image is RGB and the segmented image is a one hot encoded image with each pixel stating whether it is background (green), foreground (red) or not classified (blue).

We have created a 37 category pet dataset with roughly 200 images for each class. The images have a large variations in scale, pose and lighting. All images have an associated ground truth annotation of breed, head ROI, and pixel level trimap segmentation.

Dataset

This dataset was created by DoDat12

Released under Other (specified in description)

Contents

The Oxford-IIIT Pet Dataset is a comprehensive image dataset used in computer vision tasks such as object recognition and image segmentation. It includes multiple pet breeds with pixel-level annotations, aiding the development of accurate AI vision models.

Dataset

This dataset was created by tomasfern

Released under CC BY-NC-SA 4.0

Contents

Dataset

This dataset was created by Shenouda Safwat

Released under MIT

Contents

koorye/Oxford-Pets dataset hosted on Hugging Face and contributed by the HF Datasets community

Images of cats and dogs from the Oxford IIIT Pet Dataset, by Omkar M Parkhi and Andrea Vedaldi and Andrew Zisserman and C. V. Jawahar, created under the Creative Commons Attribution-ShareAlike 4.0 International License.

The Oxford-IIIT Pet Dataset is a 37 classes pet dataset created by the Visual Geometry Group at Oxford. Citation: O. M. Parkhi et al., 2012

TFRecords have been made by using this Kaggle dataset of Oxford's Pets.

The data is split into train and test set of files where trainX-Y has a total of Y images. TFRecords itself have the following features: feature = { 'image': _bytes_feature, 'image_name': _bytes_feature, 'target': _int64_feature } Images are resized to 224x224 and range of the target labels is shifted from original 1-37 to 0-36.

Dataset Card for "Oxford-IIIT-Pet"

This is a non-official Oxford IIIT Pet dataset for fine-grained Image Classification.
If you want to download the official dataset, please refer to the here.