Dataset Card for Stanford Dogs

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. Contents of this dataset:

Number of categories: 120

Number of images: 20,580

Annotations: Class labels, Bounding boxes (not imported to HF)

Website: http://vision.stanford.edu/aditya86/ImageNetDogs/

Paper:… See the full description on the dataset page: https://huggingface.co/datasets/maurice-fp/stanford-dogs.

Who doesn't love dogs? 🐕 Those wonderful creatures make our life so much better! So if you love dogs as much as I do, you'd be probably interested in this dataset.

It includes the name of the breed, country of origin, longevity, height, color of fur and eyes, their character traits and typical health problems for each breed.

Dataset Card for Cats Vs. Dogs

  Dataset Summary

A large set of images of cats and dogs. There are 1738 corrupted images that are dropped. This dataset is part of a now-closed Kaggle competition and represents a subset of the so-called Asirra dataset. From the competition page:

The Asirra data set Web services are often protected with a challenge that's supposed to be easy for people to solve, but difficult for computers. Such a challenge is often called a CAPTCHA… See the full description on the dataset page: https://huggingface.co/datasets/microsoft/cats_vs_dogs.

Context

This 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. It was originally collected for fine-grain image categorization, a challenging problem as certain dog breeds have near identical features or differ in colour and age.

Content

• Number of categories: 120
• Number of images: 20,580
• Annotations: Class labels, Bounding boxes

Acknowledgements

The original data source is found on http://vision.stanford.edu/aditya86/ImageNetDogs/ and contains additional information on the train/test splits and baseline results. If you use this dataset in a publication, please cite the dataset on the following papers: Aditya Khosla, Nityananda Jayadevaprakash, Bangpeng Yao and Li Fei-Fei. Novel dataset for Fine-Grained Image Categorization. First Workshop on Fine-Grained Visual Categorization (FGVC), IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2011. Secondary: J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li and L. Fei-Fei, ImageNet: A Large-Scale Hierarchical Image Database. IEEE Computer Vision and Pattern Recognition (CVPR), 2009.

Inspiration

• Can you correctly identify dog breeds that have similar features, such as the basset hound and bloodhound?
• Is this chihuahua young or old?

Over a 1000 images of cats and dogs scraped off of google images. The problem statement is to build a model that can classify between a cat and a dog in an image as accurately as possible.

Image sizes range from roughly 100x100 pixels to 2000x1000 pixels.

Image format is jpeg.

Duplicates have been removed.

6 Dog Breeds

## Overview

6 Dog Breeds is a dataset for object detection tasks - it contains Dogs annotations for 1,257 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).

Dataset Summary

Mini(24 MB) Classification dataset for mini projects. Cats, dogs and rabbit are included as pet in this dataset.

  Supported Tasks and Leaderboards

image-classification: Based on a pet image, the goal of this task is to predict the type of pet (i.e., dog or cat or rabbit).

  Languages

English

  Class Label Mappings:

{ "cat": 0, "dog": 1, "rabbit": 2, }

  Load Dataset

from datasets import load_dataset

train_dataset =… See the full description on the dataset page: https://huggingface.co/datasets/rokmr/pets.

Dataset Card for SDXL Dogs

Images of dogs breeds in the Stanford Dogs dataset, generated by SDXL

This is a FiftyOne dataset with 191 samples.

  Installation

If you haven't already, install FiftyOne: pip install -U fiftyone

  Usage

import fiftyone as fo import fiftyone.utils.huggingface as fouh

Load the dataset

Note: other available arguments include 'max_samples', etc

dataset = fouh.load_from_hub("Voxel51/SDXL-Dogs")

Launch the App

session =… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/SDXL-Dogs.

Here are a few use cases for this project:

1. "Pet Identification App": The model can be used to create an application that helps users identify the breed of their pets or stray dogs. It would be useful for new pet owners, pet shelters, or people considering adoption/rescue.

2. "Dog Breed Study Research": For researchers studying canine genetics, behaviors, or diseases, this model would provide an efficient tool for recognizing different breeds, helping to collect data faster and more accurately.

3. "Virtual Dog Show": In virtual dog shows, this model could be employed to identify and classify the breeds. It could be implemented as part of the pre-judging process to ensure eligibility based on breed.

4. "Lost and Found Assistance": The model could be applied in a lost and found system to identify the breed of lost dogs, helping pet owners and shelters to more rapidly track missing pets.

5. "Pet Service Customization": Businesses offering pet services (like grooming, dog walking, or boarding) could use the model for identifying dog breeds to tailor their services more accurately according to the distinct needs of different breeds.

This dataset consists of a large collection of images, each of which contains either a dog or something else.

The images in the dataset come from a diverse range of sources and include a wide variety of dog breeds, as well as other objects and scenes. This makes the dataset suitable for testing the robustness and generalization abilities of machine learning models.

Dataset Summary

A dataset from kaggle with duplicate data removed.

  Data Fields

The data instances have the following fields:

image: A PIL.Image.Image object containing the image. Note that when accessing the image column: dataset[0]["image"] the image file is automatically decoded. Decoding of a large number of image files might take a significant amount of time. Thus it is important to first query the sample index before the "image" column, i.e. dataset[0]["image"]… See the full description on the dataset page: https://huggingface.co/datasets/Bingsu/Cat_and_Dog.

Dog Breed Detection 2

## Overview

Dog Breed Detection 2 is a dataset for classification tasks - it contains Dogs Ub9z annotations for 17,390 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).

Dataset Card for the Dog 🐶 vs. Food 🍔 (a.k.a. Dog Food) Dataset

  Dataset Summary

This is a dataset for binary image classification, between 'dog' and 'food' classes. The 'dog' class contains images of dogs that look like fried chicken and some that look like images of muffins, and the 'food' class contains images of (you guessed it) fried chicken and muffins 😋

  Supported Tasks and Leaderboards

TBC

  Languages

The labels are in English (['dog'… See the full description on the dataset page: https://huggingface.co/datasets/sasha/dog-food.

Cute Dogs

## Overview

Cute Dogs is a dataset for object detection tasks - it contains Hazmat Sign annotations for 679 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).

This dataset is for running the code from this site: https://becominghuman.ai/building-an-image-classifier-using-deep-learning-in-python-totally-from-a-beginners-perspective-be8dbaf22dd8.

This is how to show a picture from the training set: display(Image('../input/cat-and-dog/training_set/training_set/dogs/dog.423.jpg'))

From the test set: display(Image('../input/cat-and-dog/test_set/test_set/cats/cat.4453.jpg'))

See an example of using this dataset. https://www.kaggle.com/tongpython/nattawut-5920421014-cat-vs-dog-dl

This dataset aims to collect multiple images from dogs worldwide for identification and classification purposes. Though at this stage, it is mostly US and Australia. I aim to continue to improve it over time. Please message me if you want your dog to be included in the dataset.

It 300k+ dog images, across 200k+ identities and 240+ breeds

Each dog is tagged with the following attributes:

• Breed
• Gender
• Age in months (where available)
• Location

Most dogs in the collection have more than one image. There are 126,550 identities across over 313,688 images.

The dataset is a work in progress. I aim to include dogs across more countries and breeds in future releases.

Dogs Behavior

## Overview

Dogs Behavior is a dataset for object detection tasks - it contains Dog Behaviors annotations for 350 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).

Dog Breeds 3

## Overview

Dog Breeds 3 is a dataset for object detection tasks - it contains Dogs annotations for 210 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).

Summary of evidence for hypotheses 1–5 in wolf puppies, dog puppies, and adult dogs.

Dataset Card for Generated Dogs

10+ images for each class in the Stanford Dogs dataset, but all generated with SDXL. Images were filtered for CLIP score, and cartoonish images were removed.

This is a FiftyOne dataset with 1305 samples.

  Installation

If you haven't already, install FiftyOne: pip install -U fiftyone

  Usage

import fiftyone as fo import fiftyone.utils.huggingface as fouh

Load the dataset

Note: other available arguments include… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/SDXL-Generated-Stanford-Dogs.