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.

Stanford Dogs Dataset Dog Breed

## Overview

Stanford Dogs Dataset Dog Breed is a dataset for object detection tasks - it contains Dogs annotations for 20,491 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).

This dataset is a redistribution of the following dataset. https://github.com/suzuki256/dog-dataset The dataset and its contents are made available on an "as is" basis and without warranties of any kind, including without limitation satisfactory quality and conformity, merchantability, fitness for a particular purpose, accuracy or completeness, or absence of errors.

The Stanford Dogs dataset contains 20,580 images of 120 classes of dogs from around the world, which are divided into 12,000 images for training and 8,580 images for testing.

I created this dataset for my junior year independent work at Princeton University. I could not find any pre-existing dataset of mixed breed dogs with their genetic breed breakdown, so I made my own!

My project was to develop a machine learning algorithm to classify mixed breed dogs; I adapted the Xception model to classify purebred dog breeds and trained the model on the Stanford Dog Dataset. Then I fine-tuned the model on my mixed-breed dog dataset.

I have provided here two folders of images. One folder of images has folders for each dog, and multiple images within each folder. The second folder of images has just one image per dog.

I have also provided two .csv files. The first contains the genetic breed breakdown of each dog in the dataset. The second contains the genetic breed breakdown of each dog in the dataset, but normalized to only include the 120 breeds covered by the Stanford Dog Dataset. The genetic results are from Wisdom Panel Dog DNA kits - I collected all images and genetic results through public posts in the Wisdom Panel Facebook community!

Hope that you find this dataset useful and continue to add to it!

Detection Of Stray Dogs

## Overview

Detection Of Stray Dogs is a dataset for object detection tasks - it contains Stray Dogs annotations for 305 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).

Tsinghua Dogs is a fine-grained classification dataset for dogs, over 65% of whose images are collected from people's real life. Each dog breed in the dataset contains at least 200 images and a maximum of 7,449 images, basically in proportion to their frequency of occurrence in China, so it significantly increases the diversity for each breed over existing dataset. Furthermore, Tsinghua Dogs annotated bounding boxes of the dog’s whole body and head in each image, which can be used for supervising the training of learning algorithms as well as testing them.

amaye15/stanford-dogs dataset hosted on Hugging Face and contributed by the HF Datasets community

A dog breed image classification dataset is a collection of images of dogs, each labeled with their respective breeds. These datasets are commonly used in the field of computer vision and machine learning for tasks such as image classification and object recognition..

This statistic shows common complaints of Americans who have bought puppies from breeders, pet stores or so-called brokers and realized their new pet is not in good health. The complaints were collected from 2007 to 2011 by the Humane Society of America via e-mail, a website complaint form and a tip line. Overall, 2,479 complaints were registered during these five years, 40 percent of those were complaints about the puppies suffering from an illness.

Active Dog Licenses. All dog owners residing in NYC are required by law to license their dogs. The data is sourced from the DOHMH Dog Licensing System (https://a816-healthpsi.nyc.gov/DogLicense), where owners can apply for and renew dog licenses. Each record represents a unique dog license that was active during the year, but not necessarily a unique record per dog, since a license that is renewed during the year results in a separate record of an active license period. Each record stands as a unique license period for the dog over the course of the yearlong time frame.

This dataset contains a list of shelter animals that are ready to be adopted from the Montgomery County Animal Services and Adoption Center at 7315 Muncaster Mill Rd., Derwood MD 20855. The 'How To Adopt' details are posted on https://www.montgomerycountymd.gov/animalservices/adoption/howtoadopt.html. Update Frequency : Every two hours

How many dogs are there in the US? According to a pet owners survey, there were approximately 89.7 million dogs owned in the United States in 2017. This is an increase of over 20 million since the beginning of the survey period in 2000, when around 68 million dogs were owned in the United States.

Why has this figure increased?

The resident population of the United States has also increased significantly within this time period. It is, therefore, no surprise that the number of dogs owned in U.S. households has also increased, especially when considering that the household penetration rate for dog-ownership reached almost 50 percent in recent years.

The dog food market in the United States

The large number of dogs owned by Americans creates a lucrative market for pet food brands and retailers. Pedigree, the leading dry dog food name brand in the U.S., had sales amounting to around 550 million U.S. dollars in 2017. Pedigree also led the pack in the wet dog food category , with sales of around 240 million U.S. dollars in the same year.

A large set of images of cats and dogs.

Homepage: https://www.microsoft.com/en-us/download/details.aspx?id=54765

Source code: tfds.image_classification.CatsVsDogs

Versions:

4.0.0 (default): New split API (https://tensorflow.org/datasets/splits) Download size: 786.68 MiB

Source: https://www.tensorflow.org/datasets/catalog/cats_vs_dogs

alexrosen45/dogs dataset hosted on Hugging Face and contributed by the HF Datasets community

Here are a few use cases for this project:

1. Lost Pet Finder: This computer vision model can be used in a lost pet finder app that allows users to upload pictures of lost pets, which then searches through databases of found pets in shelters or reported by others, helping to reunite pet owners with their missing animals.

2. Pet Adoption Platform: The model can be employed in a pet adoption website or app, streamlining the process of finding specific types of pets, such as particular breeds of cats or dogs. Users can easily find the pets they are interested in adopting by simply providing images or searching through the platform's catalog.

3. Pet Breed Identification: The "pets" computer vision model can be utilized to identify and provide essential information about different breeds of cats and dogs to potential pet owners or enthusiasts wanting to learn more about specific breeds. This can help in making educated decisions while choosing a suitable pet based on specific needs or preferences.

4. Pet Care and Training Customization: This model can help pet care providers or trainers to customize their services for different breeds of cats and dogs. By accurately identifying pets, they can tailor their services, advice, and recommendations to better suit the specific needs and traits of the animals.

5. Monitoring Wildlife and Tracking Stray Pets: This computer vision model can be integrated into surveillance systems in urban or suburban areas to monitor and identify stray pets or invasive species, allowing authorities to take appropriate action for animal control, relocation or rescue operations.

Dog

## Overview

Dog is a dataset for classification tasks - it contains Angry Or Happy Or Lelaxed Or Sad annotations for 1,000 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.

Activity Recognition On Dogs

## Overview

Activity Recognition On Dogs is a dataset for object detection tasks - it contains Dogs annotations for 707 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).

I1t and I2t are Indicator or Dummy variables indicating the stimulus category (I1t: 1 = African infants, 0 = Caucasian infants; I2t: 1 = dog puppies, 0 = Caucasian infants). St represents participants’ sex (0 = male, 1 = female). A indicates participants’ age (0 = mean age of the sample).Robust estimators were used for statistical inference with respect to fixed effects and variance components to account for possible violations of model assumptions, such as normality of Level-2 residuals. Degrees of freedom were computed based on the Satterthwaite’s Approximation to account for the moderate sample size at Level 2 [46]. Therefore, the degrees of freedom were not necessarily integers and could vary across tests independent of the number of parameters.Results of Study 1 (Adoption-Task).

Here are a few use cases for this project:

1. Dog Identification App: "dddog" can be used to build an app that helps users identify various dog breeds from images. This can be useful for pet owners, vets, or enthusiasts who wish to get detailed information about a specific dog breed.

2. Enhanced Security Surveillance: The model can be used in security cameras or surveillance systems, where it can identify and separate movement instances of a dog or a human. The information can be valuable in ensuring security in home or public spaces.

3. Animal Control & Welfare: Animal control agencies can use this model to track and monitor dog populations in various cities. They can identify both stray dogs and dogs with owners, helping with planning and executing animal welfare policies.

4. Augmented Reality Games: Developers can use this model for AR games where users need to identify or interact with virtual dogs or humans in real-world environments.

5. Smart Pet Doors: The model can be used in the development of "smart" pet doors which only operate when detecting a specific type of animal (dogs in this case) approaching, preventing unwanted animals from entering the house.