Stanford Dogs Dataset

## Overview

Stanford Dogs Dataset is a dataset for object detection tasks - it contains Dogs annotations for 1,137 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).

Small sample of the Kaggle Cats and Dogs dataset (https://www.kaggle.com/c/dogs-vs-cats/data).

Contains 1000 images for the train set (500 cats and 500 dogs), and 400 images for the test set (200 each).

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).

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.

Dogs Intelligence and Size

An Exploration of Breed-Based Characteristics

By len fishman [source]

About this dataset

This dataset provides valuable insights into the potential relationship between size and intelligence in different breeds of dogs. It includes data from a research conducted by Stanley Coren, a professor of canine psychology at the University of British Columbia, as well as breed size data from the American Kennel Club (AKC). With this dataset, users will be able to explore how larger and smaller breeds compare when it comes to obedience and intelligence. The columns present in this dataset include Breed, Classification, Obey (probability that the breed obeys the first command), Repetitions Lower/Upper Limits (for understanding new commands). From examining this data, users may gain further insight on our furry friends and their behaviors. Dive deeper into these intricate relationships with this powerful dataset!

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How to use the dataset

This dataset provides insight into how intelligence and size may be connected in dogs. It includes information on dog breeds, including their size, how well they obey commands, and the number of repetitions required for them to understand new commands. This can help pet owners who are looking for a dog that fits their lifestyle and residential requirements.

To get started using this dataset, begin by exploring the different attributes included: Breed (the type of breed), Classification (the size classification of the dog - small, medium or large), height_low_inches & height_high_inches (these are the lower limit and upper limit in inches when it comes to the height of the breed), weight_low_lbs & weight_high lbs (these are the lower limit and upper limit in pounds when it comes to the weight of a breed). Also included is obey (the probability that a particular breed obeys a given command) as well as reps_lower & reps_upper which represent respectively lower and upper repetitions required for a given breed to understand new commands

Once you have an understanding of what each attribute represents you can start exploring specific questions such as 'how many breeds fit in within certain size categories?', 'what type of 'obey' score do large breeds tend to achieve?', or you could try comparing size with intelligence by plotting out obey against both reps_lower & reps_upper . If higher obedience scores correlate with smaller numbers on either attributes this might suggest that smaller breeds tend require fewer repetitions when attempting learn something new.

By combining these attributes with other datasets such as those focusing on energy levels it’s possible create even more specific metrics based questions regarding which types of dogs might suit certain lifestyles better than others!

Research Ideas

• Examining the correlation between obedience and intelligence in different dog breeds.
• Investigating how size is related to other traits such as energy level, sociability and trainability in a particular breed of dog.
• Analyzing which sizes are associated with specific behavior patterns or medical issues for dogs of various breeds

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: Dataset copyright by authors - You are free to: - Share - copy and redistribute the material in any medium or format for any purpose, even commercially. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contributions under the same license as the original. - Keep intact - all notices that refer to this license, including copyright notices.

Columns

File: AKC Breed Info.csv | Column name | Description | |:-----------------------|:--------------------------------------------------------------| | Breed | The breed of the dog. (String) | | height_low_inches | The lower range of the height of the dog in inches. (Integer) | | height_high_inches | The upper range of the height of the dog in inches. (Integer) | | weight_low_lbs | The lower range of the weight of the dog in pounds. (Integer) | |...

Dogs And Cats

## Overview

Dogs And Cats is a dataset for object detection tasks - it contains Dogs And Cats annotations for 613 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).

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

Dataset

This dataset was created by Moulhanout

Released under Database: Open Database, Contents: © Original Authors

Contents

Overview

This dataset contains a total of 1000 images, with an equal distribution of 500 images of dog and 500 images of cat. The images are standardized to a resolution of 512x512 pixels.

Details

• Total Images: 1000
  • Dog: 500 images
  • Cat: 500 images
• Image Resolution: 512x512 pixels
• File Format: .png
• Source: Images generated using Stable Diffusion 1.5

Usage

This dataset is ideal for tasks such as: - Binary classification - Image recognition and processing - Machine learning and deep learning model training

Dogs

## Overview

Dogs is a dataset for object detection tasks - it contains Dogs annotations for 203 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 [MIT license](https://creativecommons.org/licenses/MIT).

The Stanford Dogs dataset consists of 20,580 images of different breeds of dogs.

A dataset containing 5 common dog's breeds:

French Bulldog German Shephard Golden Retriever Poodle Yorkshire Terrier

Description

This dataset contains a collection of images for 10 different dog breeds, meticulously gathered and organized to facilitate various computer vision tasks such as image classification and object detection. The dataset includes the following breeds:

• Golden Retriever
• German Shepherd
• Labrador Retriever
• Bulldog
• Beagle
• Poodle
• Rottweiler
• Yorkshire Terrier
• Boxer
• Dachshund

Each breed is represented by 100 images, stored in separate directories named after the respective breed. The images have been curated to ensure diversity and relevance, making this dataset a valuable resource for training and evaluating machine learning models in the field of computer vision.

Context

To practice the generation of images using deep learning, a starter dataset like the Stanford dogs could be utilised. For this purpose, this dataset suffers from flaws like unequal dimensions and 'useless' data surrounding the dogs in the images. This dataset is a resized and cropped version of all the original Stanford dogs.

Content

The dataset contains 2 directories: 'annotations' and 'images'. The annotations directory contains the original annotations from the Stanford dogs dataset, with the addition of the resize factor and cropped region in the original image. Evidently, the dimensions of the image and bbox are no longer valid. The images are the newly resized and cropped images.

About

12k labelled instances of dogs in-the-wild with 2D keypoint and segmentations.

This dataset was released with our ECCV 2020 paper: Who Left the Dogs Out? 3D Animal Reconstruction with Expectation Maximization in the Loop.

Installation

For installation details, please visit our GitHub repo.

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 contains images of cats and dogs, which is used for training deep neural networks.

This dataset contains a collection of images featuring cats and dogs, intended for use in image classification tasks. It's a valuable resource for training and evaluating machine learning models that can distinguish between these two popular pet species. The dataset is well-structured, making it suitable for both beginners and experienced data scientists looking to build and test image classification algorithms. Dataset contains more than 27500 training and testing images of dog and cat

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.