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. There are 20,580 images, out of which 12,000 are used for training and 8580 for testing. Class labels and bounding box annotations are provided for all the 12,000 images.
To use this dataset:
import tensorflow_datasets as tfds
ds = tfds.load('stanford_dogs', split='train')
for ex in ds.take(4):
print(ex)
See the guide for more informations on tensorflow_datasets.
https://storage.googleapis.com/tfds-data/visualization/fig/stanford_dogs-0.2.0.png" alt="Visualization" width="500px">
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.
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.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
A dataset of cat and dog images that can be used to train machine learning models to classify images.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
The test set contains 12,500 cat and dog images. The images in the test set are evenly split between cats and dogs, with 6,250 images of each.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
The training set contains 25,000 cat and dog images.
A large set of images of cats and dogs. There are 1738 corrupted images that are dropped.
To use this dataset:
import tensorflow_datasets as tfds
ds = tfds.load('cats_vs_dogs', split='train')
for ex in ds.take(4):
print(ex)
See the guide for more informations on tensorflow_datasets.
https://storage.googleapis.com/tfds-data/visualization/fig/cats_vs_dogs-4.0.1.png" alt="Visualization" width="500px">
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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).
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
Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
License information was derived automatically
alexrosen45/dogs dataset hosted on Hugging Face and contributed by the HF Datasets community
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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.… See the full description on the dataset page: https://huggingface.co/datasets/Bingsu/Cat_and_Dog.
Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
License information was derived automatically
This dataset was created by Adeel Waheed
Released under Apache 2.0
This dataset was created by hongwei cao
Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
License information was derived automatically
This dataset was created by Syed Abdul Qadir
Released under Apache 2.0
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset is a copy of a subset of the full Stanford Dogs Dataset.
Source: http://vision.stanford.edu/aditya86/ImageNetDogs/
The original dataset contained 20,580 images of 120 breeds of dogs.
This subset contains 9884 images of 60 breeds of dogs.
ODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
License information was derived automatically
This dataset displays the name, breed, and approximate location of dogs in Cambridge. It is based on dog license data collected by Cambridge's Animal Commission. All locations listed in this dataset have been obscured to protect privacy. Please see the limitations section below for more information.
Open Database License (ODbL) v1.0https://www.opendatacommons.org/licenses/odbl/1.0/
License information was derived automatically
This dataset was created by Moulhanout
Released under Database: Open Database, Contents: © Original Authors
https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/
This dataset was created by Rafael R. Lima
Released under CC0: Public Domain
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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.
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.
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. There are 20,580 images, out of which 12,000 are used for training and 8580 for testing. Class labels and bounding box annotations are provided for all the 12,000 images.
To use this dataset:
import tensorflow_datasets as tfds
ds = tfds.load('stanford_dogs', split='train')
for ex in ds.take(4):
print(ex)
See the guide for more informations on tensorflow_datasets.
https://storage.googleapis.com/tfds-data/visualization/fig/stanford_dogs-0.2.0.png" alt="Visualization" width="500px">