huggingface/cats-image dataset hosted on Hugging Face and contributed by the HF Datasets community
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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.
This dataset contains 300 images of three types of animals: cats, dogs, and foxes. Each category has 100 pictures. The images can help in learning about animals and building computer programs that recognize them. You can use this dataset for school projects, studies in artificial intelligence, or just to learn more about these animals.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset was created by exporting the Oxford Pets dataset from Roboflow Universe, generating a version with Modify Classes to drop all of the classes for the labeled dog breeds and consolidating all cat breeds under the label, "cat." The bounding boxes were also modified to incude the entirety of the cats within the images, rather than only their faces/heads.
https://i.imgur.com/3IEzlCf.png" alt="Annotated image of a cat from the 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.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
## Overview
Gray Cats is a dataset for object detection tasks - it contains Cats annotations for 985 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).
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
## Overview
COCO 2017 Cats is a dataset for object detection tasks - it contains Cats annotations for 4,112 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).
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DALL-E-Cats is a dataset meant to produce a synthetic animal dataset. This is a successor to DALL-E-Dogs. DALL-E-Dogs and DALL-E-Cats will be fed into an image classifier to see how it performs. This is under the BirdL-AirL License.
This dataset was created by Arpit Dwivedi
MIT Licensehttps://opensource.org/licenses/MIT
License information was derived automatically
## Overview
Cats And Dogs is a dataset for object detection tasks - it contains Cats And Dogs annotations for 1,994 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).
huggan/cats dataset hosted on Hugging Face and contributed by the HF Datasets community
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The Controlled Anomalies Time Series (CATS) Dataset consists of commands, external stimuli, and telemetry readings of a simulated complex dynamical system with 200 injected anomalies.
The CATS Dataset exhibits a set of desirable properties that make it very suitable for benchmarking Anomaly Detection Algorithms in Multivariate Time Series [1]:
Change Log
Version 2
[1] Example Benchmark of Anomaly Detection in Time Series: “Sebastian Schmidl, Phillip Wenig, and Thorsten Papenbrock. Anomaly Detection in Time Series: A Comprehensive Evaluation. PVLDB, 15(9): 1779 - 1797, 2022. doi:10.14778/3538598.3538602”
About Solenix
Solenix is an international company providing software engineering, consulting services and software products for the space market. Solenix is a dynamic company that brings innovative technologies and concepts to the aerospace market, keeping up to date with technical advancements and actively promoting spin-in and spin-out technology activities. We combine modern solutions which complement conventional practices. We aspire to achieve maximum customer satisfaction by fostering collaboration, constructivism, and flexibility.
This dataset is a modelled dataset, describing an upper estimate of cats per square kilometre across GB. The figures are aligned to the British national grid, with a population estimate provided for each 1km square. These data were generated as part of the delivery of commissioned research. The data contained within this dataset are modelled figures, based on upper 95th percentile national estimates for pet population, and available information on Veterinary activity across GB. The data are accurate as of 01/01/2015. The data provided are summarised to the 1km level. Further information on this research is available in a research publication by James Aegerter, David Fouracre & Graham C. Smith, discussing the structure and density of pet cat and dog populations across Great Britain. Attribution statement: ©Crown Copyright, APHA 2016
Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
License information was derived automatically
This Kaggle dataset includes 1000 JPEG images of diverse cats, paired with 1000 text files containing bounding box annotations in YOLO format. It's designed for training object detection models to recognize cats, and is suitable for various computer vision applications and educational use
https://choosealicense.com/licenses/cc0-1.0/https://choosealicense.com/licenses/cc0-1.0/
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.
CATS-ISS_L2O_D-M7.2-V3-01_05kmPro is the Cloud-Aerosol Transport System (CATS) International Space Station (ISS) Level 2 Operational Day Mode 7.2 Version 3-01 5 km Profile data product. This collection spans from March 25, 2015 to October 29, 2017. CATS, which was launched on January 10, 2015, was a lidar remote sensing instrument that provided range-resolved profile measurements of atmospheric aerosols and clouds from the ISS. CATS was intended to operate on-orbit for up to three years. CATS provides vertical profiles at three wavelengths, orbiting between ~230 and ~270 miles above the Earth's surface at a 51-degree inclination with nearly a three-day repeat cycle. For the first time, scientists were able to study diurnal (day-to-night) changes in cloud and aerosol effects from space by observing the same spot on Earth at different times each day. CATS Level 2 Layer data products contain geophysical parameters and are derived from Level 1 data, at 60m vertical and 5km horizontal resolution.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
## Overview
Cats And Dogs Image Classification is a dataset for classification tasks - it contains Cats And Dogs annotations for 2,000 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.
## License
This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).
The estimated number of cats owned by households in Sweden increased in selected years from 2010 to 2024. The cat population in Sweden was measured at approximately **** million in 2024, an increase from the previous year.
Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
License information was derived automatically
In this dataset, I collected cat faces from memes. I tried to take photos with only one cat and without labels (but you can find some images with it). The dataset also has some ordinary photos of cats. You can try to create a GAN or diffuser model to generate memes or use this dataset as you like :)
It's my first dataset so I will be grateful if you suggest how to upgrade it
This statistic presents the estimated number of cats owned by households in Europe in 2010, 2012, 2014, 2016, 2017, 2018, 2019, 2020, 2021, 2022, and 2023. The cat population in Europe was measured at approximately ****** million in 2023.
The estimated number of cats owned by households in Turkey constantly increased in the observed years from 2012 to 2023. The cat population in Turkey peaked at over *** million in 2023.
huggingface/cats-image dataset hosted on Hugging Face and contributed by the HF Datasets community