1) Data Introduction • The Wildlife Animals Images Dataset is a computer vision dataset designed for image classification and generation tasks, containing various images of wild animals.

2) Data Utilization (1) Characteristics of the Wildlife Animals Images Dataset: • The dataset includes animals with visually similar features, such as species from the canine (Canidae) and feline (Felidae) families, making it suitable for training models to distinguish between animals that are often easily confused.

(2) Applications of the Wildlife Animals Images Dataset: • Wild animal classification model training: Useful for developing deep learning-based image classifiers capable of distinguishing between animal species with high visual similarity.

Identifying Animals

## Overview

Identifying Animals is a dataset for object detection tasks - it contains Animals annotations for 4,063 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.

Animal Categories: Masters of Survival, Speed, and Strategy

This dataset categorizes animals into unique groups based on their survival traits, physical abilities, and behavioral strategies. From stealthy nocturnal hunters to fast-paced predators and intelligent problem-solvers, this collection highlights the diversity and adaptability of the animal kingdom. Each category is carefully curated to showcase the unique characteristics that make these animals stand out in their respective environments.

Dataset Structure: In labels.csv file

• image_name: The image_name column contains the file paths or names of the images. The names are structured in a way that indicates the type of animal or object in the image (e.g., beetle/687486f1cb.jpg, parrot/5affc48d37.jpg).
• category: The category column contains the label or category associated with each image. These categories describe the type of animal or object in the image, such as Tiny Survivors, Survival Geniuses, Apex Predators, etc.

Categories Included:

• Stealth & Shadows: Masters of camouflage and nocturnal survival (e.g., bat, leopard, owl).
• Speed Demons: Fastest animals on land, air, or water (e.g., cheetah, falcon, dolphin).
• Tough Defenders: Hard-shelled or armored animals (e.g., turtle, armadillo, hedgehog).
• Apex Predators: Top of the food chain (e.g., lion, shark, tiger).
• Survival Geniuses: Highly intelligent and skilled problem-solvers (e.g., chimpanzee, octopus, crow).
• Flight Masters: Birds and insects that dominate the skies (e.g., eagle, hummingbird, butterfly).
• Underwater Specialists: Ocean-based creatures (e.g., whale, jellyfish, seahorse).
• Cold-Climate Survivors: Adapted to harsh winters (e.g., penguin, polar bear, arctic fox).
• Pack Hunters & Social Strategists: Animals that work in groups to hunt or survive (e.g., wolf, lion, meerkat).
• Tiny Survivors: Small but resilient creatures (e.g., rat, cockroach, ladybugs).
• Other: Miscellaneous animals that don’t fit into the above categories.

Acknowledgments: This dataset was inspired by the incredible diversity of the animal kingdom. Special thanks to the dataset Animal Image Dataset (90 Different Animals) by Sourav Banerjee for providing a rich collection of animal images that can complement this categorical dataset. Combining these datasets could enable exciting projects, such as image classification or trait-based animal recognition.

A dataset of images of different animals.

Fr0styKn1ght/Animals dataset hosted on Hugging Face and contributed by the HF Datasets community

Rapidata Other Animals-10

This dataset contains the remaining images that were included in the original Animals-10 (kaggle) and which were not sorted into one of the existing 10 classes (Rapidata Animals-10). If you get value from this dataset and would like to see more in the future, please consider liking it.

  Dataset Details

33 classes 103 Images

Curated by: @canwiper Funded by: Rapidata License: gpl-2.0

  Dataset Sources

Blog post describing the setup… See the full description on the dataset page: https://huggingface.co/datasets/Rapidata/Other-Animals-10.

Classify Animals.

## Overview

 Classify Animals. is a dataset for object detection tasks - it contains Classify Animals annotations for 515 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).

Common Road Animals 2

## Overview

Common Road Animals 2 is a dataset for instance segmentation tasks - it contains Common Road Animals annotations for 510 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).

In early 2017, the Bloomington Animal Shelter migrated management software from AnimalShelterNet to Shelter Manager. We attempted to preserve as much information as possible from the old system.

The outcome fields in animal shelter are scattered in multiple fields not just one, for example Dead on arrival, Put to sleep, Movement Type and others are all considered as part of outcome.

The NYS Department of Environmental Conservation (DEC) collects and maintains several datasets on the locations, distribution and status of species of plants and animals. Information on distribution by county from the following three databases was extracted and compiled into this dataset. First, the New York Natural Heritage Program biodiversity database: Rare animals, rare plants, and significant natural communities. Significant natural communities are rare or high-quality wetlands, forests, grasslands, ponds, streams, and other types of habitats. Next, the 2nd NYS Breeding Bird Atlas Project database: Birds documented as breeding during the atlas project from 2000-2005. And last, DEC’s NYS Reptile and Amphibian Database: Reptiles and amphibians; most records are from the NYS Amphibian & Reptile Atlas Project (Herp Atlas) from 1990-1999.

This dataset contains images used in the monograph titled Zastosowanie wybranych metod uczenia głębokiego w wizji komputerowej (Application of Selected Deep Learning Methods in Computer Vision) to build the Faster R-CNN model. The full collection consists of 600 image files showing 6 classes of objects: kot (cat), krowa (cow), pies (dog), koń (horse), człowiek (human), owca (sheep) (https://drive.google.com/file/d/1g3O1Qq2YqmCb8WSMDHaoFJPoHe6yujlQ/view?usp=drive_link). All images were scaled so that the smaller side is no shorter than 600 pixels and the larger side is no longer than 1000 pixels. The set was randomly divided into a training part (75% of the full set) and a test part (25% of the full set). As a result, the training part contains 450 files, and the test part - 150. Both parts are balanced - they contain a similar number of detected objects. The images are labeled with bounding boxes in the Pacal VOC format, according to which the description of each file is contained in an XML file with the same name. The dataset can be used to build models for object detection.

In 2019, 797,546 animals were used for research in research facilities in the United States. This is an increase from the previous year, when about 780,070 animals were used for research in the country.

COS30049 Animals

## Overview

COS30049 Animals is a dataset for object detection tasks - it contains Animals annotations for 10,000 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).

* = juveniles.

PenguinPush/animals-large dataset hosted on Hugging Face and contributed by the HF Datasets community

Detecting Animals

## Overview

Detecting Animals is a dataset for object detection tasks - it contains Animalssss annotations for 591 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).

Biological Classification Of Animals

Biological classification or scientific classification is a method of classification and arrangement of biologists with distinctive organisms. Which classifies the types according to the common physical properties.

Content

This data frame has more than 1300 biological classification of animals. The delightful thing about this data frame is that, anyone who took any biology class in their life can simply understand, use and benefits from. I would love to see how other people would deal with this data frame, I think it is useful and they will be so creative.

• Animal Name: The animal name. • Kingdom: The animal kingdom. • Phylum: The animal phylum. • Subphylum: The animal subphylum, if it has. • Class: The animal class. • Subclass: The animal subclass, if it has. • Infraclass: The animal infraclass, if it has. • Order: The animal order. • Superorder: The animal superorder, if it has. • Suborder: The animal suborder, if it has. • Infraorder: The animal infraorder, if it has. • Family: The animal family. • Superfamily: The animal superfamily, if it has. • Subfamily: The animal subfamily, if it has. • Genus: The animal genus, can be empty in rare conditions. • Subgenus: The animal subgenus, if it has. • Tribe: The animal tribe, if it has. • Clade: The animal clade, if it has.

Attention

• The main classification must not be empty.
• Main classifications are: Animal Name, Kingdom, Phylum, Class, Order, Family, Genus (can be empty in rare conditions), so If you find the main classifications of an animal is fulfilled, other classifications can be dispensed with.

The data base includes reports of findings of mammals, birds, reptiles, and fish of the area of Polissya Nature Reserve (Selezivske, Kopyschanske and Perganske forestries), in the protected area of the Nature Reserve and in the neighborhood.

United States Imports of Live animals was US$4.8 Billion during 2024, according to the United Nations COMTRADE database on international trade. United States Imports of Live animals - data, historical chart and statistics - was last updated on September of 2025.