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Animals

Datasets, Pre-Trained Models, and APIs for Object Detection, Classification

Oxford Pets

Example Annotations

About this 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.

Aerial Sheep

  • Riis
  • sheep Dataset
  • 1727 images

Overview

The Aerial Sheep dataset contains images taken from a birds-eye view with instances of sheep in them. Images do not differentiate between gender or breed of sheep, instead grouping them into a single class named "sheep".

Example Footage

Aerial Sheep

See RIIS's sheep counter application for additional use case examples.
Link - https://riis.com/blog/counting-sheep-using-drones-and-ai/

About RIIS

https://riis.com/about/

NE Bird

Aquarium Combined

CreateML Output

Dataset Details

This dataset consists of 638 images collected by Roboflow from two aquariums in the United States: The Henry Doorly Zoo in Omaha (October 16, 2020) and the National Aquarium in Baltimore (November 14, 2020). The images were labeled for object detection by the Roboflow team (with some help from SageMaker Ground Truth). Images and annotations are released under a Creative Commons By-Attribution license. You are free to use them for any purposes personal, commercial, or academic provided you give acknowledgement of their source.

Projects Using this Dataset:

No-Code Object Detection Tutorial
No-Code Object Detection Tutorial

Class Breakdown

The following classes are labeled: fish, jellyfish, penguins, sharks, puffins, stingrays, and starfish. Most images contain multiple bounding boxes.

Class Balance

Usage

The dataset is provided in many popular formats for easily training machine learning models. We have trained a model with CreateML (see gif above).

This dataset could be used for coral reef conservation, environmental health monitoring, swimmer safety, pet analytics, automated feeding, and much more. We're excited to see what you build!

My Game Pics

Annotated pictures of animals from trail cameras in East Texas.

Cats

About this Dataset

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.

Annotated image of a cat from the dataset

Oxford Pets

  • 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.

bees

  • bees
  • bumblebees Dataset
  • 10284 images

Brackish Underwater

Example image from the dataset

Dataset Information

This dataset contains 14,674 images (12,444 of which contain objects of interest with bounding box annotations) of fish, crabs, and other marine animals. It was collected with a camera mounted 9 meters below the surface on the Limfjords bridge in northern Denmark by Aalborg University.

Composition

Roboflow has extracted and processed the frames from the source videos and converted the annotations for use with many popular computer vision models. We have maintained the same 80/10/10 train/valid/test split as the original dataset.

The class balance in the annotations is as follows:
Class Balance

Most of the identified objects are congregated towards the bottom of the frames.

Annotation Heatmap

More Information

For more information, see the Detection of Marine Animals in a New Underwater Dataset with Varying Visibility paper.

If you find the dataset useful, the authors request that you please cite their paper:

@InProceedings{pedersen2019brackish,
                                title={Detection of Marine Animals in a New Underwater Dataset with Varying Visibility},
                                author={Pedersen, Malte and Haurum, Joakim Bruslund and Gade, Rikke and Moeslund, Thomas B. and Madsen, Niels},
                                booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
                                month = {June},
                                year = {2019}
                            }
                            

Thermal Cheetah

Thermal Cheetahs

About this Dataset

This is a collection of images and video frames of cheetahs at the Omaha Henry Doorly Zoo taken in October, 2020. The capture device was a SEEK Thermal Compact XR connected to an iPhone 11 Pro. Video frames were sampled and labeled by hand with bounding boxes for object detection using Robofow.

Using this Dataset

We have provided the dataset for download under a creative commons by-attribution license. You may use this dataset in any project (including for commercial use) but must cite Roboflow as the source.

Example Use Cases

This dataset could be used for conservation of endangered species, cataloging animals with a trail camera, gathering statistics on wildlife behavior, or experimenting with other thermal and infrared imagery.

About Roboflow

Roboflow creates tools that make computer vision easy to use for any developer, even if you're not a machine learning expert. You can use it to organize, label, inspect, convert, and export your image datasets. And even to train and deploy computer vision models with no code required.