Aquarium Combined Object Detection Dataset and Pre-Trained Model by Roboflow

Images

638 images

Explore Dataset

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

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!

Trained Model API

This project has a trained model available that you can try in your browser and use to get predictions via our Hosted Inference API and other deployment methods.

Cite This Project

If you use this dataset in a research paper, please cite it using the following BibTeX:

@misc{
                            aquarium-combined_dataset,
                            title = { Aquarium Combined Dataset },
                            type = { Open Source Dataset },
                            author = { Roboflow },
                            howpublished = { \url{ https://universe.roboflow.com/brad-dwyer/aquarium-combined } },
                            url = { https://universe.roboflow.com/brad-dwyer/aquarium-combined },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { sep },
                            note = { visited on 2024-04-23 },
                            }