
RarePlanes
Provided by: In-Q-Tel - CosmiQ Works, part of the AWS Open Data Sponsorship Program
Provided by: In-Q-Tel - CosmiQ Works, part of the AWS Open Data Sponsorship Program

RarePlanes
Provided by: In-Q-Tel - CosmiQ Works, part of the AWS Open Data Sponsorship Program
Provided by: In-Q-Tel - CosmiQ Works, part of the AWS Open Data Sponsorship Program
This product is part of the AWS Open Data Sponsorship Program and contains data sets that are publicly available for anyone to access and use. No subscription is required. Unless specifically stated in the applicable data set documentation, data sets available through the AWS Open Data Sponsorship Program are not provided and maintained by AWS.
Description
RarePlanes is a unique open-source machine learning dataset from CosmiQ Works and AI.Reverie that incorporates both real and synthetically generated satellite imagery. The RarePlanes dataset specifically focuses on the value of AI.Reverie synthetic data to aid computer vision algorithms in their ability to automatically detect aircraft and their attributes in satellite imagery. Although other synthetic/real combination datasets exist, RarePlanes is the largest openly-available very high resolution dataset built to test the value of synthetic data from an overhead perspective. The real portion of the dataset consists of 253 Maxar WorldView-3 satellite scenes spanning 112 locations and 2,142 km^2 with 14,700 hand-annotated aircraft. The accompanying synthetic dataset is generated via AI.Reverie’s novel simulation platform and features 50,000 synthetic satellite images with ~630,000 aircraft annotations.
License
Documentation
www.cosmiqworks.org/RarePlanes
How to cite
RarePlanes was accessed on DATE
from https://registry.opendata.aws/rareplanes .
Update frequency
None Planned
Support information
Managed by: In-Q-Tel - CosmiQ Works
Contact: jss5102@gmail.com and avanetten@iqt.org
General AWS Data Exchange support
Resources on AWS
Description
Real and synthetic satellite imagery, annotations, and metadata
Resource type
S3 Bucket
Amazon Resource Name (ARN)
arn:aws:s3:::rareplanes-public
AWS Region
us-west-2
AWS CLI Access (No AWS account required)
aws s3 ls --no-sign-request s3://rareplanes-public/
Usage examples
Tutorials
- Announcing YOLTv4: Improved Satellite Imagery Object Detection by Adam Van Etten
- Automatically compress and archive satellite imagery for Amazon S3 by Newel Hirst, Joseph Fahimi, and Justin Downes
- Getting Started with YOLTv4 for Object Detection in Imagery: Getting Training Data by Sophia Parafina
- Notebook for training and testing YOLYv4 by Adam Van Etten
Publications
- RarePlanes: Synthetic Data Takes Flight by Jacob Shermeyer, Thomas Hossler, Adam Van Etten, Daniel Hogan, Ryan Lewis, Daeil Kim
Tools & Applications
- RarePlanes Codebase by Thomas Hossler and Jacob Shermeyer