Astrophysics > Instrumentation and Methods for Astrophysics
[Submitted on 2 Jul 2025
]
Title: Image Marker
Title: 图像标记
Abstract: A wide range of scientific imaging datasets benefit from human inspection for purposes ranging from prosaic-such as fault identification and quality inspection-to profound, enabling the discovery of new phenomena. As such, these datasets come in a wide variety of forms, with diverse inspection needs. In this paper we present a software package, Image Marker, designed to help facilitate human categorization of images. The software allows for quick seeking through images and enables flexible marking and logging of up to 9 different classes of features and their locations in files of FITS, TIFF, PNG, and JPEG format. Additional tools are provided to add text-based comments to the marking logs and for displaying external mark datasets on images during the classification process. As our primary use case will be the identification of features in astronomical survey data, Image Marker will also utilize standard world coordinate system (WCS) headers embedded in FITS headers and TIFF metadata when available. The lightweight software, based on the Qt Framework to build the GUI application, enables efficient marking of thousands of images on personal-scale computers. We provide Image Marker as a Python package, and as Mac and Windows 11 executables. It is available on GitHub or via pip installation.
Current browse context:
astro-ph.IM
Change to browse by:
References & Citations
Bookmark
Bibliographic and Citation Tools
Bibliographic Explorer (What is the Explorer?)
Connected Papers (What is Connected Papers?)
Litmaps (What is Litmaps?)
scite Smart Citations (What are Smart Citations?)
Code, Data and Media Associated with this Article
alphaXiv (What is alphaXiv?)
CatalyzeX Code Finder for Papers (What is CatalyzeX?)
DagsHub (What is DagsHub?)
Gotit.pub (What is GotitPub?)
Hugging Face (What is Huggingface?)
Papers with Code (What is Papers with Code?)
ScienceCast (What is ScienceCast?)
Demos
Recommenders and Search Tools
Influence Flower (What are Influence Flowers?)
CORE Recommender (What is CORE?)
IArxiv Recommender
(What is IArxiv?)
arXivLabs: experimental projects with community collaborators
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.
Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.
Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.